International Nuclear Information System (INIS)
Rafaj, Peter; Kypreos, Socrates
2007-01-01
The Global MARKAL-Model (GMM), a multi-regional 'bottom-up' partial equilibrium model of the global energy system with endogenous technological learning, is used to address impacts of internalisation of external costs from power production. This modelling approach imposes additional charges on electricity generation, which reflect the costs of environmental and health damages from local pollutants (SO 2 , NO x ) and climate change, wastes, occupational health, risk of accidents, noise and other burdens. Technologies allowing abatement of pollutants emitted from power plants are rapidly introduced into the energy system, for example, desulphurisation, NO x removal, and CO 2 scrubbers. The modelling results indicate substantial changes in the electricity production system in favour of natural gas combined cycle, nuclear power and renewables induced by internalisation of external costs and also efficiency loss due to the use of scrubbers. Structural changes and fuel switching in the electricity sector result in significant reduction of emissions of both local pollution and CO 2 over the modelled time period. Strong decarbonisation impact of internalising local externalities suggests that ancillary benefits can be expected from policies directly addressing other issues then CO 2 mitigation. Finally, the detailed analysis of the total generation cost of different technologies points out that inclusion of external cost in the price of electricity increases competitiveness of non-fossil generation sources and fossil power plants with emission control
A comparison between MARKAL-MACRO and MARKAL
International Nuclear Information System (INIS)
Schepers, E.
1995-11-01
Differences between CO 2 -reduction scenarios of the MARKAL-MACRO model and the MARKAL model are studied. Also attention is paid to the rebound effect, i.e. the effect on a price decrease leads to an increase of the energy demand, and energy savings will result in a redistribution of saved income over other goods and services. MARKAL is an energy supply model and MACRO is a macro-economic model. The combination of the two is an example of a hard-linked model between a top-down model (MACRO) and a bottom-up model (MARKAL). 15 figs., 5 tabs., 18 refs., 2 appendices
International Nuclear Information System (INIS)
Guel, Timur; Kypreos, Socrates; Turton, Hal; Barreto, Leonardo
2009-01-01
This paper deals with the long-term prospects of alternative fuels in global personal transport. It aims at assessing key drivers and key bottlenecks for their deployment, focusing particularly on the role of biofuels and hydrogen in meeting climate policy objectives. The analysis is pursued using the Global Multi-regional MARKAL model (GMM), a perfect foresight ''bottom-up'' model of the global energy system with a detailed representation of alternative fuel chains, linked to the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC). The analysis shows that biofuels are limited by the regional availability of low-cost biomass, but can be important for meeting mild climate policy targets. If policy-makers intend to pursue more stringent climate policy, then hydrogen becomes a competitive option. However, the analysis finds that the use of hydrogen in personal transport is restricted to very stringent climate policy, as only such policy provides enough incentive to build up the required delivery infrastructure. An analysis of costs additionally shows that ''keeping the hydrogen option open'' does not take considerable investments compared to the investment needs in the power sector within the next decades, but allows the use of hydrogen for the pursuit of stringent climate policy in the second half of the century. (author)
Italian energy scenarios: Markal model
International Nuclear Information System (INIS)
Gracceva, Francesco
2005-01-01
Energy scenarios carried out through formal models comply with scientific criteria such as internal coherence and transparency. Besides, Markal methodology allows a good understanding of the complex nature of the energy system. The business-as-usual scenario carried out through the Markal-Italy model shows that structural changes occurring in end-use sectors will continue to drive up energy consumption, in spite of the slow economic growth and the quite high energy prices [it
The MARKAL-MACRO model and the climate change
International Nuclear Information System (INIS)
Kypreos, S.
1996-07-01
MARKAL-MACRO and its extensions is a model appropriate to study partial and general equilibrium in the energy markets and the implications of the carbon dioxide mitigation policy. The main advantage of MM is the explicit treatment of energy demand, supply and conversion technologies, including emission control and conservation options, within a general equilibrium framework. The famous gap between top-down and bottom-up models is resolved and the economic implications of environmental and supply policy constraints can be captured either in an aggregated (Macro) or in a sectorial (Micro) level. The multi-regional trade version of the model allows to study questions related to efficient and equitable allocation of cost and benefits associated with the climate change issue. Finally, the stochastic version of the model allows to assess policies related to uncertain and even catastrophic effects and define appropriate hedging strategies. The report is divided in three parts: - the first part gives an overview of the new model structure. It describes its macro economic part and explains its calibration, - the second part refers to the model applications for Switzerland when analyzing the economic implications of curbing CO 2 emissions or policies related to the introduction of a carbon tax, including a hedging strategy, - the last part is organized in form of Appendices and gives a mathematical description and some potential extensions of the model. It describes also a sensitivity analysis done with MARKAL-MACRO in 1992. (author) figs., tabs., refs
International Nuclear Information System (INIS)
Bahn, O.; Barreto, L.; Bueeler, B.; Kypreos, S.
1997-11-01
The development of a multi-regional MARKAL-MACRO (mMM) model and associated solution techniques have been actively continued during the first year (July 1996 - June 1997) of the IEA/ETSAP/Annex VI. This has been a joint research effort between: - the Systems Analysis Section of the Paul Scherrer Institute (PSI), - the Inst. for Operations Research (IFOR) of the Swiss Federal Inst. of Technology at Zurich, - the Logistics Lab. (Logilab) of the Univ. of Geneva, and - the different ETSAP partners that provide the regional MARKAL-MACRO (MM) models. This report intends to give an update on the development of mMM and associated solution techniques, highlighting the progress made since July 1996. It details also first JI study performed with mMM. The mMM model enables one to study an international co-operation to curb jointly carbon dioxide (CO 2 ) emissions through a market of emission permits, and to evaluate the economic implications of co-ordinating abatement policies on the participating regions. Along with emission permits, the regions may exchange other goods. So far, only an aggregate good in monetary unit has been considered. The mMM model integrates regional MM models into a meta-modelling framework. This integration can be done following two equivalent alternatives: mMM can be formulated either with market equilibrium conditions, or with an aggregated utility function and a global excess constraint. In both alternatives, regional MM models have to be extended by coherent budget and/or trade relationships. A first coding of a mMM model with three countries had been done in GAMS. Work has been done to generalise this coding to consider more traded goods and more countries. To solve mMM, two alternative mathematical methods can be used. The first one considers mMM formulated with market equilibrium conditions, and solves it as a variational inequality problem using a cutting plane algorithm. The second one considers mMM formulated with an aggregated utility
MARKAL-MACRO: A linked model for energy-economy analysis
International Nuclear Information System (INIS)
Manne, A.S.; Wene, C.O.
1992-02-01
MARKAL-MACRO is an experiment in model linkage for energy and economy analysis. This new tool is intended as an improvement over existing methods for energy strategy assessment. It is designed specifically for estimating the costs and analyzing the technologies proposed for reducing environmental risks such as global climate change or regional air pollution. The greenhouse gas debate illustrates the usefulness of linked energy-economy models. A central issue is the coupling between economic growth, the level of energy demands, and the development of an energy system to supply these demands. The debate is often connected with alternative modeling approaches. The competing philosophies may be labeled ''top-down macroeconomic'' and ''bottom-up engineering'' perspectives. MARKAL is a systems engineering (physical process) analysis built on the concept of a Reference Energy System (RES). MARKAL is solved by means of dynamic linear programming. In most applications, the end use demands are fixed, and an economically efficient solution is obtained by minimizing the present value of energy system's costs throughout the planning horizon. MACRO is a macroeconomic model with an aggregated view of long-term economic growth. The basis input factors of production are capital, labor and individual forms of energy. MACRO is solved by nonlinear optimization
Energy Technology Data Exchange (ETDEWEB)
Bahn, O.; Barreto, L.; Bueeler, B.; Kypreos, S. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)
1997-11-01
The development of a multi-regional MARKAL-MACRO (mMM) model and associated solution techniques have been actively continued during the first year (July 1996 - June 1997) of the IEA/ETSAP/Annex VI. This has been a joint research effort between: - the Systems Analysis Section of the Paul Scherrer Institute (PSI), - the Inst. for Operations Research (IFOR) of the Swiss Federal Inst. of Technology at Zurich, - the Logistics Lab. (Logilab) of the Univ. of Geneva, and - the different ETSAP partners that provide the regional MARKAL-MACRO (MM) models. This report intends to give an update on the development of mMM and associated solution techniques, highlighting the progress made since July 1996. It details also first JI study performed with mMM. The mMM model enables one to study an international co-operation to curb jointly carbon dioxide (CO{sub 2}) emissions through a market of emission permits, and to evaluate the economic implications of co-ordinating abatement policies on the participating regions. Along with emission permits, the regions may exchange other goods. So far, only an aggregate good in monetary unit has been considered. The mMM model integrates regional MM models into a meta-modelling framework. This integration can be done following two equivalent alternatives: mMM can be formulated either with market equilibrium conditions, or with an aggregated utility function and a global excess constraint. In both alternatives, regional MM models have to be extended by coherent budget and/or trade relationships. A first coding of a mMM model with three countries had been done in GAMS. Work has been done to generalise this coding to consider more traded goods and more countries. To solve mMM, two alternative mathematical methods can be used. The first one considers mMM formulated with market equilibrium conditions, and solves it as a variational inequality problem using a cutting plane algorithm. The second one considers mMM formulated with an aggregated utility
Modelling regional trade of CO{sub 2} certificates
Energy Technology Data Exchange (ETDEWEB)
Bueeler, B.; Bahn, O.; Kypreos, S. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)
1997-06-01
Many countries have developed energy models (such as MARKAL-MACRO---MM) to assess their energy policies, in particular concerning the curbing of their carbon dioxide (CO{sub 2}) emissions. To integrate national MM models, we propose a multi-regional MARKAL-MACRO (3M) model. It enables one to study an international co-operation to curb jointly CO{sub 2} emissions through a market of emission permits. Furthermore, from a decision support perspective, the 3M model can be used to integrate aspects of ecological sustainability (in relation to global climate change issue), economic welfare, efficient resource use and technological innovation. To solve 3M, we follow two alternative mathematical methods. (author) 4 refs.
Waste management system optimisation for Southern Italy with MARKAL model
Energy Technology Data Exchange (ETDEWEB)
Salvia, M.; Cosmi, C. [Istituto di Metodologie Avanzate di Analisi Ambientale, Consiglio Nazionale delle Ricerche, C. da S. Loja, 85050 (PZ) Tito Scalo (Italy); Macchiato, M. [Dipartimento di Scienze Fisiche, Universita Federico II, Via Cintia, 80126 Napoli (Italy); Mangiamele, L. [Dipartimento di Ingegneria e Fisica dell' Ambiente, Universita degli Studi della Basilicata, C. da Macchia Romana, 85100 Potenza (Italy)
2002-01-01
The MARKAL models generator was utilised to build up a comprehensive model of the anthropogenic activities system which points out the linkages between productive processes and waste disposal technologies. The aim of such a study is to determine the optimal configuration of the waste management system for the Basilicata region (Southern Italy), in order to support the definition of the regional waste management plan in compliance with the Italian laws. A sensitivity analysis was performed to evaluate the influence of landfilling fees on the choice of waste processing technologies, in order to foster waste management strategies which are environmentally sustainable, economically affordable and highly efficient. The results show the key role of separate collection and mechanical pre-treatments in the achievement of the legislative targets.
MARKAL-QUEBEC dictionary and data base
Energy Technology Data Exchange (ETDEWEB)
Haurie, A
1985-07-01
This two-part volume contains the data base of the MARKAL-QUEBEC energy modeling program. The first part, which constitutes the MARKAL dictionary, contains the list of all classes and their members. The second part contains the complete data set, presented as input tables to meet the requirements of the model. The tables are regrouped in sections in accordance with the class definition: in this way, one can find successively the tables SRC, CON, PRC, DMD, and ADRATIO (one table TCH is associated with each of the first four classes). At the beginning of each section, a brief description of the input data is given.
Exploring some Australian energy alternatives using MARKAL
Energy Technology Data Exchange (ETDEWEB)
Musgrove, A.R.D.; Stocks, K.J.; Essam, P.; Le, D.; Hoetzl, J.V.
1983-01-01
MARKAL is a linear programming model for the optimisation of the technologies associated with energy supply and demand within the complete energy system of a country as it evolves over a given time period. It was developed in the course of a project sponsored by the International Energy Agency, which was carried out at two main centres: Kernforschungsanlage, Juelich, FRG, and Brookhaven National Laboratory, Upton, New York, USA, Australia's participation in the Project has enabled the latest version of MARKAL to be installed on the computer at the Lucas Heights Research Laboratories together with the necessary supporting software programs.
Analytical study for Japan's energy system with MARKAL model
International Nuclear Information System (INIS)
Koyama, Shigeo; Kashihara, Toshinori; Endo, Eiichi
1984-01-01
Taking part in the 1982 collaboration activity of the Energy Technology Systems Analysis Project (ETSAP), which was started in November, 1980 by the International Energy Agency (IEA), the authors have analyzed extensive scenarios, including common scenarios of the Project, using a version of energy system model MARKAL programmed by their group and input data set up with various ideas. Important points to be considered in conducting the analysis and noteworthy results obtained from the analysis of Japan's energy systems are given. (AUTHOR)
International Nuclear Information System (INIS)
Vaillancourt, K.; Kanudia, A.
2004-01-01
The World-MARKAL model was used to examine a permit trading system to stabilize greenhouse gas emissions. The model considered the participation of all countries, including developing countries. Allocation schemes aimed at fair distribution of net abatement costs among world regions were proposed. The net abatement costs for each region are good indicators of where more abatement measures are needed. Equity issues relative to permit allocations and burden sharing were also presented along with the allocation methodology. The gross abatement costs before permit trading were calculated for each region. The main advantages and disadvantages of this approach were listed. It was concluded that permit allocation schemes based on cost distribution make it possible to obtain solutions with equalized net costs per gross domestic product for all regions. 30 refs., 6 tabs., 3 figs
International Nuclear Information System (INIS)
Builes J, Luis A; Franco M, Cristina; Rave Claudia C
2008-01-01
For the integrated analysis and assessment of the air quality improvement guidelines in the Aburra Valley region and its municipality Itagui, it is used a multi-period optimization model Markal for an Energy-Environment-Economy scenario analysis on industry and transport sector and, a Targets evaluation methodology for policy assessment on air quality, environmental noise and morbidity. The methodological approach offers the possibility to integrate different variables and decisions to analyze this very complex problem, review different technological scenarios and to analyze their relationships with land use policies among others. The results provide a more integrated panorama of the air quality problematic to policy design and assessment including externalises indicators. The proposed methodology is replicable in other municipalities of the region.
International Nuclear Information System (INIS)
Contreras, A.; Guervos, E.; Posso, F.
2009-01-01
Nobody can doubt today that hydrogen will, in the not-too-distant future, represent a very significant percentage of the total energy used by the transport sector. This study therefore consists of the modelling and simulation of energy consumption, by type of vehicle and fuel or energetic vector, in the road transport sector of the Madrid Region, during the period 2010-2050, using the MARKAL model. It has been necessary to complete this model by adding numerous specifications in order to determine the features of the Madrid Region, the richest Region in Spain. For the purpose of the study, three growth scenarios, based on short-term energy forecasts made by different official organizations, have been proposed for the energy consumption of the road transport sector in the Region. The results show a profound change in the current situation as there is a significant decrease in the consumption of fossil fuels and an increase in that of alternative non-fossil fuels and hydrogen. The latter, in particular, will rise from 0.1% in the year 2010, to around 50% in the year 2050, which will mean a drastic drop in the sector's CO 2 and atmospheric pollutant emissions. (author)
Biomass resources for energy in Ohio: The OH-MARKAL modeling framework
Shakya, Bibhakar
The latest reports from the Intergovernmental Panel on Climate Change have indicated that human activities are directly responsible for a significant portion of global warming trends. In response to the growing concerns regarding climate change and efforts to create a sustainable energy future, biomass energy has come to the forefront as a clean and sustainable energy resource. Biomass energy resources are environmentally clean and carbon neutral with net-zero carbon dioxide (CO2) emissions, since CO2 is absorbed or sequestered from the atmosphere during the plant growth. Hence, biomass energy mitigates greenhouse gases (GHG) emissions that would otherwise be added to the environment by conventional fossil fuels, such as coal. The use of biomass resources for energy is even more relevant in Ohio, as the power industry is heavily based on coal, providing about 90 percent of the state's total electricity while only 50 percent of electricity comes from coal at the national level. The burning of coal for electricity generation results in substantial GHG emissions and environmental pollution, which are responsible for global warming and acid rain. Ohio is currently one of the top emitters of GHG in the nation. This dissertation research examines the potential use of biomass resources by analyzing key economic, environmental, and policy issues related to the energy needs of Ohio over a long term future (2001-2030). Specifically, the study develops a dynamic linear programming model (OH-MARKAL) to evaluate biomass cofiring as an option in select coal power plants (both existing and new) to generate commercial electricity in Ohio. The OH-MARKAL model is based on the MARKAL (MARKet ALlocation) framework. Using extensive data on the power industry and biomass resources of Ohio, the study has developed the first comprehensive power sector model for Ohio. Hence, the model can serve as an effective tool for Ohio's energy planning, since it evaluates economic and environmental
Energy Technology Data Exchange (ETDEWEB)
Contreras, A.; Guervos, E. [Chemical Engineering Department, Universidad Nacional de Educacion a Distancia (UNED), Juan del Rosal 12, Madrid 28040 (Spain); Posso, F. [Science Department, ULA - Tachira, San Cristobal 5001 (Venezuela)
2009-01-15
Nobody can doubt today that hydrogen will, in the not-too-distant future, represent a very significant percentage of the total energy used by the transport sector. This study therefore consists of the modelling and simulation of energy consumption, by type of vehicle and fuel or energetic vector, in the road transport sector of the Madrid Region, during the period 2010-2050, using the MARKAL model. It has been necessary to complete this model by adding numerous specifications in order to determine the features of the Madrid Region, the richest Region in Spain. For the purpose of the study, three growth scenarios, based on short-term energy forecasts made by different official organizations, have been proposed for the energy consumption of the road transport sector in the Region. The results show a profound change in the current situation as there is a significant decrease in the consumption of fossil fuels and an increase in that of alternative non-fossil fuels and hydrogen. The latter, in particular, will rise from 0.1% in the year 2010, to around 50% in the year 2050, which will mean a drastic drop in the sector's CO{sub 2} and atmospheric pollutant emissions. (author)
Energy scenarios for the nordic region towards 2035
Energy Technology Data Exchange (ETDEWEB)
Fidje, Audun
2008-07-01
This report summarizes the assumptions, methodology and main results of the MARKAL analysis of options for a sustainable energy future in the Nordic region. The work is based on the Nordic MARKAL model, which has been modified such that it may be used to analyse a large number of scenarios, typically 500 to 5000. The scenarios are developed by analysis a set of strategies and uncertainties. All these strategies and uncertainties are combined such that we generate in total 1 152 scenarios. The main purpose of generating a large number of scenarios was to facilitate for multi-criteria trade-off analysis. Overall results from this analysis show that large reductions of CO{sub 2} emissions are possible at CO{sub 2} cost below 50 EUR/t CO{sub 2} (author)
International Nuclear Information System (INIS)
Hu, Ming-Che; Hobbs, Benjamin F.
2010-01-01
Investments in power generation, pollution controls, and electricity end use equipment are made in the face of uncertainty. Unanticipated events can cause regret-commitments that in retrospect were the wrong choices. We analyze how three uncertainties-electricity demand growth, natural gas prices, and power sector greenhouse gas regulations-could affect electric power sector investment decisions and costs in the U.S. over the next four decades. The effect of multi-pollutant regulations such as the Clean Air Interstate Rule (CAIR) upon these decisions and costs is also considered. We use decision trees to structure the problem, defining multiple futures for each uncertainty and then simulating how the U.S. energy market responds to them. A two-stage stochastic version of the energy-economy model MARKAL simulates the market. Relative importance of the uncertainties is assessed using two indices: expected cost of ignoring uncertainty (ECIU) and expected value of perfect information (EVPI). We also calculate the value of policy coordination (VPC), the cost saved by avoiding surprise changes in policy. An example shows how a stochastic program can be used to compute these indices. The analysis shows that the possibility of greenhouse gas regulation is the most important uncertainty by these measures.
Integrated economic assessment of energy and forestry mitigation options using MARKAL
International Nuclear Information System (INIS)
1998-01-01
There have been a number of economic assessment of GHG mitigation studies carried out in Indonesia. Several alternative mitigation options for energy and non-energy sectors have been described and the economic assessment of the options has been done for each sectors. However, most of the economic assessment particularly for non-energy sector, was not to find a least cost option but the lowest cost options. A program called MARKAL developed by a consortium of energy specialists from more than a dozen countries in the early 1980s, is a program that can be used for optimization, so that the least cost options could be selected. Indonesia has used this program intensively for energy system analysis. Attempt to use this program for other sector has not been developed as this program was designed for energy sector. Therefore, using MARKAL for other sector, all activities of the other sectors should be treated as energy activities. This study is aimed to use MARKAL for analysing both energy and forestry sector together. This paper described briefly the methodology of using MARKAL for both energy and forestry sectors. As the activities in energy sector have unique characteristics, thus only forest activities are described in more detail. (au)
EPAUS9R - An Energy Systems Database for use with the Market Allocation (MARKAL) Model
EPA’s MARKAL energy system databases estimate future-year technology dispersals and associated emissions. These databases are valuable tools for exploring a variety of future scenarios for the U.S. energy-production systems that can impact climate change c
An analysis of energy strategies for CO2 emission reduction in China. Case studies by MARKAL model
International Nuclear Information System (INIS)
Li Guangya
1994-12-01
The China's energy system has been analyzed by using the MARKAL model in this study and the time period is from the year 1990 to 2050. The MARKAL model is applied here to evaluate the cost effective energy strategies for CO 2 emission reduction in China. Firstly the Reference Energy System (RES) of China and its database were established, and the useful energy demand was projected on the basis of China's economic target and demographic forecasting. Four scenarios, BASE1-BASE4 were defined with different assumptions of crude oil and natural uranium availability. Analytical results show that without CO 2 emission constrains coal consumption will continue to hold a dominant position in primary energy supply, and CO 2 emissions in 2050 will be 9.55 BtCO 2 and 10.28 BtCO 2 with different natural uranium availability. Under the CO 2 emission constraints, nuclear and renewable energy will play important roles in CO 2 emission reduction, and feasible maximum CO 2 emission reduction estimated by this study is 3.16 BtCO 2 in 2050. The cumulative CO 2 emission from 1990 to 2050 will be 418.25 BtCO 2 and 429.16 BtCO 2 with different natural uranium availability. Total feasible maximum CO 2 emission reduction from 1990 to 2050 is 95.97 BtCO 2 . (author)
Biomass for energy or materials? A Western European MARKAL MATTER 1.0 model characterization
International Nuclear Information System (INIS)
Gielen, D.J.; Gerlagh, T.; Bos, A.J.M.
1998-12-01
The structure and input data for the biomass module of the MATTER 1.0 model, a MARKAL energy and materials systems engineering model for Western Europe, is discussed. This model is used for development of energy and materials strategies for greenhouse gas emission reduction. Preliminary biomass results are presented in order to identify key processes and key parameters that deserve further analysis. The results show that the production of biomaterials is an attractive option for the reduction of greenhouse gas emissions. Biomaterials can substitute materials which require a lot of energy for production or they can substitute fossil fuel feedstocks. Increased biomaterials production will result in increasing amounts of waste biomass which can be used for energy production. An increase of the use of biomass for the production of materials needs more attention in the forthcoming BRED analysis. 93 refs
MARKAL SCENARIO ANALYSES OF TECHNOLOGY OPTIONS FOR THE ELECTRIC SECTOR: THE IMPACT ON AIR QUALITY
This report provides a general overview of EPA’s national MARKAL database and energy systems model and compares various scenarios to a business as usual baseline scenario. Under baseline assumptions, total electricity use increases 1.3% annually until 2030. Annual growth in ele...
Phase II - final report of MARKAL studies for the United Kingdom
International Nuclear Information System (INIS)
Finnis, M.W.
1980-10-01
A system analysis approach to the assessment of comparative cost and energy contributions of some new technologies is presented. The work reported here refers to the energy system of the United Kingdom, and was carried out within the context of a multi-national R and D Strategy Project. The main tool of analysis is the linear program MARKAL, the function and method of operation of which are described briefly. A range of 14 scenarios is analysed, covering various assumption about the availability of oil, of nuclear power, and of the new technologies themselves. The input data used are described in detail. An overall view of the results is obtained in terms of the trade-off between independence from imported oil and total extra cost, and a cross-section of the detailed results is presented to illustrate and analyse the role of a number of new technologies. (orig.) [de
International Nuclear Information System (INIS)
McDowall, Will; Anandarajah, Gabrial; Dodds, Paul E.; Tomei, Julia
2012-01-01
Bioenergy is an important renewable energy resource. However, assessments of the future of bioenergy are beset with uncertainty and contested values, suggesting that a precautionary approach to bioenergy resource development may be warranted. This paper uses UK MARKAL to examine the implications of adopting a precautionary approach to bioenergy development in the UK. The paper reports a detailed review of UK bioenergy resources and sustainability constraints, and develops precautionary and optimistic resource scenarios. The paper then examines the implications of these scenarios using the energy systems model MARKAL, finding that a precautionary approach adds to the cost of decarbonisation, but does not significantly alter the optimal technology mix. In particular, biomass and co-firing CCS emerge as optimal technologies across scenarios. The question of UK land availability for bioenergy production is highlighted within the paper. With less land available for bioenergy production, the costs of decarbonisation will rise; whereas if more land is available for bioenergy, then less land is available for either food production or ecosystem conservation. This paper quantifies one side of this trade-off, by estimating the additional costs incurred when UK land availability for bioenergy production is constrained. - Highlights: ► We assess UK bioenergy resources under optimistic and precautionary approaches. ► Using MARKAL, we find that sustainability constraints add to decarbonisation costs. ► Preferred use of bioenergy is similar in optimistic and precautionary cases. ► Best use of bioenergy is heat and power, not transport, if CCS is available. ► The marginal value of additional land availability to the energy system is high.
Market penetration analysis of fuel cell vehicles in Japan by using the energy system model MARKAL
International Nuclear Information System (INIS)
Endo, Eiichi
2007-01-01
The objective of the present work is to validate the hydrogen energy roadmap of Japan by analyzing the market penetration of fuel cell vehicles (FCVs) and the effects of a carbon tax using an energy system model of Japan based on MARKAL. The results of the analysis show that a hydrogen FCV would not be cost competitive until 2050 without a more severe carbon tax than the government's planned 2400 JPY/t-C carbon tax. However, as the carbon tax rate increases, instead of conventional vehicles including the gasoline hybrid electric vehicle, hydrogen FCVs gain market penetration earlier and more. By assuming a more severe carbon tax rate, such as 10 000 JPY/t-C, the market share of hydrogen FCVs approaches the governmental goal. This suggests that cheaper vehicle cost and hydrogen cost than those targeted in the roadmap should be attained or subsidies to hydrogen FCV and hydrogen refueling station will be necessary for achieving the goal of earlier market penetration. (author)
International Nuclear Information System (INIS)
Jiang Binbin; Wenying, Chen; Yu Yuefeng; Zeng Lemin; Victor, David
2008-01-01
Natural gas could possibly become a si0gnificant portion of the future fuel mix in China. However, there is still great uncertainty surrounding the size of this potential market and therefore its impact on the global gas trade. In order to identify some of the important factors that might drive natural gas consumption in key demand areas in China, we focus on three regions: Beijing, Guangdong, and Shanghai. Using the economic optimization model MARKAL, we initially assume that the drivers are government mandates of emissions standards, reform of the Chinese financial structure, the price and available supply of natural gas, and the rate of penetration of advanced power generating and end-use. The results from the model show that the level of natural gas consumption is most sensitive to policy scenarios, which strictly limit SO 2 emissions from power plants. The model also revealed that the low cost of capital for power plants in China boosts the economic viability of capital-intensive coal-fired plants. This suggests that reform within the financial sector could be a lever for encouraging increased natural gas use
Directory of Open Access Journals (Sweden)
Anandarajah Gabrial
2009-07-01
Full Text Available Abstract Background This work explores the potential contribution of bioenergy technologies to 60% and 80% carbon reductions in the UK energy system by 2050, by outlining the potential for accelerated technological development of bioenergy chains. The investigation was based on insights from MARKAL modelling, detailed literature reviews and expert consultations. Due to the number and complexity of bioenergy pathways and technologies in the model, three chains and two underpinning technologies were selected for detailed investigation: (1 lignocellulosic hydrolysis for the production of bioethanol, (2 gasification technologies for heat and power, (3 fast pyrolysis of biomass for bio-oil production, (4 biotechnological advances for second generation bioenergy crops, and (5 the development of agro-machinery for growing and harvesting bioenergy crops. Detailed literature searches and expert consultations (looking inter alia at research and development needs and economic projections led to the development of an 'accelerated' dataset of modelling parameters for each of the selected bioenergy pathways, which were included in five different scenario runs with UK-MARKAL (MED. The results of the 'accelerated runs' were compared with a low-carbon (LC-Core scenario, which assesses the cheapest way to decarbonise the energy sector. Results Bioenergy was deployed in larger quantities in the bioenergy accelerated technological development scenario compared with the LC-Core scenario. In the electricity sector, solid biomass was highly utilised for energy crop gasification, displacing some deployment of wind power, and nuclear and marine to a lesser extent. Solid biomass was also deployed for heat in the residential sector from 2040 in much higher quantities in the bioenergy accelerated technological development scenario compared with LC-Core. Although lignocellulosic ethanol increased, overall ethanol decreased in the transport sector in the bioenergy
Modelling innovation performance of European regions using multi-output neural networks.
Hajek, Petr; Henriques, Roberto
2017-01-01
Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.
Modelling innovation performance of European regions using multi-output neural networks.
Directory of Open Access Journals (Sweden)
Petr Hajek
Full Text Available Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.
Robu, Sergiu; Bikova, Elena; Siakkis, Philip; Giannakidis, George
2010-01-01
The paper presents results of analyses of energy efficiency measures and renewable energy sources implementation in the Republic of Moldova using MARKAL model. Detailed analyses of four scenarios are presented for: Reference Scenario; Energy Efficiency Scenario; Renewable Energy Sources Scenario; Energy Efficiency&Renewable Energy Scenario. Energy savings and costs are identified for implementation of renewable energy sources and Energy efficiency measures.
CONSTRUCTING A MULTI-REGIONAL SOCIAL ACCOUNTING MATRIX FOR TURKEY
Directory of Open Access Journals (Sweden)
Metin Piskin
2017-12-01
Full Text Available Regional impacts of public policies in Turkey have led to Regional Development Agencies and related institutions having responsibility for setting and achieving sustainability policies at the regional level. As a result, there is a significant interest in developing empirical models that can deal with the macro, micro and regional impacts of economic policies and interregional spillover effects. Spatial or Multi-Regional Computable General Equilibrium models are the most capable models to handle a wide range of policy relevant regional questions and the effects of policies on a comprehensive set of regional and national economic variables. However, an important ingredient in meeting the Multi-Regional CGE analysis is Multi-Regional Social Accounting Matrices. This study is focusing on the building the first Multi-Regional Social Accounting Matrix for Turkey with 11 regions and 8 sectors. We utilize from the most updated available datasets and implement the most conveninent non-survey methods which fit to data availability in Turkey.
A scenario analysis of investment options for the Cuban power sector using the MARKAL model
International Nuclear Information System (INIS)
Wright, Evelyn L.; Belt, Juan A.B.; Chambers, Adam; Delaquil, Pat; Goldstein, Gary
2010-01-01
The Cuban power sector faces a need for extensive investment in new generating capacity, under a large number of uncertainties regarding future conditions, including: rate of demand growth, fluctuations in fuel prices, access to imported fuel, and access to investment capital for construction of new power plants and development of fuel import infrastructure. To identify cost effective investment strategies under these uncertainties, a supply and power sector MARKAL model was assembled, following an extensive review of available data on the Cuban power system and resource potentials. Two scenarios were assessed, a business-as-usual (BAU) scenario assuming continued moderate electricity load growth and domestic fuel production growth, and a high growth (HI) scenario assuming rapid electricity demand growth, rapid increase in domestic fuel production, and a transition to market pricing of electricity. Within these two scenarios sets, sensitivity analyses were conducted on a number of variables. The implications of least-cost investment strategies for new capacity builds, investment spending requirements, electricity prices, fuel expenditures, and carbon dioxide emissions for each scenario were assessed. Natural gas was found to be the cost effective fuel for new generation across both scenarios and most sensitivity cases, suggesting that access to natural gas, through increased domestic production and LNG import, is a clear priority for further analysis in the Cuban context.
A scenario analysis of investment options for the Cuban power sector using the MARKAL model
Energy Technology Data Exchange (ETDEWEB)
Wright, Evelyn L.; Chambers, Adam; Delaquil, Pat; Goldstein, Gary [International Resources Group, 1211 Connecticut Avenue, NW, Suite 700, Washington, DC 20036 (United States); Belt, Juan A.B. [US Agency for International Development, 1300 Pennsylvania Avenue, NW, Washington, DC 20523-3800 (United States)
2010-07-15
The Cuban power sector faces a need for extensive investment in new generating capacity, under a large number of uncertainties regarding future conditions, including: rate of demand growth, fluctuations in fuel prices, access to imported fuel, and access to investment capital for construction of new power plants and development of fuel import infrastructure. To identify cost effective investment strategies under these uncertainties, a supply and power sector MARKAL model was assembled, following an extensive review of available data on the Cuban power system and resource potentials. Two scenarios were assessed, a business-as-usual (BAU) scenario assuming continued moderate electricity load growth and domestic fuel production growth, and a high growth (HI) scenario assuming rapid electricity demand growth, rapid increase in domestic fuel production, and a transition to market pricing of electricity. Within these two scenarios sets, sensitivity analyses were conducted on a number of variables. The implications of least-cost investment strategies for new capacity builds, investment spending requirements, electricity prices, fuel expenditures, and carbon dioxide emissions for each scenario were assessed. Natural gas was found to be the cost effective fuel for new generation across both scenarios and most sensitivity cases, suggesting that access to natural gas, through increased domestic production and LNG import, is a clear priority for further analysis in the Cuban context. (author)
Energy Technology Data Exchange (ETDEWEB)
Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)
2012-07-15
We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)
The costs of mitigating carbon emissions in China: findings from China MARKAL-MACRO modeling
International Nuclear Information System (INIS)
Chen Wenying
2005-01-01
In this paper MARKAL-MACRO, an integrated energy-environment-economy model, is used to generate China's reference scenario for future energy development and carbon emission through the year 2050. The results show that with great efforts on structure adjustment, energy efficiency improvement and energy substitution, China's primary energy consumption is expected to be 4818 Mtce and carbon emission 2394 MtC by 2050 with annual decrease rate of 3% for the carbon intensity per GDP during the period 2000-2050. On the basis of this reference scenario, China's marginal abatement cost curves of carbon for the year 2010, 2020 and 2030 are derived from the model, and the impacts of carbon emission abatement on GDP are also simulated. The results are compared with those from other sources. The research shows that the marginal abatement costs vary from 12US$/tC to 216US$/tC and the rates of GDP losses relative to reference range from 0.1% to 2.54% for the reduction rates between 5% and 45%. Both the marginal abatement costs and the rates of GDP losses further enlarge on condition that the maximum capacity of nuclear power is constrained to 240 GW or 160 GW by 2050. The paper concludes that China's costs of carbon abatement is rather high in case of carbon emissions are further cut beyond the reference scenario, and China's carbon abatement room is limited due to her coal-dominant energy resource characteristic. As economic development still remains the priority and per capita income as well as per capita carbon emission are far below the world average, it will be more realistic for China to make continuous contributions to combating global climate change by implementing sustainable development strategy domestically and playing an active role in the international carbon mitigation cooperation mechanisms rather than accepting a carbon emission ceiling
A Multi-Region Model of Economic Growth with Human Capital and Negative Externalities in Innovation
Batabyal, A.; Nijkamp, P.
2013-01-01
We use a multi-region model and provide the first theoretical analysis of the effects of human capital use and a particular kind of innovative activity on economic growth. In each of the N heterogeneous regions in our model, consumers have constant relative risk aversion preferences, there are
Erfanian, A.; Fomenko, L.; Wang, G.
2016-12-01
Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling
Energy Technology Data Exchange (ETDEWEB)
Barreto, L.; Kypreos, S.
1999-09-01
Understanding technology dynamics, a fundamental driving factor of the evolution of energy systems, is essential for sound policy formulation and decision making. Technological change is not an autonomous process, but evolves from a number of endogenous interactions within the social system. Technologies evolve and improve only if experience with them is possible. Efforts must be devoted to improve our analytical tools concerning the treatment given to the technological variable, recognising the cumulative and gradual nature of technological change and the important role played by learning processes. This report presents a collection of works developed by the authors concerning the endogenisation of technological change in energy optimisation models, as a contribution to the Energy Technology Dynamics andAdvanced Energy System Modelling Project (TEEM), developed in the framework of the Non Nuclear Energy Programme JOULE III of the European Union (DGXII). Here, learning curves, an empirically observed manifestation of the cumulative technological learning processes, are endogenised in two energy optimisation models. MARKAL, a widely used bottom-up model developed by the ETSAP programme of the IEA and ERIS, a model prototype, developed within the TEEM project for assessing different concepts and approaches. The methodological approach is described and some results and insights derived from the model analyses are presented. The incorporation of learning curves results in significantly different model outcomes than those obtained with traditional approaches. New, innovative technologies, hardly considered by the standard models, are introduced to the solution when endogenous learning is present. Up-front investments in initially expensive, but promising, technologies allow the necessary accumulation of experience to render them cost-effective. When uncertainty in emission reduction commitments is considered, the results point also in the direction of undertaking early
International Nuclear Information System (INIS)
Barreto, L.; Kypreos, S.
1999-09-01
Understanding technology dynamics, a fundamental driving factor of the evolution of energy systems, is essential for sound policy formulation and decision making. Technological change is not an autonomous process, but evolves from a number of endogenous interactions within the social system. Technologies evolve and improve only if experience with them is possible. Efforts must be devoted to improve our analytical tools concerning the treatment given to the technological variable, recognising the cumulative and gradual nature of technological change and the important role played by learning processes. This report presents a collection of works developed by the authors concerning the endogenisation of technological change in energy optimisation models, as a contribution to the Energy Technology Dynamics and Advanced Energy System Modelling Project (TEEM), developed in the framework of the Non Nuclear Energy Programme JOULE III of the European Union (DGXII). Here, learning curves, an empirically observed manifestation of the cumulative technological learning processes, are endogenised in two energy optimisation models. MARKAL, a widely used bottom-up model developed by the ETSAP programme of the IEA and ERIS, a model prototype, developed within the TEEM project for assessing different concepts and approaches. The methodological approach is described and some results and insights derived from the model analyses are presented. The incorporation of learning curves results in significantly different model outcomes than those obtained with traditional approaches. New, innovative technologies, hardly considered by the standard models, are introduced to the solution when endogenous learning is present. Up-front investments in initially expensive, but promising, technologies allow the necessary accumulation of experience to render them cost-effective. When uncertainty in emission reduction commitments is considered, the results point also in the direction of undertaking early
Zakary, Omar; Rachik, Mostafa; Elmouki, Ilias
2017-08-01
First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions.
Kang, S.; IM, E. S.; Eltahir, E. A. B.
2016-12-01
In this study, the future change in precipitation due to global warming is investigated over the Maritime Continent using the MIT Regional Climate Model (MRCM). A total of nine 30-year projections under multi-GCMs (CCSM, MPI, ACCESS) and multi-scenarios of emissions (Control, RCP4.5, RCP8.5) are dynamically downscaled using the MRCM with 12km horizontal resolution. Since downscaled results tend to systematically overestimate the precipitation regardless of GCM used as lateral boundary conditions, the Parametric Quantile Mapping (PQM) is applied to reduce this wet bias. The cross validation for the control simulation shows that the PQM method seems to retain the spatial pattern and temporal variability of raw simulation, however it effectively reduce the wet bias. Based on ensemble projections produced by dynamical downscaling and statistical bias correction, a reduction of future precipitation is discernible, in particular during dry season (June-July-August). For example, intense precipitation in Singapore is expected to be reduced in RCP8.5 projection compared to control simulation. However, the geographical patterns and magnitude of changes still remain uncertain, suffering from statistical insignificance and a lack of model agreement. Acknowledgements This research is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise programme. The Center for Environmental Sensing and Modeling is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology
A multi-model assessment of regional climate disparities caused by solar geoengineering
International Nuclear Information System (INIS)
Kravitz, Ben; Rasch, Philip J; Singh, Balwinder; Yoon, Jin-Ho; MacMartin, Douglas G; Robock, Alan; Ricke, Katharine L; Cole, Jason N S; Curry, Charles L; Irvine, Peter J; Ji, Duoying; Moore, John C; Keith, David W; Egill Kristjánsson, Jón; Muri, Helene; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting
2014-01-01
Global-scale solar geoengineering is the deliberate modification of the climate system to offset some amount of anthropogenic climate change by reducing the amount of incident solar radiation at the surface. These changes to the planetary energy budget result in differential regional climate effects. For the first time, we quantitatively evaluate the potential for regional disparities in a multi-model context using results from a model experiment that offsets the forcing from a quadrupling of CO 2 via reduction in solar irradiance. We evaluate temperature and precipitation changes in 22 geographic regions spanning most of Earth's continental area. Moderate amounts of solar reduction (up to 85% of the amount that returns global mean temperatures to preindustrial levels) result in regional temperature values that are closer to preindustrial levels than an un-geoengineered, high CO 2 world for all regions and all models. However, in all but one model, there is at least one region for which no amount of solar reduction can restore precipitation toward its preindustrial value. For most metrics considering simultaneous changes in both variables, temperature and precipitation values in all regions are closer to the preindustrial climate for a moderate amount of solar reduction than for no solar reduction. (letter)
Strategic research on CO2 emission reduction for China. Application of MARKAL to China energy system
International Nuclear Information System (INIS)
Wang Yongping
1995-09-01
MARKAL was applied to the energy system for analyzing the CO 2 emission reduction in China over the time period from 1990 to 2050. First the Chinese Reference Energy System (CRES) was established based on the framework of MARKAL model. The following conclusions can be drawn from this study. When shifting from scenario LH (low useful energy demand and high import fuel prices) to HL (high demand and low prices), another 33 EJ of primary energy will be consumed and another 2.31 billion tons of CO 2 will be emitted in 2050. Detailed analyses on the disaggregation of CO 2 emissions by Kaya Formula show. The energy intensity (primary energy/GDP) decreases much faster in scenario HL, but the higher growth rate of GDP per capita is the overwhelming factor that results in higher CO 2 emission per capita in the baseline case of scenario HL in comparison with LH. When the carbon taxes are imposed on CO 2 emissions, the residential sector will make the biggest contribution to CO 2 emission abatement from a long-term point of view. However, it's difficult to stabilize CO 2 emission per capita before 2030 in both scenarios even with heavy carbon taxes. When nuclear moratorium occurs, more 560 million tons of CO 2 will be emitted to the atmosphere in 2050 under the same CO 2 tax regime. From the analysis of value flow, CO 2 emission reduction depends largely on new or advanced technologies particularly in the field of electricity generation. The competent technologies switch to those CO 2 less-emitting technologies when surcharging CO 2 emissions. Nuclear power shows significant potential in saving fossil energy resources and reducing CO 2 emissions. (J.P.N.)
Energy Technology Data Exchange (ETDEWEB)
Yongping, Wang [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1995-09-01
MARKAL was applied to the energy system for analyzing the CO{sub 2} emission reduction in China over the time period from 1990 to 2050. First the Chinese Reference Energy System (CRES) was established based on the framework of MARKAL model. The following conclusions can be drawn from this study. When shifting from scenario LH (low useful energy demand and high import fuel prices) to HL (high demand and low prices), another 33 EJ of primary energy will be consumed and another 2.31 billion tons of CO{sub 2} will be emitted in 2050. Detailed analyses on the disaggregation of CO{sub 2} emissions by Kaya Formula show. The energy intensity (primary energy/GDP) decreases much faster in scenario HL, but the higher growth rate of GDP per capita is the overwhelming factor that results in higher CO{sub 2} emission per capita in the baseline case of scenario HL in comparison with LH. When the carbon taxes are imposed on CO{sub 2} emissions, the residential sector will make the biggest contribution to CO{sub 2} emission abatement from a long-term point of view. However, it`s difficult to stabilize CO{sub 2} emission per capita before 2030 in both scenarios even with heavy carbon taxes. When nuclear moratorium occurs, more 560 million tons of CO{sub 2} will be emitted to the atmosphere in 2050 under the same CO{sub 2} tax regime. From the analysis of value flow, CO{sub 2} emission reduction depends largely on new or advanced technologies particularly in the field of electricity generation. The competent technologies switch to those CO{sub 2} less-emitting technologies when surcharging CO{sub 2} emissions. Nuclear power shows significant potential in saving fossil energy resources and reducing CO{sub 2} emissions. (J.P.N.).
Directory of Open Access Journals (Sweden)
Tor A Johnsen
1996-07-01
Full Text Available In Norway, the system engineering model MARKAL and the macroeconomic model MSG-EE are both used in studies of national CO2 controlling strategies. MARKAL is a linear programming model that calculates a composite set of technologies necessary to meet demand and environmental constraints at minimised total energy expenditure. MSG-EE is an applied general equilibrium model including the link between economic activity, energy demand and emissions to air. MSG-EE has a theory consistent description of the link between income, prices and energy demand, but the representation of technological improvements is simple. MARKAL has a sophisticated description of future energy technology options, but includes no feedback to the general economy. A project for studying the potential for a coordinated use of these two models was initiated and funded by the Norwegian Research Council (NFR. This paper gives a brief presentation of the two models. Results from independent model calculations show that MARKAL gives a signficant lower residential energy demand than MSG-EE does. This is explained by major differences in modelling approach. A first attempt of coordinating the residential energy demand in the models is reported. This attempt shows that implementing results from MARKAL, in MSG-EE for the residential sector alone gives little impact on the general economy. A further development of an iteration procedure between the models should include all energy using sectors.
Jathar, S. H.; Cappa, C. D.; Wexler, A. S.; Seinfeld, J. H.; Kleeman, M. J.
2016-02-01
Multi-generational oxidation of volatile organic compound (VOC) oxidation products can significantly alter the mass, chemical composition and properties of secondary organic aerosol (SOA) compared to calculations that consider only the first few generations of oxidation reactions. However, the most commonly used state-of-the-science schemes in 3-D regional or global models that account for multi-generational oxidation (1) consider only functionalization reactions but do not consider fragmentation reactions, (2) have not been constrained to experimental data and (3) are added on top of existing parameterizations. The incomplete description of multi-generational oxidation in these models has the potential to bias source apportionment and control calculations for SOA. In this work, we used the statistical oxidation model (SOM) of Cappa and Wilson (2012), constrained by experimental laboratory chamber data, to evaluate the regional implications of multi-generational oxidation considering both functionalization and fragmentation reactions. SOM was implemented into the regional University of California at Davis / California Institute of Technology (UCD/CIT) air quality model and applied to air quality episodes in California and the eastern USA. The mass, composition and properties of SOA predicted using SOM were compared to SOA predictions generated by a traditional two-product model to fully investigate the impact of explicit and self-consistent accounting of multi-generational oxidation.Results show that SOA mass concentrations predicted by the UCD/CIT-SOM model are very similar to those predicted by a two-product model when both models use parameters that are derived from the same chamber data. Since the two-product model does not explicitly resolve multi-generational oxidation reactions, this finding suggests that the chamber data used to parameterize the models captures the majority of the SOA mass formation from multi-generational oxidation under the conditions
Symeonakis, Elias; Higginbottom, Thomas
2015-04-01
Accelerated soil erosion is the principal cause of soil degradation across the world. In Africa, it is seen as a serious problem creating negative impacts on agricultural production, infrastructure and water quality. Regarding the Mt Kenya region, specifically, soil erosion is a serious threat mainly due to unplanned and unsustainable practices linked to tourism, agriculture and rapid population growth. The soil types roughly correspond with different altitudinal zones and are generally very fertile due to their volcanic origin. Some of them have been created by eroding glaciers while others are due to millions of years of fluvial erosion. The soils on the mountain are easily eroded once exposed: when vegetation is removed, the soil quickly erodes down to bedrock by either animals or humans, as tourists erode paths and local people clear large swaths of forested land for agriculture, mostly illegally. It is imperative, therefore, that a soil erosion monitoring system for the Mt Kenya region is in place in order to understand the magnitude of, and be able to respond to, the increasing number of demands on this renewable resource. In this paper, we employ a simple regional-scale soil erosion modelling framework based on the Thornes model and suggest an operational methodology for quantifying and monitoring water runoff and soil erosion using multi-sensor and multi-temporal remote sensing data in a GIS framework. We compare the estimates of this study with general data on the severity of soil erosion over Kenya and with measured rates of soil loss at different locations over the area of study. The results show that the measured and estimated rates of erosion are generally similar and within the same order of magnitude. They also show that, over the last years, erosion rates are increasing in large parts of the region at an alarming rate, and that mitigation measures are needed to reverse the negative effects of uncontrolled socio-economic practices.
Modelling approaches to assess and design the deployment of CO2 capture, transport and storage
van den Broek, M.A.
