WorldWideScience

Sample records for system cost uncertainty

  1. Launcher Systems Development Cost: Behavior, Uncertainty, Influences, Barriers and Strategies for Reduction

    Science.gov (United States)

    Shaw, Eric J.

    2001-01-01

    This paper will report on the activities of the IAA Launcher Systems Economics Working Group in preparations for its Launcher Systems Development Cost Behavior Study. The Study goals include: improve launcher system and other space system parametric cost analysis accuracy; improve launcher system and other space system cost analysis credibility; and provide launcher system and technology development program managers and other decisionmakers with useful information on development cost impacts of their decisions. The Working Group plans to explore at least the following five areas in the Study: define and explain development cost behavior terms and concepts for use in the Study; identify and quantify sources of development cost and cost estimating uncertainty; identify and quantify significant influences on development cost behavior; identify common barriers to development cost understanding and reduction; and recommend practical, realistic strategies to accomplish reductions in launcher system development cost.

  2. SunShot solar power reduces costs and uncertainty in future low-carbon electricity systems.

    Science.gov (United States)

    Mileva, Ana; Nelson, James H; Johnston, Josiah; Kammen, Daniel M

    2013-08-20

    The United States Department of Energy's SunShot Initiative has set cost-reduction targets of $1/watt for central-station solar technologies. We use SWITCH, a high-resolution electricity system planning model, to study the implications of achieving these targets for technology deployment and electricity costs in western North America, focusing on scenarios limiting carbon emissions to 80% below 1990 levels by 2050. We find that achieving the SunShot target for solar photovoltaics would allow this technology to provide more than a third of electric power in the region, displacing natural gas in the medium term and reducing the need for nuclear and carbon capture and sequestration (CCS) technologies, which face technological and cost uncertainties, by 2050. We demonstrate that a diverse portfolio of technological options can help integrate high levels of solar generation successfully and cost-effectively. The deployment of GW-scale storage plays a central role in facilitating solar deployment and the availability of flexible loads could increase the solar penetration level further. In the scenarios investigated, achieving the SunShot target can substantially mitigate the cost of implementing a carbon cap, decreasing power costs by up to 14% and saving up to $20 billion ($2010) annually by 2050 relative to scenarios with Reference solar costs.

  3. Joint cost of energy under an optimal economic policy of hybrid power systems subject to uncertainty

    International Nuclear Information System (INIS)

    Díaz, Guzmán; Planas, Estefanía; Andreu, Jon; Kortabarria, Iñigo

    2015-01-01

    Economical optimization of hybrid systems is usually performed by means of LCoE (levelized cost of energy) calculation. Previous works deal with the LCoE calculation of the whole hybrid system disregarding an important issue: the stochastic component of the system units must be jointly considered. This paper deals with this issue and proposes a new fast optimal policy that properly calculates the LCoE of a hybrid system and finds the lowest LCoE. This proposed policy also considers the implied competition among power sources when variability of gas and electricity prices are taken into account. Additionally, it presents a comparative between the LCoE of the hybrid system and its individual technologies of generation by means of a fast and robust algorithm based on vector logical computation. Numerical case analyses based on realistic data are presented that valuate the contribution of technologies in a hybrid power system to the joint LCoE. - Highlights: • We perform the LCoE calculation with the stochastic component jointly considered. • We propose a fast an optimal policy that minimizes the LCoE. • We compare the obtained LCoEs by means of a fast and robust algorithm. • We take into account the competition among gas prices and electricity prices

  4. Nuclear costs: indicators and uncertainties

    International Nuclear Information System (INIS)

    Leveque, Francois

    2013-01-01

    In order to identify whether it is better to build a gas plant, a nuclear plant or a wind farm, to identify the technology leading to the lowest KWh cost, to identify under which conditions nuclear production is profitable for a private investor, and to identify whether taking the dismantling cost and the waste storage cost into account modifies the nuclear competitiveness with respect to general interest, the author first discusses the different costs of the nuclear sector, their sensitivity to different factors. In a second part, he proposes a retrospective discussion of cost dynamics. Then, as nuclear technology seems characterized by always increasing costs, and as this trend may last, notably because of safety concerns, the author proposes an analysis of the poor competitiveness of nuclear with respect to its cost

  5. Uncertainty in relative cost investigation

    International Nuclear Information System (INIS)

    Bunn, D.; Viahos, K.