2010-01-01
Chapter 2 presents a quantitative scenario study for the electricity and cogeneration sector in the Netherlands using MARKAL-NL-UU. This model is specifically developed for this research and is a dynamic bottom-up energy model with special CCS features generated with MARKAL. The focus of this
International Nuclear Information System (INIS)
Mundaca, Luis; Santi, Federico
2004-01-01
This report summarises the modelling exercise carried out in order to assess the implications of selected policy instruments using the energy model of Western Europe (WEU) generated by the Market Allocation (MARKAL) modelling tool. The chosen methodology was the usage of the WEU MARKAL model for analysing the response of this energy system to the following policy instruments: White Certificates, Green Certificates, and Carbon Dioxide (CO 2 ) emissions trading. Results show that the order of magnitude of the effects of the analysed instruments depends on the target/cap that is applied. For the case of White Certificates, it can be observed that up to certain level (i.e., around 15% of cumulated energy savings by 2020 compared to the base case) energy savings are obtained at negative costs. Major savings occur in the residential sector for all the applied targets. Results for CO 2 emissions appear to be robust for the years 2015 and 2020, but it should also be observed that these emission trends are less robust for the years 2005 and 2010. Energy efficiency improvements for the WEU economy that are policy-induced around 6%, 9% and 15% for the low, medium and high target scenarios respectively. For the case of Green Certificates, results show that the sustained penetration of renewable energy sources is dominated by wind and biomass. By examining the autonomous fossil fuel intensity of the WEU economy, energy efficiency improvements that are policy induced account for around 1%, 4% and 6% for each scenario respectively. All the targets are technically possible. For the case of CO 2 emissions trading, due to the fact that these results address just the power sector, they must be seen as complementary of other modelling works that deal with a wider industrial coverage. In our case, the more ambitious the cap is, the lower the share of fossil fuels in electricity production becomes. The different trends for the electricity production seem to be less robust. Compared to
Multi-objective optimization for generating a weighted multi-model ensemble
Lee, H.
2017-12-01
Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic
Multi-region relaxed magnetohydrodynamics with flow
Energy Technology Data Exchange (ETDEWEB)
Dennis, G. R., E-mail: graham.dennis@anu.edu.au; Dewar, R. L.; Hole, M. J. [Research School of Physics and Engineering, Australian National University, ACT 0200 (Australia); Hudson, S. R. [Princeton Plasma Physics Laboratory, PO Box 451, Princeton, New Jersey 08543 (United States)
2014-04-15
We present an extension of the multi-region relaxed magnetohydrodynamics (MRxMHD) equilibrium model that includes plasma flow. This new model is a generalization of Woltjer's model of relaxed magnetohydrodynamics equilibria with flow. We prove that as the number of plasma regions becomes infinite, our extension of MRxMHD reduces to ideal MHD with flow. We also prove that some solutions to MRxMHD with flow are not time-independent in the laboratory frame, and instead have 3D structure which rotates in the toroidal direction with fixed angular velocity. This capability gives MRxMHD potential application to describing rotating 3D MHD structures such as 'snakes' and long-lived modes.
Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan
2017-04-01
Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.
Directory of Open Access Journals (Sweden)
S. H. Jathar
2016-02-01
Full Text Available Multi-generational oxidation of volatile organic compound (VOC oxidation products can significantly alter the mass, chemical composition and properties of secondary organic aerosol (SOA compared to calculations that consider only the first few generations of oxidation reactions. However, the most commonly used state-of-the-science schemes in 3-D regional or global models that account for multi-generational oxidation (1 consider only functionalization reactions but do not consider fragmentation reactions, (2 have not been constrained to experimental data and (3 are added on top of existing parameterizations. The incomplete description of multi-generational oxidation in these models has the potential to bias source apportionment and control calculations for SOA. In this work, we used the statistical oxidation model (SOM of Cappa and Wilson (2012, constrained by experimental laboratory chamber data, to evaluate the regional implications of multi-generational oxidation considering both functionalization and fragmentation reactions. SOM was implemented into the regional University of California at Davis / California Institute of Technology (UCD/CIT air quality model and applied to air quality episodes in California and the eastern USA. The mass, composition and properties of SOA predicted using SOM were compared to SOA predictions generated by a traditional two-product model to fully investigate the impact of explicit and self-consistent accounting of multi-generational oxidation.Results show that SOA mass concentrations predicted by the UCD/CIT-SOM model are very similar to those predicted by a two-product model when both models use parameters that are derived from the same chamber data. Since the two-product model does not explicitly resolve multi-generational oxidation reactions, this finding suggests that the chamber data used to parameterize the models captures the majority of the SOA mass formation from multi-generational oxidation under
International Nuclear Information System (INIS)
De Feber, M.A.P.C.; Schaeffer, G.J.; Seebregts, A.J.; Smekens, K.E.L.
2003-04-01
The primary topic of the SAPIENT project and its predecessor TEEM has been the issue of incorporating technology learning endogenously in energy models and trying to determine the impact of public R and D on this learning process. ECN has incorporated the learning mechanism into the MARKAL model using an extended database for the Western Europe energy system. By using advanced modelling techniques (Mixed Integer Programming) and the concepts of key components and technology clusters more than 60 technologies in the power sector have been endowed with learning characteristics. By this approach solving times could be kept within a reasonable length, i.e. less than 20 minutes per run. An important insight gained from model runs with many learning technologies, including conventional technologies, is that new technologies aiming to 'beat' conventional ones are aiming at a 'moving target'. Also conventional technologies can learn, and this aspect makes it much more difficult for new sustainable technologies to penetrate the market in the model. By using a Monte Carlo approach uncertainties in important learning parameters could be analysed. It appeared for instance that the main factor that determines the uncertainty on floor costs for photovoltaic (PV) energy production is the uncertainty in the PV progress ratio. One of the main targets of the SAPIENT project was to find ways to model the effect of R and D on technology learning. ECN has explored an approach to capture this effect by assuming a relationship between the R and D-intensity of a technology and its progress ratio. Following this approach it was found that uncertainties in the overall progress ratio are often higher than the effect additional R and D can have on a certain technology. Also, model outcomes depended rather on the carbon prices used in the scenarios than on the enhancement of learning by R and D. This suggests that a stimulus for sustainable technologies cannot be reached by R and D
Multi-region relaxed magnetohydrodynamics with anisotropy and flow
Energy Technology Data Exchange (ETDEWEB)
Dennis, G. R., E-mail: graham.dennis@anu.edu.au; Dewar, R. L.; Hole, M. J. [Research School of Physics and Engineering, Australian National University, Canberra, Australian Capital Territory 0200 (Australia); Hudson, S. R. [Princeton Plasma Physics Laboratory, PO Box 451, Princeton, New Jersey 08543 (United States)
2014-07-15
We present an extension of the multi-region relaxed magnetohydrodynamics (MRxMHD) equilibrium model that includes pressure anisotropy and general plasma flows. This anisotropic extension to our previous isotropic model is motivated by Sun and Finn's model of relaxed anisotropic magnetohydrodynamic equilibria. We prove that as the number of plasma regions becomes infinite, our anisotropic extension of MRxMHD reduces to anisotropic ideal MHD with flow. The continuously nested flux surface limit of our MRxMHD model is the first variational principle for anisotropic plasma equilibria with general flow fields.
Assessment and simulation tools for sustainable energy systems theory and applications
Cavallaro, Fausto
2013-01-01
This book covers both simulations using markal model and linear programming (LP) and methods and applications of multi-criteria, fuzzy-sets, algorithm genetics and neural nets (artificial intelligence) to energy systems.
McLeod, Jeffrey
The recent increase in U.S. natural gas production made possible through advancements in extraction techniques including hydraulic fracturing has transformed the U.S. energy supply landscape while raising questions regarding the balance of environmental impacts associated with natural gas production and use. Impact areas at issue include emissions of methane and criteria pollutants from natural gas production, alongside changes in emissions from increased use of natural gas in place of coal for electricity generation. In the Rocky Mountain region, these impact areas have been subject to additional scrutiny due to the high level of regional oil and gas production activity and concerns over its links to air quality. Here, the MARKAL (MArket ALlocation) least-cost energy system optimization model in conjunction with the EPA-MARKAL nine-region database has been used to characterize future regional and national emissions of CO 2, CH4, VOC, and NOx attributed to natural gas production and use in several sectors of the economy. The analysis is informed by comparing and contrasting a base case, business-as-usual scenario with scenarios featuring variations in future natural gas supply characteristics, constraints affecting the electricity generation mix, carbon emission reduction strategies and increased demand for natural gas in the transportation sector. Emission trends and their associated sensitivities are identified and contrasted between the Rocky Mountain region and the U.S. as a whole. The modeling results of this study illustrate the resilience of the short term greenhouse gas emission benefits associated with fuel switching from coal to gas in the electric sector, but also call attention to the long term implications of increasing natural gas production and use for emissions of methane and VOCs, especially in the Rocky Mountain region. This analysis can help to inform the broader discussion of the potential environmental impacts of future natural gas production
Directory of Open Access Journals (Sweden)
Shasha Lu
2015-10-01
Full Text Available A large body of recent studies—from both inside and outside of China—are devoted to the understanding of China’s regional inequality. The current study introduces “the spatial field model” to achieve comprehensive evaluation and multi-scale analysis of regional inequality. The model is based on the growth pole theory, regional interaction theory, and energy space theory. The spatial field is an abstract concept that defines the potential energy difference that is formed in the process of a regional growth pole driving the economic development of peripheral areas through transportation and communication corridors. The model is able to provide potentially more precise regional inequality estimates and generates isarithmic maps that will provide highly intuitive and visualized presentations. The model is applied to evaluate the spatiotemporal pattern of economic inequality in China from 2000 to 2012 amongst internal eastern-central-western regions as well as north-south regions at three geographical scales—i.e., inter-province, inter-city, and inter-county. The results indicate that the spatial field model could comprehensively evaluate regional inequality, provide aesthetically pleasing and highly adaptable presentations based on a pixel-based raster, and realise the multi-scale analyses of the regional inequality. The paper also investigates the limitations and extensions of the spatial field model in future application.
Fournier, N.; Tang, Y.S.; Dragosits, U.; Kluizenaar, Y.de; Sutton, M.A.
2005-01-01
Atmospheric budgets of reduced nitrogen for the major political regions of the British Isles are investigated with a multi-layer atmospheric transport model. The model is validated against measurements of NH3 concentration and is developed to provide atmospheric budgets for defined subdomains of the
International Nuclear Information System (INIS)
Koltsaklis, Nikolaos E.; Liu, Pei; Georgiadis, Michael C.
2015-01-01
The power sector faces a rapid transformation worldwide from a dominant fossil-fueled towards a low carbon electricity generation mix. Renewable energy technologies (RES) are steadily becoming a greater part of the global energy mix, in particular in regions that have put in place policies and measures to promote their utilization. This paper presents an optimization-based approach to address the generation expansion planning (GEP) problem of a large-scale, central power system in a highly uncertain and volatile electricity industry environment. A multi-regional, multi-period linear mixed-integer linear programming (MILP) model is presented, combining optimization techniques with a Monte Carlo (MCA) method and demand response concepts. The optimization goal concerns the minimization of the total discounted cost by determining optimal power capacity additions per time interval and region, and the power generation mix per technology and time period. The model is evaluated on the Greek power system (GPS), taking also into consideration the scheduled interconnection of the mainland power system with those of selected autonomous islands (Cyclades and Crete), and aims at providing full insight into the composition of the long-term energy roadmap at a national level. - Highlights: • A spatial, multi-period, long-term generation expansion planning model is presented. • A Monte-Carlo method along with a demand response mechanism are incorporated. • Autonomous power systems interconnection is considered. • Electricity and CO 2 emission trade are taken into account. • Lignite, natural gas and wind power comprise the dominant power technologies
International Nuclear Information System (INIS)
Djemaa, A.
2009-01-01
Among the energy users in France and Europe, some industrial sectors are very important and should have a key role when assessing the final energy demand patterns in the future. The aim of our work is to apply a prospective model for the long range analysis of energy/technology choices in the industrial sector, focussing on the energy-intensive sectors. The modelling tool applied in this study is the TIMES model (family of best known MARKAL model). It is an economic linear programming model generator for local, national or multi regional energy systems, which provides a technology-rich basis for estimating energy dynamics over a long term, multi period time. We illustrate our work with nine energy-intensive industrial sectors: paper, steel, glass, cement, lime, tiles, brick, ceramics and plaster. It includes a detailed description of the processes involved in the production of industrial products, providing typical energy uses in each process step. In our analysis, we identified for each industry, several commercially available state-of-the-art technologies, characterized and chosen by the Model on the basis of cost effectiveness. Furthermore, we calculated potential energy savings, carbon dioxide emissions' reduction and we estimated the energy impact of a technological rupture. This work indicates that there still exists a significant potential for energy savings and carbon dioxide emissions' reduction in all industries. (author)
International Nuclear Information System (INIS)
Rout, Ullash K.; Fahl, Ulrich; Remme, Uwe; Blesl, Markus; Voss, Alfred
2009-01-01
Evaluation of global diffusion potential of learning technologies and their timely specific cost development across regions is always a challenging issue for the future technology policy preparation. Further the process of evaluation gains interest especially by endogenous treatment of energy technologies under uncertainty in learning rates with technology gap across the regions in global regional cluster learning approach. This work devised, implemented, and examined new methodologies on technology gaps (a practical problem), using two broad concepts of knowledge deficit and time lag approaches in global learning, applying the floor cost approach methodology. The study was executed in a multi-regional, technology-rich and long horizon bottom-up linear energy system model on The Integrated MARKAL EFOM System (TIMES) framework. Global learning selects highest learning technologies in maximum uncertainty of learning rate scenario, whereas any form of technology gap retards the global learning process and discourages the technologies deployment. Time lag notions of technology gaps prefer heavy utilization of learning technologies in developed economies for early reduction of specific cost. Technology gaps of any kind should be reduced among economies through the promotion and enactment of various policies by governments, in order to utilize the technological resources by mass deployment to combat ongoing climate change.
International Nuclear Information System (INIS)
Zhang, Yan; Zheng, Hongmei; Yang, Zhifeng; Su, Meirong; Liu, Gengyuan; Li, Yanxian
2015-01-01
Chinese regions frequently exchange materials, but regional differences in economic development create unbalanced flows of these resources. In this study, we examined energy by assessing embodied energy consumption to describe the energy-flow structure in China's seven regions. Based on multi-regional monetary input–output tables and energy statistical yearbooks for Chinese provinces in 2002 and 2007, we accounted for both direct and indirect energy consumption, respectively, and the integral input and output of the provinces. Most integral inputs of energy flowed from north to south or from east to west, whereas integral output flows were mainly from northeast to southwest. This differed from the direct flows, which were predominantly from north to south and west to east. This demonstrates the importance of calculating both direct and indirect energy flows. Analysis of the distance and direction traveled by the energy consumption centers of gravity showed that the centers for embodied energy consumption and inputs moved southeast because of the movements of the centers of the Eastern region. However, the center for outputs moved northeast because the movement of the Central region. These analyses provide a basis for identifying how regional economic development policies influence the embodied energy consumption and its flows among regions. - Highlights: • We integrated multi-regional input–output analysis with ecological network analysis. • We accounted for both direct and indirect energy consumption. • The centers of gravity for embodied energy flows moved southeast from 2002 to 2007. • The results support planning of energy consumption and energy flows among regions.
Reference Models for Multi-Layer Tissue Structures
2016-09-01
function of multi-layer tissues (etiology and management of pressure ulcers ). What was the impact on other disciplines? As part of the project, a data...simplification to develop cost -effective models of surface manipulation of multi-layer tissues. Deliverables. Specimen- (or subject) and region-specific...simplification to develop cost -effective models of surgical manipulation. Deliverables. Specimen-specific surrogate models of upper legs confirmed against data
BUILES JARAMILLO, LUIS ALEJANDRO; FRANCO, MARIA CRISTINA; RAVE, CLAUDIA C.
2010-01-01
Enmarcado en una propuesta metodológica para la formulación de lineamientos de acción para el mejoramiento de la calidad del aire en el Municipio de Itagüí, se emplea un modelo de optimización multi-periodo, basado en programación lineal, del tipo Energía-Ambiente-Economía (MARKAL-estándar) y una metodología de Evaluación de metas normativas, para el análisis prospectivo de alternativas integrales de intervención en los sectores industria, transporte y de apoyo para la evaluación de normativa...
Barriers to knowledge spillovers and regional convergence in an evolutionary model
Caniëls, M.C.J.; Verspagen, B.
2001-01-01
This paper will present a multi-region/multi-country model in which inter-regional knowledge spillovers determine the growth of regions. Key parameters in the model are the learning capability of a region and the rate of knowledge generation (R&D). The intensity of spillovers depends on geographical
Wave Model Development in Multi-Ion Plasmas
Directory of Open Access Journals (Sweden)
Sung-Hee Song
1999-06-01
Full Text Available Near-earth space is composed of plasmas which embed a number of plasma waves. Space plasmas consist of electrons and multi-ion that determine local wave propagation characteristics. In multi-ion plasmas, it is di cult to find out analytic solution from the dispersion relation in general. In this work, we have developed a model with an arbitrary magnetic field and density as well as multi-ion plasmas. This model allows us to investigate how plasma waves behave when they propagate along realistic magnetic field lines, which are assumed by IGRF(International Geomagnetic Reference Field. The results are found to be useful for the analysis of the in situ observational data in space. For instance, if waves are assumed to propagate into the polar region, from the equatorial region, our model quantitatively shows how polarization is altered along earth travel path.
International Nuclear Information System (INIS)
Kato, K.; Ihara, S.
1993-01-01
Hydrogen is expected to be an important energy carrier, especially in the frame of global warming problem solution. The purpose of this study is to examine the condition of market penetration of hydrogen technologies in reducing CO 2 emissions. A multi-time-period linear programming model (MARKAL, Market Allocation)) is used to explore technology options and cost for meeting the energy demands while reducing CO 2 emissions from energy systems. The results show that hydrogen technologies become economical when CO 2 emissions are stringently constrained. 9 figs., 2 refs
Directory of Open Access Journals (Sweden)
Yunbo Chu
2016-10-01
Full Text Available Economic evaluation in the form of cost-effectiveness analysis has become a popular means to inform decisions in healthcare. With multi-regional clinical trials in a global development program becoming a new venue for drug efficacy testing in recent decades, questions in methods for cost-effectiveness analysis in the multi-regional clinical trials setting also emerge. This paper addresses some challenges from variation across regions in cost effectiveness analysis in multi-regional clinical trials. Several discussion points are raised for further attention and a multi-regional clinical trial example is presented to illustrate the implications in industrial application. A general message is delivered to call for a depth discussion by all stakeholders to reach an agreement on a good practice in cost-effectiveness analysis in the multi-regional clinical trials. Meanwhile, we recommend an additional consideration of cost-effectiveness analysis results based on the clinical evidence from a certain homogeneous population as sensitivity or scenario analysis upon data availability.
Microphysics in Multi-scale Modeling System with Unified Physics
Tao, Wei-Kuo
2012-01-01
Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.
The multi region molten-salt reactor concept
International Nuclear Information System (INIS)
Gyula, Csom; Sandor, Feher; Szieberth, M.; Szabolcs, Czifrus
2003-01-01
The molten-salt reactor (MSR) concept is one of the most promising systems for the realisation of transmutation. The objective is the development of a transmutation technique along with a device implementing it, which yield higher transmutation efficiencies than that of the known procedures. The procedure is the multi-step transmutation, in which the transformation is carried out in several consecutive steps of different neutron flux and spectrum. In order to implement this, a multi-region transmutation device, i.e. nuclear reactor or sub-critical system is proposed, in which several separate flow-through irradiation rooms are formed with various neutron spectra and fluxes. The paper presents calculations that were performed for a special 5-region version of the multi-region molten-salt reactor. (author)
Directory of Open Access Journals (Sweden)
Wei-Bin Zhang
2016-01-01
Full Text Available El objetivo de este artículo es generalizar el conocido modelo de Uzawa de dos sectores para una economía nacional para su aplicación en contextos globales con muchos países y muchas regiones dentro de cada país. Se estudia el desarrollo económico internacional e interregional a través de un modelo de equilibrio general donde se considera la acumulación de riqueza, el intercambio de recursos y la estructura económica bajo los supuestos de maximización de beneficios y utilidad y competencia perfecta. Para ello se aplica el modelo alternativo de Zhang sobre el comportamiento de los hogares simulándolo para un contexto multi-país y multi-región en una economía global, identificando la existencia del equilibrio y confirmando la estabilidad del mismo. Adicionalmente, se realiza un análisis comparativo dinámico para la productividad total de los factores, tanto del sector industrial como del terciario en cada región, así como de la propensión del ahorro, la asignación regional de recursos, la propensión al consumo de los hogares y los efectos de la población.
The Goddard multi-scale modeling system with unified physics
Directory of Open Access Journals (Sweden)
W.-K. Tao
2009-08-01
Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.
This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.
A Dynamic Multi-Level Factor Model with Long-Range Dependence
DEFF Research Database (Denmark)
Ergemen, Yunus Emre; Rodríguez-Caballero, Carlos Vladimir
A dynamic multi-level factor model with stationary or nonstationary global and regional factors is proposed. In the model, persistence in global and regional common factors as well as innovations allows for the study of fractional cointegrating relationships. Estimation of global and regional...
Application of thin plate splines for accurate regional ionosphere modeling with multi-GNSS data
Krypiak-Gregorczyk, Anna; Wielgosz, Pawel; Borkowski, Andrzej
2016-04-01
GNSS-derived regional ionosphere models are widely used in both precise positioning, ionosphere and space weather studies. However, their accuracy is often not sufficient to support precise positioning, RTK in particular. In this paper, we presented new approach that uses solely carrier phase multi-GNSS observables and thin plate splines (TPS) for accurate ionospheric TEC modeling. TPS is a closed solution of a variational problem minimizing both the sum of squared second derivatives of a smoothing function and the deviation between data points and this function. This approach is used in UWM-rt1 regional ionosphere model developed at UWM in Olsztyn. The model allows for providing ionospheric TEC maps with high spatial and temporal resolutions - 0.2x0.2 degrees and 2.5 minutes, respectively. For TEC estimation, EPN and EUPOS reference station data is used. The maps are available with delay of 15-60 minutes. In this paper we compare the performance of UWM-rt1 model with IGS global and CODE regional ionosphere maps during ionospheric storm that took place on March 17th, 2015. During this storm, the TEC level over Europe doubled comparing to earlier quiet days. The performance of the UWM-rt1 model was validated by (a) comparison to reference double-differenced ionospheric corrections over selected baselines, and (b) analysis of post-fit residuals to calibrated carrier phase geometry-free observational arcs at selected test stations. The results show a very good performance of UWM-rt1 model. The obtained post-fit residuals in case of UWM maps are lower by one order of magnitude comparing to IGS maps. The accuracy of UWM-rt1 -derived TEC maps is estimated at 0.5 TECU. This may be directly translated to the user positioning domain.
Energy Technology Data Exchange (ETDEWEB)
Leimbach, Marian [Potsdam-Institut fuer Klimafolgenforschung e.V., Potsdam (Germany); Eisenack, Klaus [Oldenburg Univ. (Germany). Dept. of Economics and Statistics
2008-11-15
In this paper we present an algorithm that deals with trade interactions within a multi-region model. In contrast to traditional approaches this algorithm is able to handle spillover externalities. Technological spillovers are expected to foster the diffusion of new technologies, which helps to lower the cost of climate change mitigation. We focus on technological spillovers which are due to capital trade. The algorithm of finding a pareto-optimal solution in an intertemporal framework is embedded in a decomposed optimization process. The paper analyzes convergence and equilibrium properties of this algorithm. In the final part of the paper, we apply the algorithm to investigate possible impacts of technological spillovers. While benefits of technological spillovers are significant for the capital-importing region, benefits for the capital-exporting region depend on the type of regional disparities and the resulting specialization and terms-of-trade effects. (orig.)
Direct regional energy/economic modeling (DREEM) design
Energy Technology Data Exchange (ETDEWEB)
Hall, P.D.; Pleatsikas, C.J.
1979-10-01
This report summarizes an investigation into the use of regional and multiregional economic models for estimating the indirect and induced impacts of Federally-mandated energy policies. It includes an examination of alternative types of energy policies that can impact regional economies and the available analytical frameworks for measuring the magnitudes and spatial extents of these impacts. One such analytical system, the National Regional Impact Evaluation System (NRIES), currently operational in the Bureau of Economic Analysis (BEA), is chosen for more detailed investigation. The report summarizes the models capabilities for addressing various energy policy issues and then demonstrates the applicability of the model in specified contexts by developing appropriate input data for three scenarios. These scenarios concern the multi-state impacts of alternative coal-mining-development decisions, multi-regional impacts of macroeconomic change, and the comprehensive effects of an alternative national energy supply trajectory. On the basis of this experience, the capabilities of NRIES for analyzing energy-policy issues are summarized in a concluding chapter.
visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data.
Directory of Open Access Journals (Sweden)
Matthew Scales
Full Text Available We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk, a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R, Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser or the WashU Epigenome Browser allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV. Other locally run data visualisation software such as Circos require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…. It also allows annotation of genes and other custom features in the plotted region(s. Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3.
International Nuclear Information System (INIS)
Wang, Ge; Zhang, Qi; Mclellan, Benjamin C.; Li, Hailong
2016-01-01
Renewable energy is expected to play much more important role in future low-carbon energy system, however, renewable energy has problems with regard to load-following and regional imbalance. This study aims to plan the deployment of intermittent renewable energy in multiple regions considering the impacts of regional natural conditions and generation capacity mix as well as interregional transmission capacity using a multi-region dynamic optimization model. The model was developed to find optimized development paths toward future smart electricity systems with high level penetration of intermittent renewable energy considering regional differences and interregional transmission at national scale. As a case study, the model was applied to plan power generation in nine interconnected regions in Japan out to 2030. Four scenarios were proposed with different supporting policies for the interregional power transmission infrastructures and different nuclear power phase-out scenarios. The analysis results show that (i) the government's support for power transmission infrastructures is vital important to develop more intermittent renewable energy in appropriate regions and utilize renewable energy more efficiently; (ii) nuclear and renewable can complement rather than replace each other if enough interregional transmission capacity is provided. - Highlights: • Plan the optimal deployment of intermittent renewable energy in multiple regions. • A multi-region dynamic optimization model was developed. • The impacts of natural conditions and interregional transmission are studied. • The government's support for transmission is vital important for renewable energy. • Nuclear and renewable can complement rather than replace each other.
Generation of multi annual land use and crop rotation data for regional agro-ecosystem modeling
Waldhoff, G.; Lussem, U.; Sulis, M.; Bareth, G.
2017-12-01
For agro-ecosystem modeling on a regional scale with systems like the Community Land Model (CLM), detailed crop type and crop rotation information on the parcel-level is of key importance. Only with this, accurate assessments of the fluxes associated with the succession of crops and their management are possible. However, sophisticated agro-ecosystem modeling for large regions is only feasible at grid resolutions, which are much coarser than the spatial resolution of modern land use maps (usually ca. 30 m). As a result, much of the original information content of the maps has to be dismissed during resampling. Here we present our mapping approach for the Rur catchment (located in the west of Germany), which was developed to address these demands and issues. We integrated remote sensing and geographic information system (GIS) methods to classify multi temporal images of (e.g.) Landsat, RapidEye and Sentinel-2 to generate annual crop maps for the years 2008-2017 at 15 m spatial resolution (accuracy always ca. 90 %). A key aspect of our method is the consideration of crop phenology for the data selection and the analysis. In a GIS, the annul crop maps were integrated to a crop sequence dataset from which the major crop rotations were derived (based on the 10-years). To retain the multi annual crop succession and crop area information at coarser grid resolutions, cell-based land use fractions, including other land use classes were calculated for each year and for various target cell sizes (1-32 arc seconds). The resulting datasets contain the contribution (in percent) of every land use class to each cell. Our results show that parcels with the major crop types can be differentiated with a high accuracy and on an annual basis. The analysis of the crop sequence data revealed a very large number of different crop rotations, but only relatively few crop rotations cover larger areas. This strong diversity emphasizes the importance of information on crop rotations to reduce
Multi-scale climate modelling over Southern Africa using a variable-resolution global model
CSIR Research Space (South Africa)
Engelbrecht, FA
2011-12-01
Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...
Markert, K. N.; Limaye, A. S.; Rushi, B. R.; Adams, E. C.; Anderson, E.; Ellenburg, W. L.; Mithieu, F.; Griffin, R.
2017-12-01
Water resource management is the process by which governments, businesses and/or individuals reach and implement decisions that are intended to address the future quantity and/or quality of water for societal benefit. The implementation of water resource management typically requires the understanding of the quantity and/or timing of a variety of hydrologic variables (e.g. discharge, soil moisture and evapotranspiration). Often times these variables for management are simulated using hydrologic models particularly in data sparse regions. However, there are several large barriers to entry in learning how to use models, applying best practices during the modeling process, and selecting and understanding the most appropriate model for diverse applications. This presentation focuses on a multi-tiered approach to bring the state-of-the-art hydrologic modeling capabilities and methods to developing regions through the SERVIR program, a joint NASA and USAID initiative that builds capacity of regional partners and their end users on the use of Earth observations for environmental decision making. The first tier is a series of trainings on the use of multiple hydrologic models, including the Variable Infiltration Capacity (VIC) and Ensemble Framework For Flash Flood Forecasting (EF5), which focus on model concepts and steps to successfully implement the models. We present a case study for this in a pilot area, the Nyando Basin in Kenya. The second tier is focused on building a community of practice on applied hydrology modeling aimed at creating a support network for hydrologists in SERVIR regions and promoting best practices. The third tier is a hydrologic inter-comparison project under development in the SERVIR regions. The objective of this step is to understand model performance under specific decision-making scenarios, and to share knowledge among hydrologists in SERVIR regions. The results of these efforts include computer programs, training materials, and new
International Nuclear Information System (INIS)
Zakeri, Behnam; Virasjoki, Vilma; Syri, Sanna; Connolly, David; Mathiesen, Brian V.; Welsch, Manuel
2016-01-01
The EU energy policy aims at creating a single European electricity market through market couplings and grid expansions. To analyse the implications of such power market couplings, we propose a market-based multi-region energy system model. The model simulates a multi-region power market (by applying market optimization and network theory), with detailed representation of each region as an energy system (by simulation of both heat and power sectors). We examine the impact of further integration of variable renewable energy (VRE) in Germany on the Nordic power market. The results indicate that the average electricity price slightly grows in the Nordic power market after Germany's Energy Transition (Energiewende). Hence, the economic surplus of Nordic consumers diminishes while Nordic producers improve their gain under new market conditions. Considering the gird congestion income, the overall system-level benefits (social welfare) will improve in the Nordic region after Germany's Energiewende. However, this gain is not equally distributed among different Nordic countries and across different stakeholders. Furthermore, the Energiewende slightly increases carbon emissions from power and district heating (DH) sectors, and reduces the flexibility in integration of VRE in some Nordic countries like Denmark. The direct interconnection of Norway and Germany through NordLink will contribute to the flexibility in wind integration in other Nordic countries, such as Denmark and Finland. - Highlights: • By an integrated hourly analysis, we model the energy systems of several networked countries and their common electricity market. • The proposed model can inform energy policy on implications of renewable energy integration in an international power market. • Among Nordic countries, Norway gains the highest economic benefits from Germany's energy transition. • Germany's energy transition constrains the flexibility of the Nordic countries in wind integration. • Nord
Wang, Bao-Zhen; Chen, Zhi
2013-01-01
This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.
Energy Technology Data Exchange (ETDEWEB)
Xu, Tianfu
2006-07-13
The need to consider aqueous and sorption kinetics andmicrobiological processes arises in many subsurface problems. Ageneral-rate expression has been implemented into the TOUGHREACTsimulator, which considers multiple mechanisms (pathways) and includesmultiple product, Monod, and inhibition terms. This paper presents aformulation for incorporating kinetic rates among primary species intomass-balance equations. The space discretization used is based on aflexible integral finite difference approach that uses irregular griddingto model bio-geologic structures. A general multi-region model forhydrological transport interacted with microbiological and geochemicalprocesses is proposed. A 1-D reactive transport problem with kineticbiodegradation and sorption was used to test the enhanced simulator,which involves the processes that occur when a pulse of water containingNTA (nitrylotriacetate) and cobalt is injected into a column. The currentsimulation results agree very well with those obtained with othersimulators. The applicability of this general multi-region model wasvalidated by results from a published column experiment ofdenitrification and sulfate reduction. The matches with measured nitrateand sulfate concentrations were adjusted with the interficial areabetween mobile hydrological and immobile biological regions. Resultssuggest that TOUGHREACT can not only be a useful interpretative tool forbiogeochemical experiments, but also can produce insight into processesand parameters of microscopic diffusion and their interplay withbiogeochemical reactions. The geometric- and process-based multi-regionmodel may provide a framework for understanding field-scalehydrobiogeochemical heterogeneities and upscaling parameters.
International Nuclear Information System (INIS)
Tan, Raymond R.; Aviso, Kathleen B.; Barilea, Ivan U.; Culaba, Alvin B.; Cruz, Jose B.
2012-01-01
Interest in bioenergy in recent years has been stimulated by both energy security and climate change concerns. Fuels derived from agricultural crops offer the promise of reducing energy dependence for countries that have traditionally been dependent on imported energy. Nevertheless, it is evident that the potential for biomass production is heavily dependent on the availability of land and water resources. Furthermore, capacity expansion through land conversion is now known to incur a significant carbon debt that may offset any benefits in greenhouse gas reductions arising from the biofuel life cycle. Because of such constraints, there is increasing use of non-local biomass through regional trading. The main challenge in the analysis of such arrangements is that individual geographic regions have their own respective goals. This work presents a multi-region, fuzzy input–output optimization model that reflects production and consumption of bioenergy under land, water and carbon footprint constraints. To offset any local production deficits or surpluses, the model allows for trade to occur among different regions within a defined system; furthermore, importation of additional biofuel from external sources is also allowed. Two illustrative case studies are given to demonstrate the key features of the model.
Alipour, M.; Kibler, K. M.
2017-12-01
Despite advances in flow prediction, managers of ungauged rivers located within broad regions of sparse hydrometeorologic observation still lack prescriptive methods robust to the data challenges of such regions. We propose a multi-objective streamflow prediction framework for regions of minimum observation to select models that balance runoff efficiency with choice of accurate parameter values. We supplement sparse observed data with uncertain or low-resolution information incorporated as `soft' a priori parameter estimates. The performance of the proposed framework is tested against traditional single-objective and constrained single-objective calibrations in two catchments in a remote area of southwestern China. We find that the multi-objective approach performs well with respect to runoff efficiency in both catchments (NSE = 0.74 and 0.72), within the range of efficiencies returned by other models (NSE = 0.67 - 0.78). However, soil moisture capacity estimated by the multi-objective model resonates with a priori estimates (parameter residuals of 61 cm versus 289 and 518 cm for maximum soil moisture capacity in one catchment, and 20 cm versus 246 and 475 cm in the other; parameter residuals of 0.48 versus 0.65 and 0.7 for soil moisture distribution shape factor in one catchment, and 0.91 versus 0.79 and 1.24 in the other). Thus, optimization to a multi-criteria objective function led to very different representations of soil moisture capacity as compared to models selected by single-objective calibration, without compromising runoff efficiency. These different soil moisture representations may translate into considerably different hydrological behaviors. The proposed approach thus offers a preliminary step towards greater process understanding in regions of severe data limitations. For instance, the multi-objective framework may be an adept tool to discern between models of similar efficiency to select models that provide the "right answers for the right reasons
Multi-Task Vehicle Detection with Region-of-Interest Voting.
Chu, Wenqing; Liu, Yao; Shen, Chen; Cai, Deng; Hua, Xian-Sheng
2017-10-12
Vehicle detection is a challenging problem in autonomous driving systems, due to its large structural and appearance variations. In this paper, we propose a novel vehicle detection scheme based on multi-task deep convolutional neural networks (CNN) and region-of-interest (RoI) voting. In the design of CNN architecture, we enrich the supervised information with subcategory, region overlap, bounding-box regression and category of each training RoI as a multi-task learning framework. This design allows the CNN model to share visual knowledge among different vehicle attributes simultaneously, thus detection robustness can be effectively improved. In addition, most existing methods consider each RoI independently, ignoring the clues from its neighboring RoIs. In our approach, we utilize the CNN model to predict the offset direction of each RoI boundary towards the corresponding ground truth. Then each RoI can vote those suitable adjacent bounding boxes which are consistent with this additional information. The voting results are combined with the score of each RoI itself to find a more accurate location from a large number of candidates. Experimental results on the real-world computer vision benchmarks KITTI and the PASCAL2007 vehicle dataset show that our approach achieves superior performance in vehicle detection compared with other existing published works.
Cost-benefit analysis of multi-regional nuclear energy systems deployment
International Nuclear Information System (INIS)
Van Den Durpel, L.G.G.; Wade, D.C.; Yacout, A.M.
2007-01-01
The paper describes the preliminary results of a cost/benefit-analysis of multi-regional nuclear energy system approaches with a focus on how multi-regional approaches may benefit a growing nuclear energy system in various world regions also being able to limit, or even reduce, the costs associated with the nuclear fuel cycle and facilitating the introduction of nuclear energy in various regions in the world. The paper highlights the trade-off one might envisage in deploying such multi-regional approaches but also the pay backs possible and concludes on the economical benefits one may associate to regional fuel cycle centres serving a world-fleet of STAR (small fast reactors of long refueling interval) where these STARs may be competitive compared to the LWRs (Light Water Reactors) as a base-case nuclear reactor option. (authors)
International Nuclear Information System (INIS)
Rout, Ullash K.; Blesl, Markus; Fahl, Ulrich; Remme, Uwe; Voss, Alfred
2009-01-01
The diffusion of promising energy technologies in the market depends on their future energy production-cost development. When analyzing these technologies in an integrated assessment model using endogenous technological learning, the uncertainty in the assumed learning rates (LRs) plays a crucial role in the production-cost development and model outcomes. This study examines the uncertainty in LRs of some energy technologies under endogenous global learning implementation and presents a floor-cost modeling procedure to systematically regulate the uncertainty in LRs of energy technologies. The article narrates the difficulties of data assimilation, as compatible with mixed integer programming segmentations, and comprehensively presents the causes of uncertainty in LRs. This work is executed using a multi-regional and long-horizon energy system model based on 'TIMES' framework. All regions receive an economic advantage to learn in a common domain, and resource-ample regions obtain a marginal advantage for better exploitation of the learning technologies, due to a lower supply-side fuel-cost development. The lowest learning investment associated with the maximum LR mobilizes more deployment of the learning technologies. The uncertainty in LRs has an impact on the diffusion of energy technologies tested, and therefore this study scrutinizes the role of policy support for some of the technologies investigated. (author)
Approaching the Kyoto targets: a case study for Basilicata region (Italy)
Energy Technology Data Exchange (ETDEWEB)
Salvia, M.; Cuomo, V. [Consiglio Nazionale delle Ricerche, Tito Scalo (Italy). Istituto di Metodologie per l' Analisi Ambientale; Pietrapertosa, F. [Consiglio Nazionale delle Ricerche, Tito Scalo (Italy). Istituto di Metodologie per l' Analisi Ambientale; Universita degli Studi della Basilicata, Potenza (Italy). Dip. di Ingegneria e Fisica dell' Ambiente; Cosmi, C. [Consiglio Nazionale delle Ricerche, Tito Scalo (Italy). Istituto di Metodologie per l' Analisi Ambientale; Istituto Nazionale di Fisica della Materia, Napoli (Italy); Macchiato, M. [Universita Federico II, Napoli (Italy). Dip. di Scienze Fisiche
2004-02-01
Approaching the national Kyoto Protocol (KP) targets involves a re-definition of the actual configuration of local energy systems. This study deals with a local scale application of the IEA-MARKAL models generator, in which the anthropogenic system of Basilicata Region (Southern Italy) is investigated to support the definition of coherent long- term strategies and sound climate protection policies. A scenario by scenario analysis points out the behaviour of the optimal mix of fuels and technologies in the presence of carbon dioxide emissions constraints. Trade off curves and reduced costs analyses outline the most effective actions for contributing to the national KP targets, with particular emphasis on the interventions in Civil (Residential, Commercial and Services) and waste management sectors. (author)
Energy Technology Data Exchange (ETDEWEB)
Edwards, David, E-mail: dej@kingcon.com [IJL Research Center, Newark, VT 05871 (United States)
2011-07-21
This paper is a review of multi-region FDM, a numerical technique for accurately determining electrostatic potentials in cylindrically symmetric geometries. Multi-region FDM can be thought of as the union of various individual elements: a single region FDM process: a method for algorithmic development; a method for auto creating a multi-region structure; the process for the relaxation of multi-region structures. Each element will be briefly described along with its integration into the multi-region relaxation process itself.
International Nuclear Information System (INIS)
Lee, Duk Hee; Park, Sang Yong; Hong, Jong Chul; Choi, Sang Jin; Kim, Jong Wook
2013-01-01
Highlights: ► A new methodology for improving energy system analysis models was proposed. ► The MARKAL model was integrated with the diffusion model. ► The new methodology was applied to green car technology. ► The ripple effect of green car technology on the energy system can be analyzed. -- Abstract: By 2020, Korea has set itself the challenging target of reducing nationwide greenhouse gas emissions by 30%, more than the BAU (Business as Usual) scenario, as the implementation goal required to achieve the new national development paradigm of green growth. To achieve such a target, it is necessary to diffuse innovative technologies with the capacity to drastically reduce greenhouse gas emissions. To that end, the ripple effect of diffusing innovative technologies on the energy and environment must be quantitatively analyzed using an energy system analysis model such as the MARKAL (Market Allocation) model. However, energy system analysis models based on an optimization methodology have certain limitations in that a technology with superior cost competitiveness dominates the whole market and non-cost factors cannot be considered. Therefore, this study proposes a new methodology for overcoming problems associated with the use of MARKAL models, by interfacing with a forecasting model based on the discrete-choice model. The new methodology was applied to green car technology to verify its usefulness and to study the ripple effects of green car technology on greenhouse gas reduction. The results of this study can be used as a reference when establishing a strategy for effectively reducing greenhouse gas emissions in the transportation sector, and could be of assistance to future studies using the energy system analysis model.
Computation of multi-region relaxed magnetohydrodynamic equilibria
Energy Technology Data Exchange (ETDEWEB)
Hudson, S. R.; Lazerson, S. [Princeton Plasma Physics Laboratory, P.O. Box 451, Princeton, New Jersey 08543 (United States); Dewar, R. L.; Dennis, G.; Hole, M. J.; McGann, M.; Nessi, G. von [Plasma Research Laboratory, Research School of Physics and Engineering, Australian National University, Canberra ACT 0200 (Australia)
2012-11-15
We describe the construction of stepped-pressure equilibria as extrema of a multi-region, relaxed magnetohydrodynamic (MHD) energy functional that combines elements of ideal MHD and Taylor relaxation, and which we call MRXMHD. The model is compatible with Hamiltonian chaos theory and allows the three-dimensional MHD equilibrium problem to be formulated in a well-posed manner suitable for computation. The energy-functional is discretized using a mixed finite-element, Fourier representation for the magnetic vector potential and the equilibrium geometry; and numerical solutions are constructed using the stepped-pressure equilibrium code, SPEC. Convergence studies with respect to radial and Fourier resolution are presented.
International Nuclear Information System (INIS)
Watcharejyothin, Mayurachat; Shrestha, Ram M.
2009-01-01
The paper evaluates effects of energy resource development within the Greater Mekong Sub-region (GMS) on energy supply mix, energy system cost, energy security and environment during 2000-2035. A MARKAL-based integrated energy system model of the five GMS countries was developed to examine benefits of regional energy resource development for meeting the energy demand of these countries. The study found that an unrestricted energy resource development and trade within the region would reduce the total-regional energy systems cost by 18% and would abate the total CO 2 emission by 5% as compared to the base case. All the five countries except Myanmar would benefit from the expansion of regional energy resource integration in terms of lower energy systems costs and better environmental qualities. An imposition of CO 2 emission reduction constraint by 5% on each of the study countries from that of the corresponding emissions under the unrestricted energy resource development in the GMS is found to improve energy security, reduce energy import and fossil fuels dependences and increase volume of power trade within the region. The total energy system cost under the joint CO 2 emission reduction strategy would be less costly than that under the individual emission targets set for each country.
MULTIAGENT IMITATION MODEL OF A REGIONAL CONSTRUCTION CLUSTER AS A HETERARCHICAL SYSTEM
Directory of Open Access Journals (Sweden)
Anufriev Dmitriy Petrovich
2018-01-01
Full Text Available Subject: a regional construction cluster, which is viewed as a complex system territorially localized within the region, consisting of interconnected and complementary enterprises of construction and related industries that are united with local institutions, authorities and cooperating enterprises by heterarchic relations. Research objectives: development of multi-agent simulation model that allows us to examine the business-processes in the regional construction cluster as a complex heterarchical system. Materials and methods: we formulate the mathematical problem for description of processes in a heterarchic system as in a special multi-agent queueing network. Conclusions: the article substantiates application of the decentralized approach which is based on the use of agent methodology. Several types of agents that model elementary organizational structures have been developed. We describe the functional core of the multi-agent simulation model characterizing the heterarchic organizational model. Using the Fishman-Kivia criterion, the adequacy of the logical functioning of the developed model was established.
Global transportation scenarios in the multi-regional EFDA-TIMES energy model
International Nuclear Information System (INIS)
Muehlich, P.; Hamacher, T.
2009-01-01
The aim of this study is to assess the potential impact of the transportation sector on the role of fusion power in the energy system of the 21st century. Key indicators in this context are global passenger and freight transportation activities, consumption levels of fuels used for transportation purposes, the electricity generation mix and greenhouse gas emissions. These quantities are calculated by means of the global multi-regional EFDA-TIMES energy system model. For the present study a new transportation module has been linked to the EFDA-TIMES framework in order to arrive at a consistent projection of future transportation demands. Results are discussed implying various global energy scenarios including assumed crossovers of road transportation activities towards hydrogen or electricity infrastructures and atmospheric CO 2 concentration stabilization levels at 550 ppm and 450 ppm. Our results show that the penetration of fusion power plants is only slightly sensitive to transportation fuel choices but depends strongly on assumed climate policies. In the most stringent case considered here the contribution of electricity produced by fusion power plants can become as large as about 50% at the end of the 21st century. This statement, however, is still of preliminary nature as the EFDA-TIMES project has not yet reached a final status.
Efficient 3D multi-region prostate MRI segmentation using dual optimization.
Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron
2013-01-01
Efficient and accurate extraction of the prostate, in particular its clinically meaningful sub-regions from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, we propose a novel multi-region segmentation approach to simultaneously locating the boundaries of the prostate and its two major sub-regions: the central gland and the peripheral zone. The proposed method utilizes the prior knowledge of the spatial region consistency and employs a customized prostate appearance model to simultaneously segment multiple clinically meaningful regions. We solve the resulted challenging combinatorial optimization problem by means of convex relaxation, for which we introduce a novel spatially continuous flow-maximization model and demonstrate its duality to the investigated convex relaxed optimization problem with the region consistency constraint. Moreover, the proposed continuous max-flow model naturally leads to a new and efficient continuous max-flow based algorithm, which enjoys great advantages in numerics and can be readily implemented on GPUs. Experiments using 15 T2-weighted 3D prostate MR images, by inter- and intra-operator variability, demonstrate the promising performance of the proposed approach.
Multi-scale Regions from Edge Fragments
DEFF Research Database (Denmark)
Kazmi, Wajahat; Andersen, Hans Jørgen
2014-01-01
In this article we introduce a novel method for detecting multi-scale salient regions around edges using a graph based image compression algorithm. Images are recursively decomposed into triangles arranged into a binary tree using linear interpolation. The entropy of any local region of the image......), their performance is comparable to SIFT (Lowe, 2004).We also show that when they are used together with MSERs (Matas et al., 2002), the performance of MSERs is boosted....
Energy Technology Data Exchange (ETDEWEB)
Watcharejyothin, Mayurachat; Shrestha, Ram M. [School of Environment, Resources and Development, Asian Institute of Technology (Thailand)
2009-11-15
The paper evaluates effects of energy resource development within the Greater Mekong Sub-region (GMS) on energy supply mix, energy system cost, energy security and environment during 2000-2035. A MARKAL-based integrated energy system model of the five GMS countries was developed to examine benefits of regional energy resource development for meeting the energy demand of these countries. The study found that an unrestricted energy resource development and trade within the region would reduce the total-regional energy systems cost by 18% and would abate the total CO{sub 2} emission by 5% as compared to the base case. All the five countries except Myanmar would benefit from the expansion of regional energy resource integration in terms of lower energy systems costs and better environmental qualities. An imposition of CO{sub 2} emission reduction constraint by 5% on each of the study countries from that of the corresponding emissions under the unrestricted energy resource development in the GMS is found to improve energy security, reduce energy import and fossil fuels dependences and increase volume of power trade within the region. The total energy system cost under the joint CO{sub 2} emission reduction strategy would be less costly than that under the individual emission targets set for each country. (author)
Data structures supporting multi-region adaptive isogeometric analysis
Perduta, Anna; Putanowicz, Roman
2018-01-01
Since the first paper published in 2005 Isogeometric Analysis (IGA) has gained strong interest and found applications in many engineering problems. Despite the advancement of the method, there are still far fewer software implementations comparing to Finite Element Method. The paper presents an approach to the development of data structures that can support multi-region IGA with local mesh refinement (patch-based) and possible application in IGA-FEM models. The purpose of this paper is to share original design concepts, that authors have created while developing an IGA package, which other researchers may find beneficial for their own simulation codes.
A Model for Generating Multi-hazard Scenarios
Lo Jacomo, A.; Han, D.; Champneys, A.
2017-12-01
Communities in mountain areas are often subject to risk from multiple hazards, such as earthquakes, landslides, and floods. Each hazard has its own different rate of onset, duration, and return period. Multiple hazards tend to complicate the combined risk due to their interactions. Prioritising interventions for minimising risk in this context is challenging. We developed a probabilistic multi-hazard model to help inform decision making in multi-hazard areas. The model is applied to a case study region in the Sichuan province in China, using information from satellite imagery and in-situ data. The model is not intended as a predictive model, but rather as a tool which takes stakeholder input and can be used to explore plausible hazard scenarios over time. By using a Monte Carlo framework and varrying uncertain parameters for each of the hazards, the model can be used to explore the effect of different mitigation interventions aimed at reducing the disaster risk within an uncertain hazard context.
Iordache, Octavian
2011-01-01
This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...
Variational formulation of relaxed and multi-region relaxed magnetohydrodynamics
Dewar, R. L.; Yoshida, Z.; Bhattacharjee, A.; Hudson, S. R.
2015-12-01
> Ideal magnetohydrodynamics (IMHD) is strongly constrained by an infinite number of microscopic constraints expressing mass, entropy and magnetic flux conservation in each infinitesimal fluid element, the latter preventing magnetic reconnection. By contrast, in the Taylor relaxation model for formation of macroscopically self-organized plasma equilibrium states, all these constraints are relaxed save for the global magnetic fluxes and helicity. A Lagrangian variational principle is presented that leads to a new, fully dynamical, relaxed magnetohydrodynamics (RxMHD), such that all static solutions are Taylor states but also allows state with flow. By postulating that some long-lived macroscopic current sheets can act as barriers to relaxation, separating the plasma into multiple relaxation regions, a further generalization, multi-region relaxed magnetohydrodynamics (MRxMHD) is developed.
Hawie, Nicolas; Deschamps, Remy; Granjeon, Didier; Nader, Fadi-Henri; Gorini, Christian; Müller, Carla; Montadert, Lucien; Baudin, François
2015-04-01
Recent scientific work underlined the presence of a thick Cenozoic infill in the Levant Basin reaching up to 12 km. Interestingly; restricted sedimentation was observed along the Levant margin in the Cenozoic. Since the Late Eocene successive regional geodynamic events affecting Afro-Arabia and Eurasia (collision and strike slip deformation)induced fast marginal uplifts. The initiation of local and long-lived regional drainage systems in the Oligo-Miocene period (e.g. Lebanon versus Nile) provoked a change in the depositional pattern along the Levant margin and basin. A shift from carbonate dominated environments into clastic rich systems has been observed. Through this communication we explore the importance of multi-scale constraints (i.e.,seismic, well and field data) in the quantification of the subsidence history, sediment transport and deposition of a Middle-Upper Miocene "multi-source" to sink system along the northernLevant frontier region. We prove through a comprehensive forward stratigraphic modeling workflow that the contribution to the infill of the northern Levant Basin (offshore Lebanon) is split in between proximal and more distal clastic sources as well as in situ carbonate/hemipelagic deposition. In a wider perspective this work falls under the umbrella of multi-disciplinary source to sink studies that investigate the impact of geodynamic events on basin/margin architectural evolutions, consequent sedimentary infill and thus on petroleum systems assessment.
Energy Technology Data Exchange (ETDEWEB)
Unsihuay-Vila, Clodomiro; Marangon-Lima, J.W.; Souza, A.C Zambroni de [Universidade Federal de Itajuba (UNIFEI), MG (Brazil)], emails: clodomirounsihuayvila @gmail.com, marangon@unifei.edu.br, zambroni@unifei.edu.br; Perez-Arriaga, I.J. [Universidad Pontificia Comillas, Madrid (Spain)], email: ipa@mit.edu
2010-07-01
A novel multi objective, multi area and multistage model to long-term expansion-planning of integrated generation and transmission corridors incorporating sustainable energy developing is presented in this paper. The proposed MESEDES model is a multi-regional multi-objective and 'bottom-up' energy model which considers the electricity generation/transmission value-chain, i.e., power generation alternatives including renewable, nuclear and traditional thermal generation along with transmission corridors. The model decides the optimal location and timing of the electricity generation/transmission abroad the multistage planning horizon. The MESEDES model considers three objectives belonging to sustainable energy development criteria such as: a) the minimization of investments and operation costs of : power generation, transmission corridors, energy efficiency (demand side management (DSM) programs) considering CO2 capture technologies; b) minimization of Life Cycle Greenhouse Gas Emissions (LC GHG); c) maximization of the diversification of electricity generation mix. The proposed model consider aspects of the carbon abatement policy under the CDM - Clean Development Mechanism or European Union Greenhouse Gas Emission Trading Scheme. A case study is used to illustrate the proposed framework. (author)
Energy demand analytics using coupled technological and economic models
Impacts of a range of policy scenarios on end-use energy demand are examined using a coupling of MARKAL, an energy system model with extensive supply and end-use technological detail, with Inforum LIFT, a large-scale model of the us. economy with inter-industry, government, and c...
Learning curves in energy planning models
Energy Technology Data Exchange (ETDEWEB)
Barreto, L; Kypreos, S [Paul Scherrer Inst. (PSI), Villigen (Switzerland)
1999-08-01
This study describes the endogenous representation of investment cost learning curves into the MARKAL energy planning model. A piece-wise representation of the learning curves is implemented using Mixed Integer Programming. The approach is briefly described and some results are presented. (author) 3 figs., 5 refs.
Modeling multi-source flooding disaster and developing simulation framework in Delta
Liu, Y.; Cui, X.; Zhang, W.
2016-12-01
Most Delta regions of the world are densely populated and with advanced economies. However, due to impact of the multi-source flooding (upstream flood, rainstorm waterlogging, storm surge flood), the Delta regions is very vulnerable. The academic circles attach great importance to the multi-source flooding disaster in these areas. The Pearl River Delta urban agglomeration in south China is selected as the research area. Based on analysis of natural and environmental characteristics data of the Delta urban agglomeration(remote sensing data, land use data, topographic map, etc.), hydrological monitoring data, research of the uneven distribution and process of regional rainfall, the relationship between the underlying surface and the parameters of runoff, effect of flood storage pattern, we use an automatic or semi-automatic method for dividing spatial units to reflect the runoff characteristics in urban agglomeration, and develop an Multi-model Ensemble System in changing environment, including urban hydrologic model, parallel computational 1D&2D hydrodynamic model, storm surge forecast model and other professional models, the system will have the abilities like real-time setting a variety of boundary conditions, fast and real-time calculation, dynamic presentation of results, powerful statistical analysis function. The model could be optimized and improved by a variety of verification methods. This work was supported by the National Natural Science Foundation of China (41471427); Special Basic Research Key Fund for Central Public Scientific Research Institutes.
Fischer, Andreas; Keller, Denise; Liniger, Mark; Rajczak, Jan; Schär, Christoph; Appenzeller, Christof
2014-05-01
Fundamental changes in the hydrological cycle are expected in a future warmer climate. This is of particular relevance for the Alpine region, as a source and reservoir of several major rivers in Europe and being prone to extreme events such as floodings. For this region, climate change assessments based on the ENSEMBLES regional climate models (RCMs) project a significant decrease in summer mean precipitation under the A1B emission scenario by the mid-to-end of this century, while winter mean precipitation is expected to slightly rise. From an impact perspective, projected changes in seasonal means, however, are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we revisit the full matrix of the ENSEMBLES RCM projections regarding changes in frequency and intensity, precipitation-type (convective versus stratiform) and temporal structure (wet/dry spells and transition probabilities) over Switzerland and surroundings. As proxies for raintype changes, we rely on the model parameterized convective and large-scale precipitation components. Part of the analysis involves a Bayesian multi-model combination algorithm to infer changes from the multi-model ensemble. The analysis suggests a summer drying that evolves altitude-specific: over low-land regions it is associated with wet-day frequency decreases of convective and large-scale precipitation, while over elevated regions it is primarily associated with a decline in large-scale precipitation only. As a consequence, almost all the models project an increase in the convective fraction at elevated Alpine altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in multi-day wet (dry) spells. This shift in multi-day episodes also lowers the likelihood of short dry spell occurrence in all of the models. For spring and autumn the combined multi-model projections indicate higher mean precipitation intensity north of the
Multi-model Simulation for Optimal Control of Aeroacoustics.
Energy Technology Data Exchange (ETDEWEB)
Collis, Samuel Scott; Chen, Guoquan
2005-05-01
functional to changes in control are also solved with same ap-proach by weakly enforcing continuity ofnormal fluxes across a coupling surface.Such formulations have been validated extensively for several aeroacoustics state andcontrol problems.A multi-model based optimal control framework has been constructed and ap-plied to our interested BVI noise control problem. This model problem consists ofthe interaction of a compressible vortex with Bell AH-1 rotor blade with wall-normal3 velocity used as control on the rotor blade surface. The computational domain isdecomposed into the near-field and far-field. The near-field is obtained by numericalsolution of the Navier-Stokes equations while far away from the noise source, wherethe effect of nonlinearities is negligible, the linearized Euler equations are used tomodel the acoustic wave propagation. The BVI wave packet is targeted by definingan objective function that measures the square amplitude of pressure fluctuations inan observation region, at a time interval encompassing the dominant leading edgecompressibility waves. Our control results show that a 12dB reduction in the ob-servation region is obtained. Interestingly, the control mechanism focuses on theobservation region and only minimize the sound level in that region at the expense ofother regions. The vortex strength and trajectory get barely changed. However, theoptimal control does alter the interaction of the vortical and potential fields, whichis the source of BVI noise. While this results in a slight increase in drag, there is asignificant reduction in the temporal gradient of lift leading to a reduction in BVIsound levels.4
Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling
Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.
2016-11-01
A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is
TRANSFER-FUNCTIONS OF A LINEARIZED MULTI-REGION REACTOR
Energy Technology Data Exchange (ETDEWEB)
Higgins, Thomas J.
1963-09-15
The development of the transfer functions for a linearized multi-region reactor is studied, and an illustration is made of application of the corresponding theory by a numerical illustrative example. (auth)
Directory of Open Access Journals (Sweden)
Morgan E. Smith
2017-03-01
Full Text Available Mathematical models of parasite transmission provide powerful tools for assessing the impacts of interventions. Owing to complexity and uncertainty, no single model may capture all features of transmission and elimination dynamics. Multi-model ensemble modelling offers a framework to help overcome biases of single models. We report on the development of a first multi-model ensemble of three lymphatic filariasis (LF models (EPIFIL, LYMFASIM, and TRANSFIL, and evaluate its predictive performance in comparison with that of the constituents using calibration and validation data from three case study sites, one each from the three major LF endemic regions: Africa, Southeast Asia and Papua New Guinea (PNG. We assessed the performance of the respective models for predicting the outcomes of annual MDA strategies for various baseline scenarios thought to exemplify the current endemic conditions in the three regions. The results show that the constructed multi-model ensemble outperformed the single models when evaluated across all sites. Single models that best fitted calibration data tended to do less well in simulating the out-of-sample, or validation, intervention data. Scenario modelling results demonstrate that the multi-model ensemble is able to compensate for variance between single models in order to produce more plausible predictions of intervention impacts. Our results highlight the value of an ensemble approach to modelling parasite control dynamics. However, its optimal use will require further methodological improvements as well as consideration of the organizational mechanisms required to ensure that modelling results and data are shared effectively between all stakeholders.
MODELING MULTI-WAVELENGTH PULSE PROFILES OF THE MILLISECOND PULSAR PSR B1821–24
Energy Technology Data Exchange (ETDEWEB)
Du, Yuanjie; Shuai, Ping; Bei, Xiaomin; Chen, Shaolong; Fu, Linzhong; Huang, Liangwei; Lin, Qingqing; Meng, Jing; Wu, Yaojun; Zhang, Hengbin; Zhang, Qian; Zhang, Xinyuan [Qian Xuesen Laboratory of Space Technology, NO. 104, Youyi Road, Haidian District, Beijing 100094 (China); Qiao, Guojun, E-mail: dyj@nao.cas.cn [School of Physics, Peking University, Beijing 100871 (China)
2015-03-10
PSR B1821–24 is a solitary millisecond pulsar that radiates multi-wavelength pulsed photons. It has complex radio, X-ray, and γ-ray pulse profiles with distinct peak phase separations that challenge the traditional caustic emission models. Using the single-pole annular gap model with a suitable magnetic inclination angle (α = 40°) and viewing angle (ζ = 75°), we managed to reproduce its pulse profiles of three wavebands. It is found that the middle radio peak originated from the core gap region at high altitudes, and the other two radio peaks originated from the annular gap region at relatively low altitudes. Two peaks of both X-ray and γ-ray wavebands basically originated from the annular gap region, while the γ-ray emission generated from the core gap region contributes somewhat to the first γ-ray peak. Precisely reproducing the multi-wavelength pulse profiles of PSR B1821–24 enables us to understand emission regions of distinct wavebands and justify pulsar emission models.
A Regional Multi-permit Market for Ecosystem Services
Bernknopf, R.; Amos, P.; Zhang, E.
2014-12-01
Regional cap and trade programs have been in operation since the 1970's to reduce environmental externalities (NOx and SOx emissions) and have been shown to be beneficial. Air quality and water quality limits are enforced through numerous Federal and State laws and regulations while local communities are seeking ways to protect regional green infrastructure and their ecosystems services. Why not combine them in a market approach to reduce many environmental externalities simultaneously? In a multi-permit market program reforestation (land offsets) as part of a nutrient or carbon sequestration trading program would provide a means to reduce agrochemical discharges into streams, rivers, and groundwater. Land conversions also improve the quality and quantity of other environmental externalities such as air pollution. Collocated nonmarket ecosystem services have societal benefits that can expand the crediting system into a multi-permit trading program. At a regional scale it is possible to combine regulation of water quality, air emissions and quality, and habitat conservation and restoration into one program. This research is about the economic feasibility of a Philadelphia regional multi-permit (cap and trade) program for ecosystem services. Instead of establishing individual markets for ecosystem services, the assumption of the spatial portfolio approach is that it is based on the interdependence of ecosystem functions so that market credits encompasses a range of ecosystem services. Using an existing example the components of the approach are described in terms of scenarios of land portfolios and the calculation of expected return on investment and risk. An experiment in the Schuylkill Watershed will be described for ecosystem services such as nutrients in water and populations of bird species along with Green House Gases. The Philadelphia regional market includes the urban - nonurban economic and environmental interactions and impacts.
Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States
Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.
2013-12-01
Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.
Directory of Open Access Journals (Sweden)
Kaveh Khalili-Damghani
2017-07-01
Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.
Sippel, Sebastian; Zscheischler, Jakob; Mahecha, Miguel D.; Orth, Rene; Reichstein, Markus; Vogel, Martha; Seneviratne, Sonia I.
2017-05-01
The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land-atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land-atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land-atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T-ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T-ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected
2010-06-14
..., Regional Workshops and Multi-Stakeholder Technical Conference on the Integrated Licensing Process June 7... conducting interviews and teleconferences with a cross-section of stakeholders, four regional workshops, and a multi- stakeholder effectiveness technical conference in Washington, DC. To facilitate this review...
A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes
Tao, W. K.
2017-12-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.
International Nuclear Information System (INIS)
Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.
2003-01-01
A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)
Institute of Scientific and Technical Information of China (English)
WANG Jihua; GUO Huaicheng; LIU Lei; HAO Mingjia; ZHANG Ming; LU Xiaojian; XING Kexia
2004-01-01
This paper presents the development of an inexact multi-objective programming (IMOP) model and its application to the strategic environmental assessment (SEA) for the regional development plan for the Hunnan New Zone (HNZ) in Shenyang City, China. Inexact programming and multi-objective programming methods are employed to effectively account for extensive uncertainties in the study system and to reflect various interests from different stakeholders, respectively. In the case study, balancing-economy-and-environment scenario and focusing-industry-development scenario are analyzed by the interactive solution process for addressing the preferences from local authorities and compromises among different objectives. Through interpreting the model solutions under both scenarios, analysis of industrial structure, waste water treatment plant(WWTP) expansion, water consumption and pollution generation and treatment are undertaken for providing a solid base to justify and evaluate the HNZ regional development plan. The study results show that the developed IMOP-SEA framework is feasible and applicable in carrying comprehensive environmental impact assessments for development plan in a more effective and efficient manner.
Large-signal modeling of multi-finger InP DHBT devices at millimeter-wave frequencies
DEFF Research Database (Denmark)
Johansen, Tom Keinicke; Midili, Virginio; Squartecchia, Michele
2017-01-01
A large-signal modeling approach has been developed for multi-finger devices fabricated in an Indium Phosphide (InP) Double Heterojunction Bipolar Transistor (DHBT) process. The approach utilizes unit-finger device models embedded in a multi-port parasitic network. The unit-finger model is based...... on an improved UCSD HBT model formulation avoiding an erroneous RciCbci transit-time contribution from the intrinsic collector region as found in other III-V based HBT models. The mutual heating between fingers is modeled by a thermal coupling network with parameters extracted from electro-thermal simulations...
Lu, Meilian; Yang, Dong; Zhou, Xing
2013-03-01
Based on the analysis of the requirements of conversation history storage in CPM (Converged IP Messaging) system, a Multi-views storage model and access methods of conversation history are proposed. The storage model separates logical views from physical storage and divides the storage into system managed region and user managed region. It simultaneously supports conversation view, system pre-defined view and user-defined view of storage. The rationality and feasibility of multi-view presentation, the physical storage model and access methods are validated through the implemented prototype. It proves that, this proposal has good scalability, which will help to optimize the physical data storage structure and improve storage performance.
Wen, Xian-Huan; Gómez-Hernández, J. Jaime
1998-03-01
The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than
Quantummechanical multi-step direct models for nuclear data applications
International Nuclear Information System (INIS)
Koning, A.J.
1992-10-01
Various multi-step direct models have been derived and compared on a theoretical level. Subsequently, these models have been implemented in the computer code system KAPSIES, enabling a consistent comparison on the basis of the same set of nuclear parameters and same set of numerical techniques. Continuum cross sections in the energy region between 10 and several hundreds of MeV have successfully been analysed. Both angular distributions and energy spectra can be predicted in an essentially parameter-free manner. It is demonstrated that the quantum-mechanical MSD models (in particular the FKK model) give an improved prediction of pre-equilibrium angular distributions as compared to the experiment-based systematics of Kalbach. This makes KAPSIES a reliable tool for nuclear data applications in the afore-mentioned energy region. (author). 10 refs., 2 figs
Deckers, Dave L.E.H.; Booij, Martijn J.; Rientjes, T.H.M.; Krol, Martinus S.
2010-01-01
This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and
A case for multi-model and multi-approach based event attribution: The 2015 European drought
Hauser, Mathias; Gudmundsson, Lukas; Orth, René; Jézéquel, Aglaé; Haustein, Karsten; Seneviratne, Sonia Isabelle
2017-04-01
Science on the role of anthropogenic influence on extreme weather events such as heat waves or droughts has evolved rapidly over the past years. The approach of "event attribution" compares the occurrence probability of an event in the present, factual world with the probability of the same event in a hypothetical, counterfactual world without human-induced climate change. Every such analysis necessarily faces multiple methodological choices including, but not limited to: the event definition, climate model configuration, and the design of the counterfactual world. Here, we explore the role of such choices for an attribution analysis of the 2015 European summer drought (Hauser et al., in preparation). While some GCMs suggest that anthropogenic forcing made the 2015 drought more likely, others suggest no impact, or even a decrease in the event probability. These results additionally differ for single GCMs, depending on the reference used for the counterfactual world. Observational results do not suggest a historical tendency towards more drying, but the record may be too short to provide robust assessments because of the large interannual variability of drought occurrence. These results highlight the need for a multi-model and multi-approach framework in event attribution research. This is especially important for events with low signal to noise ratio and high model dependency such as regional droughts. Hauser, M., L. Gudmundsson, R. Orth, A. Jézéquel, K. Haustein, S.I. Seneviratne, in preparation. A case for multi-model and multi-approach based event attribution: The 2015 European drought.
Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.
2010-12-01
There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.
International Nuclear Information System (INIS)
Strachan, Neil; Hughes, Nick; Balta-Ozkan, Nazmiye; McGeevor, Kate; Joffe, David
2009-01-01
This paper describes an innovative modelling approach focusing on linking spatial (GIS) modelling of hydrogen (H 2 ) supply, demands and infrastructures, anchored within a economy-wide energy systems model (MARKAL). The UK government is legislating a groundbreaking climate change mitigation target for a 60% CO 2 reduction by 2050, and has identified H 2 infrastructures and technologies as potentially playing a major role, notably in the transport sector. An exploratory set of linked GIS-MARKAL model scenarios generate a range of nuanced insights including spatial matching of supply and demand for optimal zero-carbon H 2 deployment, a crucial finding on successive clustering of demand centres to enable economies of scale in H 2 supply and distribution, the competitiveness of imported liquid H 2 and of liquid H 2 distribution, and sectoral competition for coal with carbon sequestration between electricity and H 2 production under economy-wide CO 2 constraints. (author)
Multi-population genomic prediction using a multi-task Bayesian learning model.
Chen, Liuhong; Li, Changxi; Miller, Stephen; Schenkel, Flavio
2014-05-03
Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an
Directory of Open Access Journals (Sweden)
S. Sippel
2017-05-01
Full Text Available The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land–atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land–atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T and evapotranspiration (ET benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land–atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5 archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T–ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T–ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand
Review of regional economic models with special reference to labor impact assessment
Energy Technology Data Exchange (ETDEWEB)
Ferris, G.; Mason, B.
1979-06-01
This paper reviews several regional economic models and examines the capabilities of these models for assessing the total employment impacts of solar energy adoption. Five generic analytic methods are discussed: economic base analysis, shift-share analysis, demographic-economic interaction models, input-output analysis, and industrial location analysis. Ten regional models incorporating some aspect of these methods are reviewed. From the model review, the conclusion is drawn that there is no single model that fits all of the necessary criteria for planned research efforts. Models that appear to hold promise are the Economic Activity Analysis (EAA) Model, the Regional Industrial Multipliers System (RIMS), the Multiregion, Multi-industry (MRMI) Model, and the MULTIREGION model.
Multi-Model Ensemble Wake Vortex Prediction
Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.
2015-01-01
Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.
Age and gender estimation using Region-SIFT and multi-layered SVM
Kim, Hyunduk; Lee, Sang-Heon; Sohn, Myoung-Kyu; Hwang, Byunghun
2018-04-01
In this paper, we propose an age and gender estimation framework using the region-SIFT feature and multi-layered SVM classifier. The suggested framework entails three processes. The first step is landmark based face alignment. The second step is the feature extraction step. In this step, we introduce the region-SIFT feature extraction method based on facial landmarks. First, we define sub-regions of the face. We then extract SIFT features from each sub-region. In order to reduce the dimensions of features we employ a Principal Component Analysis (PCA) and a Linear Discriminant Analysis (LDA). Finally, we classify age and gender using a multi-layered Support Vector Machines (SVM) for efficient classification. Rather than performing gender estimation and age estimation independently, the use of the multi-layered SVM can improve the classification rate by constructing a classifier that estimate the age according to gender. Moreover, we collect a dataset of face images, called by DGIST_C, from the internet. A performance evaluation of proposed method was performed with the FERET database, CACD database, and DGIST_C database. The experimental results demonstrate that the proposed approach classifies age and performs gender estimation very efficiently and accurately.
Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi
2011-12-01
A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.
Multi-Domain Modeling Based on Modelica
Directory of Open Access Journals (Sweden)
Liu Jun
2016-01-01
Full Text Available With the application of simulation technology in large-scale and multi-field problems, multi-domain unified modeling become an effective way to solve these problems. This paper introduces several basic methods and advantages of the multidisciplinary model, and focuses on the simulation based on Modelica language. The Modelica/Mworks is a newly developed simulation software with features of an object-oriented and non-casual language for modeling of the large, multi-domain system, which makes the model easier to grasp, develop and maintain.It This article shows the single degree of freedom mechanical vibration system based on Modelica language special connection mechanism in Mworks. This method that multi-domain modeling has simple and feasible, high reusability. it closer to the physical system, and many other advantages.
A Multi-Agent Traffic Control Model Based on Distributed System
Directory of Open Access Journals (Sweden)
Qian WU
2014-06-01
Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.
A Simple Approach to Account for Climate Model Interdependence in Multi-Model Ensembles
Herger, N.; Abramowitz, G.; Angelil, O. M.; Knutti, R.; Sanderson, B.
2016-12-01
Multi-model ensembles are an indispensable tool for future climate projection and its uncertainty quantification. Ensembles containing multiple climate models generally have increased skill, consistency and reliability. Due to the lack of agreed-on alternatives, most scientists use the equally-weighted multi-model mean as they subscribe to model democracy ("one model, one vote").Different research groups are known to share sections of code, parameterizations in their model, literature, or even whole model components. Therefore, individual model runs do not represent truly independent estimates. Ignoring this dependence structure might lead to a false model consensus, wrong estimation of uncertainty and effective number of independent models.Here, we present a way to partially address this problem by selecting a subset of CMIP5 model runs so that its climatological mean minimizes the RMSE compared to a given observation product. Due to the cancelling out of errors, regional biases in the ensemble mean are reduced significantly.Using a model-as-truth experiment we demonstrate that those regional biases persist into the future and we are not fitting noise, thus providing improved observationally-constrained projections of the 21st century. The optimally selected ensemble shows significantly higher global mean surface temperature projections than the original ensemble, where all the model runs are considered. Moreover, the spread is decreased well beyond that expected from the decreased ensemble size.Several previous studies have recommended an ensemble selection approach based on performance ranking of the model runs. Here, we show that this approach can perform even worse than randomly selecting ensemble members and can thus be harmful. We suggest that accounting for interdependence in the ensemble selection process is a necessary step for robust projections for use in impact assessments, adaptation and mitigation of climate change.
de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás
2017-12-01
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of
Multi-Electrode Impedance Method for Detection of Regional Ventilation
International Nuclear Information System (INIS)
Furuya, Norio; Sakamoto, Katsuyuki
2013-01-01
By means of computer simulation and experiment, we investigated the feasibility of simultaneously measuring the transfer impedance changes in the right apex, left apex, right base and left base of the lungs using the multi-electrode impedance method. To obtain the transfer impedance in each region, while suppressing the effects of other regions, changing the amplitude and polarity of the applied current must localize the high sensitivity areas in the interest region. Twelve current and eight voltage electrodes were equidistantly arranged on the anterior and posterior chest walls. The amplitudes and polarities of the currents that were simultaneously applied to the current electrodes, and which provided the appropriate sensitivity distribution, were theoretically obtained. The effects of the localized sensitivity distribution were verified by comparing the simulation results of the investigated method with the results of the conventional four-electrode method. From the results of the computer simulation, we developed a multi-electrode impedance pneumography and applied it to healthy adult volunteers who were both in sitting position and in left decubitus. We found that the measurement results were physiologically reasonable.
Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J
2014-01-01
The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Zhao Hongbo
2009-09-01
Full Text Available Abstract Background It is quite common that the genetic architecture of complex traits involves many genes and their interactions. Therefore, dealing with multiple unlinked genomic regions simultaneously is desirable. Results In this paper we develop a regression-based approach to assess the interactions of haplotypes that belong to different unlinked regions, and we use score statistics to test the null hypothesis of non-genetic association. Additionally, multiple marker combinations at each unlinked region are considered. The multiple tests are settled via the minP approach. The P value of the "best" multi-region multi-marker configuration is corrected via Monte-Carlo simulations. Through simulation studies, we assess the performance of the proposed approach and demonstrate its validity and power in testing for haplotype interaction association. Conclusion Our simulations showed that, for binary trait without covariates, our proposed methods prove to be equal and even more powerful than htr and hapcc which are part of the FAMHAP program. Additionally, our model can be applied to a wider variety of traits and allow adjustment for other covariates. To test the validity, our methods are applied to analyze the association between four unlinked candidate genes and pig meat quality.
Multi-Model Validation in the Chesapeake Bay Region in June 2010
2013-05-31
ADOR/Director NCST E. R. Franchi , 7000 Public Affairs (Unclassified/ Unlimited Only), Code 7030_4 X no ---~~~~~~~~~~~~~~~-~-~~-~------------ thor...US Navy at global , regional and coastal scales (Rowley 2008, 2010). The NCOM model in the Chesapeake Bay region for this exercise is configured in...derived from the NRL DBDB2 global bathymetry database. Boundary forcing and initial conditions were extracted from the East Coast NCOM which has a 3-km
Multi-scale and multi-physics model of the uterine smooth muscle with mechanotransduction.
Yochum, Maxime; Laforêt, Jérémy; Marque, Catherine
2018-02-01
Preterm labor is an important public health problem. However, the efficiency of the uterine muscle during labor is complex and still poorly understood. This work is a first step towards a model of the uterine muscle, including its electrical and mechanical components, to reach a better understanding of the uterus synchronization. This model is proposed to investigate, by simulation, the possible role of mechanotransduction for the global synchronization of the uterus. The electrical diffusion indeed explains the local propagation of contractile activity, while the tissue stretching may play a role in the synchronization of distant parts of the uterine muscle. This work proposes a multi-physics (electrical, mechanical) and multi-scales (cell, tissue, whole uterus) model, which is applied to a realistic uterus 3D mesh. This model includes electrical components at different scales: generation of action potentials at the cell level, electrical diffusion at the tissue level. It then links these electrical events to the mechanical behavior, at the cellular level (via the intracellular calcium concentration), by simulating the force generated by each active cell. It thus computes an estimation of the intra uterine pressure (IUP) by integrating the forces generated by each active cell at the whole uterine level, as well as the stretching of the tissue (by using a viscoelastic law for the behavior of the tissue). It finally includes at the cellular level stretch activated channels (SACs) that permit to create a loop between the mechanical and the electrical behavior (mechanotransduction). The simulation of different activated regions of the uterus, which in this first "proof of concept" case are electrically isolated, permits the activation of inactive regions through the stretching (induced by the electrically active regions) computed at the whole organ scale. This permits us to evidence the role of the mechanotransduction in the global synchronization of the uterus. The
Parallel LC circuit model for multi-band absorption and preliminary design of radiative cooling.
Feng, Rui; Qiu, Jun; Liu, Linhua; Ding, Weiqiang; Chen, Lixue
2014-12-15
We perform a comprehensive analysis of multi-band absorption by exciting magnetic polaritons in the infrared region. According to the independent properties of the magnetic polaritons, we propose a parallel inductance and capacitance(PLC) circuit model to explain and predict the multi-band resonant absorption peaks, which is fully validated by using the multi-sized structure with identical dielectric spacing layer and the multilayer structure with the same strip width. More importantly, we present the application of the PLC circuit model to preliminarily design a radiative cooling structure realized by merging several close peaks together. This omnidirectional and polarization insensitive structure is a good candidate for radiative cooling application.
A new model and simple algorithms for multi-label mumford-shah problems
Hong, Byungwoo
2013-06-01
In this work, we address the multi-label Mumford-Shah problem, i.e., the problem of jointly estimating a partitioning of the domain of the image, and functions defined within regions of the partition. We create algorithms that are efficient, robust to undesirable local minima, and are easy-to-implement. Our algorithms are formulated by slightly modifying the underlying statistical model from which the multi-label Mumford-Shah functional is derived. The advantage of this statistical model is that the underlying variables: the labels and the functions are less coupled than in the original formulation, and the labels can be computed from the functions with more global updates. The resulting algorithms can be tuned to the desired level of locality of the solution: from fully global updates to more local updates. We demonstrate our algorithm on two applications: joint multi-label segmentation and denoising, and joint multi-label motion segmentation and flow estimation. We compare to the state-of-the-art in multi-label Mumford-Shah problems and show that we achieve more promising results. © 2013 IEEE.
Research on Multi - Person Parallel Modeling Method Based on Integrated Model Persistent Storage
Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying
2018-03-01
This paper mainly studies the multi-person parallel modeling method based on the integrated model persistence storage. The integrated model refers to a set of MDDT modeling graphics system, which can carry out multi-angle, multi-level and multi-stage description of aerospace general embedded software. Persistent storage refers to converting the data model in memory into a storage model and converting the storage model into a data model in memory, where the data model refers to the object model and the storage model is a binary stream. And multi-person parallel modeling refers to the need for multi-person collaboration, the role of separation, and even real-time remote synchronization modeling.
On the tsunami model of the origin of multi-ring basins
International Nuclear Information System (INIS)
Yue Zengyuan; Zhang Bin; Chen Daohan.
1990-03-01
By use of the theory of shallow water waves generated by an impulsive pressure, the tsunami theory of the origin of multi-ring basins is rediscussed and an approximate formula used for calculating the ring location is derived. From the computed ring spacing of three multi-ring basins on the moon (Orientale, Moscoviense and Serenitatis South), it is shown that the tsunami model can only be applied to the area within the IV ring which signifies the rim of the excavated basin and the end of the fluidized region. In the frame of the tsunami model, no explanation for ring spacing is equally plausible for exterior rings as well as interior ones. (author). 14 refs, 1 tab
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to
Projected 21st century decrease in marine productivity: a multi-model analysis
Directory of Open Access Journals (Sweden)
M. Steinacher
2010-03-01
Full Text Available Changes in marine net primary productivity (PP and export of particulate organic carbon (EP are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.
Siegert, Stefan
2017-04-01
Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.
International Nuclear Information System (INIS)
Cruz, Roberto de la; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás
2017-01-01
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction–diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction–diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge
International Nuclear Information System (INIS)
Huang, Yun-Hsun; Wu, Jung-Hua; Hsu, Yu-Ju
2016-01-01
Traditional electricity supply planning models regard the electricity demand as a deterministic parameter and require the total power output to satisfy the aggregate electricity demand. But in today's world, the electric system planners are facing tremendously complex environments full of uncertainties, where electricity demand is a key source of uncertainty. In addition, electricity demand patterns are considerably different for different regions. This paper developed a multi-region optimization model based on two-stage stochastic programming framework to incorporate the demand uncertainty. Furthermore, the decision tree method and Monte Carlo simulation approach are integrated into the model to simplify electricity demands in the form of nodes and determine the values and probabilities. The proposed model was successfully applied to a real case study (i.e. Taiwan's electricity sector) to show its applicability. Detail simulation results were presented and compared with those generated by a deterministic model. Finally, the long-term electricity development roadmap at a regional level could be provided on the basis of our simulation results. - Highlights: • A multi-region, two-stage stochastic programming model has been developed. • The decision tree and Monte Carlo simulation are integrated into the framework. • Taiwan's electricity sector is used to illustrate the applicability of the model. • The results under deterministic and stochastic cases are shown for comparison. • Optimal portfolios of regional generation technologies can be identified.
Perturbation and Stability Analysis of the Multi-Anticipative Intelligent Driver Model
Chen, Xi-Qun; Xie, Wei-Jun; Shi, Jing; Shi, Qi-Xin
This paper discusses three kinds of IDM car-following models that consider both the multi-anticipative behaviors and the reaction delays of drivers. Here, the multi-anticipation comes from two ways: (1) the driver is capable of evaluating the dynamics of several preceding vehicles, and (2) the autonomous vehicles can obtain the velocity and distance information of several preceding vehicles via inter-vehicle communications. In this paper, we study the stability of homogeneous traffic flow. The linear stability analysis indicates that the stable region will generally be enlarged by the multi-anticipative behaviors and reduced by the reaction delays. The temporal amplification and the spatial divergence of velocities for local perturbation are also studied, where the results further prove this conclusion. Simulation results also show that the multi-anticipative behaviors near the bottleneck will lead to a quicker backwards propagation of oscillations.
Monitoring the Dead Sea Region by Multi-Parameter Stations
Mohsen, A.; Weber, M. H.; Kottmeier, C.; Asch, G.
2015-12-01
The Dead Sea Region is an exceptional ecosystem whose seismic activity has influenced all facets of the development, from ground water availability to human evolution. Israelis, Palestinians and Jordanians living in the Dead Sea region are exposed to severe earthquake hazard. Repeatedly large earthquakes (e.g. 1927, magnitude 6.0; (Ambraseys, 2009)) shook the whole Dead Sea region proving that earthquake hazard knows no borders and damaging seismic events can strike anytime. Combined with the high vulnerability of cities in the region and with the enormous concentration of historical values this natural hazard results in an extreme earthquake risk. Thus, an integration of earthquake parameters at all scales (size and time) and their combination with data of infrastructure are needed with the specific aim of providing a state-of-the-art seismic hazard assessment for the Dead Sea region as well as a first quantitative estimate of vulnerability and risk. A strong motivation for our research is the lack of reliable multi-parameter ground-based geophysical information on earthquakes in the Dead Sea region. The proposed set up of a number of observatories with on-line data access will enable to derive the present-day seismicity and deformation pattern in the Dead Sea region. The first multi-parameter stations were installed in Jordan, Israel and Palestine for long-time monitoring. All partners will jointly use these locations. All stations will have an open data policy, with the Deutsches GeoForschungsZentrum (GFZ, Potsdam, Germany) providing the hard and software for real-time data transmission via satellite to Germany, where all partners can access the data via standard data protocols.
Directory of Open Access Journals (Sweden)
Puchalski Bartosz
2015-12-01
Full Text Available In the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller which is designed for nominal power level of the nuclear reactor operates insufficiently well in wide range of operational conditions, especially at the low thermal power level. Thus the steam generator is often controlled manually by operators. Incorrect water level in the steam generator may lead to accidental shutdown of the nuclear reactor and consequently financial losses. In the paper a comparison of proposed multi region fuzzy logic controller and traditional PID controllers designed only for nominal condition is presented. The gains of the local PID controllers have been derived by solving appropriate optimization tasks with the cost function in a form of integrated squared error (ISE criterion. In both cases, a model of steam generator which is readily available in literature was used for control algorithms synthesis purposes. The proposed multi-region fuzzy logic controller and traditional PID controller were subjected to broad-based simulation tests in rapid prototyping software - Matlab/Simulink. These tests proved the advantage of multi-region fuzzy logic controller with local PID controllers over its traditional counterpart.
Multi-modal trip planning system : Northeastern Illinois Regional Transportation Authority.
2013-01-01
This report evaluates the Multi-Modal Trip Planner System (MMTPS) implemented by the Northeastern Illinois Regional Transportation Authority (RTA) against the specific functional objectives enumerated by the Federal Transit Administration (FTA) in it...
Market penetration analysis of hydrogen vehicles in Norwegian passenger transport towards 2050
International Nuclear Information System (INIS)
Rosenberg, Eva; Fidje, Audun; Espegren, Kari Aamodt; Stiller, Christoph; Svensson, Ann Mari; Moeller-Holst, Steffen
2010-01-01
The Norwegian energy system is characterized by high dependency on electricity, mainly hydro power. If the national targets to reduce emissions of greenhouse gases should be met, a substantial reduction of CO 2 emissions has to be obtained from the transport sector. This paper presents the results of the analyses of three Norwegian regions with the energy system model MARKAL during the period 2005-2050. The MARKAL models were used in connection with an infrastructure model H2INVEST. The analyses show that a transition to a hydrogen fuelled transportation sector could be feasible in the long run, and indicate that with substantial hydrogen distribution efforts, fuel cell cars can become competitive compared to other technologies both in urban (2025) and rural areas (2030). In addition, the result shows the importance of the availability of local energy resources for hydrogen production, like the advantages of location close to chemical industry or surplus of renewable electricity. (author)
The impact of domestic trade on China's regional energy uses: A multi-regional input–output modeling
International Nuclear Information System (INIS)
Zhang, Bo; Chen, Z.M.; Xia, X.H.; Xu, X.Y.; Chen, Y.B.
2013-01-01
To systematically reveal how domestic trade impacts on China's regional energy uses, an interprovincial input–output modeling is carried out to address demand-derived energy requirements for the regional economies in 2007 based on the recently available data. Both the energy uses embodied in final demand and interregional trade are investigated from the regional and sectoral insights. Significant net transfers of embodied energy flows are identified from the central and western areas to the eastern area via interregional trade. Shanxi is the largest energy producer and interregional embodied energy deficit receiver, in contrast to Guangdong as the largest energy user and surplus receiver. By considering the impacts of interregional trade, the energy uses of most eastern regions increase remarkably. For instance, Shanghai, Hainan, Zhejiang, Beijing, Jiangsu and Guangdong have their embodied energy requirements 87.49, 19.97, 13.64, 12.60, 6.46 and 6.38 times of their direct energy inputs, respectively. In contrast, the embodied energy uses of some central and western regions such as Inner Mongolia, Shanxi, Xinjiang, Shaanxi and Guizhou decrease largely. The results help understand the hidden network linkages of interregional embodied energy flows and provide critical insight to amend China's current end-reduction-oriented energy policies by addressing the problem of regional responsibility transfer. - Highlights: • Demand-derived energy requirements for China's regional economies are addressed. • Significant interregional transfers of embodied energy flows are identified. • Energy surpluses are obtained by 19 regions and deficits by the other 11 regions. • The eastern regions should take more responsibility for reducing China's energy uses
Multi-wavelength Observations of Solar Acoustic Waves Near Active Regions
Monsue, Teresa; Pesnell, Dean; Hill, Frank
2018-01-01
Active region areas on the Sun are abundant with a variety of waves that are both acoustically helioseismic and magnetohydrodynamic in nature. The occurrence of a solar flare can disrupt these waves, through MHD mode-mixing or scattering by the excitation of these waves. We take a multi-wavelength observational approach to understand the source of theses waves by studying active regions where flaring activity occurs. Our approach is to search for signals within a time series of images using a Fast Fourier Transform (FFT) algorithm, by producing multi-frequency power map movies. We study active regions both spatially and temporally and correlate this method over multiple wavelengths using data from NASA’s Solar Dynamics Observatory. By surveying the active regions on multiple wavelengths we are able to observe the behavior of these waves within the Solar atmosphere, from the photosphere up through the corona. We are able to detect enhancements of power around active regions, which could be acoustic power halos and of an MHD-wave propagating outward by the flaring event. We are in the initial stages of this study understanding the behaviors of these waves and could one day contribute to understanding the mechanism responsible for their formation; that has not yet been explained.
International Nuclear Information System (INIS)
Koltsaklis, Nikolaos E.; Georgiadis, Michael C.
2015-01-01
Highlights: • A short-term structured investment planning model has been developed. • Unit commitment problem is incorporated into the long-term planning horizon. • Inherent intermittency of renewables is modelled in a comprehensive way. • The impact of CO_2 emission pricing in long-term investment decisions is quantified. • The evolution of system’s marginal price is evaluated for all the planning horizon. - Abstract: This work presents a generic mixed integer linear programming (MILP) model that integrates the unit commitment problem (UCP), i.e., daily energy planning with the long-term generation expansion planning (GEP) framework. Typical daily constraints at an hourly level such as start-up and shut-down related decisions (start-up type, minimum up and down time, synchronization, soak and desynchronization time constraints), ramping limits, system reserve requirements are combined with representative yearly constraints such as power capacity additions, power generation bounds of each unit, peak reserve requirements, and energy policy issues (renewables penetration limits, CO_2 emissions cap and pricing). For modelling purposes, a representative day (24 h) of each month over a number of years has been employed in order to determine the optimal capacity additions, electricity market clearing prices, and daily operational planning of the studied power system. The model has been tested on an illustrative case study of the Greek power system. Our approach aims to provide useful insight into strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level by providing the optimal energy roadmap under real operating and design constraints.
Multi-model analysis in hydrological prediction
Lanthier, M.; Arsenault, R.; Brissette, F.
2017-12-01
Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been
Dairaku, K.
2017-12-01
The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.
Integrated multi-scale modelling and simulation of nuclear fuels
International Nuclear Information System (INIS)
Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.
2015-01-01
This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)
A multi-objective programming model for assessment the GHG emissions in MSW management
Energy Technology Data Exchange (ETDEWEB)
Mavrotas, George, E-mail: mavrotas@chemeng.ntua.gr [National Technical University of Athens, Iroon Polytechniou 9, Zografou, Athens, 15780 (Greece); Skoulaxinou, Sotiria [EPEM SA, 141 B Acharnon Str., Athens, 10446 (Greece); Gakis, Nikos [FACETS SA, Agiou Isidorou Str., Athens, 11471 (Greece); Katsouros, Vassilis [Athena Research and Innovation Center, Artemidos 6 and Epidavrou Str., Maroussi, 15125 (Greece); Georgopoulou, Elena [National Observatory of Athens, Thisio, Athens, 11810 (Greece)
2013-09-15
Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH{sub 4} generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the
A multi-objective programming model for assessment the GHG emissions in MSW management
International Nuclear Information System (INIS)
Mavrotas, George; Skoulaxinou, Sotiria; Gakis, Nikos; Katsouros, Vassilis; Georgopoulou, Elena
2013-01-01
Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH 4 generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application
Innovation, Decentralization and Planning in a Multi-Region Model of Schumpeterian Economic Growth
Batabyal, A.; Nijkamp, P.
2014-01-01
We study innovation and the resulting Schumpeterian economic growth that this innovation gives rise to in a model with N heterogeneous regions. For each region i where i = 1,…,N, our analysis leads to six findings. First, we define the balanced growth path (BGP) allocations and the equilibrium of
Directory of Open Access Journals (Sweden)
BUILES JARAMILLO LUIS ALEJANDRO
2010-05-01
Full Text Available Enmarcado en una propuesta metodológica para la formulación de lineamientos de acción para el mejoramiento de la calidad del aire en el Municipio de Itagüí, se emplea un modelo de optimización multi-periodo, basado en programación lineal, del tipo Energía-Ambiente-Economía (MARKAL-estándar y una metodología de Evaluación de metas normativas, para el análisis prospectivo de alternativas integrales de intervención en los sectores industria, transporte y de apoyo para la evaluación de normativa territorial en el municipio de Itagüí. Los resultados ofrecen información e indicadores transversales a diferentes aspectos que configuran la problemática de la calidad del aire y aportan una herramienta útil para la integración de aspectos asociados al mejoramiento de la calidad del recurso en la planeación local. La metodología es replicable en otros municipios del Valle de Aburrá
Dynamical Downscaling of NASA/GISS ModelE: Continuous, Multi-Year WRF Simulations
Otte, T.; Bowden, J. H.; Nolte, C. G.; Otte, M. J.; Herwehe, J. A.; Faluvegi, G.; Shindell, D. T.
2010-12-01
The WRF Model is being used at the U.S. EPA for dynamical downscaling of the NASA/GISS ModelE fields to assess regional impacts of climate change in the United States. The WRF model has been successfully linked to the ModelE fields in their raw hybrid vertical coordinate, and continuous, multi-year WRF downscaling simulations have been performed. WRF will be used to downscale decadal time slices of ModelE for recent past, current, and future climate as the simulations being conducted for the IPCC Fifth Assessment Report become available. This presentation will focus on the sensitivity to interior nudging within the RCM. The use of interior nudging for downscaled regional climate simulations has been somewhat controversial over the past several years but has been recently attracting attention. Several recent studies that have used reanalysis (i.e., verifiable) fields as a proxy for GCM input have shown that interior nudging can be beneficial toward achieving the desired downscaled fields. In this study, the value of nudging will be shown using fields from ModelE that are downscaled using WRF. Several different methods of nudging are explored, and it will be shown that the method of nudging and the choices made with respect to how nudging is used in WRF are critical to balance the constraint of ModelE against the freedom of WRF to develop its own fields.
Energy Technology Data Exchange (ETDEWEB)
Pradhan, Santosh K., E-mail: santosh@aerb.gov.in [Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai 400094 (India); Obaidurrahman, K. [Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai 400094 (India); Iyer, Kannan N. [Department of Mechanical Engineering, IIT Bombay, Mumbai 400076 (India); Gaikwad, Avinash J. [Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai 400094 (India)
2016-04-15
Highlights: • A multi-point kinetics model is developed for RELAP5 system thermal hydraulics code. • Model is validated against extensive 3D kinetics code. • RELAP5 multi-point kinetics formulation is used to investigate critical break for LOCA in PHWR. - Abstract: Point kinetics approach in system code RELAP5 limits its use for many of the reactivity induced transients, which involve asymmetric core behaviour. Development of fully coupled 3D core kinetics code with system thermal-hydraulics is the ultimate requirement in this regard; however coupling and validation of 3D kinetics module with system code is cumbersome and it also requires access to source code. An intermediate approach with multi-point kinetics is appropriate and relatively easy to implement for analysis of several asymmetric transients for large cores. Multi-point kinetics formulation is based on dividing the entire core into several regions and solving ODEs describing kinetics in each region. These regions are interconnected by spatial coupling coefficients which are estimated from diffusion theory approximation. This model offers an advantage that associated ordinary differential equations (ODEs) governing multi-point kinetics formulation can be solved using numerical methods to the desired level of accuracy and thus allows formulation based on user defined control variables, i.e., without disturbing the source code and hence also avoiding associated coupling issues. Euler's method has been used in the present formulation to solve several coupled ODEs internally at each time step. The results have been verified against inbuilt point-kinetics models of RELAP5 and validated against 3D kinetics code TRIKIN. The model was used to identify the critical break in RIH of a typical large PHWR core. The neutronic asymmetry produced in the core due to the system induced transient was effectively handled by the multi-point kinetics model overcoming the limitation of in-built point kinetics model
Innovation, Decentralization, and Planning in a Multi-Region Model of Schumpeterian Economic Growth
Batabyal, Amit; Nijkamp, Peter
2014-01-01
We study innovation and the resulting Schumpeterian economic growth that this innovation gives rise to in a model with N heterogeneous regions. For each region i where i=1,...,N, our analysis leads to five findings. First, we define the balanced growth path (BGP) allocations and the equilibrium of interest. Second, we stipulate the form of the innovation possibilities frontier that is consistent with balanced economic growth. Third, we derive the growth rate of the ith region in the decentral...
International Nuclear Information System (INIS)
Zhang, Wencheng; Peng, Shuijun; Sun, Chuanwang
2015-01-01
As the service sector dominates the economy in developed countries, its environmental impact has become an important issue. Based on a multi-regional input–output model, this paper estimates consumption-based emissions of service sectors of 41 countries and regions, and discusses the emission abatement policy of service sectors. The results indicate that consumption-based emissions of the service sector in most countries and regions are much greater than direct emissions generated by the service sector. Further decomposition by production sources demonstrates that final demand for services in certain countries causes substantial emissions in the other countries. In most countries, major parts of consumption-based emissions of the service sector come from upstream emissions in non-service sectors due to the intermediate consumption of non-service inputs in the service sector. For the US and China, the consumption-based emissions of their service sectors are traced back to different service consumption bundles and production sectors, which enable us to identify service categories and production sectors that play key roles in the impact of service sectors on CO 2 emissions. Finally, policy implications of the results are discussed for the climate effect of the service-oriented economy, global mitigation of climate change, sustainability, and the decarbonization of the service sector. - Highlights: • A consumption perspective for the assessment of the environmental impact of the service sector. • International supply chain effect is analyzed using a global input–output model. • Consumption-based emissions of the service sector are decomposed in two ways. • Policy implications for emissions mitigation in the service-oriented economy.
Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.
Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua
2018-02-01
Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.
Analysis of Phenix End-of-Life asymmetry test with multi-dimensional pool modeling of MARS-LMR code
International Nuclear Information System (INIS)
Jeong, H.-Y.; Ha, K.-S.; Choi, C.-W.; Park, M.-G.
2015-01-01
Highlights: • Pool behaviors under asymmetrical condition in an SFR were evaluated with MARS-LMR. • The Phenix asymmetry test was analyzed one-dimensionally and multi-dimensionally. • One-dimensional modeling has limitation to predict the cold pool temperature. • Multi-dimensional modeling shows improved prediction of stratification and mixing. - Abstract: The understanding of complicated pool behaviors and its modeling is essential for the design and safety analysis of a pool-type Sodium-cooled Fast Reactor. One of the remarkable recent efforts on the study of pool thermal–hydraulic behaviors is the asymmetrical test performed as a part of Phenix End-of-Life tests by the CEA. To evaluate the performance of MARS-LMR code, which is a key system analysis tool for the design of an SFR in Korea, in the prediction of thermal hydraulic behaviors during an asymmetrical condition, the Phenix asymmetry test is analyzed with MARS-LMR in the present study. Pool regions are modeled with two different approaches, one-dimensional modeling and multi-dimensional one, and the prediction results are analyzed to identify the appropriateness of each modeling method. The prediction with one-dimensional pool modeling shows a large deviation from the measured data at the early stage of the test, which suggests limitations to describe the complicated thermal–hydraulic phenomena. When the pool regions are modeled multi-dimensionally, the prediction gives improved results quite a bit. This improvement is explained by the enhanced modeling of pool mixing with the multi-dimensional modeling. On the basis of the results from the present study, it is concluded that an accurate modeling of pool thermal–hydraulics is a prerequisite for the evaluation of design performance and safety margin quantification in the future SFR developments
A characteristics of East Asian climate using high-resolution regional climate model
Yhang, Y.
2013-12-01
Climate research, particularly application studies for water, agriculture, forestry, fishery and energy management require fine scale multi-decadal information of meteorological, oceanographic and land states. Unfortunately, spatially and temporally homogeneous multi-decadal observations of these variables in high horizontal resolution are non-existent. Some long term surface records of temperature and precipitation exist, but the number of observation is very limited and the measurements are often contaminated by changes in instrumentation over time. Some climatologically important variables, such as soil moisture, surface evaporation, and radiation are not even measured over most of East Asia. Reanalysis is one approach to obtaining long term homogeneous analysis of needed variables. However, the horizontal resolution of global reanalysis is of the order of 100 to 200 km, too coarse for many application studies. Regional climate models (RCMs) are able to provide valuable regional finescale information, especially in regions where the climate variables are strongly regulated by the underlying topography and the surface heterogeneity. In this study, we will provide accurately downscaled regional climate over East Asia using the Global/Regional Integrated Model system [GRIMs; Hong et al. 2013]. A mixed layer model is embedded within the GRIMs in order to improve air-sea interaction. A detailed description of the characteristics of the East Asian summer and winter climate will be presented through the high-resolution numerical simulations. The increase in horizontal resolution is expected to provide the high-quality data that can be used in various application areas such as hydrology or environmental model forcing.
Ortiz-Jaramillo, B.; Fandiño Toro, H. A.; Benitez-Restrepo, H. D.; Orjuela-Vargas, S. A.; Castellanos-Domínguez, G.; Philips, W.
2012-03-01
Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.
Clustering of European winter storms: A multi-model perspective
Renggli, Dominik; Buettner, Annemarie; Scherb, Anke; Straub, Daniel; Zimmerli, Peter
2016-04-01
The storm series over Europe in 1990 (Daria, Vivian, Wiebke, Herta) and 1999 (Anatol, Lothar, Martin) are very well known. Such clusters of severe events strongly affect the seasonally accumulated damage statistics. The (re)insurance industry has quantified clustering by using distribution assumptions deduced from the historical storm activity of the last 30 to 40 years. The use of storm series simulated by climate models has only started recently. Climate model runs can potentially represent 100s to 1000s of years, allowing a more detailed quantification of clustering than the history of the last few decades. However, it is unknown how sensitive the representation of clustering is to systematic biases. Using a multi-model ensemble allows quantifying that uncertainty. This work uses CMIP5 decadal ensemble hindcasts to study clustering of European winter storms from a multi-model perspective. An objective identification algorithm extracts winter storms (September to April) in the gridded 6-hourly wind data. Since the skill of European storm predictions is very limited on the decadal scale, the different hindcast runs are interpreted as independent realizations. As a consequence, the available hindcast ensemble represents several 1000 simulated storm seasons. The seasonal clustering of winter storms is quantified using the dispersion coefficient. The benchmark for the decadal prediction models is the 20th Century Reanalysis. The decadal prediction models are able to reproduce typical features of the clustering characteristics observed in the reanalysis data. Clustering occurs in all analyzed models over the North Atlantic and European region, in particular over Great Britain and Scandinavia as well as over Iberia (i.e. the exit regions of the North Atlantic storm track). Clustering is generally weaker in the models compared to reanalysis, although the differences between different models are substantial. In contrast to existing studies, clustering is driven by weak
Li, D.; Fang, N. Z.
2017-12-01
Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.
Effectiveness of meta-models for multi-objective optimization of centrifugal impeller
Energy Technology Data Exchange (ETDEWEB)
Bellary, Sayed Ahmed Imran; Samad, Abdus [Indian Institute of Technology Madras, Chennai (India); Husain, Afzal [Sultan Qaboos University, Al-Khoudh (Oman)
2014-12-15
The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.
Effectiveness of meta-models for multi-objective optimization of centrifugal impeller
International Nuclear Information System (INIS)
Bellary, Sayed Ahmed Imran; Samad, Abdus; Husain, Afzal
2014-01-01
The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.
DEFF Research Database (Denmark)
Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne
2003-01-01
Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...
A framework to analyze emissions implications of ...
Future year emissions depend highly on the evolution of the economy, technology and current and future regulatory drivers. A scenario framework was adopted to analyze various technology development pathways and societal change while considering existing regulations and future uncertainty in regulations and evaluate resulting emissions growth patterns. The framework integrates EPA’s energy systems model with an economic Input-Output (I/O) Life Cycle Assessment model. The EPAUS9r MARKAL database is assembled from a set of technologies to represent the U.S. energy system within MARKAL bottom-up technology rich energy modeling framework. The general state of the economy and consequent demands for goods and services from these sectors are taken exogenously in MARKAL. It is important to characterize exogenous inputs about the economy to appropriately represent the industrial sector outlook for each of the scenarios and case studies evaluated. An economic input-output (I/O) model of the US economy is constructed to link up with MARKAL. The I/O model enables user to change input requirements (e.g. energy intensity) for different sectors or the share of consumer income expended on a given good. This gives end-users a mechanism for modeling change in the two dimensions of technological progress and consumer preferences that define the future scenarios. The framework will then be extended to include environmental I/O framework to track life cycle emissions associated
Multi-Agent Modeling in Managing Six Sigma Projects
Directory of Open Access Journals (Sweden)
K. Y. Chau
2009-10-01
Full Text Available In this paper, a multi-agent model is proposed for considering the human resources factor in decision making in relation to the six sigma project. The proposed multi-agent system is expected to increase the acccuracy of project prioritization and to stabilize the human resources service level. A simulation of the proposed multiagent model is conducted. The results show that a multi-agent model which takes into consideration human resources when making decisions about project selection and project team formation is important in enabling efficient and effective project management. The multi-agent modeling approach provides an alternative approach for improving communication and the autonomy of six sigma projects in business organizations.
Quan, Hui; Mao, Xuezhou; Tanaka, Yoko; Binkowitz, Bruce; Li, Gang; Chen, Josh; Zhang, Ji; Zhao, Peng-Liang; Ouyang, Soo Peter; Chang, Mark
2017-07-01
Extensive research has been conducted in the Multi-Regional Clinical Trial (MRCT) area. To effectively apply an appropriate approach to a MRCT, we need to synthesize and understand the features of different approaches. In this paper, examples are used to illustrate considerations regarding design, conduct, analysis and interpretation of result of MRCTs. We start with a brief discussion of region definitions and the scenarios where different regions have differing requirements for a MRCT. We then compare different designs and models as well as the corresponding interpretation of the results. We highlight the importance of paying special attention to trial monitoring and conduct to prevent potential issues associated with the final trial results. Besides evaluating the overall treatment effect for the entire MRCT, we also consider other key analyses including quantification of regional treatment effects within a MRCT, and assessment of consistency of these regional treatment effects. Copyright © 2017 Elsevier Inc. All rights reserved.
Lamarque, J.-F.; Dentener, F.; McConnell, J.; Ro, C.-U.; Shaw, M.; Vet, R.; Bergmann, D.; Cameron-Smith, P.; Doherty, R.; Faluvegi, G.;
2013-01-01
We present multi-model global datasets of nitrogen and sulfate deposition covering time periods from 1850 to 2100, calculated within the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The computed deposition fluxes are compared to surface wet deposition and ice-core measurements. We use a new dataset of wet deposition for 2000-2002 based on critical assessment of the quality of existing regional network data. We show that for present-day (year 2000 ACCMIP time-slice), the ACCMIP results perform similarly to previously published multi-model assessments. For this time slice, we find a multi-model mean deposition of 50 Tg(N) yr1 from nitrogen oxide emissions, 60 Tg(N) yr1 from ammonia emissions, and 83 Tg(S) yr1 from sulfur emissions. The analysis of changes between 1980 and 2000 indicates significant differences between model and measurements over the United States but less so over Europe. This difference points towards misrepresentation of 1980 NH3 emissions over North America. Based on ice-core records, the 1850 deposition fluxes agree well with Greenland ice cores but the change between 1850 and 2000 seems to be overestimated in the Northern Hemisphere for both nitrogen and sulfur species. Using the Representative Concentration Pathways to define the projected climate and atmospheric chemistry related emissions and concentrations, we find large regional nitrogen deposition increases in 2100 in Latin America, Africa and parts of Asia under some of the scenarios considered. Increases in South Asia are especially large, and are seen in all scenarios, with 2100 values more than double 2000 in some scenarios and reaching 1300 mg(N) m2 yr1 averaged over regional to continental scale regions in RCP 2.6 and 8.5, 3050 larger than the values in any region currently (2000). The new ACCMIP deposition dataset provides novel, consistent and evaluated global gridded deposition fields for use in a wide range of climate and ecological studies.
The framework of a UAS-aided flash flood modeling system for coastal regions
Zhang, H.; Xu, H.
2016-02-01
Flash floods cause severe economic damage and are one of the leading causes of fatalities connected with natural disasters in the Gulf Coast region. Current flash flood modeling systems rely on empirical hydrological models driven by precipitation estimates only. Although precipitation is the driving factor for flash floods, soil moisture, urban drainage system and impervious surface have been recognized to have significant impacts on the development of flash floods. We propose a new flash flooding modeling system that integrates 3-D hydrological simulation with satellite and multi-UAS observations. It will have three advantages over existing modeling systems. First, it will incorporate 1-km soil moisture data through integrating satellite images from European SMOS mission and NASA's SMAP mission. The utilization of high-resolution satellite images will provide essential information to determine antecedent soil moisture condition, which is an essential control on flood generation. Second, this system is able to adjust flood forecasting based on real-time inundation information collected by multi-UAS. A group of UAS will be deployed during storm events to capture the changing extent of flooded areas and water depth at multiple critical locations simultaneously. Such information will be transmitted to a hydrological model to validate and improve flood simulation. Third, the backbone of this system is a state-of-the-art 3-D hydrological model that assimilates the hydrological information from satellites and multi-UAS. The model is able to address surface water-groundwater interactions and reflect the effects of various infrastructures. Using Web-GIS technologies, the modeling results will be available online as interactive flood maps accessible to the public. To support the development and verification of this modeling system, surface and subsurface hydrological observations will be conducted in a number of small watersheds in the Coastal Bend region. We envision this
A parametric investigation of hydrogen hcci combustion using a multi-zone model approach
International Nuclear Information System (INIS)
Komninos, N.P.; Hountalas, D.T.; Rakopoulos, C.D.
2007-01-01
The purpose of the present study is to examine the effect of various operating variables of a homogeneous charge compression ignition (HCCI) engine fueled with hydrogen, using a multi-zone model developed by the authors. The multi-zone model consists of zones, which are allotted spatial locations within the combustion chamber. The model takes into account heat transfer between the zones and the combustion chamber walls, providing a spatial temperature distribution during the closed part of the engine cycle, i.e. compression, combustion and expansion. Mass transfer between zones is also accounted for, based on the geometric configuration of the zones, and includes the flow of mass in and out of the crevice regions, represented by the crevice zone. Combustion is incorporated using chemical kinetics based on a chemical reaction mechanism for the oxidation of hydrogen. This chemical reaction mechanism also includes the reactions for nitrogen oxides formation. Using the multi-zone model a parametric investigation is conducted, in order to determine the effect of engine speed, equivalence ratio, compression ratio, inlet pressure and inlet temperature, on the performance, combustion characteristics and emissions of an HCCI engine fueled with hydrogen
Hierarchical Model for the Similarity Measurement of a Complex Holed-Region Entity Scene
Directory of Open Access Journals (Sweden)
Zhanlong Chen
2017-11-01
Full Text Available Complex multi-holed-region entity scenes (i.e., sets of random region with holes are common in spatial database systems, spatial query languages, and the Geographic Information System (GIS. A multi-holed-region (region with an arbitrary number of holes is an abstraction of the real world that primarily represents geographic objects that have more than one interior boundary, such as areas that contain several lakes or lakes that contain islands. When the similarity of the two complex holed-region entity scenes is measured, the number of regions in the scenes and the number of holes in the regions are usually different between the two scenes, which complicates the matching relationships of holed-regions and holes. The aim of this research is to develop several holed-region similarity metrics and propose a hierarchical model to measure comprehensively the similarity between two complex holed-region entity scenes. The procedure first divides a complex entity scene into three layers: a complex scene, a micro-spatial-scene, and a simple entity (hole. The relationships between the adjacent layers are considered to be sets of relationships, and each level of similarity measurements is nested with the adjacent one. Next, entity matching is performed from top to bottom, while the similarity results are calculated from local to global. In addition, we utilize position graphs to describe the distribution of the holed-regions and subsequently describe the directions between the holes using a feature matrix. A case study that uses the Great Lakes in North America in 1986 and 2015 as experimental data illustrates the entire similarity measurement process between two complex holed-region entity scenes. The experimental results show that the hierarchical model accounts for the relationships of the different layers in the entire complex holed-region entity scene. The model can effectively calculate the similarity of complex holed-region entity scenes, even if the
McLeod, Jeffrey D; Brinkman, Gregory L; Milford, Jana B
2014-11-18
Enhanced prospects for natural gas production raise questions about the balance of impacts on air quality, as increased emissions from production activities are considered alongside the reductions expected when natural gas is burned in place of other fossil fuels. This study explores how trends in natural gas production over the coming decades might affect emissions of greenhouse gases (GHG), volatile organic compounds (VOCs) and nitrogen oxides (NOx) for the United States and its Rocky Mountain region. The MARKAL (MARKet ALlocation) energy system optimization model is used with the U.S. Environmental Protection Agency's nine-region database to compare scenarios for natural gas supply and demand, constraints on the electricity generation mix, and GHG emissions fees. Through 2050, total energy system GHG emissions show little response to natural gas supply assumptions, due to offsetting changes across sectors. Policy-driven constraints or emissions fees are needed to achieve net reductions. In most scenarios, wind is a less expensive source of new electricity supplies in the Rocky Mountain region than natural gas. U.S. NOx emissions decline in all the scenarios considered. Increased VOC emissions from natural gas production offset part of the anticipated reductions from the transportation sector, especially in the Rocky Mountain region.
The two-loop symbol of all multi-Regge regions
International Nuclear Information System (INIS)
Bargheer, Till; Papathanasiou, Georgios; Schomerus, Volker
2016-01-01
We study the symbol of the two-loop n-gluon MHV amplitude for all Mandelstam regions in multi-Regge kinematics in N=4 super Yang-Mills theory. While the number of distinct Mandelstam regions grows exponentially with n, the increase of independent symbols turns out to be merely quadratic. We uncover how to construct the symbols for any number of external gluons from just two building blocks which are naturally associated with the six- and seven-gluon amplitude, respectively. The second building block is entirely new, and in addition to its symbol, we also construct a prototype function that correctly reproduces all terms of maximal functional transcendentality.
The two-loop symbol of all multi-Regge regions
International Nuclear Information System (INIS)
Bargheer, Till; Schomerus, Volker; Papathanasiou, Georgios
2015-12-01
We study the symbol of the two-loop n-gluon MHV amplitude for all Mandelstam regions in multi-Regge kinematics in N= 4 super Yang-Mills theory. While the number of distinct Mandelstam regions grows exponentially with n, the increase of independent symbols turns out to be merely quadratic. We uncover how to construct the symbols for any number of external gluons from just two building blocks which are naturally associated with the six- and seven-gluon amplitude, respectively. The second building block is entirely new, and in addition to its symbol, we also construct a prototype function that correctly reproduces all terms of maximal functional transcendentality.
Assessment of Surface Air Temperature over China Using Multi-criterion Model Ensemble Framework
Li, J.; Zhu, Q.; Su, L.; He, X.; Zhang, X.
2017-12-01
The General Circulation Models (GCMs) are designed to simulate the present climate and project future trends. It has been noticed that the performances of GCMs are not always in agreement with each other over different regions. Model ensemble techniques have been developed to post-process the GCMs' outputs and improve their prediction reliabilities. To evaluate the performances of GCMs, root-mean-square error, correlation coefficient, and uncertainty are commonly used statistical measures. However, the simultaneous achievements of these satisfactory statistics cannot be guaranteed when using many model ensemble techniques. Meanwhile, uncertainties and future scenarios are critical for Water-Energy management and operation. In this study, a new multi-model ensemble framework was proposed. It uses a state-of-art evolutionary multi-objective optimization algorithm, termed Multi-Objective Complex Evolution Global Optimization with Principle Component Analysis and Crowding Distance (MOSPD), to derive optimal GCM ensembles and demonstrate the trade-offs among various solutions. Such trade-off information was further analyzed with a robust Pareto front with respect to different statistical measures. A case study was conducted to optimize the surface air temperature (SAT) ensemble solutions over seven geographical regions of China for the historical period (1900-2005) and future projection (2006-2100). The results showed that the ensemble solutions derived with MOSPD algorithm are superior over the simple model average and any single model output during the historical simulation period. For the future prediction, the proposed ensemble framework identified that the largest SAT change would occur in the South Central China under RCP 2.6 scenario, North Eastern China under RCP 4.5 scenario, and North Western China under RCP 8.5 scenario, while the smallest SAT change would occur in the Inner Mongolia under RCP 2.6 scenario, South Central China under RCP 4.5 scenario, and
Directory of Open Access Journals (Sweden)
Dan Wu
2009-06-01
Full Text Available The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and water sectors within a basin. With the precondition of strictly controlling maximum emissions rights, initial water rights were allocated between the first and the second levels of the hierarchy in order to promote fair and coordinated development across different regions of the basin and coordinated and efficient water use across different water sectors, realize the maximum comprehensive benefits to the basin, promote the unity of quantity and quality of initial water rights allocation, and eliminate water conflict across different regions and water sectors. According to interactive decision-making theory, a principal-subordinate hierarchical interactive iterative algorithm based on the satisfaction degree was developed and used to solve the initial water rights allocation model. A case study verified the validity of the model.
Kerr, Gaige Hunter; DeGaetano, Arthur T.; Stoof, Cathelijne R.; Ward, Daniel
2018-01-01
This study is among the first to investigate wildland fire risk in the Northeastern and the Great Lakes states under a changing climate. We use a multi-model ensemble (MME) of regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) together with the Canadian Forest
A Multi-Model Approach for System Diagnosis
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur
2007-01-01
A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....
Qin, Changbo; Qin, C.; Su, Zhongbo; Bressers, Johannes T.A.; Jia, Y.; Wang, H.
2013-01-01
This paper describes a multi-region computable general equilibrium model for analyzing the effectiveness of measures and policies for mitigating North China’s water scarcity with respect to three different groups of scenarios. The findings suggest that a reduction in groundwater use would negatively
Multi-basin, Multi-sector Drought Economic Impact Model in Python: Development and Applications
Gutenson, J. L.; Zhu, L.; Ernest, A. N. S.; Oubeidillah, A.; Bearden, B.; Johnson, T. G.
2015-12-01
Drought is one of the most economically disastrous natural hazards, one whose impacts are exacerbated by the lack of abrupt onset and offset that define tornados and hurricanes. In the United States, about 30 billion dollars losses is caused by drought in 2012, resulting in widespread economic impacts for societies, industries, agriculture, and recreation. And in California, the drought cost statewide economic losses about 2.2 billion, with a total loss of 17,100 seasonal and part-time jobs. Driven by a variety of factors including climate change, population growth, increased water demands, alteration to land cover, drought occurs widely all over the world. Drought economic consequence assessment tool are greatly needed to allow decision makers and stakeholders to anticipate and manage effectively. In this study, current drought economic impact modeling methods were reviewed. Most of these models only deal with the impact in the agricultural sector with a focus on a single basin; few of these models analyze long term impact. However, drought impacts are rarely restricted to basin boundaries, and cascading economic impacts are likely to be significant. A holistic approach to multi-basin, multi-sector drought economic impact assessment is needed.In this work, we developed a new model for drought economic impact assessment, Drought Economic Impact Model in Python (PyDEM). This model classified all business establishments into thirteen categories based on NAICS, and using a continuous dynamic social accounting matrix approach, coupled with calculation of the indirect consequences for the local and regional economies and the various resilience. In addition, Environmental Policy Integrated Climate model was combined for analyzing drought caused soil erosion together with agriculture production, and then the long term impacts of drought were achieved. A visible output of this model was presented in GIS. In this presentation, Choctawhatchee-Pea-Yellow River Basins, Alabama
Multi-region relaxed Hall magnetohydrodynamics with flow
Energy Technology Data Exchange (ETDEWEB)
Lingam, Manasvi, E-mail: mlingam@princeton.edu [Department of Astrophysical Sciences, Princeton University, Princeton, New Jersey 08544 (United States); Abdelhamid, Hamdi M., E-mail: hamdi@ppl.k.u-tokyo.ac.jp [Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561 (Japan); Physics Department, Faculty of Science, Mansoura University, Mansoura 35516 (Egypt); Hudson, Stuart R., E-mail: shudson@pppl.gov [Princeton Plasma Physics Laboratory, PO Box 451, Princeton, New Jersey 08543 (United States)
2016-08-15
The recent formulations of multi-region relaxed magnetohydrodynamics (MRxMHD) have generalized the famous Woltjer-Taylor states by incorporating a collection of “ideal barriers” that prevent global relaxation and flow. In this paper, we generalize MRxMHD with flow to include Hall effects, and thereby obtain the partially relaxed counterparts of the famous double Beltrami states as a special subset. The physical and mathematical consequences arising from the introduction of the Hall term are also presented. We demonstrate that our results (in the ideal MHD limit) constitute an important subset of ideal MHD equilibria, and we compare our approach against other variational principles proposed for deriving the partially relaxed states.
Multi-time, multi-scale correlation functions in turbulence and in turbulent models
Biferale, L.; Boffetta, G.; Celani, A.; Toschi, F.
1999-01-01
A multifractal-like representation for multi-time, multi-scale velocity correlation in turbulence and dynamical turbulent models is proposed. The importance of subleading contributions to time correlations is highlighted. The fulfillment of the dynamical constraints due to the equations of motion is
Coexisting chaotic and multi-periodic dynamics in a model of cardiac alternans
Energy Technology Data Exchange (ETDEWEB)
Skardal, Per Sebastian, E-mail: skardals@gmail.com [Departament d' Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona (Spain); Restrepo, Juan G., E-mail: juanga@colorado.edu [Department of Applied Mathematics, University of Colorado, Boulder, Colorado 80309 (United States)
2014-12-15
The spatiotemporal dynamics of cardiac tissue is an active area of research for biologists, physicists, and mathematicians. Of particular interest is the study of period-doubling bifurcations and chaos due to their link with cardiac arrhythmogenesis. In this paper, we study the spatiotemporal dynamics of a recently developed model for calcium-driven alternans in a one dimensional cable of tissue. In particular, we observe in the cable coexistence of regions with chaotic and multi-periodic dynamics over wide ranges of parameters. We study these dynamics using global and local Lyapunov exponents and spatial trajectory correlations. Interestingly, near nodes—or phase reversals—low-periodic dynamics prevail, while away from the nodes, the dynamics tend to be higher-periodic and eventually chaotic. Finally, we show that similar coexisting multi-periodic and chaotic dynamics can also be observed in a detailed ionic model.
International Nuclear Information System (INIS)
Kacha, K.; Djeffal, F.; Ferhati, H.; Arar, D.; Meguellati, M.
2015-01-01
We present a new approach based on the multi-trench technique to improve the electrical performances, which are the fill factor and the electrical efficiency. The key idea behind this approach is to introduce a new multi-trench region in the intrinsic layer, in order to modulate the total resistance of the solar cell. Based on 2-D numerical investigation and optimization of amorphous SiGe double-junction (a-Si:H/a-SiGe:H) thin film solar cells, in the present paper numerical models of electrical and optical parameters are developed to explain the impact of the multi-trench technique on the improvement of the double-junction solar cell electrical behavior for high performance photovoltaic applications. In this context, electrical characteristics of the proposed design are analyzed and compared with conventional amorphous silicon double-junction thin-film solar cells. (paper)
Directory of Open Access Journals (Sweden)
Constanta Nicoleta BODEA
2008-01-01
Full Text Available Is an original paper, which contains a hierarchical model with three levels, for determining the linearized non-homogeneous and homogeneous credibility premiums at company level, at sector level and at contract level, founded on the relevant covariance relations between the risk premium, the observations and the weighted averages. We give a rather explicit description of the input data for the multi- level hierarchical model used, only to show that in practical situations, there will always be enough data to apply credibility theory to a real insurance portfolio.
Role of disorder in the multi-critical region of d-wave superconductivity and antiferromagnetism
International Nuclear Information System (INIS)
Yanase, Youichi; Ogata, Masao
2007-01-01
We investigate the disorder-induced microscopic inhomogeneity in the multi-critical region of d-wave superconductivity and antiferromagnetism on the basis of the microscopic t-t ' -U-V model. We find that a small amount of point disorder induces the nano-scale inhomogeneity of spin and superconducting fluctuations when the coherence length of superconductivity is remarkably short as in the under-doped cuprates. Then, the two fluctuations spatially segregate to avoid their competition. We show the remarkable electron-hole asymmetry in high-T c cuprates where the quite different spatial structure is expected in the electron-doped materials
Directory of Open Access Journals (Sweden)
Wenyi Wang
2013-12-01
Full Text Available An inexact fuzzy multi-objective programming model (IFMOP based on the environmental carrying capacity is provided for industrial structure optimization problems. In the IFMOP model, both fuzzy linear programming (FLP and inexact linear programming (ILP methods are introduced into a multi-objective programming framework. It allows uncertainties to be directly communicated into the problem solving processing, and it can effectively reflect the complexity and uncertainty of an industrial system without impractical simplification. The two objective functions utilized in the optimization study are the maximum total output value and population size, and the constraints include water environmental capacity, water resource supply, atmospheric environmental capacity and energy supply. The model is subsequently employed in a realistic case for industrial development in the Tongzhou district, Beijing, China. The results demonstrate that the model can help to analyze whether the environmental carrying capacity of Tongzhou can meet the needs of the social economic objectives in the new town plan in the two scenarios and can assist decision makers in generating stable and balanced industrial structure patterns with consideration of the resources, energy and environmental constraints to meet the maximum social economic efficiency.
Directory of Open Access Journals (Sweden)
Xiaoya Ma
2015-11-01
Full Text Available As the main feature of land use planning, land use allocation (LUA optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model. The main achievements of the present study are as follows: (a the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA. On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability.
Vliet, M.T.H. van; Blenkinsop, S.; Burton, A.; Harpham, C.; Broers, H.P.; Fowler, H.J.
2012-01-01
Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations
Modeling Regional Pollution Episodes With The Ctm Mocage.
Dufour, A.; Brocheton, F.; Amodei, M.; Peuch, V.-H.
Several regional ozone pollution episodes have been studied in the context of two recent extensive field campaigns in France: ESQUIF, in the Paris region and ES- COMPTE, in the vicinity of Marseilles. MOCAGE is an off-line multi-scale Chem- istry and Transport Model (CTM), driven by the operational numerical weather pre- diction models of Météo-France, ARPEGE and ALADIN. It covers from the global to the regional scale, by means of up to four levels of nested domains, and extends up to the middle stratosphere; thus, there is no need for external boundary conditions, neither on the horizontal or on the vertical. These original features allows to cover with MOCAGE a wide range of scientific applications, from routine air-pollution fore- casts to long-term simulations related to climate issues. The present study focuses on the simulation of regional-scale photo-oxidant episodes and on the impact on larger scales of the transport of ozone, of precursors and of reservoir species. The first ex- ample concerns a polluted episode of the ESQUIF campaign (IOP6). In addition to ground measurements, 8 flights have documented the situation, showing a diversity of chemical regimes. This variability is quite satisfactorily reproduced by the model. A special attention was also paid to vertical and horizontal exchanges, particularly to interactions between the boundary layer and the free troposphere. An interesting case of an ill-represented residual nocturnal plume in the simulation of ESQUIF IOP5 will be presented: during this IOP, the vertical structure of the lower troposphere was well characterized by four flights. Free troposphere concentrations of ozone appear to be well reproduced by the model, except for the intensity and vertical extent of a residual plume, which are overestimated. For the day after, in addition to a direct impact on surface concentrations, the simulated development of the boundary layer is found to be too slow ; both errors contribute to an
Mathematical model comparing of the multi-level economics systems
Brykalov, S. M.; Kryanev, A. V.
2017-12-01
The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.
One color multi-photon ionization of the Gadolinium atom in near UV region
International Nuclear Information System (INIS)
Kim, Jin Tae; Yi, Jong Hoon; Lhee, Yong Joo; Lee, Jong Min
1999-01-01
We have investigated the states of the gadolinium atom in near ultra-violet (UV) region (∼410 nm) using single photon excitation using resonance ionization mass spectrometry (RIMS). Around 70 transitions among observed 180 single color multi-photon ionization signals have been assigned. Most of the multi-photon processes of the assigned ion signals are through single photon resonant three photon ionization and through two photon resonant three photon ionization. (author)
A novel model and behavior analysis for a swarm of multi-agent systems with finite velocity
International Nuclear Information System (INIS)
Wang Liang-Shun; Wu Zhi-Hai
2014-01-01
Inspired by the fact that in most existing swarm models of multi-agent systems the velocity of an agent can be infinite, which is not in accordance with the real applications, we propose a novel swarm model of multi-agent systems where the velocity of an agent is finite. The Lyapunov function method and LaSalle's invariance principle are employed to show that by using the proposed model all of the agents eventually enter into a bounded region around the swarm center and finally tend to a stationary state. Numerical simulations are provided to demonstrate the effectiveness of the theoretical results. (interdisciplinary physics and related areas of science and technology)
Development of integrated models for energy-economy systems analysis at JAERI
International Nuclear Information System (INIS)
Yasukawa, Shigeru; Mankin, Shuichi; Sato, Osamu; Yonese, Hiromi
1984-08-01
This report, being a revision of the preprint for distribution to participants at IEA/ETSAP Workshop held, at JAERI, Tokyo, March 1984, describes the concept of the integrated models for energy-economy systems analysis now being carried out at JAERI. In this model system, there contains four different categories of computer codes. The first one is a series of computer codes named as E 3 -SD representatively, which are utilized to develop a dynamic scenario generation in a long-term energy economy evolution. The second one, of which the main constituents are the MARKAL, i.e. an optimal energy flow analizer, and the TRANS-I/O, i.e. a multi-sectoral economy analyzer, has been developed for the analysis of structural characteristics embodied in our energy-economy system. The third one is for a strategy analysis on nuclear power reactor installation and fuel cycle development, and its main constituent is the JALTES. The fourth one is for a cost-benefit-risk analysis including various kinds of data bases. As the model system being still under development, but the idea of application of it to such a problem as '' the role of the HTGR in the prospects of future energy supply'' is also explained in the report. (author)
Wu, Sanmang; Li, Shantong; Lei, Yalin
2016-01-01
This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects. The boosting effect for the eastern provinces is primarily generated from local exports, whereas the western provinces primarily benefit from the export spillover effect from the eastern provinces. The eastern provinces, such as Guangdong, Zhejiang, Jiangsu, and Shanghai, are the primary sources of export spillover effects, and Guangdong is the largest source of export spillover effects for almost all of the provinces in China.
Loop equations for multi-cut matrix models
International Nuclear Information System (INIS)
Akemann, G.
1995-03-01
The loop equation for the complex one-matrix model with a multi-cut structure is derived and solved in the planar limit. An iterative scheme for higher genus contributions to the free energy and the multi-loop correlators is presented for the two-cut model, where explicit results are given up to and including genus two. The double-scaling limit is analyzed and the relation to the one-cut solution of the hermitian and complex one-matrix model is discussed. (orig.)
Multi-level decision making models, methods and applications
Zhang, Guangquan; Gao, Ya
2015-01-01
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.
Multi-criterion model ensemble of CMIP5 surface air temperature over China
Yang, Tiantian; Tao, Yumeng; Li, Jingjing; Zhu, Qian; Su, Lu; He, Xiaojia; Zhang, Xiaoming
2018-05-01
The global circulation models (GCMs) are useful tools for simulating climate change, projecting future temperature changes, and therefore, supporting the preparation of national climate adaptation plans. However, different GCMs are not always in agreement with each other over various regions. The reason is that GCMs' configurations, module characteristics, and dynamic forcings vary from one to another. Model ensemble techniques are extensively used to post-process the outputs from GCMs and improve the variability of model outputs. Root-mean-square error (RMSE), correlation coefficient (CC, or R) and uncertainty are commonly used statistics for evaluating the performances of GCMs. However, the simultaneous achievements of all satisfactory statistics cannot be guaranteed in using many model ensemble techniques. In this paper, we propose a multi-model ensemble framework, using a state-of-art evolutionary multi-objective optimization algorithm (termed MOSPD), to evaluate different characteristics of ensemble candidates and to provide comprehensive trade-off information for different model ensemble solutions. A case study of optimizing the surface air temperature (SAT) ensemble solutions over different geographical regions of China is carried out. The data covers from the period of 1900 to 2100, and the projections of SAT are analyzed with regard to three different statistical indices (i.e., RMSE, CC, and uncertainty). Among the derived ensemble solutions, the trade-off information is further analyzed with a robust Pareto front with respect to different statistics. The comparison results over historical period (1900-2005) show that the optimized solutions are superior over that obtained simple model average, as well as any single GCM output. The improvements of statistics are varying for different climatic regions over China. Future projection (2006-2100) with the proposed ensemble method identifies that the largest (smallest) temperature changes will happen in the
Friend, Adrian J; Ayoko, Godwin A; Guo, Hai
2011-01-15
The multi-criteria decision making methods, Preference Ranking Organization METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site>urban site>roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8±8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region. Copyright © 2010 Elsevier B.V. All rights reserved.
A multi-model analysis of vertical ozone profiles
Directory of Open Access Journals (Sweden)
J. E. Jonson
2010-06-01
Full Text Available A multi-model study of the long-range transport of ozone and its precursors from major anthropogenic source regions was coordinated by the Task Force on Hemispheric Transport of Air Pollution (TF HTAP under the Convention on Long-range Transboundary Air Pollution (LRTAP. Vertical profiles of ozone at 12-h intervals from 2001 are available from twelve of the models contributing to this study and are compared here with observed profiles from ozonesondes. The contributions from each major source region are analysed for selected sondes, and this analysis is supplemented by retroplume calculations using the FLEXPART Lagrangian particle dispersion model to provide insight into the origin of ozone transport events and the cause of differences between the models and observations.
In the boundary layer ozone levels are in general strongly affected by regional sources and sinks. With a considerably longer lifetime in the free troposphere, ozone here is to a much larger extent affected by processes on a larger scale such as intercontinental transport and exchange with the stratosphere. Such individual events are difficult to trace over several days or weeks of transport. This may explain why statistical relationships between models and ozonesonde measurements are far less satisfactory than shown in previous studies for surface measurements at all seasons. The lowest bias between model-calculated ozone profiles and the ozonesonde measurements is seen in the winter and autumn months. Following the increase in photochemical activity in the spring and summer months, the spread in model results increases, and the agreement between ozonesonde measurements and the individual models deteriorates further.
At selected sites calculated contributions to ozone levels in the free troposphere from intercontinental transport are shown. Intercontinental transport is identified based on differences in model calculations with unperturbed emissions and
Memmesheimer, M.; Jakobs, H. J.; Wurzler, S.; Friese, E.; Piekorz, G.; Ebel, A.
2009-04-01
The Rhine-Ruhr area is a strongly industrialized region with about 10 Million inhabitants. It is one of the regions in Europe, which has the characteristics of a megacity with respect to population density, traffic, industry and environmental issues. The main centre of European steel production and the biggest inland port of the world is located in Duisburg, one of the major cities in the Rhine-Ruhr area. Together with the nearby urban agglomerations in the Benelux area including Brussels, Amsterdam and in particular Rotterdam as one of the most important sea-harbours of the world together with Singapore and Shanghai, it forms one of the regions in Europe heavily loaded with air pollutants as ozone, NO2 and particulate matter. Ammonia emissions outside the urban agglomerations but within the domain are also on a quite high level due to intense agricultural usage in Benelux, North-Rhine-Westphalia and lower Saxony. Therefore this area acts also as an important source region for gaseous precursors contributing to the formation of secondary particles in the atmosphere. The Benelux/Rhine-Ruhr area therefore has been selected within the framework of the recently established FP7 research project CityZen as one hot spot for detailed investigations of the past and current status of air pollution and its future development on different spatial and temporal scales. Some examples from numerical simulations with the regional multi-scale chemistry transport model EURAD for Central Europe and the Rhine-Ruhr area will be presented. The model calculates the transport, chemical transformations and deposition of trace constituents in the troposphere from the surface up to about 16 km using MM5 as meteorological driver, the RACM-MIM gas-phase chemistry and MADE-SORGAM for the treatment of particulate matter. Horizontal grid sizes are in the range of 100 km down to 1 km for heavily polluted urbanized areas within Benelux/Rhine-Ruhr. The planetary boundary layer is resolved by 15
Robust multi-model predictive control of multi-zone thermal plate system
Directory of Open Access Journals (Sweden)
Poom Jatunitanon
2018-02-01
Full Text Available A modern controller was designed by using the mathematical model of a multi–zone thermal plate system. An important requirement for this type of controller is that it must be able to keep the temperature set-point of each thermal zone. The mathematical model used in the design was determined through a system identification process. The results showed that when the operating condition is changed, the performance of the controller may be reduced as a result of the system parameter uncertainties. This paper proposes a weighting technique of combining the robust model predictive controller for each operating condition into a single robust multi-model predictive control. Simulation and experimental results showed that the proposed method performed better than the conventional multi-model predictive control in rise time of transient response, when used in a system designed to work over a wide range of operating conditions.
Multi baryons with flavors in the Skyrme model
Energy Technology Data Exchange (ETDEWEB)
Schat, Carlos L. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil); Scoccola, Norberto N. [Comision Nacional de Energia Atomica, Buenos Aires (Argentina). Dept. of Physics
1999-07-01
We investigate the possible existence of multi baryons with heavy flavor quantum numbers using the bound state approach to the topological soliton model and the recently proposed approximation for multi skyrmion fields based on rational maps. We use an effective interaction Lagrangian which consistently incorporates both chiral symmetry and the heavy quark symmetry including the corrections up to order {omicron}(1/m{sub Q}). The model predicts some narrow heavy flavored multi baryon states with baryon number four and seven. (author)
Multi baryons with flavors in the Skyrme model
International Nuclear Information System (INIS)
Schat, Carlos L.; Scoccola, Norberto N.
1999-07-01
We investigate the possible existence of multi baryons with heavy flavor quantum numbers using the bound state approach to the topological soliton model and the recently proposed approximation for multi skyrmion fields based on rational maps. We use an effective interaction Lagrangian which consistently incorporates both chiral symmetry and the heavy quark symmetry including the corrections up to order ο(1/m Q ). The model predicts some narrow heavy flavored multi baryon states with baryon number four and seven. (author)
International Nuclear Information System (INIS)
Jablonski, Sophie; Bauen, Ausilio; Strachan, Neil; Brand, Christian
2010-01-01
This paper explores the prospects and policy implications for bioenergy to contribute to a long-term sustainable UK energy system. The UK MARKAL technology-focused energy systems dynamic cost optimisation model - which has been used to quantify the costs and benefits of alternative energy strategies in UK policy making - is enhanced with detailed representation of bio-energy chains and end-uses. This provides an important advance in linking bioenergy expert-knowledge with a whole system modelling approach, in order to better understand the potential role of bioenergy in an evolving energy system. The new BIOSYS-MARKAL model is used to run four scenarios constructed along the pillars of UK energy policy objectives (low carbon and energy security). The results are analysed in terms of bioenergy resources use and bioenergy pathways penetration in different end use sectors. The main findings suggest that the complexity of different bioenergy pathways may have been overlooked in previous modelling exercises. A range of bioenergy pathways - notably bio-heat and biofuels for transport - may have a much wider potential role to play. The extent to which this potential is fulfilled will be further determined by resources availability, and market segment constraints, as well as policy measures to improve deployment. (author)
Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.
2018-03-01
We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.
Multi-model-based Access Control in Construction Projects
Directory of Open Access Journals (Sweden)
Frank Hilbert
2012-04-01
Full Text Available During the execution of large scale construction projects performed by Virtual Organizations (VO, relatively complex technical models have to be exchanged between the VO members. For linking the trade and transfer of these models, a so-called multi-model container format was developed. Considering the different skills and tasks of the involved partners, it is not necessary for them to know all the models in every technical detailing. Furthermore, the model size can lead to a delay in communication. In this paper an approach is presented for defining model cut-outs according to the current project context. Dynamic dependencies to the project context as well as static dependencies on the organizational structure are mapped in a context-sensitive rule. As a result, an approach for dynamic filtering of multi-models is obtained which ensures, together with a filtering service, that the involved VO members get a simplified view of complex multi-models as well as sufficient permissions depending on their tasks.
Preliminary Multi-Variable Parametric Cost Model for Space Telescopes
Stahl, H. Philip; Hendrichs, Todd
2010-01-01
This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.
Multi-compartment Fire Modeling for Switchgear Room using CFAST
International Nuclear Information System (INIS)
Han, Kiyoon; Kang, Dae Il; Lim, Ho Gon
2015-01-01
In this study, multi-compartment fire modeling for fire propagation scenario from SWGR A to SWGR B is performed using CFAST. New fire PSA method (NUREG/CR-6850) requires that the severity factor is to be calculated by fire modeling. If fire modeling is not performed, the severity factor should be estimated as one conservatively. Also, the possibility of the damages of components and cables located at adjacent compartments should be considered. Detailed fire modeling of multi-compartment fires refers to the evaluation of fire-generated conditions in one compartment that spread to adjacent ones. In general, the severity factor for multi-compartment fire scenario is smaller than that of single compartment scenario. Preliminary quantification of Hanul Unit 3 fire PSA was performed without fire modeling. As a result of quantification, multi-compartment scenario, fire propagation scenario from switchgear room (SWGR) A to SWGR B, is one of significant contributor to the CDF. In this study, fire modeling of multi-compartment was performed by Consolidated Fire Growth and Smoke Transport (CFAST) to identify the possibility of fire propagation. As a result of fire simulation, it is identified that fire propagation has little influences
Multi-compartment Fire Modeling for Switchgear Room using CFAST
Energy Technology Data Exchange (ETDEWEB)
Han, Kiyoon; Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
In this study, multi-compartment fire modeling for fire propagation scenario from SWGR A to SWGR B is performed using CFAST. New fire PSA method (NUREG/CR-6850) requires that the severity factor is to be calculated by fire modeling. If fire modeling is not performed, the severity factor should be estimated as one conservatively. Also, the possibility of the damages of components and cables located at adjacent compartments should be considered. Detailed fire modeling of multi-compartment fires refers to the evaluation of fire-generated conditions in one compartment that spread to adjacent ones. In general, the severity factor for multi-compartment fire scenario is smaller than that of single compartment scenario. Preliminary quantification of Hanul Unit 3 fire PSA was performed without fire modeling. As a result of quantification, multi-compartment scenario, fire propagation scenario from switchgear room (SWGR) A to SWGR B, is one of significant contributor to the CDF. In this study, fire modeling of multi-compartment was performed by Consolidated Fire Growth and Smoke Transport (CFAST) to identify the possibility of fire propagation. As a result of fire simulation, it is identified that fire propagation has little influences.
On the extension of multi-phase models to sub-residual saturations
International Nuclear Information System (INIS)
Lingineni, S.; Chen, Y.T.; Boehm, R.F.
1995-01-01
This paper focuses on the limitations of applying multi-phase flow and transport models to simulate the hydrothermal processes occurring when the liquid saturation falls below residual levels. A typical scenario of a heat-generating high-level waste package emplaced in a backfilled drift of a waste repository is presented. The hydrothermal conditions in the vicinity of the waste package as well as in the far-field are determined using multi-phase, non-isothermal codes such as TOUGH2 and FEHM. As the waste package temperature increases, heat-pipe effects are created and water is driven away from the package into colder regions where it condenses. The variations in the liquid saturations close to the waste package are determined using these models with extended capillary pressure-saturations relationships to sub-residual regime. The predictions indicate even at elevated temperatures, waste package surroundings are not completely dry. However, if transport based modeling is used to represent liquid saturation variations in the sub-residual regime, then complete dry conditions are predicted within the backfill for extended periods of time. The relative humidity conditions near the waste package are also found to be sensitive to the representation of capillary pressure-saturation relationship used for sub-residual regime. An experimental investigation is carried out to study the variations in liquid saturations and relative humidity conditions in sub-residual regimes. Experimental results indicated that extended multi-phase models without interphase transport can not predict dry-out conditions and the simulations underpredict the humidity conditions near the waste package
Multi-metric model-based structural health monitoring
Jo, Hongki; Spencer, B. F.
2014-04-01
ABSTRACT The inspection and maintenance of bridges of all types is critical to the public safety and often critical to the economy of a region. Recent advanced sensor technologies provide accurate and easy-to-deploy means for structural health monitoring and, if the critical locations are known a priori, can be monitored by direct measurements. However, for today's complex civil infrastructure, the critical locations are numerous and often difficult to identify. This paper presents an innovative framework for structural monitoring at arbitrary locations on the structure combining computational models and limited physical sensor information. The use of multi-metric measurements is advocated to improve the accuracy of the approach. A numerical example is provided to illustrate the proposed hybrid monitoring framework, particularly focusing on fatigue life assessment of steel structures.
Multi-angle remote sensing has been proved useful for mapping vegetation community types in desert regions. Based on Multi-angle Imaging Spectro-Radiometer (MISR) multi-angular images, this study compares roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with th...
Design and implementation of space physics multi-model application integration based on web
Jiang, Wenping; Zou, Ziming
With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into
Multi-cut solutions in Chern-Simons matrix models
Morita, Takeshi; Sugiyama, Kento
2018-04-01
We elaborate the Chern-Simons (CS) matrix models at large N. The saddle point equations of these matrix models have a curious structure which cannot be seen in the ordinary one matrix models. Thanks to this structure, an infinite number of multi-cut solutions exist in the CS matrix models. Particularly we exactly derive the two-cut solutions at finite 't Hooft coupling in the pure CS matrix model. In the ABJM matrix model, we argue that some of multi-cut solutions might be interpreted as a condensation of the D2-brane instantons.
Modelling of nanoscale multi-gate transistors affected by atomistic interface roughness
Nagy, Daniel; Aldegunde, Manuel; Elmessary, Muhammad A.; García-Loureiro, Antonio J.; Seoane, Natalia; Kalna, Karol
2018-04-01
Interface roughness scattering (IRS) is one of the major scattering mechanisms limiting the performance of non-planar multi-gate transistors, like Fin field-effect transistors (FETs). Here, two physical models (Ando’s and multi-sub-band) of electron scattering with the interface roughness induced potential are investigated using an in-house built 3D finite element ensemble Monte Carlo simulation toolbox including parameter-free 2D Schrödinger equation quantum correction that handles all relevant scattering mechanisms within highly non-equilibrium carrier transport. Moreover, we predict the effect of IRS on performance of FinFETs with realistic channel cross-section shapes with respect to the IRS correlation length (Λ) and RMS height (Δ_RMS ). The simulations of the n-type SOI FinFETs with the multi-sub-band IRS model shows its very strong effect on electron transport in the device channel compared to the Ando’s model. We have also found that the FinFETs are strongly affected by the IRS in the ON-region. The limiting effect of the IRS significantly increases as the Fin width is reduced. The FinFETs with channel orientation are affected more by the IRS than those with the crystal orientation. Finally, Λ and Δ_RMS are shown to affect the device performance similarly. A change in values by 30% (Λ) or 20% (Δ_RMS ) results in an increase (decrease) of up to 13% in the drive current.
A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)
Weber, Michael
2004-01-01
The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...
Multi-year Estimates of Methane Fluxes in Alaska from an Atmospheric Inverse Model
Miller, S. M.; Commane, R.; Chang, R. Y. W.; Miller, C. E.; Michalak, A. M.; Dinardo, S. J.; Dlugokencky, E. J.; Hartery, S.; Karion, A.; Lindaas, J.; Sweeney, C.; Wofsy, S. C.
2015-12-01
We estimate methane fluxes across Alaska over a multi-year period using observations from a three-year aircraft campaign, the Carbon Arctic Reservoirs Vulnerability Experiment (CARVE). Existing estimates of methane from Alaska and other Arctic regions disagree in both magnitude and distribution, and before the CARVE campaign, atmospheric observations in the region were sparse. We combine these observations with an atmospheric particle trajectory model and a geostatistical inversion to estimate surface fluxes at the model grid scale. We first use this framework to estimate the spatial distribution of methane fluxes across the state. We find the largest fluxes in the south-east and North Slope regions of Alaska. This distribution is consistent with several estimates of wetland extent but contrasts with the distribution in most existing flux models. These flux models concentrate methane in warmer or more southerly regions of Alaska compared to the estimate presented here. This result suggests a discrepancy in how existing bottom-up models translate wetland area into methane fluxes across the state. We next use the inversion framework to explore inter-annual variability in regional-scale methane fluxes for 2012-2014. We examine the extent to which this variability correlates with weather or other environmental conditions. These results indicate the possible sensitivity of wetland fluxes to near-term variability in climate.
A Brief Review on the Baer-Nunziato type Multi-pressure Multi-fluid Models
International Nuclear Information System (INIS)
Lee, Sang Yong; Park, Chan Eok; Lee, Gyu Cheon
2010-01-01
Single pressure two-fluid flow equations have complex characteristics. This causes ill-posedness problem. Even though some authors show that the numerical solutions are well behaved if the number of mesh points is sufficiently small, the stability of the solution is always challenged. There have been several attempts to overcome these problems. Multi-pressure multi-fluid models are one of them. Among them, Baer and Nunziato (BN) derived an interesting two-fluid model. BN model has independent phase pressures. It is closed by inserting volume fraction evolution equation. In this paper, several aspects of the BN type model will be reviewed and some suggestion for the future study will be made
Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system
Directory of Open Access Journals (Sweden)
Y. Yan
2016-02-01
Full Text Available Small-scale nonlinear chemical and physical processes over pollution source regions affect the tropospheric ozone (O3, but these processes are not captured by current global chemical transport models (CTMs and chemistry–climate models that are limited by coarse horizontal resolutions (100–500 km, typically 200 km. These models tend to contain large (and mostly positive tropospheric O3 biases in the Northern Hemisphere. Here we use the recently built two-way coupling system of the GEOS-Chem CTM to simulate the regional and global tropospheric O3 in 2009. The system couples the global model (at 2.5° long. × 2° lat. and its three nested models (at 0.667° long. × 0.5° lat. covering Asia, North America and Europe, respectively. Specifically, the nested models take lateral boundary conditions (LBCs from the global model, better capture small-scale processes and feed back to modify the global model simulation within the nested domains, with a subsequent effect on their LBCs. Compared to the global model alone, the two-way coupled system better simulates the tropospheric O3 both within and outside the nested domains, as found by evaluation against a suite of ground (1420 sites from the World Data Centre for Greenhouse Gases (WDCGG, the United States National Oceanic and Atmospheric Administration (NOAA Earth System Research Laboratory Global Monitoring Division (GMD, the Chemical Coordination Centre of European Monitoring and Evaluation Programme (EMEP, and the United States Environmental Protection Agency Air Quality System (AQS, aircraft (the High-performance Instrumented Airborne Platform for Environmental Research (HIAPER Pole-to-Pole Observations (HIPPO and Measurement of Ozone and Water Vapor by Airbus In- Service Aircraft (MOZAIC and satellite measurements (two Ozone Monitoring Instrument (OMI products. The two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean surface O3
Wenger, Trey V.; Kepley, Amanda K.; Balser, Dana S.
2017-07-01
HII Region Models fits HII region models to observed radio recombination line and radio continuum data. The algorithm includes the calculations of departure coefficients to correct for non-LTE effects. HII Region Models has been used to model star formation in the nucleus of IC 342.
Regional climate response collaboratives: Multi-institutional support for climate resilience
Averyt, Kristen; Derner, Justin D.; Dilling, Lisa; Guerrero, Rafael; Joyce, Linda A.; McNeeley, Shannon; McNie, Elizabeth; Morisette, Jeffrey T.; Ojima, Dennis; O'Malley, Robin; Peck, Dannele; Ray, Andrea J.; Reeves, Matt; Travis, William
2018-01-01
Federal investments by U.S. agencies to enhance climate resilience at regional scales grew over the past decade (2010s). To maximize efficiency and effectiveness in serving multiple sectors and scales, it has become critical to leverage existing agency-specific research, infrastructure, and capacity while avoiding redundancy. We discuss lessons learned from a multi-institutional “regional climate response collaborative” that comprises three different federally-supported climate service entities in the Rocky Mountain west and northern plains region. These lessons include leveraging different strengths of each partner, creating deliberate mechanisms to increase cross-entity communication and joint ownership of projects, and placing a common priority on stakeholder-relevant research and outcomes. We share the conditions that fostered successful collaboration, which can be transferred elsewhere, and suggest mechanisms for overcoming potential barriers. Synergies are essential for producing actionable research that informs climate-related decisions for stakeholders and ultimately enhances climate resilience at regional scales.
The design of multi-core DSP parallel model based on message passing and multi-level pipeline
Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong
2017-10-01
Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.
Long-Term Monitoring of Water Dynamics in the Sahel Region Using the Multi-Sar
Bertram, A.; Wendleder, A.; Schmitt, A.; Huber, M.
2016-06-01
Fresh water is a scarce resource in the West-African Sahel region, seasonally influenced by droughts and floods. Particularly in terms of climate change, the importance of wetlands increases for flora, fauna, human population, agriculture, livestock and fishery. Hence, access to open water is a key factor. Long-term monitoring of water dynamics is of great importance, especially with regard to the spatio-temporal extend of wetlands and drylands. It can predict future trends and facilitate the development of adequate management strategies. Lake Tabalak, a Ramsar wetland of international importance, is one of the most significant ponds in Niger and a refuge for waterbirds. Nevertheless, human population growth increased the pressure on this ecosystem, which is now degrading for all uses. The main objective of the study is a long-term monitoring of the Lake Tabalak's water dynamics to delineate permanent and seasonal water bodies, using weather- and daytime-independent multi-sensor and multi-temporal Synthetic Aperture Radar (SAR) data available for the study area. Data of the following sensors from 1993 until 2016 are used: Sentinel-1A, TerraSARX, ALOS PALSAR-1/2, Envisat ASAR, RADARSAT-1/2, and ERS-1/2. All SAR data are processed with the Multi-SAR-System, unifying the different characteristics of all above mentioned sensors in terms of geometric, radiometric and polarimetric resolution to a consistent format. The polarimetric representation in Kennaugh elements allows fusing single-polarized data acquired by older sensors with multi-polarized data acquired by current sensors. The TANH-normalization guarantees a consistent and therefore comparable description in a closed data range in terms of radiometry. The geometric aspect is solved by projecting all images to an earth-fixed coordinate system correcting the brightness by the help of the incidence angle. The elevation model used in the geocoding step is the novel global model produced by the TanDEM-X satellite
Swiss taxation policies to curb CO{sub 2} emissions
Energy Technology Data Exchange (ETDEWEB)
Bahn, O.; Kypreos, S. [Paul Scherrer Inst. (PSI), Villigen (Switzerland); Fragniere, E. [HEC-Lausanne, Lausanne (Switzerland)
1997-06-01
This study offers insights about the design of economically efficient policies to curb carbon dioxide (CO{sub 2}) emissions in Switzerland. The method uses MARKAL, a bottom-up engineering model of the energy system. Based on a stochastic programming approach, this study proposes as a first option the introduction of a hedging carbon tax. Using then a multinational MARKAL model, this study considers as a second alternative an international co-operation to curb jointly CO{sub 2} emissions by means of a uniform carbon tax. (author) 1 fig., 6 refs.
International Nuclear Information System (INIS)
Koike, Hiroki; Kirimura, Kazuki; Yamaji, Kazuya; Kosaka, Shinya; Yamamoto, Akio
2018-01-01
A unified resonance self-shielding method, which can treat general sub-divided fuel regions, is developed for lattice physics calculations in reactor physics field. In a past study, a hybrid resonance treatment has been developed by theoretically integrating equivalence theory and ultra-fine-group slowing-down calculation. It can be applied to a wide range of neutron spectrum conditions including low moderator density ranges in severe accident states, as long as each fuel region is not sub-divided. In order to extend the method for radially and azimuthally sub-divided multi-region geometry, a new resonance treatment is established by incorporating the essence of sub-group method. The present method is composed of two-step flux calculation, i.e. 'coarse geometry + fine energy' (first step) and 'fine geometry + coarse energy' (second step) calculations. The first step corresponds to a hybrid model of the equivalence theory and the ultra-fine-group calculation, and the second step corresponds to the sub-group method. From the verification results, effective cross-sections by the new method show good agreement with the continuous energy Monte-Carlo results for various multi-region geometries including non-uniform fuel compositions and temperature distributions. The present method can accurately generate effective cross-sections with short computation time in general lattice physics calculations. (author)
Directory of Open Access Journals (Sweden)
Rim Amri
2014-06-01
Full Text Available The main goal of this study is to evaluate the potential of the FAO-56 dual technique for the estimation of regional evapotranspiration (ET and its constituent components (crop transpiration and soil evaporation, for two classes of vegetation (olives trees and cereals in the semi-arid region of the Kairouan plain in central Tunisia. The proposed approach combines the FAO-56 technique with remote sensing (optical and microwave, not only for vegetation characterization, as proposed in other studies but also for the estimation of soil evaporation, through the use of satellite moisture products. Since it is difficult to use ground flux measurements to validate remotely sensed data at regional scales, comparisons were made with the land surface model ISBA-A-gs which is a physical SVAT (Soil–Vegetation–Atmosphere Transfer model, an operational tool developed by Météo-France. It is thus shown that good results can be obtained with this relatively simple approach, based on the FAO-56 technique combined with remote sensing, to retrieve temporal variations of ET. The approach proposed for the daily mapping of evapotranspiration at 1 km resolution is approved in two steps, for the period between 1991 and 2007. In an initial step, the ISBA-A-gs soil moisture outputs are compared with ERS/WSC products. Then, the output of the FAO-56 technique is compared with the output generated by the SVAT ISBA-A-gs model.
Hydrogen and Biofuels - A Modeling Analysis of Competing Energy Carriers for Western Europe
Energy Technology Data Exchange (ETDEWEB)
Guel, Timur; Kypreos, Socrates; Barreto, Leonardo
2007-07-01
This paper deals with the prospects of hydrogen and biofuels as energy carriers in the Western European transportation sector. The assessment is done by combining the US hydrogen analysis H2A models for the design of hydrogen production and delivery chains, and the Western European Hydrogen Markal Model EHM with a detailed representation of biofuels, and the European electricity and transportation sector. The paper derives policy recommendations to support the market penetration of hydrogen and biofuels, and investigates learning interactions between the different energy carriers. (auth)
Multi-channel electrical impedance tomography for regional tissue hydration monitoring
International Nuclear Information System (INIS)
Chen, Xiaohui; Kao, Tzu-Jen; Ashe, Jeffrey M; Boverman, Gregory; Sabatini, James E; Davenport, David M
2014-01-01
Poor assessment of hydration status during hemodialysis can lead to under- or over-hydration in patients with consequences of increased morbidity and mortality. In current practice, fluid management is largely based on clinical assessments to estimate dry weight (normal hydration body weight). However, hemodialysis patients usually have co-morbidities that can make the signs of fluid status ambiguous. Therefore, achieving normal hydration status remains a major challenge for hemodialysis therapy. Electrical impedance technology has emerged as a promising method for hydration monitoring due to its non-invasive nature, low cost and ease-of-use. Conventional electrical impedance-based hydration monitoring systems employ single-channel current excitation (either 2-electrode or 4-electrode methods) to perturb and extract averaged impedance from bulk tissue and use generalized models from large populations to derive hydration estimates. In the present study, a prototype, single-frequency electrical impedance tomography (EIT) system with simultaneous multi-channel current excitation was used to enable regional hydration change detection. We demonstrated the capability to detect a difference in daily impedance change between left leg and right leg in healthy human subjects, who wore a compression sock only on one leg to reduce daily gravitational fluid accumulation. The impedance difference corresponded well with the difference of lower leg volume change between left leg and right leg measured by volumetry, which on average is ∼35 ml, accounting for 0.7% of the lower leg volume. We have demonstrated the feasibility of using multi-channel EIT to extract hydration information in different tissue layers with minimal skin interference. Our simultaneous, multi-channel current excitation approach provides an effective method to separate electrode contact impedance and skin condition artifacts from hydration signals. The prototype system has the potential to be used in
Multi-channel electrical impedance tomography for regional tissue hydration monitoring.
Chen, Xiaohui; Kao, Tzu-Jen; Ashe, Jeffrey M; Boverman, Gregory; Sabatini, James E; Davenport, David M
2014-06-01
Poor assessment of hydration status during hemodialysis can lead to under- or over-hydration in patients with consequences of increased morbidity and mortality. In current practice, fluid management is largely based on clinical assessments to estimate dry weight (normal hydration body weight). However, hemodialysis patients usually have co-morbidities that can make the signs of fluid status ambiguous. Therefore, achieving normal hydration status remains a major challenge for hemodialysis therapy. Electrical impedance technology has emerged as a promising method for hydration monitoring due to its non-invasive nature, low cost and ease-of-use. Conventional electrical impedance-based hydration monitoring systems employ single-channel current excitation (either 2-electrode or 4-electrode methods) to perturb and extract averaged impedance from bulk tissue and use generalized models from large populations to derive hydration estimates. In the present study, a prototype, single-frequency electrical impedance tomography (EIT) system with simultaneous multi-channel current excitation was used to enable regional hydration change detection. We demonstrated the capability to detect a difference in daily impedance change between left leg and right leg in healthy human subjects, who wore a compression sock only on one leg to reduce daily gravitational fluid accumulation. The impedance difference corresponded well with the difference of lower leg volume change between left leg and right leg measured by volumetry, which on average is ~35 ml, accounting for 0.7% of the lower leg volume. We have demonstrated the feasibility of using multi-channel EIT to extract hydration information in different tissue layers with minimal skin interference. Our simultaneous, multi-channel current excitation approach provides an effective method to separate electrode contact impedance and skin condition artifacts from hydration signals. The prototype system has the potential to be used in clinical
Using multi-state markov models to identify credit card risk
Directory of Open Access Journals (Sweden)
Daniel Evangelista Régis
2016-06-01
Full Text Available Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk.
Yao, Hong; Li, Weixin; Qian, Xin
2015-08-21
Environmental safety in multi-district boundary regions has been one of the focuses in China and is mentioned many times in the Environmental Protection Act of 2014. Five types were categorized concerning the risk sources for surface water pollution in the multi-provincial boundary region of the Taihu basin: production enterprises, waste disposal sites, chemical storage sites, agricultural non-point sources and waterway transportations. Considering the hazard of risk sources, the purification property of environmental medium and the vulnerability of risk receptors, 52 specific attributes on the risk levels of each type of risk source were screened out. Continuous piecewise linear function model, expert consultation method and fuzzy integral model were used to calculate the integrated risk indexes (RI) to characterize the risk levels of pollution sources. In the studied area, 2716 pollution sources were characterized by RI values. There were 56 high-risk sources screened out as major risk sources, accounting for about 2% of the total. The numbers of sources with high-moderate, moderate, moderate-low and low pollution risk were 376, 1059, 101 and 1124, respectively, accounting for 14%, 38%, 5% and 41% of the total. The procedure proposed could be included in the integrated risk management systems of the multi-district boundary region of the Taihu basin. It could help decision makers to identify major risk sources in the risk prevention and reduction of surface water pollution.
Multi-state modeling of biomolecules.
Directory of Open Access Journals (Sweden)
Melanie I Stefan
2014-09-01
Full Text Available Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the "specification problem" and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem". To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler, and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim, DYNSTOC, RuleMonkey, and the Network-Free Stochastic Simulator (NFSim, and spatial simulators, including Meredys, SRSim, and MCell. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.
Cellular Automaton Modeling of Dendritic Growth Using a Multi-grid Method
International Nuclear Information System (INIS)
Natsume, Y; Ohsasa, K
2015-01-01
A two-dimensional cellular automaton model with a multi-grid method was developed to simulate dendritic growth. In the present model, we used a triple-grid system for temperature, solute concentration and solid fraction fields as a new approach of the multi-grid method. In order to evaluate the validity of the present model, we carried out simulations of single dendritic growth, secondary dendrite arm growth, multi-columnar dendritic growth and multi-equiaxed dendritic growth. From the results of the grid dependency from the simulation of single dendritic growth, we confirmed that the larger grid can be used in the simulation and that the computational time can be reduced dramatically. In the simulation of secondary dendrite arm growth, the results from the present model were in good agreement with the experimental data and the simulated results from a phase-field model. Thus, the present model can quantitatively simulate dendritic growth. From the simulated results of multi-columnar and multi-equiaxed dendrites, we confirmed that the present model can perform simulations under practical solidification conditions. (paper)
Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale
Kreibich, Heidi; Schröter, Kai; Merz, Bruno
2016-05-01
Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.
International Nuclear Information System (INIS)
Jiang, Meihui; An, Haizhong; Jia, Xiaoliang; Sun, Xiaoqi
2017-01-01
Crude benchmark oil prices play a crucial role in energy policy and investment management. Previous research confined itself to studying the static, uncertain, short- or long-term relationship between global benchmark oil prices, ignoring the time-varying, quantitative, dynamic nature of the relationship during various stages of oil price volatility. This paper proposes a novel approach combining grey relation analysis, optimization wavelet analysis, and Bayesian network modeling to explore the multi-period evolution of the dynamic relationship between global benchmark oil prices and regional oil spot price. We analyze the evolution of the most significant decision-making risk periods, as well as the combined strategy-making reference oil prices and the corresponding periods during various stages of volatility. Furthermore, we determine that the network evolution of the quantitative lead/lag relationship between different influences of global benchmark oil prices shows a multi-period evolution phenomenon. For policy makers and market investors, our combined model can provide decision-making periods with the lowest expected risk and decision-making target reference oil prices and corresponding weights for strategy adjustment and market arbitrage. This study provides further information regarding period weights of target reference oil prices, facilitating efforts to perform multi-agent energy policy and intertemporal market arbitrage. - Highlights: • Multi-period evolution of the influence of different oil prices is discovered. • We combined grey relation analysis, optimization wavelet and Bayesian network. • The intensity of volatility, synchronization, and lead/lag effects are analyzed. • The target reference oil prices and corresponding period weights are determined.
A multi-species multi-fleet bioeconomic simulation model for the English Channel artisanal fisheries
DEFF Research Database (Denmark)
Ulrich, Clara; Le Gallic, B.; Dunn, M.R.
2002-01-01
Considering the large number of technical interactions between various fishing activities, the English Channel (ICES divisions VIId and VIIe) fisheries may be regarded as one large and diverse multi-country, multi-gear and multi-species artisanal fishery, although rarely studied as such. A whole...... of the model is to study the long-term consequences of various management alternatives on the economic situation of the English and French fleets fishing in the area and on exploited resources. The model describes this feature through the links between three entities on the one hand (stocks, fleets...... and "metiers", i.e. gear x target species x fishing area), and three modules on the other hand (activity, biological production and economics). The model is described and some simulation results are presented. An example simulating a decrease of one fleet segment effort illustrates these technical interactions...
Computationally Efficient Transient Stability Modeling of multi-terminal VSC-HVDC
DEFF Research Database (Denmark)
van der Meer, Arjen A; Rueda-Torres, José; Silva, Filipe Miguel Faria da
2016-01-01
This paper studies the inclusion of averaged VSC-based grid interfaces and HVDC networks into stability type simulations, and compares the accuracy and speed of three multi-terminal DC dynamic models: 1) a state-space based model, 2) a multi-rate improved model, and 3) a reduced-order model...
Summary of multi-core hardware and programming model investigations
Energy Technology Data Exchange (ETDEWEB)
Kelly, Suzanne Marie; Pedretti, Kevin Thomas Tauke; Levenhagen, Michael J.
2008-05-01
This report summarizes our investigations into multi-core processors and programming models for parallel scientific applications. The motivation for this study was to better understand the landscape of multi-core hardware, future trends, and the implications on system software for capability supercomputers. The results of this study are being used as input into the design of a new open-source light-weight kernel operating system being targeted at future capability supercomputers made up of multi-core processors. A goal of this effort is to create an agile system that is able to adapt to and efficiently support whatever multi-core hardware and programming models gain acceptance by the community.
Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M
2018-05-07
A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.
Computational modelling of multi-cell migration in a multi-signalling substrate
International Nuclear Information System (INIS)
Mousavi, Seyed Jamaleddin; Doblaré, Manuel; Doweidar, Mohamed Hamdy
2014-01-01
Cell migration is a vital process in many biological phenomena ranging from wound healing to tissue regeneration. Over the past few years, it has been proven that in addition to cell–cell and cell-substrate mechanical interactions (mechanotaxis), cells can be driven by thermal, chemical and/or electrical stimuli. A numerical model was recently presented by the authors to analyse single cell migration in a multi-signalling substrate. That work is here extended to include multi-cell migration due to cell–cell interaction in a multi-signalling substrate under different conditions. This model is based on balancing the forces that act on the cell population in the presence of different guiding cues. Several numerical experiments are presented to illustrate the effect of different stimuli on the trajectory and final location of the cell population within a 3D heterogeneous multi-signalling substrate. Our findings indicate that although multi-cell migration is relatively similar to single cell migration in some aspects, the associated behaviour is very different. For instance, cell–cell interaction may delay single cell migration towards effective cues while increasing the magnitude of the average net cell traction force as well as the local velocity. Besides, the random movement of a cell within a cell population is slightly greater than that of single cell migration. Moreover, higher electrical field strength causes the cell slug to flatten near the cathode. On the other hand, as with single cell migration, the existence of electrotaxis dominates mechanotaxis, moving the cells to the cathode or anode pole located at the free surface. The numerical results here obtained are qualitatively consistent with related experimental works. (paper)
Predictive modeling of coupled multi-physics systems: I. Theory
International Nuclear Information System (INIS)
Cacuci, Dan Gabriel
2014-01-01
Highlights: • We developed “predictive modeling of coupled multi-physics systems (PMCMPS)”. • PMCMPS reduces predicted uncertainties in predicted model responses and parameters. • PMCMPS treats efficiently very large coupled systems. - Abstract: This work presents an innovative mathematical methodology for “predictive modeling of coupled multi-physics systems (PMCMPS).” This methodology takes into account fully the coupling terms between the systems but requires only the computational resources that would be needed to perform predictive modeling on each system separately. The PMCMPS methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution based on a priori known mean values and uncertainties characterizing the parameters and responses for both multi-physics models. This “maximum entropy”-approximate a priori distribution is combined, using Bayes’ theorem, with the “likelihood” provided by the multi-physics simulation models. Subsequently, the posterior distribution thus obtained is evaluated using the saddle-point method to obtain analytical expressions for the optimally predicted values for the multi-physics models parameters and responses along with corresponding reduced uncertainties. Noteworthy, the predictive modeling methodology for the coupled systems is constructed such that the systems can be considered sequentially rather than simultaneously, while preserving exactly the same results as if the systems were treated simultaneously. Consequently, very large coupled systems, which could perhaps exceed available computational resources if treated simultaneously, can be treated with the PMCMPS methodology presented in this work sequentially and without any loss of generality or information, requiring just the resources that would be needed if the systems were treated sequentially
Bi-dimension decomposed hidden Markov models for multi-person activity recognition
Institute of Scientific and Technical Information of China (English)
Wei-dong ZHANG; Feng CHEN; Wen-li XU
2009-01-01
We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named 'decomposed hidden Markov model' (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters.DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.
Conflicts in Coalitions: A Stability Analysis of Robust Multi-City Regional Water Supply Portfolios
Gold, D.; Trindade, B. C.; Reed, P. M.; Characklis, G. W.
2017-12-01
Regional cooperation among water utilities can improve the robustness of urban water supply portfolios to deeply uncertain future conditions such as those caused by climate change or population growth. Coordination mechanisms such as water transfers, coordinated demand management, and shared infrastructure, can improve the efficiency of resource allocation and delay the need for new infrastructure investments. Regionalization does however come at a cost. Regionally coordinated water supply plans may be vulnerable to any emerging instabilities in the regional coalition. If one or more regional actors does not cooperate or follow the required regional actions in a time of crisis, the overall system performance may degrade. Furthermore, when crafting regional water supply portfolios, decision makers must choose a framework for measuring the performance of regional policies based on the evaluation of the objective values for each individual actor. Regional evaluations may inherently favor one actor's interests over those of another. This work focuses on four interconnected water utilities in the Research Triangle region of North Carolina for which robust regional water supply portfolios have previously been designed using multi-objective optimization to maximize the robustness of the worst performing utility across several objectives. This study 1) examines the sensitivity of portfolio performance to deviations from prescribed actions by individual utilities, 2) quantifies the implications of the regional formulation used to evaluate robustness for the portfolio performance of each individual utility and 3) elucidates the inherent regional tensions and conflicts that exist between utilities under this regionalization scheme through visual diagnostics of the system under simulated drought scenarios. Results of this analysis will help inform the creation of future regional water supply portfolios and provide insight into the nature of multi-actor water supply systems.
International Nuclear Information System (INIS)
Van den Broek, M.A.; Ramirez-Ramirez, A.; Turkenburg, W.; Faaij, A; Groenenberg, H.; Neele, F.P.; Viebahn, P.
2009-09-01
This study provides insight into the feasibility of a CO2 trunkline from the Netherlands to the Utsira formation in the Norwegian part of the North Sea, which is a large geological storage reservoir for CO2. The feasibility is investigated in competition with CO2 storage in onshore and near-offshore sinks in the Netherlands. Least-cost modelling with a MARKAL model in combination with ArcGIS was used to assess the cost-effectiveness of the trunkline as part of a Dutch greenhouse gas emission reduction strategy for the Dutch electricity sector and CO2 intensive industry. The results show that under the condition that a CO2 permit price increases from 25 euro per tCO2 in 2010 to 60 euro per tCO2 in 2030, and remains at this level up to 2050, CO2 emissions in the Netherlands could reduce with 67% in 2050 compared to 1990, and investment in the Utsira trunkline may be cost-effective from 2020-2030 provided that Belgian and German CO2 is transported and stored via the Netherlands as well. In this case, by 2050 more than 2.1 GtCO2 would have been transported from the Netherlands to the Utsira formation. However, if the Utsira trunkline is not used for transportation of CO2 from Belgium and Germany, it may become cost-effective 10 years later, and less than 1.3 GtCO2 from the Netherlands would have been stored in the Utsira formation by 2050. On the short term, CO2 storage in Dutch fields appears more cost-effective than in the Utsira formation, but as yet there are major uncertainties related to the timing and effective exploitation of the Dutch offshore storage opportunities.
Energy Technology Data Exchange (ETDEWEB)
Schulz, T. F.; Barreto, L.; Kypreos, S.; Stucki, S
2005-07-15
The role of wood-based energy technologies in the Swiss energy system in the long-term is examined using the energy-system Swiss MARKAL model. The Swiss MARKAL model is a 'bottom-up' energy-systems optimization model that allows a detailed representation of energy technologies. The model has been developed as a joint effort between the Energy Economics Group (EEG) at Paul Scherrer Institute PSI) and the University of Geneva and is currently used at PSI-EEG. Using the Swiss MARKAL model, this study examines the conditions under which wood-based energy technologies could play a role in the Swiss energy system, the most attractive pathways for their use and the policy measures that could support them. Given the involvement of PSI in the ECOGAS project, especial emphasis is put on the production of bio-SNG from wood via gasification and methanation of syngas and on hydrothermal gasification of woody biomass. Of specific interest as weIl is the fraction of fuel used in passenger cars that could be produced by locally harvested wood. The report is organized as follows: Section 2 presents a brief description of the MARKAL model. Section 3 describes the results of the base case scenario, which represents a plausible, 'middle-of-the-road' development of the Swiss energy system. Section 4 discusses results illustrating the conditions under which the wood-based methanation technology could become competitive in the Swiss energy market, the role of oil and gas prices, subsidies to methanation technologies and the introduction of a competing technology, namely the wood-based Fischer-Tropsch synthesis. FinaIly, section 5 outlines some conclusions from this analysis. (author)
International Nuclear Information System (INIS)
Schulz, T. F.; Barreto, L.; Kypreos, S.; Stucki, S.
2005-07-01
The role of wood-based energy technologies in the Swiss energy system in the long-term is examined using the energy-system Swiss MARKAL model. The Swiss MARKAL model is a 'bottom-up' energy-systems optimization model that allows a detailed representation of energy technologies. The model has been developed as a joint effort between the Energy Economics Group (EEG) at Paul Scherrer Institute PSI) and the University of Geneva and is currently used at PSI-EEG. Using the Swiss MARKAL model, this study examines the conditions under which wood-based energy technologies could play a role in the Swiss energy system, the most attractive pathways for their use and the policy measures that could support them. Given the involvement of PSI in the ECOGAS project, especial emphasis is put on the production of bio-SNG from wood via gasification and methanation of syngas and on hydrothermal gasification of woody biomass. Of specific interest as weIl is the fraction of fuel used in passenger cars that could be produced by locally harvested wood. The report is organized as follows: Section 2 presents a brief description of the MARKAL model. Section 3 describes the results of the base case scenario, which represents a plausible, 'middle-of-the-road' development of the Swiss energy system. Section 4 discusses results illustrating the conditions under which the wood-based methanation technology could become competitive in the Swiss energy market, the role of oil and gas prices, subsidies to methanation technologies and the introduction of a competing technology, namely the wood-based Fischer-Tropsch synthesis. FinaIly, section 5 outlines some conclusions from this analysis. (author)
Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model
Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.
2012-12-01
The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that
Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong
2015-08-01
We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.
Directory of Open Access Journals (Sweden)
Chudech Losiri
2016-07-01
Full Text Available Urban expansion is considered as one of the most important problems in several developing countries. Bangkok Metropolitan Region (BMR is the urbanized and agglomerated area of Bangkok Metropolis (BM and its vicinity, which confronts the expansion problem from the center of the city. Landsat images of 1988, 1993, 1998, 2003, 2008, and 2011 were used to detect the land use and land cover (LULC changes. The demographic and economic data together with corresponding maps were used to determine the driving factors for land conversions. This study applied Cellular Automata-Markov Chain (CA-MC and Multi-Layer Perceptron-Markov Chain (MLP-MC to model LULC and urban expansions. The performance of the CA-MC and MLP-MC yielded more than 90% overall accuracy to predict the LULC, especially the MLP-MC method. Further, the annual population and economic growth rates were considered to produce the land demand for the LULC in 2014 and 2035 using the statistical extrapolation and system dynamics (SD. It was evident that the simulated map in 2014 resulting from the SD yielded the highest accuracy. Therefore, this study applied the SD method to generate the land demand for simulating LULC in 2035. The outcome showed that urban occupied the land around a half of the BMR.
Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana
2018-01-01
This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.
The three-zone composite productivity model for a multi-fractured horizontal shale gas well
Qi, Qian; Zhu, Weiyao
2018-02-01
Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interfere of the fractures.
Eriksen, Gitte Valsted; Malling, Bente
2014-04-14
In Denmark multi-source feedback is used in formative assessment of trainees' performance regarding the roles: communicator, collaborator, professional and manager. A web-based model was developed and evaluated useful, time-effective, acceptable and feasible. The model comprises a validated questionnaire usable in all specialities, personal feedback from an educated feedback facilitator, identification of areas for improvement and a mandatory written plan for the trainees' further professional development. The model is implemented at all hospitals in the Northern Educational Region in Denmark.
Multi-Level Marketing as a business model
Directory of Open Access Journals (Sweden)
Bogdan Gregor
2013-03-01
Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.
Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras
Andrade, Jefferson O.; Kameyama, Yukiyoshi
Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In this paper, we propose a novel, efficient algorithm for multi-valued bounded model checking. A notable feature of our algorithm is that it is not based on reduction of multi-values into two-values; instead, it generates a single formula which represents multi-valuedness by a suitable encoding, and asks a standard SAT solver to check its satisfiability. Our experimental results show a significant improvement in the number of variables and clauses and also in execution time compared with the reduction-based one.
LONG-TERM MONITORING OF WATER DYNAMICS IN THE SAHEL REGION USING THE MULTI-SAR-SYSTEM
Directory of Open Access Journals (Sweden)
A. Bertram
2016-06-01
Full Text Available Fresh water is a scarce resource in the West-African Sahel region, seasonally influenced by droughts and floods. Particularly in terms of climate change, the importance of wetlands increases for flora, fauna, human population, agriculture, livestock and fishery. Hence, access to open water is a key factor. Long-term monitoring of water dynamics is of great importance, especially with regard to the spatio-temporal extend of wetlands and drylands. It can predict future trends and facilitate the development of adequate management strategies. Lake Tabalak, a Ramsar wetland of international importance, is one of the most significant ponds in Niger and a refuge for waterbirds. Nevertheless, human population growth increased the pressure on this ecosystem, which is now degrading for all uses. The main objective of the study is a long-term monitoring of the Lake Tabalak’s water dynamics to delineate permanent and seasonal water bodies, using weather- and daytime-independent multi-sensor and multi-temporal Synthetic Aperture Radar (SAR data available for the study area. Data of the following sensors from 1993 until 2016 are used: Sentinel-1A, TerraSARX, ALOS PALSAR-1/2, Envisat ASAR, RADARSAT-1/2, and ERS-1/2. All SAR data are processed with the Multi-SAR-System, unifying the different characteristics of all above mentioned sensors in terms of geometric, radiometric and polarimetric resolution to a consistent format. The polarimetric representation in Kennaugh elements allows fusing single-polarized data acquired by older sensors with multi-polarized data acquired by current sensors. The TANH-normalization guarantees a consistent and therefore comparable description in a closed data range in terms of radiometry. The geometric aspect is solved by projecting all images to an earth-fixed coordinate system correcting the brightness by the help of the incidence angle. The elevation model used in the geocoding step is the novel global model produced by the
Algorithm for Financial Derivatives Evaluation in a Generalized Multi-Heston Model
Directory of Open Access Journals (Sweden)
Dan Negura
2013-02-01
Full Text Available In this paper we show how could a financial derivative be estimated based on an assumed Multi-Heston model support.Keywords: Euler Maruyama discretization method, Monte Carlo simulation, Heston model, Double-Heston model, Multi-Heston model
Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale
Directory of Open Access Journals (Sweden)
H. Kreibich
2016-05-01
Full Text Available Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB.In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.
The World gas model. A multi-period mixed complementarity model for the global natural gas market
International Nuclear Information System (INIS)
Egging, Ruud; Holz, Franziska; Gabriel, Steven A.
2010-01-01
We provide the description, mathematical formulation and illustrative results of the World Gas Model, a multi-period complementarity model for the global natural gas market with explicit consideration of market power in the upstream market. Market players include producers, traders, pipeline and storage operators, LNG (liquefied natural gas) liquefiers and regasifiers as well as marketers. The model data set contains more than 80 countries and regions and covers 98% of world wide natural gas production and consumption. We also include a detailed representation of cross-border natural gas pipelines and constraints imposed by long-term contracts in the LNG market. The model is calibrated to match production and consumption projections from the PRIMES [EC. European energy and transport: trends to 2030-update 2007. Brussels: European Commission; 2008] and POLES models [EC. World energy technology outlook - 2050 (WETO-H2). Brussels: European Commission; 2006] up to 2030. The results of our numerical simulations illustrate how the supply shares of pipeline and LNG in various regions in the world develop very differently over time. LNG will continue to play a major role in the Asian market, also for new importers like China and India. Europe will expand its pipeline import capacities benefiting from its relative proximity to major gas suppliers. (author)
Assessment of multi class kinematic wave models
Van Wageningen-Kessels, F.L.M.; Van Lint, J.W.C.; Vuik, C.; Hoogendoorn, S.P.
2012-01-01
In the last decade many multi class kinematic wave (MCKW) traffic ow models have been proposed. MCKW models introduce heterogeneity among vehicles and drivers. For example, they take into account differences in (maximum) velocities and driving style. Nevertheless, the models are macroscopic and the
A new multi-zone model for porosity distribution in Al–Si alloy castings
DEFF Research Database (Denmark)
Tiedje, Niels Skat; Taylor, John A.; Easton, Mark A.
2013-01-01
A new multi-zone model is proposed that explains how porosity forms in various regions of a casting under different conditions and leads to distinct zonal differences in pore shape, size and distribution. This model was developed by considering the effect of cooling rate on solidification......) a central zone where the thermal gradient is low and equiaxed dendritic grains and eutectic cells grow at the centre of the casting and larger, rounded pores tend to form. The paper discusses how Si content, modification type and cooling conditions influence the location and size (i.e. depth) of each...
Directory of Open Access Journals (Sweden)
Hong Yao
2015-08-01
Full Text Available Environmental safety in multi-district boundary regions has been one of the focuses in China and is mentioned many times in the Environmental Protection Act of 2014. Five types were categorized concerning the risk sources for surface water pollution in the multi-provincial boundary region of the Taihu basin: production enterprises, waste disposal sites, chemical storage sites, agricultural non-point sources and waterway transportations. Considering the hazard of risk sources, the purification property of environmental medium and the vulnerability of risk receptors, 52 specific attributes on the risk levels of each type of risk source were screened out. Continuous piecewise linear function model, expert consultation method and fuzzy integral model were used to calculate the integrated risk indexes (RI to characterize the risk levels of pollution sources. In the studied area, 2716 pollution sources were characterized by RI values. There were 56 high-risk sources screened out as major risk sources, accounting for about 2% of the total. The numbers of sources with high-moderate, moderate, moderate-low and low pollution risk were 376, 1059, 101 and 1124, respectively, accounting for 14%, 38%, 5% and 41% of the total. The procedure proposed could be included in the integrated risk management systems of the multi-district boundary region of the Taihu basin. It could help decision makers to identify major risk sources in the risk prevention and reduction of surface water pollution.
Yao, Hong; Li, Weixin; Qian, Xin
2015-01-01
Environmental safety in multi-district boundary regions has been one of the focuses in China and is mentioned many times in the Environmental Protection Act of 2014. Five types were categorized concerning the risk sources for surface water pollution in the multi-provincial boundary region of the Taihu basin: production enterprises, waste disposal sites, chemical storage sites, agricultural non-point sources and waterway transportations. Considering the hazard of risk sources, the purification property of environmental medium and the vulnerability of risk receptors, 52 specific attributes on the risk levels of each type of risk source were screened out. Continuous piecewise linear function model, expert consultation method and fuzzy integral model were used to calculate the integrated risk indexes (RI) to characterize the risk levels of pollution sources. In the studied area, 2716 pollution sources were characterized by RI values. There were 56 high-risk sources screened out as major risk sources, accounting for about 2% of the total. The numbers of sources with high-moderate, moderate, moderate-low and low pollution risk were 376, 1059, 101 and 1124, respectively, accounting for 14%, 38%, 5% and 41% of the total. The procedure proposed could be included in the integrated risk management systems of the multi-district boundary region of the Taihu basin. It could help decision makers to identify major risk sources in the risk prevention and reduction of surface water pollution. PMID:26308032
Pauci ex tanto numero: reduce redundancy in multi-model ensembles
Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.
2013-08-01
We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date, no attempts in this direction have been documented within the air quality (AQ) community despite the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared, dependant biases among models do not cancel out but will instead determine a biased ensemble. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated), we discourage selecting the members of the ensemble simply on the basis of scores; that is, independence and skills need to be considered disjointly.
MULTI: a shared memory approach to cooperative molecular modeling.
Darden, T; Johnson, P; Smith, H
1991-03-01
A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.
Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras
Andrade, Jefferson O.; Kameyama, Yukiyoshi
2012-01-01
Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In thi...
A multi-component evaporation model for beam melting processes
Klassen, Alexander; Forster, Vera E.; Körner, Carolin
2017-02-01
In additive manufacturing using laser or electron beam melting technologies, evaporation losses and changes in chemical composition are known issues when processing alloys with volatile elements. In this paper, a recently described numerical model based on a two-dimensional free surface lattice Boltzmann method is further developed to incorporate the effects of multi-component evaporation. The model takes into account the local melt pool composition during heating and fusion of metal powder. For validation, the titanium alloy Ti-6Al-4V is melted by selective electron beam melting and analysed using mass loss measurements and high-resolution microprobe imaging. Numerically determined evaporation losses and spatial distributions of aluminium compare well with experimental data. Predictions of the melt pool formation in bulk samples provide insight into the competition between the loss of volatile alloying elements from the irradiated surface and their advective redistribution within the molten region.
Quantifying credit portfolio losses under multi-factor models
G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)
2018-01-01
textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational
Multi-model approach to characterize human handwriting motion.
Chihi, I; Abdelkrim, A; Benrejeb, M
2016-02-01
This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.
Directory of Open Access Journals (Sweden)
Jihui Tu
2017-04-01
Full Text Available The detection of damaged building regions is crucial to emergency response actions and rescue work after a disaster. Change detection methods using multi-temporal remote sensing images are widely used for this purpose. Differing from traditional methods based on change detection for damaged building regions, semantic scene change can provide a new point of view since it can indicate the land-use variation at the semantic level. In this paper, a novel method is proposed for detecting damaged building regions based on semantic scene change in a visual Bag-of-Words model. Pre- and post-disaster scene change in building regions are represented by a uniform visual codebook frequency. The scene change of damaged and non-damaged building regions is discriminated using the Support Vector Machine (SVM classifier. An evaluation of experimental results, for a selected study site of the Longtou hill town of Yunnan, China, which was heavily damaged in the Ludian earthquake of 14 March 2013, shows that this method is feasible and effective for detecting damaged building regions. For the experiments, WorldView-2 optical imagery and aerial imagery is used.
Optimization of Regional Geodynamic Models for Mantle Dynamics
Knepley, M.; Isaac, T.; Jadamec, M. A.
2016-12-01
The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.
Hein, H.; Mai, S.; Mayer, B.; Pohlmann, T.; Barjenbruch, U.
2012-04-01
The interactions of tides, external surges, storm surges and waves with an additional role of the coastal bathymetry define the probability of extreme water levels at the coast. Probabilistic analysis and also process based numerical models allow the estimation of future states. From the physical point of view both, deterministic processes and stochastic residuals are the fundamentals of high water statistics. This study uses a so called model chain to reproduce historic statistics of tidal high water levels (Thw) as well as the prediction of future statistics high water levels. The results of the numerical models are post-processed by a stochastic analysis. Recent studies show, that for future extrapolation of extreme Thw nonstationary parametric approaches are required. With the presented methods a better prediction of time depended parameter sets seems possible. The investigation region of this study is the southern German Bright. The model-chain is the representation of a downscaling process, which starts with an emissions scenario. Regional atmospheric and ocean models refine the results of global climate models. The concept of downscaling was chosen to resolve coastal topography sufficiently. The North Sea and estuaries are modeled with the three-dimensional model HAMburg Shelf Ocean Model. The running time includes 150 years (1950 - 2100). Results of four different hindcast runs and also of one future prediction run are validated. Based on multi-scale analysis and the theory of entropy we analyze whether any significant periodicities are represented numerically. Results show that also hindcasting the climate of Thw with a model chain for the last 60 years is a challenging task. For example, an additional modeling activity must be the inclusion of tides into regional climate ocean models. It is found that the statistics of climate variables derived from model results differs from the statistics derived from measurements. E.g. there are considerable shifts in
Supporting multi-stakeholder environmental decisions.
Hajkowicz, Stefan A
2008-09-01
This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.
Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.
Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian
2017-11-23
Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.
Uncertain and multi-objective programming models for crop planting structure optimization
Directory of Open Access Journals (Sweden)
Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG
2016-03-01
Full Text Available Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP model and an inexact fuzzy linear programming (IFLP model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods
A Bayesian alternative for multi-objective ecohydrological model specification
Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori
2018-01-01
Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior
Model-Checking of Linear-Time Properties in Multi-Valued Systems
Li, Yongming; Droste, Manfred; Lei, Lihui
2012-01-01
In this paper, we study model-checking of linear-time properties in multi-valued systems. Safety property, invariant property, liveness property, persistence and dual-persistence properties in multi-valued logic systems are introduced. Some algorithms related to the above multi-valued linear-time properties are discussed. The verification of multi-valued regular safety properties and multi-valued $\\omega$-regular properties using lattice-valued automata are thoroughly studied. Since the law o...
The last Deglaciation in the Mediterranean region: a multi-archives synthesis
Bazin, Lucie; Siani, Giuseppe; Landais, Amaelle; Bassinot, Frank; Genty, Dominique; Govin, Aline; Michel, Elisabeth; Nomade, Sebastien; Waelbroeck, Claire
2016-04-01
Multiple proxies record past climatic changes in different climate archives. These proxies are influenced by different component of the climate system and bring complementary information on past climate variability. The major limitation when combining proxies from different archives comes from the coherency of their chronologies. Indeed, each climate archives possess their own dating methods, not necessarily coherent with each other's. Consequently, when we want to assess the latitudinal changes and mechanisms behind a climate event, we often have to rely on assumptions of synchronisation between the different archives, such as synchronous temperature changes during warming events (Austin and Hibbert 2010). Recently, a dating method originally developed to produce coherent chronologies for ice cores (Datice,Lemieux-Dudon et al., 2010) has been adapted in order to integrate different climate archives (ice cores, sediment cores and speleothems (Lemieux-Dudon et al., 2015, Bazin et al., in prep)). In this presentation we present the validation of this multi-archives dating tool with a first application covering the last Deglaciation in the Mediterranean region. For this experiment, we consider the records from Monticchio, the MD90-917, Tenaghi Philippon and Lake Orhid sediment cores as well as continuous speleothems from Sofular, Soreq and La Mine caves. Using the Datice dating tool, and with the identification of common tephra layers between the cores considered, we are able to produce a multi-archives coherent chronology for this region, independently of any climatic assumption. Using this common chronological framework, we show that the usual climatic synchronisation assumptions are not valid over this region for the last glacial-interglacial transition. Finally, we compare our coherent Mediterranean chronology with Greenland ice core records in order to discuss the sequence of events of the last Deglaciation between these two regions.
Modeling of Nonlinear Propagation in Multi-layer Biological Tissues for Strong Focused Ultrasound
International Nuclear Information System (INIS)
Ting-Bo, Fan; Zhen-Bo, Liu; Zhe, Zhang; Dong, Zhang; Xiu-Fen, Gong
2009-01-01
A theoretical model of the nonlinear propagation in multi-layered tissues for strong focused ultrasound is proposed. In this model, the spheroidal beam equation (SBE) is utilized to describe the nonlinear sound propagation in each layer tissue, and generalized oblique incidence theory is used to deal with the sound transmission between two layer tissues. Computer simulation is performed on a fat-muscle-liver tissue model under the irradiation of a 1 MHz focused transducer with a large aperture angle of 35°. The results demonstrate that the tissue layer would change the amplitude of sound pressure at the focal region and cause the increase of side petals. (fundamental areas of phenomenology (including applications))
A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation
Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.
2016-12-01
Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.
Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration
Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.
2017-12-01
Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.
Energy Technology Data Exchange (ETDEWEB)
Lamarque, Jean-Francois; Dentener, Frank; McConnell, J.R.; Ro, C-U; Shaw, Mark; Vet, Robert; Bergmann, D.; Cameron-Smith, Philip; Dalsoren, S.; Doherty, R.; Faluvegi, G.; Ghan, Steven J.; Josse, B.; Lee, Y. H.; MacKenzie, I. A.; Plummer, David; Shindell, Drew; Skeie, R. B.; Stevenson, D. S.; Strode, S.; Zeng, G.; Curran, M.; Dahl-Jensen, D.; Das, S.; Fritzsche, D.; Nolan, M.
2013-08-20
We present multi-model global datasets of nitrogen and sulfate deposition covering time periods from 1850 to 2100, calculated within the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The computed deposition fluxes are compared to surface wet deposition and ice-core measurements. We use a new dataset of wet deposition for 2000-2002 based on critical assessment of the quality of existing regional network data. We show that for present-day (year 2000 ACCMIP time-slice), the ACCMIP results perform similarly to previously published multi-model assessments. The analysis of changes between 1980 and 2000 indicates significant differences between model and measurements over the United States, but less so over Europe. This difference points towards misrepresentation of 1980 NH3 emissions over North America. Based on ice-core records, the 1850 deposition fluxes agree well with Greenland ice cores but the change between 1850 and 2000 seems to be overestimated in the Northern Hemisphere for both nitrogen and sulfur species. Using the Representative Concentration Pathways to define the projected climate and atmospheric chemistry related emissions and concentrations, we find large regional nitrogen deposition increases in 2100 in Latin America, Africa and parts of Asia under some of the scenarios considered. Increases in South Asia are especially large, and are seen in all scenarios, with 2100 values more than double 2000 in some scenarios and reaching >1300 mgN/m2/yr averaged over regional to continental scale regions in RCP 2.6 and 8.5, ~30-50% larger than the values in any region currently (2000). Despite known issues, the new ACCMIP deposition dataset provides novel, consistent and evaluated global gridded deposition fields for use in a wide range of climate and ecological studies.
DEFF Research Database (Denmark)
Boyd, Britta; Mangalagiu, Diana; Straatman, Bas
2018-01-01
This paper presents a consumption-based method accounting for greenhouse gas emissions at regional level based on a multi-region input-output model. The method is based on regional consumption and includes imports and exports of emissions, factual emission developments, green investments as well...
RICM, Resonance Absorption in Multi-Region Slab or Square or Hexagonal Lattice
International Nuclear Information System (INIS)
Mizuta, H.; Aoyama, K.; Fukai, Y.
1968-01-01
1 - Nature of physical problem solved: Calculates the resonance absorption integral of resonant isotope in a multi-region lattice using the first flight collision probability. The lattice configurations considered are a slab lattice, a square or hexagonal lattice and a cylindricalized lattice with isotropic or perfect reflecting boundary condition. Cases for an isolated rod or plate and homogeneous system can also be treated. 2 - Method of solution: Slowing down of neutrons by each isotope in each region is solved by either exact numerical integration of the slowing down equation or narrow - or wide-resonance approximation. Breit-Wigner's single level formula is used for the resonance cross section and Porter-Thomas distribution of neutron width is taken into account in the unresolved region. 3 - Restrictions on the complexity of the problem: Maximum number of regions: 5; Maximum Number of groups: 100
Lu, M.; Lall, U.
2013-12-01
In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The
Lee, Ching-Fang; Huang, Wei-Kai; Chang, Yu-Lin; Chi, Shu-Yeong; Liao, Wu-Chang
2018-01-01
Typhoons Megi (2010) and Saola (2012) brought torrential rainfall which triggered regional landslides and flooding hazards along Provincial Highway No. 9 in northeastern Taiwan. To reduce property loss and saving lives, this study combines multi-hazard susceptibility assessment with environmental geology map a rock mass rating system (RMR), remote sensing analysis, and micro-topography interpretation to develop an integrated landslide hazard assessment approach and reflect the intrinsic state of slopeland from the past toward the future. First, the degree of hazard as indicated by historical landslides was used to determine many landslide regions in the past. Secondly, geo-mechanical classification of rock outcroppings was performed by in-situ investigation along the vulnerable road sections. Finally, a high-resolution digital elevation model was extracted from airborne LiDAR and multi-temporal remote sensing images which was analyzed to discover possible catastrophic landslide hotspot shortly. The results of the analysis showed that 37% of the road sections in the study area were highly susceptible to landslide hazards. The spatial distribution of the road sections revealed that those characterized by high susceptibility were located near the boundaries of fault zones and in areas of lithologic dissimilarity. Headward erosion of gullies and concave-shaped topographic features had an adverse effect and was the dominant factor triggering landslides. Regional landslide reactivation on this coastal highway are almost related to the past landslide region based on hazard statistics. The final results of field validation demonstrated that an accuracy of 91% could be achieved for forecasting geohazard followed by intense rainfall events and typhoons.
Kratochvíla, Jiří; Jiřík, Radovan; Bartoš, Michal; Standara, Michal; Starčuk, Zenon; Taxt, Torfinn
2016-03-01
One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup. © 2015 Wiley Periodicals, Inc.
Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;
2013-01-01
The recent US National Academies report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability" was unequivocal in recommending the need for the development of a North American Multi-Model Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multi-model ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation, and has proven to produce better prediction quality (on average) then any single model ensemble. This multi-model approach is the basis for several international collaborative prediction research efforts, an operational European system and there are numerous examples of how this multi-model ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test Bed (CTB) NMME workshops (February 18, and April 8, 2011) a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data is readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (http://origin.cpc.ncep.noaa.gov/products/people/wd51yf/NMME/index.html). Moreover, the NMME forecast are already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, presents an overview of the multi-model forecast quality, and the complementary skill associated with individual models.
Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.
Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael
2018-01-01
An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.
International Nuclear Information System (INIS)
Egging, R.G.
2010-11-01
This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in
Directory of Open Access Journals (Sweden)
Mawloud GUERMOUI
2016-07-01
Full Text Available Accurate estimation of Daily Global Solar Radiation (DGSR has been a major goal for solar energy application. However, solar radiation measurements are not a simple task for several reasons. In the cases where data are not available, it is very common the use of computational models to estimate the missing data, which are based mainly of the search for relationships between weather variables, such as temperature, humidity, sunshine duration, etc. In this respect, the present study focuses on the development of artificial neural network (ANN model for estimation of daily global solar radiation on horizontal surface in Ghardaia city (South Algeria. In this analysis back-propagation algorithm is applied. Daily mean air temperature, relative humidity and sunshine duration was used as climatic inputs parameters, while the daily global solar radiation (DGSR was the only output of the ANN. We have evaluated Multi-Layer Perceptron (MLP models to estimate DGSR using three year of measurement (2005-2008. It was found that MLP-model based on sunshine duration and mean air temperature give accurate results in term of Mean Absolute Bias Error, Root Mean Square Error, Relative Square Error and Correlation Coefficient. The obtained values of these indicators are 0.67 MJ/m², 1.28 MJ/m², 6.12%and 98.18%, respectively which shows that MLP is highly qualified for DGSR estimation in semi-arid climates.
Energy Technology Data Exchange (ETDEWEB)
Su, H. J.; Fong, W. S. [Chevron Petroleum Technology Company (United States)
1998-12-31
A method for modeling multi-lateral wells by using a computational scheme embedded in a general-purpose, finite difference simulator was described. The calculation of wellbore pressure profile for each lateral included the frictional pressure drop along the wellbore and proper fluid mixing at lateral connection points. To obtain a good production profile the Beggs and Brill correlation, a homogenous flow model, and the model proposed by Ouyang et al, which includes an acceleration term and accounts for the lubrication effect due to radial influx, were implemented. Well performance prediction results were compared using the three models. The impact of different tubing sizes on the well performance and the prediction contribution from each lateral were also studied. Results of the study in the hypothetical example and under normal field operating conditions were reviewed. 7 refs., 10 tabs., 3 figs.
Pauci ex tanto numero: reducing redundancy in multi-model ensembles
Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.
2013-02-01
We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date no attempts in this direction are documented within the air quality (AQ) community, although the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared biases among models will determine a biased ensemble, making therefore essential the errors of the ensemble members to be independent so that bias can cancel out. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated) we discourage selecting the members of the ensemble simply on the basis of scores, that is, independence and skills need to be considered disjointly.
The Alpine snow-albedo feedback in regional climate models
Winter, Kevin J.-P. M.; Kotlarski, Sven; Scherrer, Simon C.; Schär, Christoph
2017-02-01
The effect of the snow-albedo feedback (SAF) on 2m temperatures and their future changes in the European Alps is investigated in the ENSEMBLES regional climate models (RCMs) with a focus on the spring season. A total of 14 re-analysis-driven RCM experiments covering the period 1961-2000 and 10 GCM-driven transient climate change projections for 1950-2099 are analysed. A positive springtime SAF is found in all RCMs, but the range of the diagnosed SAF is large. Results are compared against an observation-based SAF estimate. For some RCMs, values very close to this estimate are found; other models show a considerable overestimation of the SAF. Net shortwave radiation has the largest influence of all components of the energy balance on the diagnosed SAF and can partly explain its spatial variability. Model deficiencies in reproducing 2m temperatures above snow and ice and associated cold temperature biases at high elevations seem to contribute to a SAF overestimation in several RCMs. The diagnosed SAF in the observational period strongly influences the estimated SAF contribution to twenty first century temperature changes in the European Alps. This contribution is subject to a clear elevation dependency that is governed by the elevation-dependent change in the number of snow days. Elevations of maximum SAF contribution range from 1500 to 2000 m in spring and are found above 2000 m in summer. Here, a SAF contribution to the total simulated temperature change between 0 and 0.5 °C until 2099 (multi-model mean in spring: 0.26 °C) or 0 and 14 % (multi-model mean in spring: 8 %) is obtained for models showing a realistic SAF. These numbers represent a well-funded but only approximate estimate of the SAF contribution to future warming, and a remaining contribution of model-specific SAF misrepresentations cannot be ruled out.
Integration of Advanced Probabilistic Analysis Techniques with Multi-Physics Models
Energy Technology Data Exchange (ETDEWEB)
Cetiner, Mustafa Sacit; none,; Flanagan, George F. [ORNL; Poore III, Willis P. [ORNL; Muhlheim, Michael David [ORNL
2014-07-30
An integrated simulation platform that couples probabilistic analysis-based tools with model-based simulation tools can provide valuable insights for reactive and proactive responses to plant operating conditions. The objective of this work is to demonstrate the benefits of a partial implementation of the Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Framework Specification through the coupling of advanced PRA capabilities and accurate multi-physics plant models. Coupling a probabilistic model with a multi-physics model will aid in design, operations, and safety by providing a more accurate understanding of plant behavior. This represents the first attempt at actually integrating these two types of analyses for a control system used for operations, on a faster than real-time basis. This report documents the development of the basic communication capability to exchange data with the probabilistic model using Reliability Workbench (RWB) and the multi-physics model using Dymola. The communication pathways from injecting a fault (i.e., failing a component) to the probabilistic and multi-physics models were successfully completed. This first version was tested with prototypic models represented in both RWB and Modelica. First, a simple event tree/fault tree (ET/FT) model was created to develop the software code to implement the communication capabilities between the dynamic-link library (dll) and RWB. A program, written in C#, successfully communicates faults to the probabilistic model through the dll. A systems model of the Advanced Liquid-Metal Reactor–Power Reactor Inherently Safe Module (ALMR-PRISM) design developed under another DOE project was upgraded using Dymola to include proper interfaces to allow data exchange with the control application (ConApp). A program, written in C+, successfully communicates faults to the multi-physics model. The results of the example simulation were successfully plotted.
Multi-Model Projections of River Flood Risk in Europe under Global Warming
Directory of Open Access Journals (Sweden)
Lorenzo Alfieri
2018-01-01
Full Text Available Knowledge on the costs of natural disasters under climate change is key information for planning adaptation and mitigation strategies of future climate policies. Impact models for large scale flood risk assessment have made leaps forward in the past few years, thanks to the increased availability of high resolution climate projections and of information on local exposure and vulnerability to river floods. Yet, state-of-the-art flood impact models rely on a number of input data and techniques that can substantially influence their results. This work compares estimates of river flood risk in Europe from three recent case studies, assuming global warming scenarios of 1.5, 2, and 3 degrees Celsius from pre-industrial levels. The assessment is based on comparing ensemble projections of expected damage and population affected at country level. Differences and common points between the three cases are shown, to point out main sources of uncertainty, strengths, and limitations. In addition, the multi-model comparison helps identify regions with the largest agreement on specific changes in flood risk. Results show that global warming is linked to substantial increase in flood risk over most countries in Central and Western Europe at all warming levels. In Eastern Europe, the average change in flood risk is smaller and the multi-model agreement is poorer.
Multi-Model Estimation Based Moving Object Detection for Aerial Video
Directory of Open Access Journals (Sweden)
Yanning Zhang
2015-04-01
Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.
International Nuclear Information System (INIS)
Si, S.
2012-01-01
The Universal Algorithm of Stiffness Confinement Method (UASCM) for neutron kinetics model of multi-dimensional and multi-group transport equations or diffusion equations has been developed. The numerical experiments based on transport theory code MGSNM and diffusion theory code MGNEM have demonstrated that the algorithm has sufficient accuracy and stability. (authors)
Nguyen, Thuy-Huong; Min, Seung-Ki; Paik, Seungmok; Lee, Donghyun
2018-01-01
This study conducted an updated time of emergence (ToE) analysis of regional precipitation changes over land regions across the globe using multiple climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5). ToEs were estimated for 14 selected hotspots over two seasons of April to September (AS) and October to March (OM) from three RCP scenarios representing low (RCP2.6), medium (RCP4.5), and high (RCP8.5) emissions. Results from the RCP8.5 scenario indicate that ToEs would occur before 2040 over seven hotspots including three northern high-latitude regions (OM wettening), East Africa (OM wettening), South Asia (AS wettening), East Asia (AS wettening) and South Africa (AS drying). The Mediterranean (both OM and AS drying) is expected to experience ToEs in the mid-twenty-first century (2040-2080). In order to measure possible benefits from taking low-emission scenarios, ToE differences were examined between the RCP2.6 scenario and the RCP4.5 and RCP8.5 scenarios. Significant ToE delays from 26 years to longer than 67 years were identified over East Africa (OM wettening), the Mediterranean (both AS and OM drying), South Asia (AS wettening), and South Africa (AS drying). Further, we investigated ToE differences between CMIP3-based and CMIP5-based models using the same number of models for the comparable scenario pairs (SRESA2 vs. RCP8.5, and SRESB1 vs. RCP4.5). Results were largely consistent between two model groups, indicating the robustness of ToE results. Considerable differences in ToEs (larger than 20 years) between two model groups appeared over East Asia and South Asia (AS wettening) and South Africa (AS drying), which were found due to stronger signals in CMIP5 models. Our results provide useful information on the timing of emerging signals in regional and seasonal hydrological changes, having important implications for associated adaptation and mitigation plans.
Multi-Scale Models for the Scale Interaction of Organized Tropical Convection
Yang, Qiu
Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.
New York City Energy-Water Integrated Planning: A Pilot Study
Energy Technology Data Exchange (ETDEWEB)
Bhatt,V.; Crosson, K. M.; Horak, W.; Reisman, A.
2008-12-16
The New York City Energy-Water Integrated Planning Pilot Study is one of several projects funded by Sandia National Laboratories under the U.S. Department of Energy Energy-Water Nexus Program. These projects are intended to clarify some key issues and research needs identified during the Energy-Water Nexus Roadmapping activities. The objectives of the New York City Pilot Project are twofold: to identify energy-water nexus issues in an established urban area in conjunction with a group of key stakeholders and to define and apply an integrated energy and water decision support tool, as proof-of-concept, to one or more of these issues. During the course of this study, the Brookhaven National Laboratory project team worked very closely with members of a Pilot Project Steering Committee. The Steering Committee members brought a breadth of experience across the energy, water and climate disciplines, and all are well versed in the particular issues faced by an urban environment, and by New York City in particular. The first task was to identify energy-water issues of importance to New York City. This exercise was followed by discussion of the qualities and capabilities that an ideal decision support tool should display to address these issues. The decision was made to start with an existing energy model, the New York City version of the MARKAL model, developed originally at BNL and now used globally by many groups for energy analysis. MARKAL has the virtue of being well-vetted, transparent, and capable of calculating 'material' flows, such as water use by the energy system and energy requirements of water technology. The Steering Committee members defined five scenarios of interest, representing a broad spectrum of New York City energy-water issues. Brookhaven National Laboratory researchers developed a model framework (Water-MARKAL) at the desired level of detail to address the scenarios, and then attempted to gather the New York City-specific information
Energy Technology Data Exchange (ETDEWEB)
Egbendewe-Mondzozo, Aklesso [Univ. of Lome, Lome (Togo); Swinton, Scott M. [Univ. of Lome, Lome (Togo); Kang, Shujiang [Univ. of Lome, Lome (Togo); Post, Wilfred M. [Univ. of Lome, Lome (Togo); Binfield, Julian C. [Univ. of Lome, Lome (Togo); Thompson, Wyatt [Univ. of Lome, Lome (Togo)
2015-01-03
Using subregional models of crop production choices in central Wisconsin and southwest Michigan, we predict biomass production, land use, and environmental impacts with details that are unavailable from national scale models. When biomass prices are raised exogenously, we find that the subregional models overestimate the supply, the land use, and the beneficial environmental aspects of perennial biomass crops. Multi-market price feedbacks tied to realistic policy parameters predict high threshold absolute prices for biomass to enter production, resulting in intensified production of biomass from annual grain crops with damaging environmental impacts. Multi-market feedbacks also predict regional specialization in energy biomass production in areas with lower yields of food crops. Furthermore, policies promoting biofuels will not necessarily generate environmental benefits in the absence of environmental regulations.
Lindaas, J.; Commane, R.; Luus, K. A.; Chang, R. Y. W.; Miller, C. E.; Dinardo, S. J.; Henderson, J.; Mountain, M. E.; Karion, A.; Sweeney, C.; Miller, J. B.; Lin, J. C.; Daube, B. C.; Pittman, J. V.; Wofsy, S. C.
2014-12-01
The Alaskan region has historically been a sink of atmospheric CO2, but permafrost currently stores large amounts of carbon that are vulnerable to release to the atmosphere as northern high-latitudes continue to warm faster than the global average. We use aircraft CO2 data with a remote-sensing based model driven by MODIS satellite products and validated by CO2 flux tower data to calculate average daily CO2 fluxes for the region of Alaska during the growing seasons of 2012 and 2013. Atmospheric trace gases were measured during CARVE (Carbon in Arctic Reservoirs Vulnerability Experiment) aboard the NASA Sherpa C-23 aircraft. For profiles along the flight track, we couple the Weather Research and Forecasting (WRF) model with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, and convolve these footprints of surface influence with our remote-sensing based model, the Polar Vegetation Photosynthesis Respiration Model (PolarVPRM). We are able to calculate average regional fluxes for each month by minimizing the difference between the data and model column integrals. Our results provide a snapshot of the current state of regional Alaskan growing season net ecosystem exchange (NEE). We are able to begin characterizing the interannual variation in Alaskan NEE and to inform future refinements in process-based modeling that will produce better estimates of past, present, and future pan-Arctic NEE. Understanding if/when/how the Alaskan region transitions from a sink to a source of CO2 is crucial to predicting the trajectory of future climate change.
Multi-Valued Modal Fixed Point Logics for Model Checking
Nishizawa, Koki
In this paper, I will show how multi-valued logics are used for model checking. Model checking is an automatic technique to analyze correctness of hardware and software systems. A model checker is based on a temporal logic or a modal fixed point logic. That is to say, a system to be checked is formalized as a Kripke model, a property to be satisfied by the system is formalized as a temporal formula or a modal formula, and the model checker checks that the Kripke model satisfies the formula. Although most existing model checkers are based on 2-valued logics, recently new attempts have been made to extend the underlying logics of model checkers to multi-valued logics. I will summarize these new results.
Extensions to the energy system GMM model: An overview
International Nuclear Information System (INIS)
Barreto, L.; Kypreos, S.
2006-09-01
This report describes recent extensions to the energy-systems GMM (Global Multiregional MARKAL) model undertaken by the Energy Economics Group (EEG) of the Paul Scherrer Institute (PSI) in Switzerland (hereon referred to as PSI-EEG) in the context of the SAPIENTIA project sponsored by the European Commission (DG Research) and the Swiss National Centre for Competence in Research on Climate (NCCR-Climate). GMM is a multi-regional 'bottom-up' energy-systems optimization model that endogenizes technology learning. The model has been developed and is used at PSI-EEG. The main extensions undertaken here concern the incorporation of a clusters approach to technology learning, the introduction of an improved representation of the transportation sector with emphasis on the passenger sub-sector and the implementation of marginal abatement curves for CH 4 and N 2 O, two main non-CO 2 greenhouse gases. Also, a linear representation of the atmospheric concentration of CO 2 , CH 4 and N 2 O has been included. Other changes are related to the inclusion of additional technologies for production of synthetic fuels (hydrogen and Fischer- Tropsch liquids) and the inclusion of CO 2 capture in fossil-based and biomass-based hydrogen production. Several of the developments described here follow the work of Turton and Barreto (2004, 2006) for the ERIS model at the Environmentally Compatible Energy Strategies (ECS) Program of IIASA. The remainder of this report is organized as follows. Section 2 describes the basic structure of the GMM model, the main assumptions for the scenario developed and the basic approach to endogenize technology learning in the model and examine the effects of R+D and D+D programs. Section 3 discusses the implementation of technology clusters and describes the key components chosen here. Section 4 presents the improvements to the transportation sector with emphasis on the passenger car subsector. Section 5 briefly describes the new technologies for synthetic fuel
Importance-truncated shell model for multi-shell valence spaces
Energy Technology Data Exchange (ETDEWEB)
Stumpf, Christina; Vobig, Klaus; Roth, Robert [Institut fuer Kernphysik, TU Darmstadt (Germany)
2016-07-01
The valence-space shell model is one of the work horses in nuclear structure theory. In traditional applications, shell-model calculations are carried out using effective interactions constructed in a phenomenological framework for rather small valence spaces, typically spanned by one major shell. We improve on this traditional approach addressing two main aspects. First, we use new effective interactions derived in an ab initio approach and, thus, establish a connection to the underlying nuclear interaction providing access to single- and multi-shell valence spaces. Second, we extend the shell model to larger valence spaces by applying an importance-truncation scheme based on a perturbative importance measure. In this way, we reduce the model space to the relevant basis states for the description of a few target eigenstates and solve the eigenvalue problem in this physics-driven truncated model space. In particular multi-shell valence spaces are not tractable otherwise. We combine the importance-truncated shell model with refined extrapolation schemes to approximately recover the exact result. We present first results obtained in the importance-truncated shell model with the newly derived ab initio effective interactions for multi-shell valence spaces, e.g., the sdpf shell.
A rough multi-factor model of electricity spot prices
International Nuclear Information System (INIS)
Bennedsen, Mikkel
2017-01-01
We introduce a new continuous-time mathematical model of electricity spot prices which accounts for the most important stylized facts of these time series: seasonality, spikes, stochastic volatility, and mean reversion. Empirical studies have found a possible fifth stylized fact, roughness, and our approach explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein–Uhlenbeck-based multi-factor framework of and allows us to perform statistical tests to distinguish between an Ornstein–Uhlenbeck-based model and a rough model. Further, through the multi-factor approach we account for seasonality and spikes before estimating – and making inference on – the degree of roughness. This is novel in the literature and we present simulation evidence showing that these precautions are crucial for accurate estimation. Lastly, we estimate our model on recent data from six European energy exchanges and find statistical evidence of roughness in five out of six markets. As an application of our model, we show how, in these five markets, a rough component improves short term forecasting of the prices. - Highlights: • Statistical modeling of electricity spot prices • Multi-factor decomposition • Roughness • Electricity price forecasting
Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda
Directory of Open Access Journals (Sweden)
Jean Baptiste Nsengiyumva
2018-01-01
Full Text Available Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively. Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8% with no very high susceptibility (0%. Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management.
Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda
Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng
2018-01-01
Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management. PMID:29385096
Schoer, Karl; Wood, Richard; Arto, Iñaki; Weinzettel, Jan
2013-12-17
The mass of material consumed by a population has become a useful proxy for measuring environmental pressure. The "raw material equivalents" (RME) metric of material consumption addresses the issue of including the full supply chain (including imports) when calculating national or product level material impacts. The RME calculation suffers from data availability, however, as quantitative data on production practices along the full supply chain (in different regions) is required. Hence, the RME is currently being estimated by three main approaches: (1) assuming domestic technology in foreign economies, (2) utilizing region-specific life-cycle inventories (in a hybrid framework), and (3) utilizing multi-regional input-output (MRIO) analysis to explicitly cover all regions of the supply chain. While the first approach has been shown to give inaccurate results, this paper focuses on the benefits and costs of the latter two approaches. We analyze results from two key (MRIO and hybrid) projects modeling raw material equivalents, adjusting the models in a stepwise manner in order to quantify the effects of individual conceptual elements. We attempt to isolate the MRIO gap, which denotes the quantitative impact of calculating the RME of imports by an MRIO approach instead of the hybrid model, focusing on the RME of EU external trade imports. While, the models give quantitatively similar results, differences become more pronounced when tracking more detailed material flows. We assess the advantages and disadvantages of the two approaches and look forward to ways to further harmonize data and approaches.
A Systematic Multi-Time Scale Solution for Regional Power Grid Operation
Zhu, W. J.; Liu, Z. G.; Cheng, T.; Hu, B. Q.; Liu, X. Z.; Zhou, Y. F.
2017-10-01
Many aspects need to be taken into consideration in a regional grid while making schedule plans. In this paper, a systematic multi-time scale solution for regional power grid operation considering large scale renewable energy integration and Ultra High Voltage (UHV) power transmission is proposed. In the time scale aspect, we discuss the problem from month, week, day-ahead, within-day to day-behind, and the system also contains multiple generator types including thermal units, hydro-plants, wind turbines and pumped storage stations. The 9 subsystems of the scheduling system are described, and their functions and relationships are elaborated. The proposed system has been constructed in a provincial power grid in Central China, and the operation results further verified the effectiveness of the system.
Ein dynamisches Multi-Akteurs-Modell zur integrierten Bewertung des Klimawandels
Weber, M.
2004-01-01
The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...
Multi-scale Modeling of Power Plant Plume Emissions and Comparisons with Observations
Costigan, K. R.; Lee, S.; Reisner, J.; Dubey, M. K.; Love, S. P.; Henderson, B. G.; Chylek, P.
2011-12-01
The Remote Sensing Verification Project (RSVP) test-bed located in the Four Corners region of Arizona, Utah, Colorado, and New Mexico offers a unique opportunity to develop new approaches for estimating emissions of CO2. Two major power plants located in this area produce very large signals of co-emitted CO2 and NO2 in this rural region. In addition to the Environmental Protection Agency (EPA) maintaining Continuous Emissions Monitoring Systems (CEMS) on each of the power plant stacks, the RSVP program has deployed an array of in-situ and remote sensing instruments, which provide both point and integrated measurements. To aid in the synthesis and interpretation of the measurements, a multi-scale atmospheric modeling approach is implemented, using two atmospheric numerical models: the Weather Research and Forecasting Model with chemistry (WRF-Chem; Grell et al., 2005) and the HIGRAD model (Reisner et al., 2003). The high fidelity HIGRAD model incorporates a multi-phase Lagrangian particle based approach to track individual chemical species of stack plumes at ultra-high resolution, using an adaptive mesh. It is particularly suited to model buoyancy effects and entrainment processes at the edges of the power plant plumes. WRF-Chem is a community model that has been applied to a number of air quality problems and offers several physical and chemical schemes that can be used to model the transport and chemical transformation of the anthropogenic plumes out of the local region. Multiple nested grids employed in this study allow the model to incorporate atmospheric variability ranging from synoptic scales to micro-scales (~200 m), while including locally developed flows influenced by the nearby complex terrain of the San Juan Mountains. The simulated local atmospheric dynamics are provided to force the HIGRAD model, which links mesoscale atmospheric variability to the small-scale simulation of the power plant plumes. We will discuss how these two models are applied and
Multimedia Modeling System Response to Regional Land Management Change
Cooter, E. J.
2015-12-01
A multi-media system of nitrogen and co-pollutant models describing critical physical and chemical processes that cascade synergistically and competitively through the environment, the economy and society has been developed at the USEPA Office of Research and Development. It is populated with linked or fully coupled models that address nutrient research questions such as, "How might future policy, climate or land cover change in the Mississippi River Basin affect Nitrogen and Phosphorous loadings to the Gulf of Mexico" or, "What are the management implications of regional-scale land management changes for the sustainability of air, land and water quality?" This second question requires explicit consideration of economic (e.g. sector prices) and societal (e.g. land management) factors. Metrics that illustrate biosphere-atmosphere interactions such as atmospheric PM2.5 concentrations, atmospheric N loading to surface water, soil organic N and N percolation to groundwater are calculated. An example application has been completed that is driven by a coupled agricultural and energy sector model scenario. The economic scenario assumes that by 2022 there is: 1) no detectable change in weather patterns relative to 2002; 2) a concentration of stover processing facilities in the Upper Midwest; 3) increasing offshore Pacific and Atlantic marine transportation; and 4) increasing corn, soybean and wheat production that meets future demand for food, feed and energy feedstocks. This production goal is reached without adding or removing agricultural land area whose extent is defined by the National Land Cover Dataset (NLCD) 2002v2011 classes 81 and 82. This goal does require, however, crop shifts and agricultural management changes. The multi-media system response over our U.S. 12km rectangular grid resolution analysis suggests that there are regions of potential environmental and health costs, as well as large areas that could experience unanticipated environmental and health
Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
Kou, Jisheng; Sun, Shuyu
2016-08-01
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests
Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
Kou, Jisheng
2016-05-10
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests
Multi-infill strategy for kriging models used in variable fidelity optimization
Directory of Open Access Journals (Sweden)
Chao SONG
2018-03-01
Full Text Available In this paper, a computationally efficient optimization method for aerodynamic design has been developed. The low-fidelity model and the multi-infill strategy are utilized in this approach. Low-fidelity data is employed to provide a good global trend for model prediction, and multiple sample points chosen by different infill criteria in each updating cycle are used to enhance the exploitation and exploration ability of the optimization approach. Take the advantages of low-fidelity model and the multi-infill strategy, and no initial sample for the high-fidelity model is needed. This approach is applied to an airfoil design case and a high-dimensional wing design case. It saves a large number of high-fidelity function evaluations for initial model construction. What’s more, faster reduction of an aerodynamic function is achieved, when compared to ordinary kriging using the multi-infill strategy and variable-fidelity model using single infill criterion. The results indicate that the developed approach has a promising application to efficient aerodynamic design when high-fidelity analyses are involved. Keywords: Aerodynamics, Infill criteria, Kriging models, Multi-infill, Optimization
An analog computer method for solving flux distribution problems in multi region nuclear reactors
Energy Technology Data Exchange (ETDEWEB)
Radanovic, L; Bingulac, S; Lazarevic, B; Matausek, M [Boris Kidric Institute of Nuclear Sciences Vinca, Beograd (Yugoslavia)
1963-04-15
The paper describes a method developed for determining criticality conditions and plotting flux distribution curves in multi region nuclear reactors on a standard analog computer. The method, which is based on the one-dimensional two group treatment, avoids iterative procedures normally used for boundary value problems and is practically insensitive to errors in initial conditions. The amount of analog equipment required is reduced to a minimum and is independent of the number of core regions and reflectors. (author)
Methane Tracking and Mitigation Options - EPA CMOP
U.S. Environmental Protection Agency — This dataset contains the sub-model for EPA's MARKAL model, which tracks methane emissions from the energy system, and limited other sources (landfills and manure...
State-of-the-Art Report on Multi-scale Modelling of Nuclear Fuels
International Nuclear Information System (INIS)
Bartel, T.J.; Dingreville, R.; Littlewood, D.; Tikare, V.; Bertolus, M.; Blanc, V.; Bouineau, V.; Carlot, G.; Desgranges, C.; Dorado, B.; Dumas, J.C.; Freyss, M.; Garcia, P.; Gatt, J.M.; Gueneau, C.; Julien, J.; Maillard, S.; Martin, G.; Masson, R.; Michel, B.; Piron, J.P.; Sabathier, C.; Skorek, R.; Toffolon, C.; Valot, C.; Van Brutzel, L.; Besmann, Theodore M.; Chernatynskiy, A.; Clarno, K.; Gorti, S.B.; Radhakrishnan, B.; Devanathan, R.; Dumont, M.; Maugis, P.; El-Azab, A.; Iglesias, F.C.; Lewis, B.J.; Krack, M.; Yun, Y.; Kurata, M.; Kurosaki, K.; Largenton, R.; Lebensohn, R.A.; Malerba, L.; Oh, J.Y.; Phillpot, S.R.; Tulenko, J. S.; Rachid, J.; Stan, M.; Sundman, B.; Tonks, M.R.; Williamson, R.; Van Uffelen, P.; Welland, M.J.; Valot, Carole; Stan, Marius; Massara, Simone; Tarsi, Reka
2015-10-01
The Nuclear Science Committee (NSC) of the Nuclear Energy Agency (NEA) has undertaken an ambitious programme to document state-of-the-art of modelling for nuclear fuels and structural materials. The project is being performed under the Working Party on Multi-Scale Modelling of Fuels and Structural Material for Nuclear Systems (WPMM), which has been established to assess the scientific and engineering aspects of fuels and structural materials, describing multi-scale models and simulations as validated predictive tools for the design of nuclear systems, fuel fabrication and performance. The WPMM's objective is to promote the exchange of information on models and simulations of nuclear materials, theoretical and computational methods, experimental validation and related topics. It also provides member countries with up-to-date information, shared data, models, and expertise. The goal is also to assess needs for improvement and address them by initiating joint efforts. The WPMM reviews and evaluates multi-scale modelling and simulation techniques currently employed in the selection of materials used in nuclear systems. It serves to provide advice to the nuclear community on the developments needed to meet the requirements of modelling for the design of different nuclear systems. The original WPMM mandate had three components (Figure 1), with the first component currently completed, delivering a report on the state-of-the-art of modelling of structural materials. The work on modelling was performed by three expert groups, one each on Multi-Scale Modelling Methods (M3), Multi-Scale Modelling of Fuels (M2F) and Structural Materials Modelling (SMM). WPMM is now composed of three expert groups and two task forces providing contributions on multi-scale methods, modelling of fuels and modelling of structural materials. This structure will be retained, with the addition of task forces as new topics are developed. The mandate of the Expert Group on Multi-Scale Modelling of
Goodwin, I. D.; Mortlock, T.
2016-02-01
Geohistorical archives of shoreline and foredune planform geometry provides a unique evidence-based record of the time integral response to coupled directional wave climate and sediment supply variability on annual to multi-decadal time scales. We develop conceptual shoreline modelling from the geohistorical shoreline archive using a novel combination of methods, including: LIDAR DEM and field mapping of coastal geology; a decadal-scale climate reconstruction of sea-level pressure, marine windfields, and paleo-storm synoptic type and frequency, and historical bathymetry. The conceptual modelling allows for the discrimination of directional wave climate shifts and the relative contributions of cross-shore and along-shore sand supply rates at multi-decadal resolution. We present regional examples from south-eastern Australia over a large latitudinal gradient from subtropical Queensland (S 25°) to mid-latitude Bass Strait (S 40°) that illustrate the morphodynamic evolution and reorganization to wave climate change. We then use the conceptual modeling to inform a two-dimensional coupled spectral wave-hydrodynamic-morphodynamic model to investigate the shoreface response to paleo-directional wind and wave climates. Unlike one-line shoreline modelling, this fully dynamical approach allows for the investigation of cumulative and spatial bathymetric change due to wave-induced currents, as well as proxy-shoreline change. The fusion of the two modeling approaches allows for: (i) the identification of the natural range of coastal planform geometries in response to wave climate shifts; and, (ii) the decomposition of the multidecadal coastal change into the cross-shore and along-shore sand supply drivers, according to the best-matching planforms.
Error detection in GPS observations by means of Multi-process models
DEFF Research Database (Denmark)
Thomsen, Henrik F.
2001-01-01
The main purpose of this article is to present the idea of using Multi-process models as a method of detecting errors in GPS observations. The theory behind Multi-process models, and double differenced phase observations in GPS is presented shortly. It is shown how to model cycle slips in the Mul...
Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah
2017-10-01
Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.
A model of multi-purpose shopping trip behavior
Arentze, T.A.; Borgers, A.W.J.; Timmermans, H.J.P.
1993-01-01
Existing utility-based models of complex choice behavior do not adequately deal with the interdependencies of chained choices. In this paper, we introduce a model of multi-purpose shopping which is aimed at overcoming this shortcoming. In the proposed model, dependencies between choices within as
Directory of Open Access Journals (Sweden)
Ovidiu COPOȚ
2017-12-01
Full Text Available Ganoderma lucidum is one of the most valued mushrooms in the World, because of its medicinal properties. In the context of North-Eastern Region’s development, any forest product could have a valuable contribution. Therefore, it is important to understand the mushroom’s ecology and generate a map of its optimal distribution. For this, we used one of the most performant species distribution models available – Maxent, field occurrences and climatic-topographic-biotic variables. After multi-collinearity testing and step-wise Maxent modelling, we came to an end with a 0.8 final model based on two predictors. Thus, in the region, the optimal habitat distribution is found in oak, beech, riparian or mixed forests bellow approximately 800 m altitude. The species can be found in almost all forests across lowland, colline and submontane regions according to tree host presence. The approach could be promising for other fungal species for the sustainable development of the region.
Marsh, C.; Pomeroy, J. W.; Wheater, H. S.
2017-12-01
Accurate management of water resources is necessary for social, economic, and environmental sustainability worldwide. In locations with seasonal snowcovers, the accurate prediction of these water resources is further complicated due to frozen soils, solid-phase precipitation, blowing snow transport, and snowcover-vegetation-atmosphere interactions. Complex process interactions and feedbacks are a key feature of hydrological systems and may result in emergent phenomena, i.e., the arising of novel and unexpected properties within a complex system. One example is the feedback associated with blowing snow redistribution, which can lead to drifts that cause locally-increased soil moisture, thus increasing plant growth that in turn subsequently impacts snow redistribution, creating larger drifts. Attempting to simulate these emergent behaviours is a significant challenge, however, and there is concern that process conceptualizations within current models are too incomplete to represent the needed interactions. An improved understanding of the role of emergence in hydrological systems often requires high resolution distributed numerical hydrological models that incorporate the relevant process dynamics. The Canadian Hydrological Model (CHM) provides a novel tool for examining cold region hydrological systems. Key features include efficient terrain representation, allowing simulations at various spatial scales, reduced computational overhead, and a modular process representation allowing for an alternative-hypothesis framework. Using both physics-based and conceptual process representations sourced from long term process studies and the current cold regions literature allows for comparison of process representations and importantly, their ability to produce emergent behaviours. Examining the system in a holistic, process-based manner can hopefully derive important insights and aid in development of improved process representations.
Bergamasco, A.; Budgell, W. P.; Carniel, S.; Sclavo, M.
2005-03-01
Conveyor belt circulation controls global climate through heat and water fluxes with atmosphere and from tropical to polar regions and vice versa. This circulation, commonly referred to as thermohaline circulation (THC), seems to have millennium time scale and nowadays--a non-glacial period--appears to be as rather stable. However, concern is raised by the buildup of CO2 and other greenhouse gases in the atmosphere (IPCC, Third assessment report: Climate Change 2001. A contribution of working group I, II and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge Univ. Press, UK) 2001, http://www.ipcc.ch) as these may affect the THC conveyor paths. Since it is widely recognized that dense-water formation sites act as primary sources in strengthening quasi-stable THC paths (Stommel H., Tellus131961224), in order to simulate properly the consequences of such scenarios a better understanding of these oceanic processes is needed. To successfully model these processes, air-sea-ice-integrated modelling approaches are often required. Here we focus on two polar regions using the Regional Ocean Modeling System (ROMS). In the first region investigated, the North Atlantic-Arctic, where open-ocean deep convection and open-sea ice formation and dispersion under the intense air-sea interactions are the major engines, we use a new version of the coupled hydrodynamic-ice ROMS model. The second area belongs to the Antarctica region inside the Southern Ocean, where brine rejections during ice formation inside shelf seas origin dense water that, flowing along the continental slope, overflow becoming eventually abyssal waters. Results show how nowadays integrated-modelling tasks have become more and more feasible and effective; numerical simulations dealing with large computational domains or challenging different climate scenarios can be run on multi-processors platforms and on systems like LINUX clusters, made of the same hardware as PCs, and
International Nuclear Information System (INIS)
Bergamasco, A.; Carniel, S.; Sclavo, M.; Budgell, W.P.
2005-01-01
Conveyor belt circulation controls global climate through heat and water fluxes with atmosphere and from tropical to polar regions and vice versa. This circulation, commonly referred to as thermohaline circulation (THC), seems to have millennium time scale and nowadays-a non-glacial period-appears to be as rather stable. However, concern is raised by the buildup of CO 2 and other greenhouse gases in the atmosphere (IPCC, Third assessment report: Climate Change 2001. A contribution 01 working group I, n and In to the Third Assessment Report of the intergovernmental Panel on Climate Change (Cambridge Univ. Press, UK) 2001, http://www.ipcc.ch) as these may affect the THC conveyor paths. Since it is widely recognized that dense water formation sites ad as primary sources in strengthening quasi-stable THC paths (Stommel H., Tellus, 13 (1961) 224), in order to simulate properly the consequences of such scenarios a better understanding of these oceanic processes is needed. To successfully model these processes, air sea-ice-integrated modelling approaches are often required. Here we focus on two polar regions using the Regional Ocean Modeling System (ROMS). In the first region investigated, the North Atlantic-Arctic, where open-ocean Jeep convection and open-sea ire formation and dispersion under the intense air-sea interactions are the major engines, we use a new version of the coupled hydrodynamic-ice ROMS model. The second area belongs to the Antarctica region inside the Southern Ocean, where brine rejections during ice formation inside shelf seas origin dense water that, flowing along the continental slope, overflow becoming eventually abyssal waters. Results show how nowadays integrated-modelling tasks have become more and more feasible and effective; numerical simulations dealing with large computational domains or challenging different climate scenarios can be run on multi-processors platforms and on systems like LINUX clusters, made of the same hardware as PCs, and
Oberhauser, Karen; Wiederholt, Ruscena; Diffendorfer, James E.; Semmens, Darius J.; Ries, Leslie; Thogmartin, Wayne E.; Lopez-Hoffman, Laura; Semmens, Brice
2017-01-01
1. The monarch has undergone considerable population declines over the past decade, and the governments of Mexico, Canada, and the United States have agreed to work together to conserve the species.2. Given limited resources, understanding where to focus conservation action is key for widespread species like monarchs. To support planning for continental-scale monarch habitat restoration, we address the question of where restoration efforts are likely to have the largest impacts on monarch butterfly (Danaus plexippus Linn.) population growth rates.3. We present a spatially explicit demographic model simulating the multi-generational annual cycle of the eastern monarch population, and use the model to examine management scenarios, some of which focus on particular regions of North America.4. Improving the monarch habitat in the north central or southern parts of the monarch range yields a slightly greater increase in the population growth rate than restoration in other regions. However, combining restoration efforts across multiple regions yields population growth rates above 1 with smaller simulated improvements in habitat per region than single-region strategies.5. Synthesis and applications: These findings suggest that conservation investment in projects across the full monarch range will be more effective than focusing on one or a few regions, and will require international cooperation across many land use categories.
Directory of Open Access Journals (Sweden)
Ha Dong-Won
2014-01-01
Full Text Available The purpose of this study was to derive the multidimensional attributes of resource dependency of local governments in multi-regional tourism development. The questionnaire was designed based on resource dependence theory and related literature, and five factors of resource dependency were derived by analysis of the questionnaire for the civil servants who participated in the Jirisan area tourism development project which is a representative multi-regional tourism development project of Korea. The measured values of the derived possession, importance, discretion, alternative, and connection were found in various ways according to the project characteristics such as project scale and visitors in the Jirisan area tourism development project. This shows that a variety of variables have an effect on resource dependency.
Modeling Multi-commodity Trade Information Exchange Methods
Traczyk, Tomasz
2012-01-01
Market mechanisms are entering into new fields of economy, in which some constraints of physical world, e.g. Kirchoffs Law in power grid, must be taken into account during trading. On such markets, some of commodities, like telecommunication bandwidth or electrical energy, appear to be non-storable, and must be exchanged in real-time. On the other hand, the markets tend to react at shortest possible time, so an idea to delegate some competency to autonomous software agents is very attractive. Multi-commodity mechanism addresses the aforementioned requirements. Modeling the relationships between the commodities allows to formulate new, more sophisticated models and mechanisms, which reflect decision situations in a better manner. Application of multi-commodity approach requires solving several issues related to data modeling, communication, semantics aspects of communication, reliability, etc. This book answers some of the questions and points out promising paths for implementation and development. Presented s...
Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian
2017-01-01
In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.
Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen
2018-01-01
Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.
Medina, Hanoi; Tian, Di; Srivastava, Puneet; Pelosi, Anna; Chirico, Giovanni B.
2018-07-01
Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0 have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0 at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0 forecasts. Impact of individual forecast variables on ET0 forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0 forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0 forecast performances.
Application of separable parameter space techniques to multi-tracer PET compartment modeling
International Nuclear Information System (INIS)
Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J
2016-01-01
Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. (paper)
Computer Aided Multi-Data Fusion Dismount Modeling
2012-03-22
dependent on a particular environmental condition. They are costly, cumbersome, and involve dedicated software practices and particular knowledge to operate...allow manipulation of 2D matrices, like Microsoft Excel or Libre Office. The second alternative is to modify an already created model (MEM). The model... software . Therefore, with the described computer aided multi-data dismount model the researcher will be able to attach signatures to any desired
TRANTHAC-1: transient thermal-hydraulic analysis code for HTGR core of multi-channel model
International Nuclear Information System (INIS)
Sato, Sadao; Miyamoto, Yoshiaki
1980-08-01
The computer program TRANTHAC-1 is for predicting thermal-hydraulic transient behavior in HTGR's core of pin-in-block type fuel elements, taking into consideration of the core flow distribution. The program treats a multi-channel model, each single channel representing the respective column composed of fuel elements. The fuel columns are grouped in flow control regions; each region is provided with an orifice assembly. In the region, all channels are of the same shape except one channel. Core heat is removed by downward flow of the control through the channel. In any transients, for given time-dependent power, total core flow, inlet coolant temperature and coolant pressure, the thermal response of the core can be determined. In the respective channels, the heat conduction in radial and axial direction are represented. And the temperature distribution in each channel with the components is calculated. The model and usage of the program are described. The program is written in FORTRAN-IV for computer FACOM 230-75 and it is composed of about 4,000 cards. The required core memory is about 75 kilowords. (author)
Multi-terminal direct-current grids modeling, analysis, and control
Chaudhuri, Nilanjan; Majumder, Rajat; Yazdani, Amirnaser
2014-01-01
A comprehensive modeling, analysis, and control design framework for multi-terminal direct current (MTDC) grids is presented together with their interaction with the surrounding AC networks and the impact on overall stability. The first book of its kind on the topic of multi-terminal DC (MTDC) grids Presents a comprehensive modeling framework for MTDC grids which is compatible with the standard AC system modeling for stability studies Includes modal analysis and study of the interactions between the MTDC grid and the surrounding AC systems Addresses the problems of autonomous power sharing an
Comprehensive modelling for approaching the Kyoto targets on a local scale
International Nuclear Information System (INIS)
Pietrapertosa, F.; Macchiato, M.; Salvia, M.
2003-01-01
This study aimed to evaluate the effectiveness of the MARKAL comprehensive model in the development of coherent medium-term strategies and sound climate protection policies at local level. The local case study (Val d'Agri, Basilicata region, Italy) discusses the possible role of local communities in the achievement of the national objectives derived by the Kyoto Protocol, investigating the traditional sectors responsible for air pollution and providing a full picture of the main energy and material flows. A scenario analysis was performed to analyse the response of the modelled system to the introduction of an exogenous constraint on carbon dioxide (CO 2 ) emissions. The main effects are presented with reference to fuel mix, technology choice, real market prices and reduced costs of competing options. The comparison of the solutions obtained for the different scenarios is useful to point out the effects of the CO 2 constraint on the total system cost and on the emission levels of other atmospheric pollutants. A further multiobjective optimisation was performed to analyse the effects of combined environmental constraints (CO 2 and particulate) on the overall system cost as well as in terms of marginal costs. (author)
Comprehensive modelling for approaching the Kyoto targets on a local scale
Energy Technology Data Exchange (ETDEWEB)
Pietrapertosa, F. [Istituto di Metodologie per l' Analisi Ambientale, Tito Scalo (Italy); Universita degli Studi della Basilicata, Potenza (Italy). Dipartimento di Ingegneria e Fisica dell' Ambiente; Cosmi, C.; Marmo, G. [Istituto di Metodologie per l' Analisi Ambientale, Tito Scalo (Italy); Istituto Nazionale di Fisica della Materia, Napoli (Italy); Macchiato, M. [Universita Federico II, Napoli (Italy). Dipartimento di Scienze Fisiche; Salvia, M. [Istituto di Metodologie per l' Analisi Ambientale, Tito Scalo (Italy)
2003-06-01
This study aimed to evaluate the effectiveness of the MARKAL comprehensive model in the development of coherent medium-term strategies and sound climate protection policies at local level. The local case study (Val d'Agri, Basilicata region, Italy) discusses the possible role of local communities in the achievement of the national objectives derived by the Kyoto Protocol, investigating the traditional sectors responsible for air pollution and providing a full picture of the main energy and material flows. A scenario analysis was performed to analyse the response of the modelled system to the introduction of an exogenous constraint on carbon dioxide (CO{sub 2}) emissions. The main effects are presented with reference to fuel mix, technology choice, real market prices and reduced costs of competing options. The comparison of the solutions obtained for the different scenarios is useful to point out the effects of the CO{sub 2} constraint on the total system cost and on the emission levels of other atmospheric pollutants. A further multiobjective optimisation was performed to analyse the effects of combined environmental constraints (CO{sub 2} and particulate) on the overall system cost as well as in terms of marginal costs. (author)
Multi-objective possibilistic model for portfolio selection with transaction cost
Jana, P.; Roy, T. K.; Mazumder, S. K.
2009-06-01
In this paper, we introduce the possibilistic mean value and variance of continuous distribution, rather than probability distributions. We propose a multi-objective Portfolio based model and added another entropy objective function to generate a well diversified asset portfolio within optimal asset allocation. For quantifying any potential return and risk, portfolio liquidity is taken into account and a multi-objective non-linear programming model for portfolio rebalancing with transaction cost is proposed. The models are illustrated with numerical examples.
A Multi-Level Approach to Modeling Rapidly Growing Mega-Regions as a Coupled Human-Natural System
Koch, J. A.; Tang, W.; Meentemeyer, R. K.
2013-12-01
The FUTure Urban-Regional Environment Simulation (FUTURES) integrates information on nonstationary drivers of land change (per capita land area demand, site suitability, and spatial structure of conversion events) into spatial-temporal projections of changes in landscape patterns (Meentemeyer et al., 2013). One striking feature of FUTURES is its patch-growth algorithm that includes feedback effects of former development events across several temporal and spatial scales: cell-level transition events are aggregated into patches of land change and their further growth is based on empirically derived parameters controlling its size, shape, and dispersion. Here, we augment the FUTURES modeling framework by expanding its multilevel structure and its representation of human decision making. The new modeling framework is hierarchically organized as nested subsystems including the latest theory on telecouplings in coupled human-natural systems (Liu et al., 2013). Each subsystem represents a specific level of spatial scale and embraces agents that have decision making authority at a particular level. The subsystems are characterized with regard to their spatial representation and are connected via flows of information (e.g. regulations and policies) or material (e.g. population migration). To provide a modeling framework that is applicable to a wide range of settings and geographical regions and to keep it computationally manageable, we implement a 'zooming factor' that allows to enable or disable subsystems (and hence the represented processes), based on the extent of the study region. The implementation of the FUTURES modeling framework for a specific case study follows the observational modeling approach described in Grimm et al. (2005), starting from the analysis of empirical data in order to capture the processes relevant for specific scales and to allow a rigorous calibration and validation of the model application. In this paper, we give an introduction to the basic
Directory of Open Access Journals (Sweden)
Zhiheng Wang
Full Text Available The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database.The DisoMCS is available at http://cal.tongji.edu.cn/disorder/.
Modeling active region transient brightenings observed with X-ray telescope as multi-stranded loops
Energy Technology Data Exchange (ETDEWEB)
Kobelski, Adam R.; McKenzie, David E. [Department of Physics, P.O. Box 173840, Montana State University, Bozeman, MT 59717-3840 (United States); Donachie, Martin, E-mail: kobelski@solar.physics.montana.edu [University of Glasgow, Glasgow, G128QQ, Scotland (United Kingdom)
2014-05-10
Strong evidence exists that coronal loops as observed in extreme ultraviolet and soft X-rays may not be monolithic isotropic structures, but can often be more accurately modeled as bundles of independent strands. Modeling the observed active region transient brightenings (ARTBs) within this framework allows for the exploration of the energetic ramifications and characteristics of these stratified structures. Here we present a simple method of detecting and modeling ARTBs observed with the Hinode X-Ray Telescope (XRT) as groups of zero-dimensional strands, which allows us to probe parameter space to better understand the spatial and temporal dependence of strand heating in impulsively heated loops. This partially automated method can be used to analyze a large number of observations to gain a statistical insight into the parameters of coronal structures, including the number of heating events required in a given model to fit the observations. In this article, we present the methodology and demonstrate its use in detecting and modeling ARTBs in a sample data set from Hinode/XRT. These initial results show that, in general, multiple heating events are necessary to reproduce observed ARTBs, but the spatial dependence of these heating events cannot yet be established.
Modeling active region transient brightenings observed with X-ray telescope as multi-stranded loops
International Nuclear Information System (INIS)
Kobelski, Adam R.; McKenzie, David E.; Donachie, Martin
2014-01-01
Strong evidence exists that coronal loops as observed in extreme ultraviolet and soft X-rays may not be monolithic isotropic structures, but can often be more accurately modeled as bundles of independent strands. Modeling the observed active region transient brightenings (ARTBs) within this framework allows for the exploration of the energetic ramifications and characteristics of these stratified structures. Here we present a simple method of detecting and modeling ARTBs observed with the Hinode X-Ray Telescope (XRT) as groups of zero-dimensional strands, which allows us to probe parameter space to better understand the spatial and temporal dependence of strand heating in impulsively heated loops. This partially automated method can be used to analyze a large number of observations to gain a statistical insight into the parameters of coronal structures, including the number of heating events required in a given model to fit the observations. In this article, we present the methodology and demonstrate its use in detecting and modeling ARTBs in a sample data set from Hinode/XRT. These initial results show that, in general, multiple heating events are necessary to reproduce observed ARTBs, but the spatial dependence of these heating events cannot yet be established.
Directory of Open Access Journals (Sweden)
Claas Teichmann
2013-06-01
Full Text Available Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs. The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming
Al-Badriyeh, Daoud; Fahey, Michael; Alabbadi, Ibrahim; Al-Khal, Abdullatif; Zaidan, Manal
2015-12-01
Statin selection for the largest hospital formulary in Qatar is not systematic, not comparative, and does not consider the multi-indication nature of statins. There are no reports in the literature of multi-indication-based comparative scoring models of statins or of statin selection criteria weights that are based primarily on local clinicians' preferences and experiences. This study sought to comparatively evaluate statins for first-line therapy in Qatar, and to quantify the economic impact of this. An evidence-based, multi-indication, multi-criteria pharmacotherapeutic model was developed for the scoring of statins from the perspective of the main health care provider in Qatar. The literature and an expert panel informed the selection criteria of statins. Relative weighting of selection criteria was based on the input of the relevant local clinician population. Statins were comparatively scored based on literature evidence, with those exceeding a defined scoring threshold being recommended for use. With 95% CI and 5% margin of error, the scoring model was successfully developed. Selection criteria comprised 28 subcriteria under the following main criteria: clinical efficacy, best publish evidence and experience, adverse effects, drug interaction, dosing time, and fixed dose combination availability. Outcome measures for multiple indications were related to effects on LDL cholesterol, HDL cholesterol, triglyceride, total cholesterol, and C-reactive protein. Atorvastatin, pravastatin, and rosuvastatin exceeded defined pharmacotherapeutic thresholds. Atorvastatin and pravastatin were recommended as first-line use and rosuvastatin as a nonformulary alternative. It was estimated that this would produce a 17.6% cost savings in statins expenditure. Sensitivity analyses confirmed the robustness of the evaluation's outcomes against input uncertainties. Incorporating a comparative evaluation of statins in Qatari practices based on a locally developed, transparent, multi
Wu, Yiping; Liu, Shuguang; Li, Zhengpeng; Dahal, Devendra; Young, Claudia J.; Schmidt, Gail L.; Liu, Jinxun; Davis, Brian; Sohl, Terry L.; Werner, Jeremy M.; Oeding, Jennifer
2014-01-01
Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.
Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection
Bai, Yancheng
2018-01-28
Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.
Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection
Bai, Yancheng; Xu, Huijuan; Saenko, Kate; Ghanem, Bernard
2018-01-01
Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.
A risk-based multi-objective model for optimal placement of sensors in water distribution system
Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein
2018-02-01
In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value
A multi-criteria model for maintenance job scheduling
Directory of Open Access Journals (Sweden)
Sunday A. Oke
2007-12-01
Full Text Available This paper presents a multi-criteria maintenance job scheduling model, which is formulated using a weighted multi-criteria integer linear programming maintenance scheduling framework. Three criteria, which have direct relationship with the primary objectives of a typical production setting, were used. These criteria are namely minimization of equipment idle time, manpower idle time and lateness of job with unit parity. The mathematical model constrained by available equipment, manpower and job available time within planning horizon was tested with a 10-job, 8-hour time horizon problem with declared equipment and manpower available as against the required. The results, analysis and illustrations justify multi-criteria consideration. Thus, maintenance managers are equipped with a tool for adequate decision making that guides against error in the accumulated data which may lead to wrong decision making. The idea presented is new since it provides an approach that has not been documented previously in the literature.
Corporates governance: a complementary model for multi ...
African Journals Online (AJOL)
Corporates governance: a complementary model for multi frameworks and tools. ... Organization became highly needed to transform and convert the available legacy of fragmented solutions and ... Also Data considered as a vital part of the .
Multi-longitudinal-mode micro-laser model
Staliunas, Kestutis
2017-10-01
We derive a convenient model for broad aperture micro-lasers, such as microchip lasers, broad area semiconductor lasers, or VCSELs, taking into account several longitudinal mode families. We provide linear stability analysis, and show characteristic spatio-temporal dynamics in such multi-longitudinal mode laser models. Moreover, we derive the coupled mode model in the presence of intracavity refraction index modulation (intracavity photonic crystal). Contribution to the Topical Issue "Theory and Applications of the Lugiato-Lefever Equation", edited by Yanne K. Chembo, Damia Gomila, Mustapha Tlidi, Curtis R. Menyuk.
Using the IEA ETSAP modelling tools for Denmark
DEFF Research Database (Denmark)
Grohnheit, Poul Erik
signed the agreement and contributed to some early annexes. This project is motivated by an invitation to participate in ETSAP Annex X, "Global Energy Systems and Common Analyses: Climate friendly, Secure and Productive Energy Systems" for the period 2005 to 2007. The main activity is semi......-annual workshops focusing on presentations of model analyses and use of the ETSAP' tools (the MARKAL/TIMES family of models). The project was also planned to benefit from the EU project ”NEEDS - New Energy Externalities Developments for Sustainability. ETSAP is contributing to a part of NEEDS that develops......, Environment and Health (CEEH), starting from January 2007. This report summarises the activities under ETSAP Annex X and related project, emphasising the development of modelling tools that will be useful for modelling the Danish energy system. It is also a status report for the development of a model...
International Nuclear Information System (INIS)
Santos, Gabriel; Pinto, Tiago; Morais, Hugo; Sousa, Tiago M.; Pereira, Ivo F.; Fernandes, Ricardo; Praça, Isabel; Vale, Zita
2015-01-01
Highlights: • Definition of an ontology allowing the communication between multi-agents systems. • Social welfare evaluation in different electricity markets. • Demonstration of the use of the proposed ontology between two multi-agents systems. • Strategic biding in electricity markets. • European electricity markets comparison. - Abstract: The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution
Making Faces - State-Space Models Applied to Multi-Modal Signal Processing
DEFF Research Database (Denmark)
Lehn-Schiøler, Tue
2005-01-01
The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....
Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches
Egging, Rudolf Gerardus
This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. 1 The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in
Modeling and simulation of multi-physics multi-scale transport phenomenain bio-medical applications
Kenjereš, Saša
2014-08-01
We present a short overview of some of our most recent work that combines the mathematical modeling, advanced computer simulations and state-of-the-art experimental techniques of physical transport phenomena in various bio-medical applications. In the first example, we tackle predictions of complex blood flow patterns in the patient-specific vascular system (carotid artery bifurcation) and transfer of the so-called "bad" cholesterol (low-density lipoprotein, LDL) within the multi-layered artery wall. This two-way coupling between the blood flow and corresponding mass transfer of LDL within the artery wall is essential for predictions of regions where atherosclerosis can develop. It is demonstrated that a recently developed mathematical model, which takes into account the complex multi-layer arterial-wall structure, produced LDL profiles within the artery wall in good agreement with in-vivo experiments in rabbits, and it can be used for predictions of locations where the initial stage of development of atherosclerosis may take place. The second example includes a combination of pulsating blood flow and medical drug delivery and deposition controlled by external magnetic field gradients in the patient specific carotid artery bifurcation. The results of numerical simulations are compared with own PIV (Particle Image Velocimetry) and MRI (Magnetic Resonance Imaging) in the PDMS (silicon-based organic polymer) phantom. A very good agreement between simulations and experiments is obtained for different stages of the pulsating cycle. Application of the magnetic drug targeting resulted in an increase of up to ten fold in the efficiency of local deposition of the medical drug at desired locations. Finally, the LES (Large Eddy Simulation) of the aerosol distribution within the human respiratory system that includes up to eight bronchial generations is performed. A very good agreement between simulations and MRV (Magnetic Resonance Velocimetry) measurements is obtained
Modeling and simulation of multi-physics multi-scale transport phenomenain bio-medical applications
International Nuclear Information System (INIS)
Kenjereš, Saša
2014-01-01
We present a short overview of some of our most recent work that combines the mathematical modeling, advanced computer simulations and state-of-the-art experimental techniques of physical transport phenomena in various bio-medical applications. In the first example, we tackle predictions of complex blood flow patterns in the patient-specific vascular system (carotid artery bifurcation) and transfer of the so-called 'bad' cholesterol (low-density lipoprotein, LDL) within the multi-layered artery wall. This two-way coupling between the blood flow and corresponding mass transfer of LDL within the artery wall is essential for predictions of regions where atherosclerosis can develop. It is demonstrated that a recently developed mathematical model, which takes into account the complex multi-layer arterial-wall structure, produced LDL profiles within the artery wall in good agreement with in-vivo experiments in rabbits, and it can be used for predictions of locations where the initial stage of development of atherosclerosis may take place. The second example includes a combination of pulsating blood flow and medical drug delivery and deposition controlled by external magnetic field gradients in the patient specific carotid artery bifurcation. The results of numerical simulations are compared with own PIV (Particle Image Velocimetry) and MRI (Magnetic Resonance Imaging) in the PDMS (silicon-based organic polymer) phantom. A very good agreement between simulations and experiments is obtained for different stages of the pulsating cycle. Application of the magnetic drug targeting resulted in an increase of up to ten fold in the efficiency of local deposition of the medical drug at desired locations. Finally, the LES (Large Eddy Simulation) of the aerosol distribution within the human respiratory system that includes up to eight bronchial generations is performed. A very good agreement between simulations and MRV (Magnetic Resonance Velocimetry) measurements is
International Nuclear Information System (INIS)
Neshat, Elaheh; Saray, Rahim Khoshbakhti
2015-01-01
Highlights: • A new chemical kinetic mechanism for PRFs HCCI combustion is developed. • New mechanism optimization is performed using genetic algorithm and multi-zone model. • Engine-related combustion and performance parameters are predicted accurately. • Engine unburned HC and CO emissions are predicted by the model properly. - Abstract: Development of comprehensive chemical kinetic mechanisms is required for HCCI combustion and emissions prediction to be used in engine development. The main purpose of this study is development of a new chemical kinetic mechanism for primary reference fuels (PRFs) HCCI combustion, which can be applied to combustion models to predict in-cylinder pressure and exhaust CO and UHC emissions, accurately. Hence, a multi-zone model is developed for HCCI engine simulation. Two semi-detailed chemical kinetic mechanisms those are suitable for premixed combustion are used for n-heptane and iso-octane HCCI combustion simulation. The iso-octane mechanism contains 84 species and 484 reactions and the n-heptane mechanism contains 57 species and 296 reactions. A simple interaction between iso-octane and n-heptane is considered in new mechanism. The multi-zone model is validated using experimental data for pure n-heptane and iso-octane. A new mechanism is prepared by combination of these two mechanisms for n-heptane and iso-octane blended fuel, which includes 101 species and 594 reactions. New mechanism optimization is performed using genetic algorithm and multi-zone model. Mechanism contains low temperature heat release region, which decreases with increasing octane number. The results showed that the optimized chemical kinetic mechanism is capable of predicting engine-related combustion and performance parameters. Also after implementing the optimized mechanism, engine unburned HC and CO emissions predicted by the model are in good agreement with the corresponding experimental data
NHL and RCGA Based Multi-Relational Fuzzy Cognitive Map Modeling for Complex Systems
Directory of Open Access Journals (Sweden)
Zhen Peng
2015-11-01
Full Text Available In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL and Real Code Genetic Algorithm (RCGA. The multi-relational FCM fits to model the complex system with multi-dimensions and multi-granularities. The auto construct algorithm can learn the multi-relational FCM from multi-relational data resources to eliminate human intervention. The Multi-Relational Data Mining (MRDM algorithm integrates multi-instance oriented NHL and RCGA of FCM. NHL is extended to mine the causal relationships between coarse-granularity concept and its fined-granularity concepts driven by multi-instances in the multi-relational system. RCGA is used to establish high-quality high-level FCM driven by data. The multi-relational FCM and the integrating algorithm have been applied in complex system of Mutagenesis. The experiment demonstrates not only that they get better classification accuracy, but it also shows the causal relationships among the concepts of the system.
A Stochastic Geometry Model for Multi-hop Highway Vehicular Communication
Farooq, Muhammad Junaid; Elsawy, Hesham; Alouini, Mohamed-Slim
2015-01-01
dissemination. This paper exploits stochastic geometry to develop a tractable and accurate modeling framework to characterize the multi-hop transmissions for vehicular networks in a multi-lane highway setup. In particular, we study the tradeoffs between per
Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.
2011-01-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques
Delmotte, Sylvestre; Lopez-Ridaura, Santiago; Barbier, Jean-Marc; Wery, Jacques
2013-11-15
Evaluating the impacts of the development of alternative agricultural systems, such as organic or low-input cropping systems, in the context of an agricultural region requires the use of specific tools and methodologies. They should allow a prospective (using scenarios), multi-scale (taking into account the field, farm and regional level), integrated (notably multicriteria) and participatory assessment, abbreviated PIAAS (for Participatory Integrated Assessment of Agricultural System). In this paper, we compare the possible contribution to PIAAS of three modeling approaches i.e. Bio-Economic Modeling (BEM), Agent-Based Modeling (ABM) and statistical Land-Use/Land Cover Change (LUCC) models. After a presentation of each approach, we analyze their advantages and drawbacks, and identify their possible complementarities for PIAAS. Statistical LUCC modeling is a suitable approach for multi-scale analysis of past changes and can be used to start discussion about the futures with stakeholders. BEM and ABM approaches have complementary features for scenarios assessment at different scales. While ABM has been widely used for participatory assessment, BEM has been rarely used satisfactorily in a participatory manner. On the basis of these results, we propose to combine these three approaches in a framework targeted to PIAAS. Copyright © 2013 Elsevier Ltd. All rights reserved.
Multi-regional clinical trials and global drug development
Directory of Open Access Journals (Sweden)
Premnath Shenoy
2016-01-01
Full Text Available Drug development has been globalized, and multi-regional clinical trial (MRCT for regulatory submission has widely been conducted by many discovery based global pharmaceutical companies with the objective of reducing the time lag of launch in key markets and improve patient access to new and innovative treatments. Sponsors are facing several challenges while conducting multiregional clinical trials. Challenges under the heads statistics, clinical, regulatory operational, and ethics have been discussed. Regulators in different countries such as USA, EU-Japan, and China have issued guidance documents in respect of MRCT's. Lack of harmonization in the design and planning of MRCT is perceived to create a difficult situation to sponsors adversely affecting progressing MRCT in more and more discoveries. International conference on hormonisation (ICH has initiated the process for having a harmonized guidance document on MRCT. This document is likely to be issued in early 2017.
Belušić, Andreina; Prtenjak, Maja Telišman; Güttler, Ivan; Ban, Nikolina; Leutwyler, David; Schär, Christoph
2018-06-01
Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.
Overpeck, J. T.; Ault, T.; Cole, J. E.; Fasullo, J.; Loope, G. R.; Parsons, L. A.; Stevenson, S.
2015-12-01
Megadrought is one of the most significant and costly climate extremes, and one that stakeholders (e.g., water and other resource managers) the world over wish to understand better; in particular, they need estimates of the risk of severe droughts as a function of drought frequency, severity, duration, and atmospheric greenhouse gas concentration. In many dry-climate regions of the globe, megadrought is synonymous with multi-decadal drought. However, in other regions, megadrought can be defined as extended drought, mostly not seen in the period of instrumental observations, and that would have large impacts if it were to occur in the future. New and published paleoclimatic observations allow us to understand the spectrum of drought in many regions of the globe; droughts exceeding 50 years have occurred in recent Earth history in southwestern North America, sub-Saharan Africa, the Mediterranean and Australia, whereas shorter megadroughts have occurred in Monsoon Asia, Amazonia and elsewhere. Data-model comparisons for regions with sufficiently long (e.g., 1000-2000 years) records of observed hydroclimatic variability suggest that state-of-the-art models can provide realistic estimates of interannual to decadal drought risk, but underestimate the risk of megadrought. Likely reasons for this shortcoming are the lack of sufficient multi-decadal variability in simulations of the past and future, plus an underappreciated understanding about how temperature variability and land-surface feedbacks interact with hydrological and ecological drought, as well as the roles played by unusually wet hydroclimatic extremes (e.g., ENSO related) in ending droughts of long duration. Paleoclimatic records also provide the opportunity to estimate how much models underestimate megadrought risk as a function of locale, frequency, severity, duration, and atmospheric greenhouse gas concentration; they also aid in providing stakeholders with bias-corrected estimates of megadrought risk.
Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.
2016-12-01
Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.
Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems
Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.
2012-12-01
Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions
ORGEST: Regional guidelines and silvicultural models for sustainable forest management
Energy Technology Data Exchange (ETDEWEB)
Piqué, Míriam; Vericat, Pau; Beltrán, Mario
2017-11-01
Aim of the study: To develop regional guidelines for sustainable forest management. Area of the study: Forests of Catalonia (NE Spain). Material and methods: The process of developing the forest management guidelines (FMG) started by establishing a thorough classification of forest types at stand level. This classification hinges on two attributes: tree species composition and site quality based on ecological variables, which together determine potential productivity. From there, the management guidelines establish certain objectives and silvicultural models for each forest type. The forest type classifications, like the silvicultural models, were produced using both existing and newly-built growth models based on data from the National Forest Inventory (NFI) and expert knowledge. The effort involved over 20 expert working groups in order to better integrate the expertise and vision of different sectorial agents. Main results: The FMG consist in quantitative silvicultural models that include typical silvicultural variables, technical descriptions of treatments and codes of good practice. Guidelines now cover almost all forest types in Catalonia (spanning up to 90% of the Catalan forest area). Different silvicultural models have been developed for pure and mixed stands, different site quality classes (2–3 classes per species), and even- and multi-aged stands. Research highlights: FMG: i) orient the management of private and public forests, (ii) provide a technical scaffold for efficient allocation/investment of public subsidies in forest management, and (iii) bridge forest planning instruments at regional (strategic-tactical) and stand (operational) level.
ORGEST: Regional guidelines and silvicultural models for sustainable forest management
International Nuclear Information System (INIS)
Piqué, Míriam; Vericat, Pau; Beltrán, Mario
2017-01-01
Aim of the study: To develop regional guidelines for sustainable forest management. Area of the study: Forests of Catalonia (NE Spain). Material and methods: The process of developing the forest management guidelines (FMG) started by establishing a thorough classification of forest types at stand level. This classification hinges on two attributes: tree species composition and site quality based on ecological variables, which together determine potential productivity. From there, the management guidelines establish certain objectives and silvicultural models for each forest type. The forest type classifications, like the silvicultural models, were produced using both existing and newly-built growth models based on data from the National Forest Inventory (NFI) and expert knowledge. The effort involved over 20 expert working groups in order to better integrate the expertise and vision of different sectorial agents. Main results: The FMG consist in quantitative silvicultural models that include typical silvicultural variables, technical descriptions of treatments and codes of good practice. Guidelines now cover almost all forest types in Catalonia (spanning up to 90% of the Catalan forest area). Different silvicultural models have been developed for pure and mixed stands, different site quality classes (2–3 classes per species), and even- and multi-aged stands. Research highlights: FMG: i) orient the management of private and public forests, (ii) provide a technical scaffold for efficient allocation/investment of public subsidies in forest management, and (iii) bridge forest planning instruments at regional (strategic-tactical) and stand (operational) level.
Multi-scale modeling for sustainable chemical production.
Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J
2013-09-01
With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Multi-Fidelity Uncertainty Propagation for Cardiovascular Modeling
Fleeter, Casey; Geraci, Gianluca; Schiavazzi, Daniele; Kahn, Andrew; Marsden, Alison
2017-11-01
Hemodynamic models are successfully employed in the diagnosis and treatment of cardiovascular disease with increasing frequency. However, their widespread adoption is hindered by our inability to account for uncertainty stemming from multiple sources, including boundary conditions, vessel material properties, and model geometry. In this study, we propose a stochastic framework which leverages three cardiovascular model fidelities: 3D, 1D and 0D models. 3D models are generated from patient-specific medical imaging (CT and MRI) of aortic and coronary anatomies using the SimVascular open-source platform, with fluid structure interaction simulations and Windkessel boundary conditions. 1D models consist of a simplified geometry automatically extracted from the 3D model, while 0D models are obtained from equivalent circuit representations of blood flow in deformable vessels. Multi-level and multi-fidelity estimators from Sandia's open-source DAKOTA toolkit are leveraged to reduce the variance in our estimated output quantities of interest while maintaining a reasonable computational cost. The performance of these estimators in terms of computational cost reductions is investigated for a variety of output quantities of interest, including global and local hemodynamic indicators. Sandia National Labs is a multimission laboratory managed and operated by NTESS, LLC, for the U.S. DOE under contract DE-NA0003525. Funding for this project provided by NIH-NIBIB R01 EB018302.
Energy-dissipation-model for metallurgical multi-phase-systems
Energy Technology Data Exchange (ETDEWEB)
Mavrommatis, K.T. [Rheinisch-Westfaelische Technische Hochschule Aachen, Aachen (Germany)
1996-12-31
Entropy production in real processes is directly associated with the dissipation of energy. Both are potential measures for the proceed of irreversible processes taking place in metallurgical systems. Many of these processes in multi-phase-systems could then be modelled on the basis of the energy-dissipation associated with. As this entity can often be estimated using very simple assumptions from first principles, the evolution of an overall measure of systems behaviour can be studied constructing an energy-dissipation -based model of the system. In this work a formulation of this concept, the Energy-Dissipation-Model (EDM), for metallurgical multi-phase-systems is given. Special examples are studied to illustrate the concept, and benefits as well as the range of validity are shown. This concept might be understood as complement to usual CFD-modelling of complex systems on a more abstract level but reproducing essential attributes of complex metallurgical systems. (author)
Energy-dissipation-model for metallurgical multi-phase-systems
Energy Technology Data Exchange (ETDEWEB)
Mavrommatis, K T [Rheinisch-Westfaelische Technische Hochschule Aachen, Aachen (Germany)
1997-12-31
Entropy production in real processes is directly associated with the dissipation of energy. Both are potential measures for the proceed of irreversible processes taking place in metallurgical systems. Many of these processes in multi-phase-systems could then be modelled on the basis of the energy-dissipation associated with. As this entity can often be estimated using very simple assumptions from first principles, the evolution of an overall measure of systems behaviour can be studied constructing an energy-dissipation -based model of the system. In this work a formulation of this concept, the Energy-Dissipation-Model (EDM), for metallurgical multi-phase-systems is given. Special examples are studied to illustrate the concept, and benefits as well as the range of validity are shown. This concept might be understood as complement to usual CFD-modelling of complex systems on a more abstract level but reproducing essential attributes of complex metallurgical systems. (author)
Universal correlators for multi-arc complex matrix models
International Nuclear Information System (INIS)
Akemann, G.
1997-01-01
The correlation functions of the multi-arc complex matrix model are shown to be universal for any finite number of arcs. The universality classes are characterized by the support of the eigenvalue density and are conjectured to fall into the same classes as the ones recently found for the Hermitian model. This is explicitly shown to be true for the case of two arcs, apart from the known result for one arc. The basic tool is the iterative solution of the loop equation for the complex matrix model with multiple arcs, which provides all multi-loop correlators up to an arbitrary genus. Explicit results for genus one are given for any number of arcs. The two-arc solution is investigated in detail, including the double-scaling limit. In addition universal expressions for the string susceptibility are given for both the complex and Hermitian model. (orig.)
Testing multi-alternative decision models with non-stationary evidence.
Tsetsos, Konstantinos; Usher, Marius; McClelland, James L
2011-01-01
Recent research has investigated the process of integrating perceptual evidence toward a decision, converging on a number of sequential sampling choice models, such as variants of race and diffusion models and the non-linear leaky competing accumulator (LCA) model. Here we study extensions of these models to multi-alternative choice, considering how well they can account for data from a psychophysical experiment in which the evidence supporting each of the alternatives changes dynamically during the trial, in a way that creates temporal correlations. We find that participants exhibit a tendency to choose an alternative whose evidence profile is temporally anti-correlated with (or dissimilar from) that of other alternatives. This advantage of the anti-correlated alternative is well accounted for in the LCA, and provides constraints that challenge several other models of multi-alternative choice.
[Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].
Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang
2011-12-01
To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.
Multi-agent models of spatial cognition, learning and complex choice behavior in urban environments
Arentze, Theo; Timmermans, Harry; Portugali, J.
2006-01-01
This chapter provides an overview of ongoing research projects in the DDSS research program at TUE related to multi-agents. Projects include (a) the use of multi-agent models and concepts of artificial intelligence to develop models of activity-travel behavior; (b) the use of a multi-agent model to
Numerical modelling of multi-vane expander operating conditions in ORC system
Rak, Józef; Błasiak, Przemysław; Kolasiński, Piotr
2017-11-01
Multi-vane expanders are positive displacement volumetric machines which are nowadays considered for application in micro-power domestic ORC systems as promising alternative to micro turbines and other volumetric expanders. The multi-vane expander features very simple design, low gas flow capacity, low expansion ratios, an advantageous ratio of the power output to the external dimensions and are insensitive to the negative influence of the gas-liquid mixture expansion. Moreover, the multi-vane expander can be easily hermetically sealed, which is one of the key issues in the ORC system design. A literature review indicates that issues concerning the application of multi-vane expanders in such systems, especially related to operating of multi-vane expander with different low-boiling working fluids, are innovative, not fully scientifically described and have the potential for practical implementation. In this paper the results of numerical investigations on multi-vane expander operating conditions are presented. The analyses were performed on three-dimensional numerical model of the expander in ANSYS CFX software. The numerical model of the expander was validated using the data obtained from the experiment carried out on a lab test-stand. Then a series of computational analysis were performed using expanders' numerical model in order to determine its operating conditions under various flow conditions of different working fluids.
Assessment of applications of transport models on regional scale solute transport
Guo, Z.; Fogg, G. E.; Henri, C.; Pauloo, R.
2017-12-01
Regional scale transport models are needed to support the long-term evaluation of groundwater quality and to develop management strategies aiming to prevent serious groundwater degradation. The purpose of this study is to evaluate the capacity of previously-developed upscaling approaches to accurately describe main solute transport processes including the capture of late-time tails under changing boundary conditions. Advective-dispersive contaminant transport in a 3D heterogeneous domain was simulated and used as a reference solution. Equivalent transport under homogeneous flow conditions were then evaluated applying the Multi-Rate Mass Transfer (MRMT) model. The random walk particle tracking method was used for both heterogeneous and homogeneous-MRMT scenarios under steady state and transient conditions. The results indicate that the MRMT model can capture the tails satisfactorily for plume transported with ambient steady-state flow field. However, when boundary conditions change, the mass transfer model calibrated for transport under steady-state conditions cannot accurately reproduce the tailing effect observed for the heterogeneous scenario. The deteriorating impact of transient boundary conditions on the upscaled model is more significant for regions where flow fields are dramatically affected, highlighting the poor applicability of the MRMT approach for complex field settings. Accurately simulating mass in both mobile and immobile zones is critical to represent the transport process under transient flow conditions and will be the future focus of our study.
International Nuclear Information System (INIS)
Gupta, Sujata; Bhandari, Preety
1998-01-01
The focus of the presentation was on greenhouse gas mitigation options for the energy sector for India. Results from the Asia Least-cost Greenhouse gas Abatement Strategies (ALGAS) project were presented. The presentation comprised of a review of the sources of greenhouse gases, the optimisation model, ie the Markal model, used for determining the least-cost options, discussion of the results from the baseline and the abatement scenarios. The second half of the presentation focussed on a multi-criteria assessment of the abatement options using the Analytical Hierarchical Process (AHP) model. The emissions of all greenhouse gases, for India, are estimated to be 986.3 Tg of carbon dioxide equivalent for 1990. The energy sector accounted for 58 percent of the total emissions and over 90 percent of the CO2 emissions. Net emissions form land use change and forestry were zero. (au)
Aerosols at the poles: an AeroCom Phase II multi-model evaluation
Directory of Open Access Journals (Sweden)
M. Sand
2017-10-01
Full Text Available Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD at 550 nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC from fossil fuel and biomass burning, sulfate, organic aerosols (OAs, dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs, we document the role of these aerosols at high latitudes.The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (sea-salt and spring (dust, whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (defined here as north of 60° N. The models also predict a noteworthy aerosol transport to the Antarctic (south of 70° S with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE associated with BC and OA from fossil fuel and biofuel (FF, sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative (−0.12 W m−2, dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity
Asia-MIP: Multi Model-data Synthesis of Terrestrial Carbon Cycles in Asia
Ichii, K.; Kondo, M.; Ito, A.; Kang, M.; Sasai, T.; SATO, H.; Ueyama, M.; Kobayashi, H.; Saigusa, N.; Kim, J.
2013-12-01
Asia, which is characterized by monsoon climate and intense human activities, is one of the prominent understudied regions in terms of terrestrial carbon budgets and mechanisms of carbon exchange. To better understand terrestrial carbon cycle in Asia, we initiated multi-model and data intercomparison project in Asia (Asia-MIP). We analyzed outputs from multiple approaches: satellite-based observations (AVHRR and MODIS) and related products, empirically upscaled estimations (Support Vector Regression) using eddy-covariance observation network in Asia (AsiaFlux, CarboEastAsia, FLUXNET), ~10 terrestrial biosphere models (e.g. BEAMS, Biome-BGC, LPJ, SEIB-DGVM, TRIFFID, VISIT models), and atmospheric inversion analysis (e.g. TransCom models). We focused on the two difference temporal coverage: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2010; data intensive period) scales. The regions of covering Siberia, Far East Asia, East Asia, Southeast Asia and South Asia (60-80E, 10S-80N), was analyzed in this study for assessing the magnitudes, interannual variability, and key driving factors of carbon cycles. We will report the progress of synthesis effort to quantify terrestrial carbon budget in Asia. First, we analyzed the recent trends in Gross Primary Productivities (GPP) using satellite-based observation (AVHRR) and multiple terrestrial biosphere models. We found both model outputs and satellite-based observation consistently show an increasing trend in GPP in most of the regions in Asia. Mechanisms of the GPP increase were analyzed using models, and changes in temperature and precipitation play dominant roles in GPP increase in boreal and temperate regions, whereas changes in atmospheric CO2 and precipitation are important in tropical regions. However, their relative contributions were different. Second, in the decadal analysis (2001-2010), we found that the negative GPP and carbon uptake anomalies in 2003 summer in Far East Asia is one of the largest
DEFF Research Database (Denmark)
Andrade Santacoloma, Paloma de Gracia
are affected (in a positive or negative way) by the presence of the other enzymes and compounds in the media. In this thesis the concept of multi-enzyme in-pot term is adopted for processes that are carried out by the combination of enzymes in a single reactor and implemented at pilot or industrial scale...... features of the process and provides the information required to structure the process model by using a step-by-step procedure with the required tools and methods. In this way, this framework increases efficiency of the model development process with respect to time and resources needed (fast and effective....... In this way the model parameters that drives the main dynamic behavior can be identified and thus a better understanding of this type of processes. In order to develop, test and verify the methodology, three case studies were selected, specifically the bi-enzyme process for the production of lactobionic acid...
A rate-dependent multi-scale crack model for concrete
Karamnejad, A.; Nguyen, V.P.; Sluys, L.J.
2013-01-01
A multi-scale numerical approach for modeling cracking in heterogeneous quasi-brittle materials under dynamic loading is presented. In the model, a discontinuous crack model is used at macro-scale to simulate fracture and a gradient-enhanced damage model has been used at meso-scale to simulate
A business case modelling framework for smart multi-energy districts
Good, Nicholas; Martinez Cesena, Eduardo Alejandro; Liu, Xuezhi; Mancarella, Pierluigi
2017-01-01
The potential energy, environmental, technical and economic benefits that might arise from multi-energy systems are increasing interest in smart districts. However, in a liberalised market, it is essential to develop a relevant attractive business case. This paper presents a holistic techno-economic framework that couples building/district, multi-network and business case assessment models for the development of robust business cases for smart multi-energy districts. The framework is demonstr...
Three essays on multi-level optimization models and applications
Rahdar, Mohammad
The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation
A multi-element cosmological model with a complex space-time topology
Kardashev, N. S.; Lipatova, L. N.; Novikov, I. D.; Shatskiy, A. A.
2015-02-01
Wormhole models with a complex topology having one entrance and two exits into the same space-time of another universe are considered, as well as models with two entrances from the same space-time and one exit to another universe. These models are used to build a model of a multi-sheeted universe (a multi-element model of the "Multiverse") with a complex topology. Spherical symmetry is assumed in all the models. A Reissner-Norström black-hole model having no singularity beyond the horizon is constructed. The strength of the central singularity of the black hole is analyzed.
Shan, Feng; Guo, Xiasheng; Tu, Juan; Cheng, Jianchun; Zhang, Dong
The high-intensity focused ultrasound (HIFU) has become an attractive therapeutic tool for the noninvasive tumor treatment. The ultrasonic transducer is the key component in HIFU treatment to generate the HIFU energy. The dimension of focal region generated by the transducer is closely relevant to the safety of HIFU treatment. Therefore, it is essential to numerically investigate the focal region of the transducer. Although the conventional acoustic wave equations have been used successfully to describe the acoustic field, there still exist some inherent drawbacks. In this work, we presented an axisymmetric isothermal multi-relaxation-time lattice Boltzmann method (MRT-LBM) model with the Bouzidi-Firdaouss-Lallemand (BFL) boundary condition in cylindrical coordinate system. With this model, some preliminary simulations were firstly conducted to determine a reasonable value of the relaxation parameter. Then, the validity of the model was examined by comparing the results obtained with the LBM results with the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation and the Spheroidal beam equation (SBE) for the focused transducers with different aperture angles, respectively. In addition, the influences of the aperture angle on the focal region were investigated. The proposed model in this work will provide significant references for the parameter optimization of the focused transducer for applications in the HIFU treatment or other fields, and provide new insights into the conventional acoustic numerical simulations.
Multi-compartment Aerosol Transport Model
Energy Technology Data Exchange (ETDEWEB)
Hubbard, Joshua Allen; Santarpia, Joshua; Brotherton, Christopher M.; Omana, Michael Alexis; Rivera, Danielle; Lucero, Gabriel Anthony
2017-06-01
A simple aerosol transport model was developed for a multi-compartmented cleanroom. Each compartment was treated as a well-mixed volume with ventilating supply and return air. Gravitational settling, intercompartment transport, and leakage of exterior air into the system were included in the model. A set of first order, coupled, ordinary differential equations was derived from the conservation equations of aerosol mass and air mass. The system of ODEs was then solved in MATLAB using pre-existing numerical methods. The model was verified against cases of (1) constant inlet-duct concentration, and (2) exponentially decaying inlet-duct concentration. Numerical methods resulted in normalized error of less than 10 -9 when model solutions were compared to analytical solutions. The model was validated against experimental measurements from a single field test and showed good agreement in the shape and magnitude of the aerosol concentration profile with time.
Demand-driven water withdrawals by Chinese industry: a multi-regional input-output analysis
Zhang, Bo; Chen, Z. M.; Zeng, L.; Qiao, H.; Chen, B.
2016-03-01
With ever increasing water demands and the continuous intensification of water scarcity arising from China's industrialization, the country is struggling to harmonize its industrial development and water supply. This paper presents a systems analysis of water withdrawals by Chinese industry and investigates demand-driven industrial water uses embodied in final demand and interregional trade based on a multi-regional input-output model. In 2007, the Electric Power, Steam, and Hot Water Production and Supply sector ranks first in direct industrial water withdrawal (DWW), and Construction has the largest embodied industrial water use (EWU). Investment, consumption, and exports contribute to 34.6%, 33.3%, and 30.6% of the national total EWU, respectively. Specifically, 58.0%, 51.1%, 48.6%, 43.3%, and 37.5% of the regional EWUs respectively in Guangdong, Shanghai, Zhejiang, Jiangsu, and Fujian are attributed to international exports. The total interregional import/export of embodied water is equivalent to about 40% of the national total DWW, of which 55.5% is associated with the DWWs of Electric Power, Steam, and Hot Water Production and Supply. Jiangsu is the biggest interregional exporter and deficit receiver of embodied water, in contrast to Guangdong as the biggest interregional importer and surplus receiver. Without implementing effective water-saving measures and adjusting industrial structures, the regional imbalance between water availability and water demand tends to intensify considering the water impact of domestic trade of industrial products. Steps taken to improve water use efficiency in production, and to enhance embodied water saving in consumption are both of great significance for supporting China's water policies.
Multi-Model Assessment of Trends and Variability in Terrestrial Carbon Uptake in India
Rao, A. S.; Bala, G.; Ravindranath, N. H.
2015-12-01
Indian terrestrial ecosystem exhibits large temporal and spatial variability in carbon sources and sinks due to its monsoon based climate system, diverse land use and land cover distribution and cultural practices. In this study, a multi-model based assessment is made to study the trends and variability in the land carbon uptake for India over the 20th century. Data from nine models which are a part of a recent land surface model intercomparison project called TRENDY is used for the study. These models are driven with common forcing data over the period of 1901-2010. Model output variables assessed include: gross primary production (GPP), heterotrophic respiration (Rh), autotrophic respiration (Ra) and net primary production (NPP). The net ecosystem productivity (NEP) for the Indian region was calculated as a difference of NPP and Rh and it was found that NEP for the region indicates an estimated increase in uptake over the century by -0.6 TgC/year per year. NPP for India also shows an increasing trend of 2.03% per decade from 1901-2010. Seasonal variation in the multimodel mean NPP is maximum during the southwest monsoon period (JJA) followed by the post monsoon period (SON) and is attributed to the maximum in rainfall for the region during the months of JJA. To attribute the changes seen in the land carbon variables, influence of climatic drivers such as precipitation, temperature and remote influences of large scale phenomenon such as ENSO on the land carbon of the region are also estimated in the study. It is found that although changes in precipitation shows a good correlation to the changes seen in NEP, remote drivers like ENSO do not have much effect on them. The Net Ecosystem Exchange is calculated with the inclusion of the land use change flux and fire flux from the models. NEE suggests that the region behaves as a small sink for carbon with an net uptake of 5 GtC over the past hundred years.
Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy
Directory of Open Access Journals (Sweden)
Changsheng Zhu
2018-03-01
Full Text Available In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.
Microscopic modeling of multi-lane highway traffic flow
Hodas, Nathan O.; Jagota, Anand
2003-12-01
We discuss a microscopic model for the study of multi-lane highway traffic flow dynamics. Each car experiences a force resulting from a combination of the desire of the driver to attain a certain velocity, aerodynamic drag, and change of the force due to car-car interactions. The model also includes multi-lane simulation capability and the ability to add and remove obstructions. We implement the model via a Java applet, which is used to simulate traffic jam formation, the effect of bottlenecks on traffic flow, and the existence of light, medium, and heavy traffic flow. The simulations also provide insight into how the properties of individual cars result in macroscopic behavior. Because the investigation of emergent characteristics is so common in physics, the study of traffic in this manner sheds new light on how the micro-to-macro transition works in general.
Multi-fidelity wake modelling based on Co-Kriging method
DEFF Research Database (Denmark)
Wang, Y. M.; Réthoré, Pierre-Elouan; van der Laan, Paul
2016-01-01
models, respectively. Both the univariate and multivariate based surrogate models are established by taking the local wind speed and wind direction as variables of the wind farm power efficiency function. Various multi-fidelity surrogate models are compared and different sampling schemes are discussed...
Directory of Open Access Journals (Sweden)
Muayad Al-Qaisy
2015-02-01
Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.
Global Ionospheric Modelling using Multi-GNSS: BeiDou, Galileo, GLONASS and GPS.
Ren, Xiaodong; Zhang, Xiaohong; Xie, Weiliang; Zhang, Keke; Yuan, Yongqiang; Li, Xingxing
2016-09-15
The emergence of China's Beidou, Europe's Galileo and Russia's GLONASS satellites has multiplied the number of ionospheric piercing points (IPP) offered by GPS alone. This provides great opportunities for deriving precise global ionospheric maps (GIMs) with high resolution to improve positioning accuracy and ionospheric monitoring capabilities. In this paper, the GIM is developed based on multi-GNSS (GPS, GLONASS, BeiDou and Galileo) observations in the current multi-constellation condition. The performance and contribution of multi-GNSS for ionospheric modelling are carefully analysed and evaluated. Multi-GNSS observations of over 300 stations from the Multi-GNSS Experiment (MGEX) and International GNSS Service (IGS) networks for two months are processed. The results show that the multi-GNSS GIM products are better than those of GIM products based on GPS-only. Differential code biases (DCB) are by-products of the multi-GNSS ionosphere modelling, the corresponding standard deviations (STDs) are 0.06 ns, 0.10 ns, 0.18 ns and 0.15 ns for GPS, GLONASS, BeiDou and Galileo, respectively in satellite, and the STDs for the receiver are approximately 0.2~0.4 ns. The single-frequency precise point positioning (SF-PPP) results indicate that the ionospheric modelling accuracy of the proposed method based on multi-GNSS observations is better than that of the current dual-system GIM in specific areas.
Modeling of a production system using the multi-agent approach
Gwiazda, A.; Sękala, A.; Banaś, W.
2017-08-01
The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the
Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region
Ichoku, Charles; Petrenko, Maksym
2012-01-01
Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.
Device-Level Models Using Multi-Valley Effective Mass
Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Gao, Xujiao; Jacobson, N. Tobias; Mitchell, John A.; Montaño, Inès; Muller, Richard P.; Nielsen, Erik
2015-03-01
Continued progress in quantum electronics depends critically on the availability of robust device-level modeling tools that capture a wide range of physics and effective mass theory (EMT) is one means of building such models. Recent developments in multi-valley EMT show quantitative agreement with more detailed atomistic tight-binding calculations of phosphorus donors in silicon (Gamble, et. al., arXiv:1408.3159). Leveraging existing PDE solvers, we are developing a framework in which this multi-valley EMT is coupled to an integrated device-level description of several experimentally active qubit technologies. Device-level simulations of quantum operations will be discussed, as well as the extraction of process matrices at this level of theory. The authors gratefully acknowledge support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.
Generating Multi-Destination Maps.
Zhang, Junsong; Fan, Jiepeng; Luo, Zhenshan
2017-08-01
Multi-destination maps are a kind of navigation maps aimed to guide visitors to multiple destinations within a region, which can be of great help to urban visitors. However, they have not been developed in the current online map service. To address this issue, we introduce a novel layout model designed especially for generating multi-destination maps, which considers the global and local layout of a multi-destination map. We model the layout problem as a graph drawing that satisfies a set of hard and soft constraints. In the global layout phase, we balance the scale factor between ROIs. In the local layout phase, we make all edges have good visibility and optimize the map layout to preserve the relative length and angle of roads. We also propose a perturbation-based optimization method to find an optimal layout in the complex solution space. The multi-destination maps generated by our system are potential feasible on the modern mobile devices and our result can show an overview and a detail view of the whole map at the same time. In addition, we perform a user study to evaluate the effectiveness of our method, and the results prove that the multi-destination maps achieve our goals well.
Improved hydrogen combustion model for multi-compartment analysis
International Nuclear Information System (INIS)
Ogino, Masao; Hashimoto, Takashi
2000-01-01
NUPEC has been improving a hydrogen combustion model in MELCOR code for severe accident analysis. In the proposed combustion model, the flame velocity in a node was predicted using six different flame front shapes of fireball, prism, bubble, spherical jet, plane jet, and parallelepiped. A verification study of the proposed model was carried out using the NUPEC large-scale combustion test results following the previous work in which the GRS/Battelle multi-compartment combustion test results had been used. The selected test cases for the study were the premixed test and the scenario-oriented test which simulated the severe accident sequences of an actual plant. The improved MELCOR code replaced by the proposed model could predict sufficiently both results of the premixed test and the scenario-oriented test of NUPEC large-scale test. The improved MELCOR code was confirmed to simulate the combustion behavior in the multi-compartment containment vessel during a severe accident with acceptable degree of accuracy. Application of the new model to the LWR severe accident analysis will be continued. (author)
New Sodium Cooled Long-Life Cores with Axially Multi-Driver Regions
International Nuclear Information System (INIS)
Hyun, Hae Ri; Hong, Ser Gi
2014-01-01
In this concept of long-life core (they are sometimes called B-B (Breed and Burn)), tall blanket is placed above the relatively short driver fuel. In the initial stage of burning, the power by fission is mostly generated in the driver region and it moves into the blanket region. The power and flux distributions that are highly peaked in the axial direction propagates slowly from the driver into the blanket region. This concept of long-life core fully utilizes the breeding of blanket in the fast spectra and it can achieve very high burnup of fuel. In this work, we introduce new sodium cooled longlife cores rating 600MWe (1800MWt). In these cores, the driver regions are heterogeneously placed into blanket region so as to achieve stabilized and less peaked axial power distribution as depletion proceeds. At present, our study is focused on only two axial driver regions but this concept can be easily extended onto the multi-driver region concept. The cores designed in this paper have two axial driver regions so as to have stabilized and less peaked axial power distributions as depletion proceeds. The results of the core design and analyses show that the cores have very long-lives longer than -49EFPYs and high discharge burnup higher than 200GWD/kg. Additionally, we considered a long-life core having no blanket. As expected, it was shown that these cores have stabilized and less peaked axial power distribution as the fuel depletes. However, the study shows that the cores having two driver regions still show high initial peaking of the axial power distributions and the core can be optimized by changing the driver fuel height
High Performance Multi-GPU SpMV for Multi-component PDE-Based Applications
Abdelfattah, Ahmad
2015-07-25
Leveraging optimization techniques (e.g., register blocking and double buffering) introduced in the context of KBLAS, a Level 2 BLAS high performance library on GPUs, the authors implement dense matrix-vector multiplications within a sparse-block structure. While these optimizations are important for high performance dense kernel executions, they are even more critical when dealing with sparse linear algebra operations. The most time-consuming phase of many multicomponent applications, such as models of reacting flows or petroleum reservoirs, is the solution at each implicit time step of large, sparse spatially structured or unstructured linear systems. The standard method is a preconditioned Krylov solver. The Sparse Matrix-Vector multiplication (SpMV) is, in turn, one of the most time-consuming operations in such solvers. Because there is no data reuse of the elements of the matrix within a single SpMV, kernel performance is limited by the speed at which data can be transferred from memory to registers, making the bus bandwidth the major bottleneck. On the other hand, in case of a multi-species model, the resulting Jacobian has a dense block structure. For contemporary petroleum reservoir simulations, the block size typically ranges from three to a few dozen among different models, and still larger blocks are relevant within adaptively model-refined regions of the domain, though generally the size of the blocks, related to the number of conserved species, is constant over large regions within a given model. This structure can be exploited beyond the convenience of a block compressed row data format, because it offers opportunities to hide the data motion with useful computations. The new SpMV kernel outperforms existing state-of-the-art implementations on single and multi-GPUs using matrices with dense block structure representative of porous media applications with both structured and unstructured multi-component grids.
Optimized production planning model for a multi-plant cultivation system under uncertainty
Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng
2015-02-01
An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.
Tamrakar, Radha; Varma, P.; Tiwari, M. S.
2018-05-01
Kinetic Alfven wave (KAW) generation due to variation of loss-cone index J and density of multi-ions (H+, He+ and O+) in the plasma sheet boundary layer region (PSBL) is investigated. Kinetic approach is used to derive dispersion relation of wave using Vlasov equation. Variation of frequency with respect to wide range of k⊥ρi (where k⊥ is wave vector across the magnetic field, ρi is gyroradius of ions and i denotes H+, He+ and O+ ions) is analyzed. It is found that each ion gyroradius and number density shows different effect on wave generation with varying width of loss-cone. KAW is generated with multi-ions (H+, He+ and O+) over wide regime for J=1 and shows dissimilar effect for J=2. Frequency is reduced with increasing density of gyrating He+ and O+ ions. Wave frequency is obtained within the reported range which strongly supports generation of kinetic Alfven waves. A sudden drop of frequency is also observed for H+ and He+ ion which may be due to heavy penetration of these ions through the loss-cone. The parameters of PSBL region are used for numerical calculation. The application of these results are in understanding the effect of gyrating multi-ions in transfer of energy and Poynting flux losses from PSBL region towards ionosphere and also describing the generation of aurora.
Numerical modelling of multi-vane expander operating conditions in ORC system
Directory of Open Access Journals (Sweden)
Rak Józef
2017-01-01
Full Text Available Multi-vane expanders are positive displacement volumetric machines which are nowadays considered for application in micro-power domestic ORC systems as promising alternative to micro turbines and other volumetric expanders. The multi-vane expander features very simple design, low gas flow capacity, low expansion ratios, an advantageous ratio of the power output to the external dimensions and are insensitive to the negative influence of the gas-liquid mixture expansion. Moreover, the multi-vane expander can be easily hermetically sealed, which is one of the key issues in the ORC system design. A literature review indicates that issues concerning the application of multi-vane expanders in such systems, especially related to operating of multi-vane expander with different low-boiling working fluids, are innovative, not fully scientifically described and have the potential for practical implementation. In this paper the results of numerical investigations on multi-vane expander operating conditions are presented. The analyses were performed on three-dimensional numerical model of the expander in ANSYS CFX software. The numerical model of the expander was validated using the data obtained from the experiment carried out on a lab test-stand. Then a series of computational analysis were performed using expanders' numerical model in order to determine its operating conditions under various flow conditions of different working fluids.
Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions
Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph
2017-04-01
The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal
Simulation of ultrasonic surface waves with multi-Gaussian and point source beam models
International Nuclear Information System (INIS)
Zhao, Xinyu; Schmerr, Lester W. Jr.; Li, Xiongbing; Sedov, Alexander
2014-01-01
In the past decade, multi-Gaussian beam models have been developed to solve many complicated bulk wave propagation problems. However, to date those models have not been extended to simulate the generation of Rayleigh waves. Here we will combine Gaussian beams with an explicit high frequency expression for the Rayleigh wave Green function to produce a three-dimensional multi-Gaussian beam model for the fields radiated from an angle beam transducer mounted on a solid wedge. Simulation results obtained with this model are compared to those of a point source model. It is shown that the multi-Gaussian surface wave beam model agrees well with the point source model while being computationally much more efficient
Multi-perspective workflow modeling for online surgical situation models.
Franke, Stefan; Meixensberger, Jürgen; Neumuth, Thomas
2015-04-01
Surgical workflow management is expected to enable situation-aware adaptation and intelligent systems behavior in an integrated operating room (OR). The overall aim is to unburden the surgeon and OR staff from both manual maintenance and information seeking tasks. A major step toward intelligent systems behavior is a stable classification of the surgical situation from multiple perspectives based on performed low-level tasks. The present work proposes a method for the classification of surgical situations based on multi-perspective workflow modeling. A model network that interconnects different types of surgical process models is described. Various aspects of a surgical situation description were considered: low-level tasks, high-level tasks, patient status, and the use of medical devices. A study with sixty neurosurgical interventions was conducted to evaluate the performance of our approach and its robustness against incomplete workflow recognition input. A correct classification rate of over 90% was measured for high-level tasks and patient status. The device usage models for navigation and neurophysiology classified over 95% of the situations correctly, whereas the ultrasound usage was more difficult to predict. Overall, the classification rate decreased with an increasing level of input distortion. Autonomous adaptation of medical devices and intelligent systems behavior do not currently depend solely on low-level tasks. Instead, they require a more general type of understanding of the surgical condition. The integration of various surgical process models in a network provided a comprehensive representation of the interventions and allowed for the generation of extensive situation descriptions. Multi-perspective surgical workflow modeling and online situation models will be a significant pre-requisite for reliable and intelligent systems behavior. Hence, they will contribute to a cooperative OR environment. Copyright © 2015 Elsevier Inc. All rights reserved.
Multi-criteria decision analysis for bioenergy in the Centre Region of Portugal
Esteves, T. C. J.; Cabral, P.; Ferreira, A. J. D.; Teixeira, J. C.
2012-04-01
With the consumption of fossil fuels, the resources essential to Man's survival are being rapidly contaminated. A sustainable future may be achieved by the use of renewable energies, allowing countries without non-renewable energy resources to guarantee energetic sovereignty. Using bioenergy may mean a steep reduction and/or elimination of the external dependency, enhancing the countries' capital and potentially reducing of the negative effects that outcome from the use of fossil fuels, such as loss of biodiversity, air, water, and soil pollution, … This work's main focus is to increase bioenergy use in the centre region of Portugal by allying R&D to facilitate determination of bioenergy availability and distribution throughout the study area.This analysis is essential, given that nowadays this knowledge is still very limited in the study area. Geographic Information Systems (GIS) was the main tool used to asses this study, due to its unseeingly ability to integrate various types of information (such as alphanumerical, statistical, geographical, …) and various sources of biomass (forest, agricultural, husbandry, municipal and industrial residues, shrublands, used vegetable oil and energy crops) to determine the bioenergy potential of the study area, as well as their spatial distribution. By allying GIS with multi-criteria decision analysis, the initial table-like information of difficult comprehension is transformed into tangible and easy to read results: both intermediate and final results of the created models will facilitate the decision making process. General results show that the major contributors for the bioenergy potential in the Centre Region of Portugal are forest residues, which are mostly located in the inner region of the study area. However, a more detailed analysis should be made to analyze the viability to use energy crops. As a main conclusion, we can say that, although this region may not use only this type of energy to be completely
Multi-Model Adaptive Fuzzy Controller for a CSTR Process
Directory of Open Access Journals (Sweden)
Shubham Gogoria
2015-09-01
Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.
Multi-scale modeling of composites
DEFF Research Database (Denmark)
Azizi, Reza
A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....
The Dynamics of Regional and Global Expansion
DEFF Research Database (Denmark)
Geisler Asmussen, Christian; Nielsen, Bo Bernhard; Osegowitsch, Tom
2015-01-01
Purpose – The purpose of this paper is to model and test the dynamics of home-regional and global penetration by multi-national enterprises (MNEs). Design/methodology/approach – Drawing on international business (IB) theory, the authors model MNEs adjusting their home-regional and global market...... domain. Findings – The authors demonstrate that MNEs do penetrate both home-regional and global markets, often simultaneously, and that penetration levels often oscillate within an MNE over time. The authors show firms’ rates of regional and global expansion to be affected by their existing regional...
Energy Technology Data Exchange (ETDEWEB)
Xiao, Nan [Department of Bioengineering, Stanford University, Stanford, CA 94305 (United States); Department of Biomedical Engineering, King’s College London, London SE1 7EH (United Kingdom); Humphrey, Jay D. [Department of Biomedical Engineering, Yale University, New Haven, CT 06520 (United States); Figueroa, C. Alberto, E-mail: alberto.figueroa@kcl.ac.uk [Department of Biomedical Engineering, King’s College London, London SE1 7EH (United Kingdom)
2013-07-01
In this article, we present a computational multi-scale model of fully three-dimensional and unsteady hemodynamics within the primary large arteries in the human. Computed tomography image data from two different patients were used to reconstruct a nearly complete network of the major arteries from head to foot. A linearized coupled-momentum method for fluid–structure-interaction was used to describe vessel wall deformability and a multi-domain method for outflow boundary condition specification was used to account for the distal circulation. We demonstrated that physiologically realistic results can be obtained from the model by comparing simulated quantities such as regional blood flow, pressure and flow waveforms, and pulse wave velocities to known values in the literature. We also simulated the impact of age-related arterial stiffening on wave propagation phenomena by progressively increasing the stiffness of the central arteries and found that the predicted effects on pressure amplification and pulse wave velocity are in agreement with findings in the clinical literature. This work demonstrates the feasibility of three-dimensional techniques for simulating hemodynamics in a full-body compliant arterial network.
TLS for generating multi-LOD of 3D building model
International Nuclear Information System (INIS)
Akmalia, R; Setan, H; Majid, Z; Suwardhi, D; Chong, A
2014-01-01
The popularity of Terrestrial Laser Scanners (TLS) to capture three dimensional (3D) objects has been used widely for various applications. Development in 3D models has also led people to visualize the environment in 3D. Visualization of objects in a city environment in 3D can be useful for many applications. However, different applications require different kind of 3D models. Since a building is an important object, CityGML has defined a standard for 3D building models at four different levels of detail (LOD). In this research, the advantages of TLS for capturing buildings and the modelling process of the point cloud can be explored. TLS will be used to capture all the building details to generate multi-LOD. This task, in previous works, involves usually the integration of several sensors. However, in this research, point cloud from TLS will be processed to generate the LOD3 model. LOD2 and LOD1 will then be generalized from the resulting LOD3 model. Result from this research is a guiding process to generate the multi-LOD of 3D building starting from LOD3 using TLS. Lastly, the visualization for multi-LOD model will also be shown
TLS for generating multi-LOD of 3D building model
Akmalia, R.; Setan, H.; Majid, Z.; Suwardhi, D.; Chong, A.
2014-02-01
The popularity of Terrestrial Laser Scanners (TLS) to capture three dimensional (3D) objects has been used widely for various applications. Development in 3D models has also led people to visualize the environment in 3D. Visualization of objects in a city environment in 3D can be useful for many applications. However, different applications require different kind of 3D models. Since a building is an important object, CityGML has defined a standard for 3D building models at four different levels of detail (LOD). In this research, the advantages of TLS for capturing buildings and the modelling process of the point cloud can be explored. TLS will be used to capture all the building details to generate multi-LOD. This task, in previous works, involves usually the integration of several sensors. However, in this research, point cloud from TLS will be processed to generate the LOD3 model. LOD2 and LOD1 will then be generalized from the resulting LOD3 model. Result from this research is a guiding process to generate the multi-LOD of 3D building starting from LOD3 using TLS. Lastly, the visualization for multi-LOD model will also be shown.
Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.
2017-12-01
Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall
International Nuclear Information System (INIS)
Zeng, X.T.; Zhang, S.J.; Feng, J.; Huang, G.H.; Li, Y.P.; Zhang, P.; Chen, J.P.; Li, K.L.
2017-01-01
Highlights: • A multi-reservoir system can handle water/energy deficit, flood and sediment damage. • A MWH model is developed for planning a water allocation and energy generation issue. • A mixed fuzzy-stochastic risk analysis method (MFSR) can handle uncertainties in MWH. • A hybrid MWH model can plan human-recourse-energy with a robust and effective manner. • Results can support adjusting water-energy policy to satisfy increasing demands. - Abstract: In this study, a multi-reservoir based water-hydroenergy management (MWH) model is developed for planning water allocation and hydroenergy generation (WAHG) under uncertainties. A mixed fuzzy-stochastic risk analysis method (MFSR) is introduced to handle objective and subjective uncertainties in MWH model, which can couple fuzzy credibility programming and risk management within a general two-stage context, with aim to reflect the infeasibility risks between expected targets and random second-stage recourse costs. The developed MWH model (embedded by MFSR method) can be applied to a practical study of WAHG issue in Jing River Basin (China), which encounters conflicts between human activity and resource/energy crisis. The construction of water-energy nexus (WEN) is built to reflect integrity of economic development and resource/energy conservation, as well as confronting natural and artificial damages such as water deficit, electricity insufficient, floodwater, high sedimentation deposition contemporarily. Meanwhile, the obtained results with various credibility levels and target-violated risk levels can support generating a robust plan associated with risk control for identification of the optimized water-allocation and hydroenergy-generation alternatives, as well as flood controls. Moreover, results can be beneficial for policymakers to discern the optimal water/sediment release routes, reservoirs’ storage variations (impacted by sediment deposition), electricity supply schedules and system benefit
Vehicle technology under CO2 constraint: a general equilibrium analysis
International Nuclear Information System (INIS)
Schaefer, Andreas; Jacoby, Henry D.
2006-01-01
A study is presented of the rates of penetration of different transport technologies under policy constraints on CO 2 emissions. The response of this sector is analyzed within an overall national level of restriction, with a focus on automobiles, light trucks, and heavy freight trucks. Using the US as an example, a linked set of three models is used to carry out the analysis: a multi-sector computable general equilibrium model of the economy, a MARKAL-type model of vehicle and fuel supply technology, and a model simulating the split of personal and freight transport among modes. Results highlight the importance of incremental improvements in conventional internal combustion engine technology, and, in the absence of policies to overcome observed consumer discount rates, the very long time horizons before radical alternatives like the internal combustion engine hybrid drive train vehicle are likely to take substantial market share
Creating Büchi automata for multi-valued model checking
Vijzelaar, Stefan J.J.; Fokkink, Wan J.
2017-01-01
In explicit state model checking of linear temporal logic properties, a Büchi automaton encodes a temporal property. It interleaves with a Kripke model to form a state space, which is searched for counterexamples. Multi-valued model checking considers additional truth values beyond the Boolean true
Tutorial in biostatistics: competing risks and multi-state models
Putter, H.; Fiocco, M.; Geskus, R. B.
2007-01-01
Standard survival data measure the time span from some time origin until the occurrence of one type of event. If several types of events occur, a model describing progression to each of these competing risks is needed. Multi-state models generalize competing risks models by also describing
Action detection by double hierarchical multi-structure space-time statistical matching model
Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang
2018-03-01
Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.
Directory of Open Access Journals (Sweden)
Tianxiang Cui
Full Text Available Estimating gross primary production (GPP and net primary production (NPP are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR and its fraction absorbed by vegetation (FPAR using a light use efficiency (LUE model. The autotrophic respiration (Ra was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m(-2 d(-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m(-2 d(-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of
A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System
Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.
2017-10-01
A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.
Using synchronization in multi-model ensembles to improve prediction
Hiemstra, P.; Selten, F.
2012-04-01
In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of
Directory of Open Access Journals (Sweden)
Marine Elbakidze
2010-06-01
Full Text Available Building the adaptive capacity of interlinked social and ecological systems is assumed to improve implementation of sustainable forest management (SFM policies. One mechanism is collaborative learning by continuous evaluation, communication, and transdisciplinary knowledge production. The Model Forest (MF concept, developed in Canada, is intended to encourage all dimensions of sustainable development through collaboration among stakeholders of forest resources in a geographical area. Because the MF approach encompasses both social and ecological systems, it can be seen as a process aimed at improving adaptive capacity to deal with uncertainty and change. We analyzed multi-stakeholder approaches used in four MF initiatives representing social-ecological systems with different governance legacies and economic histories in the northwest of the Russian Federation (Komi MF and Pskov MF and in Sweden (Vilhelmina MF and the Foundation Säfsen Forests in the Bergslagen region. To describe the motivations behind development of the initiative and the governance systems, we used qualitative open-ended interviews and analyzed reports and official documents. The initial driving forces for establishing new local governance arrangements were different in all four cases. All MFs were characterized by multi-level and multi-sector collaboration. However, the distribution of power among stakeholders ranged from clearly top down in the Russian Federation to largely bottom up in Sweden. All MF initiatives shared three main challenges: (a to develop governance arrangements that include representative actors and stakeholders, (b to combine top-down and bottom-up approaches to governance, and (c to coordinate different sectors' modes of landscape governance. We conclude that, in principle, the MF concept is a promising approach to multi-stakeholder collaboration. However, to understand the local and regional dimensions of sustainability, and the level of adaptability
Hu, X.; Li, X.; Lu, L.
2017-12-01
Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.
A fuzzy multi-criteria decision-making model for trigeneration system
International Nuclear Information System (INIS)
Wang Jiangjiang; Jing Youyin; Zhang Chunfa; Shi Guohua; Zhang Xutao
2008-01-01
The decision making for trigeneration systems is a compositive project and it should be evaluated and compared in a multi-criteria analysis method. This paper presents a fuzzy multi-criteria decision-making model (FMCDM) for trigeneration systems selection and evaluation. The multi-criteria decision-making methods are briefly reviewed combining the general decision-making process. Then the fuzzy set theory, weighting method and the FMCDM model are presented. Finally, several kinds of trigeneration systems, whose dynamical sources are, respectively stirling engine, gas turbine, gas engine and solid oxide fuel cell, are compared and evaluated with a separate generation system. The case for selecting the optimal trigeneration system applied to a residential building is assessed from the technical, economical, environmental and social aspects, and the FMCDM model combining analytic hierarchical process is applied to the trigeneration case to demonstrate the decision-making process and effectiveness of proposed model. The results show that the gas engine plus lithium bromide absorption water heater/chiller unit for the residential building is the best scheme in the five options
Merging information from multi-model flood projections in a hierarchical Bayesian framework
Le Vine, Nataliya
2016-04-01
Multi-model ensembles are becoming widely accepted for flood frequency change analysis. The use of multiple models results in large uncertainty around estimates of flood magnitudes, due to both uncertainty in model selection and natural variability of river flow. The challenge is therefore to extract the most meaningful signal from the multi-model predictions, accounting for both model quality and uncertainties in individual model estimates. The study demonstrates the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach facilitates explicit treatment of shared multi-model discrepancy as well as the probabilistic nature of the flood estimates, by treating the available models as a sample from a hypothetical complete (but unobserved) set of models. The advantages of the approach are: 1) to insure an adequate 'baseline' conditions with which to compare future changes; 2) to reduce flood estimate uncertainty; 3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; 4) to adjust multi-model consistency criteria when model biases are large; and 5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.
Sur, D.; Paul, A.
2017-12-01
region. The use of VTEC gradients from ANN based VTEC model removes the necessity of continuous operation of multi-station ground based TEC receivers in this low latitude region.
A development of multi-Species mass transport model considering thermodynamic phase equilibrium
DEFF Research Database (Denmark)
Hosokawa, Yoshifumi; Yamada, Kazuo; Johannesson, Björn
2008-01-01
) variation in solid-phase composition when using different types of cement, (ii) physicochemical evaluation of steel corrosion initiation behaviour by calculating the molar ratio of chloride ion to hydroxide ion [Cl]/[OH] in pore solution, (iii) complicated changes of solid-phase composition caused......In this paper, a multi-species mass transport model, which can predict time dependent variation of pore solution and solid-phase composition due to the mass transport into the hardened cement paste, has been developed. Since most of the multi-species models established previously, based...... on the Poisson-Nernst-Planck theory, did not involve the modeling of chemical process, it has been coupled to thermodynamic equilibrium model in this study. By the coupling of thermodynamic equilibrium model, the multi-species model could simulate many different behaviours in hardened cement paste such as: (i...
Users guide to REGIONAL-1: a regional assessment model
International Nuclear Information System (INIS)
Davis, W.E.; Eadie, W.J.; Powell, D.C.
1979-09-01
A guide was prepared to allow a user to run the PNL long-range transport model, REGIONAL 1. REGIONAL 1 is a computer model set up to run atmospheric assessments on a regional basis. The model has the capability of being run in three modes for a single time period. The three modes are: (1) no deposition, (2) dry deposition, (3) wet and dry deposition. The guide provides the physical and mathematical basis used in the model for calculating transport, diffusion, and deposition for all three modes. Also the guide includes a program listing with an explanation of the listings and an example in the form of a short-term assessment for 48 hours. The purpose of the example is to allow a person who has past experience with programming and meteorology to operate the assessment model and compare his results with the guide results. This comparison will assure the user that the program is operating in a proper fashion
Investigation and Control of VIVs with Multi-Lock-in Regions on Wide Flat Box Girders
Directory of Open Access Journals (Sweden)
Bo Wu
2017-01-01
Full Text Available On the preliminary designing of a wide flat box girder with the slenderness ratio 12, vertical and torsional vortex-induced vibrations (VIV are observed in wind tunnel tests. More than one lock-in region, which are defined as “multi-lock-in regions,” are recorded. Therefore, suspicions should be aroused regarding the viewpoint that wide box girders are aerodynamic friendly. As the three nascent vortexes originating at the pedestrian guardrails and inspection rails shed to near-wake through different pathways with different frequencies, the mechanisms of VIVs and multi-lock-in regions are analyzed to be determined by the inappropriate subsidiary structures. A hybrid method combining Large Eddy Simulation (LES with experimental results is introduced to study the flow-structure interactions (FSI when undergoing VIVs; the vortex mode of torsional VIV on wide flat box girders is defined as “4/2S,” which is different from any other known ones. Based on the mechanism of VIV, a new approach by increasing ventilation rate of the pedestrian guardrails is proved to be effective in suppressing vertical and torsional VIVs, and it is more feasible than other control schemes. Then, the control mechanisms are deeper investigated by analyzing the evolution of vortex mode and FSI using Hybrid-LES method.
A multi-agent safety response model in the construction industry.
Meliá, José L
2015-01-01
The construction industry is one of the sectors with the highest accident rates and the most serious accidents. A multi-agent safety response approach allows a useful diagnostic tool in order to understand factors affecting risk and accidents. The special features of the construction sector can influence the relationships among safety responses along the model of safety influences. The purpose of this paper is to test a model explaining risk and work-related accidents in the construction industry as a result of the safety responses of the organization, the supervisors, the co-workers and the worker. 374 construction employees belonging to 64 small Spanish construction companies working for two main companies participated in the study. Safety responses were measured using a 45-item Likert-type questionnaire. The structure of the measure was analyzed using factor analysis and the model of effects was tested using a structural equation model. Factor analysis clearly identifies the multi-agent safety dimensions hypothesized. The proposed safety response model of work-related accidents, involving construction specific results, showed a good fit. The multi-agent safety response approach to safety climate is a useful framework for the assessment of organizational and behavioral risks in construction.
Thober, Stephan; Kumar, Rohini; Wanders, Niko; Marx, Andreas; Pan, Ming; Rakovec, Oldrich; Samaniego, Luis; Sheffield, Justin; Wood, Eric F.; Zink, Matthias
2018-01-01
Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 general circulation models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over the entirety of Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (impacts of global warming could be similar under 1.5 K and 2 K global warming, but have to account for significantly higher changes under 3 K global warming.
Directory of Open Access Journals (Sweden)
Aribet M De Jesus
Full Text Available Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours, structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient
A Multi-Fidelity Surrogate Model for the Equation of State for Mixtures of Real Gases
Ouellet, Frederick; Park, Chanyoung; Koneru, Rahul; Balachandar, S.; Rollin, Bertrand
2017-11-01
The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the products of detonated explosives must be treated as real gases while the ideal gas equation of state is used for the ambient air. As the products expand outward, they mix with the air and create a region where both state equations must be satisfied. One of the most accurate, yet expensive, methods to handle this problem is an algorithm that iterates between both state equations until both pressure and thermal equilibrium are achieved inside of each computational cell. This work creates a multi-fidelity surrogate model to replace this process. This is achieved by using a Kriging model to produce a curve fit which interpolates selected data from the iterative algorithm. The surrogate is optimized for computing speed and model accuracy by varying the number of sampling points chosen to construct the model. The performance of the surrogate with respect to the iterative method is tested in simulations using a finite volume code. The model's computational speed and accuracy are analyzed to show the benefits of this novel approach. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA00023.
Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Brocca, Luca; Todini, Ezio
2017-08-01
This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts: the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.
Rational Multi-curve Models with Counterparty-risk Valuation Adjustments
DEFF Research Database (Denmark)
Crépey, Stéphane; Macrina, Andrea; Nguyen, Tuyet Mai
2016-01-01
We develop a multi-curve term structure set-up in which the modelling ingredients are expressed by rational functionals of Markov processes. We calibrate to London Interbank Offer Rate swaptions data and show that a rational two-factor log-normal multi-curve model is sufficient to match market da...... with regulatory obligations. In order to compute counterparty-risk valuation adjustments, such as credit valuation adjustment, we show how default intensity processes with rational form can be derived. We flesh out our study by applying the results to a basis swap contract....... with accuracy. We elucidate the relationship between the models developed and calibrated under a risk-neutral measure Q and their consistent equivalence class under the real-world probability measure P. The consistent P-pricing models are applied to compute the risk exposures which may be required to comply...
Senay, Gabriel B.; Velpuri, Naga Manohar; Alemu, Henok; Pervez, Shahriar Md; Asante, Kwabena O; Karuki, Gatarwa; Taa, Asefa; Angerer, Jay
2013-01-01
Timely information on the availability of water and forage is important for the sustainable development of pastoral regions. The lack of such information increases the dependence of pastoral communities on perennial sources, which often leads to competition and conflicts. The provision of timely information is a challenging task, especially due to the scarcity or non-existence of conventional station-based hydrometeorological networks in the remote pastoral regions. A multi-source water balance modelling approach driven by satellite data was used to operationally monitor daily water level fluctuations across the pastoral regions of northern Kenya and southern Ethiopia. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used for mapping and estimating the surface area of the waterholes. Satellite-based rainfall, modelled run-off and evapotranspiration data were used to model daily water level fluctuations. Mapping of waterholes was achieved with 97% accuracy. Validation of modelled water levels with field-installed gauge data demonstrated the ability of the model to capture the seasonal patterns and variations. Validation results indicate that the model explained 60% of the observed variability in water levels, with an average root-mean-squared error of 22%. Up-to-date information on rainfall, evaporation, scaled water depth and condition of the waterholes is made available daily in near-real time via the Internet (http://watermon.tamu.edu). Such information can be used by non-governmental organizations, governmental organizations and other stakeholders for early warning and decision making. This study demonstrated an integrated approach for establishing an operational waterhole monitoring system using multi-source satellite data and hydrologic modelling.
Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA
International Nuclear Information System (INIS)
Lee, Minhyuk; Song, Jae Wook; Park, Ji Hwan; Chang, Woojin
2017-01-01
Highlights: • ‘Index-based A-MFDFA’ model is proposed to assess the asymmetric multi-fractality. • The asymmetric multi-fractality in the U.S. stock indices are investigated using ‘Index-based’ and ‘Return-based’ A-MFDFA. • The asymmetric feature is more significantly identified by ‘Index-based’ model than ‘return-based’ model. • Source of multi-fractality and time-varying features are analyzed. - Abstract: We detect the asymmetric multi-fractality in the U.S. stock indices based on the asymmetric multi-fractal detrended fluctuation analysis (A-MFDFA). Instead using the conventional return-based approach, we propose the index-based model of A-MFDFA where the trend based on the evolution of stock index rather than stock price return plays a role for evaluating the asymmetric scaling behaviors. The results show that the multi-fractal behaviors of the U.S. stock indices are asymmetric and the index-based model detects the asymmetric multi-fractality better than return-based model. We also discuss the source of multi-fractality and its asymmetry and observe that the multi-fractal asymmetry in the U.S. stock indices has a time-varying feature where the degree of multi-fractality and asymmetry increase during the financial crisis.
Upper Mantle Shear Wave Structure Beneath North America From Multi-mode Surface Wave Tomography
Yoshizawa, K.; Ekström, G.
2008-12-01
The upper mantle structure beneath the North American continent has been investigated from measurements of multi-mode phase speeds of Love and Rayleigh waves. To estimate fundamental-mode and higher-mode phase speeds of surface waves from a single seismogram at regional distances, we have employed a method of nonlinear waveform fitting based on a direct model-parameter search using the neighbourhood algorithm (Yoshizawa & Kennett, 2002). The method of the waveform analysis has been fully automated by employing empirical quantitative measures for evaluating the accuracy/reliability of estimated multi-mode phase dispersion curves, and thus it is helpful in processing the dramatically increasing numbers of seismic data from the latest regional networks such as USArray. As a first step toward modeling the regional anisotropic shear-wave velocity structure of the North American upper mantle with extended vertical resolution, we have applied the method to long-period three-component records of seismic stations in North America, which mostly comprise the GSN and US regional networks as well as the permanent and transportable USArray stations distributed by the IRIS DMC. Preliminary multi-mode phase-speed models show large-scale patterns of isotropic heterogeneity, such as a strong velocity contrast between the western and central/eastern United States, which are consistent with the recent global and regional models (e.g., Marone, et al. 2007; Nettles & Dziewonski, 2008). We will also discuss radial anisotropy of shear wave speed beneath North America from multi-mode dispersion measurements of Love and Rayleigh waves.
Spatial scale separation in regional climate modelling
Energy Technology Data Exchange (ETDEWEB)
Feser, F.
2005-07-01
In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter
Multi-scale Modelling of Segmentation
DEFF Research Database (Denmark)
Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri
2016-01-01
pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...
Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.
2015-12-01
Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and
A Multi-Phase Equation of State and Strength Model for Tin
International Nuclear Information System (INIS)
Cox, G. A.
2006-01-01
This paper considers a multi-phase equation of state and a multi-phase strength model for tin in the β, γ and liquid phases. At a phase transition there are changes in volume, energy, and properties of a material that should be included in an accurate model. The strength model will also be affected by a solid-solid phase transition. For many materials there is a lack of experimental data for strength at high pressures making the derivation of strength parameters for some phases difficult. In the case of tin there are longitudinal sound speed data on the Hugoniot available that have been used here in conjunction with a multi-phase equation of state to derive strength parameters for the γ phase, a phase which does not exist at room temperature and pressure
Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
Kou, Jisheng; Sun, Shuyu
2016-01-01
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic
IEA-ETSAP TIMES models in Denmark. Preliminary edition
Energy Technology Data Exchange (ETDEWEB)
Grohnheit, P.E.
2011-03-15
This report presents the project 'Danish participation in IEAETSAP, Annex XI, 2008-2010', which continued the Danish participation in ETSAP under Annex XI 'JOint STudies for New And Mitigated Energy Systems (JOSTNAMES): Climate friendly, Secure and Productive Energy Systems'. The main activity has been semi-annual workshops focusing on presentations of model analyses and use of the ETSAP tools (the MARKAL/TIMES family of models). Contributions to these workshops have been based on various collaborative projects within the EU research programmes and the Danish Centre for Environment, Energy and Health (CEEH). In addition, the DTU Climate Centre at Risoe, which was founded in the autumn of 2008, has taken part in the ETSAP workshops, and used the ETSAP model tools for projects, papers, and presentations, as well as for a Ph.D. project. (Author)
Analysis of GRI North American Regional Gas Supply-Demand Model
International Nuclear Information System (INIS)
Nesbitt, D.M.; Singh, J.; Pine, G.D.; Kline, D.; Barron, M.; Cheung, P.D.
1989-01-01
This paper summarizes the results from the GRI North American Regional Gas Supply-Demand Model using the four scenarios defined for the Energy Modeling Forum Number 9 (EMF-9) described in EMF-9 Working Paper 9.4 (1987). The analysis is designed both to showcase the GRI North American Regional model as well as to infer meaningful results about the North American natural gas system. The focus of the analysis is not R ampersand D per se; R ampersand D analysis using the model is conducted regularly by GRI and described elsewhere. Rather, the objective is to analyze some of the major uncertainties in the North American gas market, uncertainties that potentially affect all players including GRI. In particular, the authors seek to quantify the overall economic environment in which production, transmission, distribution, consumption, and R ampersand D decisions will be made and how different that overall environment might be under alternative assumptions. An attendant objective of this analysis has been to enlist economists from a range of organizations (producers, regulators, GRI, and consultants) to carefully scrutinize the GRI North American Regional model and results. In particular, the coauthors were assembled from diverse organizations to review and evaluate model outputs, applying their particular experience and perspective. The four EMF-9 scenarios upon which this paper is based are described in detail later in this document. Briefly, scenario one represents a world with a surfeit of gas and a relatively high oil price projection; scenario two considers a lower oil price forecast; scenario three assumes a pessimistic outlook for the gas resource base with the same oil prices as scenario one; and scenario four examines a higher level of demand for gas in the North American gas market. An important objective of this analysis is to illustrate the predictive power of multi-scenario comparisons (as contrasted with detailed analysis of any individual scenario)
Energy Technology Data Exchange (ETDEWEB)
Zhang, X. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Izaurralde, R. C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zong, Z. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhao, K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Thomson, A. M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2012-08-20
The efficiency of calibrating physically-based complex hydrologic models is a major concern in the application of those models to understand and manage natural and human activities that affect watershed systems. In this study, we developed a multi-core aware multi-objective evolutionary optimization algorithm (MAMEOA) to improve the efficiency of calibrating a worldwide used watershed model (Soil and Water Assessment Tool (SWAT)). The test results show that MAMEOA can save about 1-9%, 26-51%, and 39-56% time consumed by calibrating SWAT as compared with sequential method by using dual-core, quad-core, and eight-core machines, respectively. Potential and limitations of MAMEOA for calibrating SWAT are discussed. MAMEOA is open source software.
Screening wells by multi-scale grids for multi-stage Markov Chain Monte Carlo simulation
DEFF Research Database (Denmark)
Akbari, Hani; Engsig-Karup, Allan Peter
2018-01-01
/production wells, aiming at accurate breakthrough capturing as well as above mentioned efficiency goals. However this short time simulation needs fine-scale structure of the geological model around wells and running a fine-scale model is not as cheap as necessary for screening steps. On the other hand applying...... it on a coarse-scale model declines important data around wells and causes inaccurate results, particularly accurate breakthrough capturing which is important for prediction applications. Therefore we propose a multi-scale grid which preserves the fine-scale model around wells (as well as high permeable regions...... and fractures) and coarsens rest of the field and keeps efficiency and accuracy for the screening well stage and coarse-scale simulation, as well. A discrete wavelet transform is used as a powerful tool to generate the desired unstructured multi-scale grid efficiently. Finally an accepted proposal on coarse...
Kanudia, A.; Berghout, N.A.; Boavida, D.; van den Broek, M.A.
2013-01-01
This paper briefly illustrates a method to represent national energy systems and the geographical details of CCS infrastructures in the same technical-economic model. In the MARKAL-TIMES modeling framework a model of Morocco, Portugal and Spain with both spatial and temporal details has been
[Research progress of multi-model medical image fusion and recognition].
Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian
2013-10-01
Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.
Computational implementation of the multi-mechanism deformation coupled fracture model for salt
International Nuclear Information System (INIS)
Koteras, J.R.; Munson, D.E.
1996-01-01
The Multi-Mechanism Deformation (M-D) model for creep in rock salt has been used in three-dimensional computations for the Waste Isolation Pilot Plant (WIPP), a potential waste, repository. These computational studies are relied upon to make key predictions about long-term behavior of the repository. Recently, the M-D model was extended to include creep-induced damage. The extended model, the Multi-Mechanism Deformation Coupled Fracture (MDCF) model, is considerably more complicated than the M-D model and required a different technology from that of the M-D model for a computational implementation
Ardilouze, Constantin; Batté, L.; Bunzel, F.; Decremer, D.; Déqué, M.; Doblas-Reyes, F. J.; Douville, H.; Fereday, D.; Guemas, V.; MacLachlan, C.; Müller, W.; Prodhomme, C.
2017-12-01
Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992-2010 period performed by five different global coupled ocean-atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land-atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.
Thober, S.; Kumar, R.; Wanders, N.; Marx, A.; Pan, M.; Rakovec, O.; Samaniego, L. E.; Sheffield, J.; Wood, E. F.; Zink, M.
2017-12-01
Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 General Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over entire Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow water equivalent decreases flood events in this region. The contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share of the overall uncertainty and exceed GCM uncertainty in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but has to account for significantly higher changes under 3 K global warming.
Two-equation and multi-fluid turbulence models for Rayleigh–Taylor mixing
International Nuclear Information System (INIS)
Kokkinakis, I.W.; Drikakis, D.; Youngs, D.L.; Williams, R.J.R.
2015-01-01
Highlights: • We present a new improved version of the K–L model. • The improved K–L is found in good agreement with the multi-fluid model and ILES. • The study concerns Rayleigh–Taylor flows at initial density ratios 3:1 and 20:1. - Abstract: This paper presents a new, improved version of the K–L model, as well as a detailed investigation of K–L and multi-fluid models with reference to high-resolution implicit large eddy simulations of compressible Rayleigh–Taylor mixing. The accuracy of the models is examined for different interface pressures and specific heat ratios for Rayleigh–Taylor flows at initial density ratios 3:1 and 20:1. It is shown that the original version of the K–L model requires modifications in order to provide comparable results to the multi-fluid model. The modifications concern the addition of an enthalpy diffusion term to the energy equation; the formulation of the turbulent kinetic energy (source) term in the K equation; and the calculation of the local Atwood number. The proposed modifications significantly improve the results of the K–L model, which are found in good agreement with the multi-fluid model and implicit large eddy simulations with respect to the self-similar mixing width; peak turbulent kinetic energy growth rate, as well as volume fraction and turbulent kinetic energy profiles. However, a key advantage of the two-fluid model is that it can represent the degree of molecular mixing in a direct way, by transferring mass between the two phases. The limitations of the single-fluid K–L model as well as the merits of more advanced Reynolds-averaged Navier–Stokes models are also discussed throughout the paper.
Connected Component Model for Multi-Object Tracking.
He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan
2016-08-01
In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.
Seeking a Multi-Construct Model of Morality
McDaniel, Brenda L.; Grice, James W.; Eason, E. Allen
2010-01-01
The present study explored a multi-construct model of moral development. Variables commonly seen in the moral development literature, such as family interactions, spiritual life, ascription to various sources of moral authority, empathy, shame, guilt and moral judgement competence, were investigated. Results from the current study support previous…
The DART general equilibrium model: A technical description
Springer, Katrin
1998-01-01
This paper provides a technical description of the Dynamic Applied Regional Trade (DART) General Equilibrium Model. The DART model is a recursive dynamic, multi-region, multi-sector computable general equilibrium model. All regions are fully specified and linked by bilateral trade flows. The DART model can be used to project economic activities, energy use and trade flows for each of the specified regions to simulate various trade policy as well as environmental policy scenarios, and to analy...
Adapting crop rotations to climate change in regional impact modelling assessments.
Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank
2018-03-01
The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used
International Nuclear Information System (INIS)
Modak, R.S.; Sahni, D.C.
1996-01-01
Some simple reciprocity-like relations that exist in multi-group neutron diffusion and transport theory over bare homogeneous regions are presented. These relations do not involve the adjoint solutions and are directly related to numerical schemes based on an explicit evaluation of the fission matrix. (author)
Multi-scale modelling and numerical simulation of electronic kinetic transport
International Nuclear Information System (INIS)
Duclous, R.
2009-11-01
This research thesis which is at the interface between numerical analysis, plasma physics and applied mathematics, deals with the kinetic modelling and numerical simulations of the electron energy transport and deposition in laser-produced plasmas, having in view the processes of fuel assembly to temperature and density conditions necessary to ignite fusion reactions. After a brief review of the processes at play in the collisional kinetic theory of plasmas, with a focus on basic models and methods to implement, couple and validate them, the author focuses on the collective aspect related to the free-streaming electron transport equation in the non-relativistic limit as well as in the relativistic regime. He discusses the numerical development and analysis of the scheme for the Vlasov-Maxwell system, and the selection of a validation procedure and numerical tests. Then, he investigates more specific aspects of the collective transport: the multi-specie transport, submitted to phase-space discontinuities. Dealing with the multi-scale physics of electron transport with collision source terms, he validates the accuracy of a fast Monte Carlo multi-grid solver for the Fokker-Planck-Landau electron-electron collision operator. He reports realistic simulations for the kinetic electron transport in the frame of the shock ignition scheme, the development and validation of a reduced electron transport angular model. He finally explores the relative importance of the processes involving electron-electron collisions at high energy by means a multi-scale reduced model with relativistic Boltzmann terms
LenoxKaplan_Role of natural gas in meeting electric sector emissions reduction strategy_dataset
U.S. Environmental Protection Agency — This dataset is for an analysis that used the MARKAL linear optimization model to compare the carbon emissions profiles and system-wide global warming potential of...
Modeling Macroscopic Shape Distortions during Sintering of Multi-layers
DEFF Research Database (Denmark)
Tadesse Molla, Tesfaye
as to help achieve defect free multi-layer components. The initial thickness ratio between the layers making the multi-layer has also significant effect on the extent of camber evolution depending on the material systems. During sintering of tubular bi-layer structures, tangential (hoop) stresses are very...... large compared to radial stresses. The maximum value of hoop stress, which can generate processing defects such as cracks and coating peel-offs, occurs at the beginning of the sintering cycle. Unlike most of the models defining material properties based on porosity and grain size only, the multi...... (firing). However, unintended features like shape instabilities of samples, cracks or delamination of layers may arise during sintering of multi-layer composites. Among these defects, macroscopic shape distortions in the samples can cause problems in the assembly or performance of the final component...
Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.
Dao, Tien Tuan
2017-06-01
Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.
Multi-model ensembles for assessment of flood losses and associated uncertainty
Figueiredo, Rui; Schröter, Kai; Weiss-Motz, Alexander; Martina, Mario L. V.; Kreibich, Heidi
2018-05-01
Flood loss modelling is a crucial part of risk assessments. However, it is subject to large uncertainty that is often neglected. Most models available in the literature are deterministic, providing only single point estimates of flood loss, and large disparities tend to exist among them. Adopting any one such model in a risk assessment context is likely to lead to inaccurate loss estimates and sub-optimal decision-making. In this paper, we propose the use of multi-model ensembles to address these issues. This approach, which has been applied successfully in other scientific fields, is based on the combination of different model outputs with the aim of improving the skill and usefulness of predictions. We first propose a model rating framework to support ensemble construction, based on a probability tree of model properties, which establishes relative degrees of belief between candidate models. Using 20 flood loss models in two test cases, we then construct numerous multi-model ensembles, based both on the rating framework and on a stochastic method, differing in terms of participating members, ensemble size and model weights. We evaluate the performance of ensemble means, as well as their probabilistic skill and reliability. Our results demonstrate that well-designed multi-model ensembles represent a pragmatic approach to consistently obtain more accurate flood loss estimates and reliable probability distributions of model uncertainty.
Thermochemical modelling of multi-component systems
International Nuclear Information System (INIS)
Sundman, B.; Gueneau, C.
2015-01-01
Computational thermodynamic, also known as the Calphad method, is a standard tool in industry for the development of materials and improving processes and there is an intense scientific development of new models and databases. The calculations are based on thermodynamic models of the Gibbs energy for each phase as a function of temperature, pressure and constitution. Model parameters are stored in databases that are developed in an international scientific collaboration. In this way, consistent and reliable data for many properties like heat capacity, chemical potentials, solubilities etc. can be obtained for multi-component systems. A brief introduction to this technique is given here and references to more extensive documentation are provided. (authors)
International Nuclear Information System (INIS)
Enaux, C.
2007-11-01
The simulation of indirect laser implosion requires an accurate knowledge of the inter-penetration of the laser target materials turned into plasma. This work is devoted to the study of a multi-velocity multi-fluid model recently proposed by Scannapieco and Cheng (SC) to describe the inter-penetration of miscible fluids. In this document, we begin with presenting the SC model in the context of miscible fluids flow modelling. Afterwards, the mathematical analysis of the model is carried out (study of the hyperbolicity, existence of a strictly convex mathematical entropy, asymptotic analysis and diffusion limit). As a conclusion the problem is well set. Then, we focus on the problem of numerical resolution of systems of conservation laws with a relaxation source term, because SC model belongs to this class. The main difficulty of this task is to capture on a coarse grid the asymptotic behaviour of the system when the source term is stiff. The main contribution of this work lies in the proposition of a new technique, allowing us to construct a Lagrangian numerical flux taking into account the presence of the source term. This technique is applied first on the model-problem of a one-dimensional Euler system with friction, and then on the multi-fluid SC model. In both cases, we prove that the new scheme is asymptotic-preserving and entropic under a CFL-like condition. The two-dimensional extension of the scheme is done by using a standard alternate directions method. Some numerical results highlight the contribution of the new flux, compared with a standard Lagrange plus Remap scheme where the source term is processed using an operator splitting. (author)
Cultural similarities and differences in medical professionalism: a multi-region study.
Chandratilake, Madawa; McAleer, Sean; Gibson, John
2012-03-01
Over the last two decades, many medical educators have sought to define professionalism. Initial attempts to do so were focused on defining professionalism in a manner that allowed for universal agreement. This quest was later transformed into an effort to 'understand professionalism' as many researchers realised that professionalism is a social construct and is culture-sensitive. The determination of cultural differences in the understanding of professionalism, however, has been subject to very little research, possibly because of the practical difficulties of doing so. In this multi-region study, we illustrate the universal and culture-specific aspects of medical professionalism as it is perceived by medical practitioners. Forty-six professional attributes were identified by reviewing the literature. A total of 584 medical practitioners, representing the UK, Europe, North America and Asia, participated in a survey in which they indicated the importance of each of these attributes. We determined the 'essentialness' of each attribute in different geographic regions using the content validity index, supplemented with kappa statistics. With acceptable levels of consensus, all regional groups identified 29 attributes as 'essential', thereby indicating the universality of these professional attributes, and six attributes as non-essential. The essentialness of the rest varied by regional group. This study has helped to identify regional similarities and dissimilarities in understandings of professionalism, most of which can be explained by cultural differences in line with the theories of cultural dimensions and cultural value. However, certain dissonances among regions may well be attributable to socio-economic factors. Some of the responses appear to be counter-cultural and demonstrate practitioners' keenness to overcome cultural barriers in order to provide better patient care. © Blackwell Publishing Ltd 2012.
An Overview of Multi-Dimensional Models of the Sacramento–San Joaquin Delta
Directory of Open Access Journals (Sweden)
Michael L. MacWilliams
2016-12-01
Full Text Available doi: https://doi.org/10.15447/sfews.2016v14iss4art2Over the past 15 years, the development and application of multi-dimensional hydrodynamic models in San Francisco Bay and the Sacramento–San Joaquin Delta has transformed our ability to analyze and understand the underlying physics of the system. Initial applications of three-dimensional models focused primarily on salt intrusion, and provided a valuable resource for investigating how sea level rise and levee failures in the Delta could influence water quality in the Delta under future conditions. However, multi-dimensional models have also provided significant insights into some of the fundamental biological relationships that have shaped our thinking about the system by exploring the relationship among X2, flow, fish abundance, and the low salinity zone. Through the coupling of multi-dimensional models with wind wave and sediment transport models, it has been possible to move beyond salinity to understand how large-scale changes to the system are likely to affect sediment dynamics, and to assess the potential effects on species that rely on turbidity for habitat. Lastly, the coupling of multi-dimensional hydrodynamic models with particle tracking models has led to advances in our thinking about residence time, the retention of food organisms in the estuary, the effect of south Delta exports on larval entrainment, and the pathways and behaviors of salmonids that travel through the Delta. This paper provides an overview of these recent advances and how they have increased our understanding of the distribution and movement of fish and food organisms. The applications presented serve as a guide to the current state of the science of Delta modeling and provide examples of how we can use multi-dimensional models to predict how future Delta conditions will affect both fish and water supply.
International Nuclear Information System (INIS)
Lee, Seok Min; Lee, Un Chul; Bae, Sung Won; Chung, Bub Dong
2004-01-01
The Multi-Dimensional flow models in system code have been developed during the past many years. RELAP5-3D, CATHARE and TRACE has its specific multi-dimensional flow models and successfully applied it to the system safety analysis. In KAERI, also, MARS(Multi-dimensional Analysis of Reactor Safety) code was developed by integrating RELAP5/MOD3 code and COBRA-TF code. Even though COBRA-TF module can analyze three-dimensional flow models, it has a limitation to apply 3D shear stress dominant phenomena or cylindrical geometry. Therefore, Multi-dimensional analysis models are newly developed by implementing three-dimensional momentum flux and diffusion terms. The multi-dimensional model has been assessed compared with multi-dimensional conceptual problems and CFD code results. Although the assessment results were reasonable, the multi-dimensional model has not been validated to two-phase flow using experimental data. In this paper, the multi-dimensional air-water two-phase flow experiment was simulated and analyzed
Optimal region of latching activity in an adaptive Potts model for networks of neurons
International Nuclear Information System (INIS)
Abdollah-nia, Mohammad-Farshad; Saeedghalati, Mohammadkarim; Abbassian, Abdolhossein
2012-01-01
In statistical mechanics, the Potts model is a model for interacting spins with more than two discrete states. Neural networks which exhibit features of learning and associative memory can also be modeled by a system of Potts spins. A spontaneous behavior of hopping from one discrete attractor state to another (referred to as latching) has been proposed to be associated with higher cognitive functions. Here we propose a model in which both the stochastic dynamics of Potts models and an adaptive potential function are present. A latching dynamics is observed in a limited region of the noise(temperature)–adaptation parameter space. We hence suggest noise as a fundamental factor in such alternations alongside adaptation. From a dynamical systems point of view, the noise–adaptation alternations may be the underlying mechanism for multi-stability in attractor-based models. An optimality criterion for realistic models is finally inferred
Chung, Dongjun; Kuan, Pei Fen; Li, Bo; Sanalkumar, Rajendran; Liang, Kun; Bresnick, Emery H; Dewey, Colin; Keleş, Sündüz
2011-07-01
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip) as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads). This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads). Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.
Directory of Open Access Journals (Sweden)
Dongjun Chung
2011-07-01
Full Text Available Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads. This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads. Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.