    1989-01-01

    One of the consequences of the privatization of the Central Electricity Generating Board has been a weakening of the economic case for nuclear generation over coal. Nuclear has higher capital, but lower operating costs than coal and is therefore favoured in capital budgeting by discounting at lower rates of return. In the Sizewell case (in 1987), discounting at the public sector rate of 5 per cent favoured nuclear. However, the private sector will require higher rates of return, thus rendering nuclear less attractive. Hence the imposition by the government of a diversity constraint on the privatized industry to ensure that contracts are made for a minimum fraction of non-fossil (essentially nuclear) energy. An electricity capacity planning model was developed to estimate the costs of imposing various non-fossil energy constraints on the planning decision of a privatized electricity supply industry, as a function of various discount rates. Using a large-scale linear programming technique, the model optimizes over a 50 year horizon the schedule of installation, and mix of generating capacity, both with and without a minimum non-fossil constraint. The conclusion is that the opportunity cost of diversity may be a complex joint substation of more than one type of plant (eg coal and gas) depending on the discount rate. (author)

  6. Low cost high performance uncertainty quantification

    KAUST Repository

    Bekas, C.

    2009-01-01

    Uncertainty quantification in risk analysis has become a key application. In this context, computing the diagonal of inverse covariance matrices is of paramount importance. Standard techniques, that employ matrix factorizations, incur a cubic cost which quickly becomes intractable with the current explosion of data sizes. In this work we reduce this complexity to quadratic with the synergy of two algorithms that gracefully complement each other and lead to a radically different approach. First, we turned to stochastic estimation of the diagonal. This allowed us to cast the problem as a linear system with a relatively small number of multiple right hand sides. Second, for this linear system we developed a novel, mixed precision, iterative refinement scheme, which uses iterative solvers instead of matrix factorizations. We demonstrate that the new framework not only achieves the much needed quadratic cost but in addition offers excellent opportunities for scaling at massively parallel environments. We based our implementation on BLAS 3 kernels that ensure very high processor performance. We achieved a peak performance of 730 TFlops on 72 BG/P racks, with a sustained performance 73% of theoretical peak. We stress that the techniques presented in this work are quite general and applicable to several other important applications. Copyright © 2009 ACM.

  7. Risk management of energy system for identifying optimal power mix with financial-cost minimization and environmental-impact mitigation under uncertainty

    International Nuclear Information System (INIS)

    Nie, S.; Li, Y.P.; Liu, J.; Huang, Charley Z.

    2017-01-01

    An interval-stochastic risk management (ISRM) method is launched to control the variability of the recourse cost as well as to capture the notion of risk in stochastic programming. The ISRM method can examine various policy scenarios that are associated with economic penalties under uncertainties presented as probability distributions and interval values. An ISRM model is then formulated to identify the optimal power mix for the Beijing's energy system. Tradeoffs between risk and cost are evaluated, indicating any change in targeted cost and risk level would yield different expected costs. Results reveal that the inherent uncertainty of system components and risk attitude of decision makers have significant effects on the city's energy-supply and electricity-generation schemes as well as system cost and probabilistic penalty. Results also disclose that import electricity as a recourse action to compensate the local shortage would be enforced. The import electricity would increase with a reduced risk level; under every risk level, more electricity would be imported with an increased demand. The findings can facilitate the local authority in identifying desired strategies for the city's energy planning and management in association with financial-cost minimization and environmental-impact mitigation. - Highlights: • Interval-stochastic risk management method is launched to identify optimal power mix. • It is advantageous in capturing the notion of risk in stochastic programming. • Results reveal that risk attitudes can affect optimal power mix and financial cost. • Developing renewable energies would enhance the sustainability of energy management. • Import electricity as an action to compensate the local shortage would be enforced.

  8. The Impact of Shale Gas on the Cost and Feasibility of Meeting Climate Targets—A Global Energy System Model Analysis and an Exploration of Uncertainties

    Directory of Open Access Journals (Sweden)

    Sheridan Few

    2017-01-01

    Full Text Available There exists considerable uncertainty over both shale and conventional gas resource availability and extraction costs, as well as the fugitive methane emissions associated with shale gas extraction and its possible role in mitigating climate change. This study uses a multi-region energy system model, TIAM (TIMES integrated assessment model, to consider the impact of a range of conventional and shale gas cost and availability assessments on mitigation scenarios aimed at achieving a limit to global warming of below 2 °C in 2100, with a 50% likelihood. When adding shale gas to the global energy mix, the reduction to the global energy system cost is relatively small (up to 0.4%, and the mitigation cost increases by 1%–3% under all cost assumptions. The impact of a “dash for shale gas”, of unavailability of carbon capture and storage, of increased barriers to investment in low carbon technologies, and of higher than expected leakage rates, are also considered; and are each found to have the potential to increase the cost and reduce feasibility of meeting global temperature goals. We conclude that the extraction of shale gas is not likely to significantly reduce the effort required to mitigate climate change under globally coordinated action, but could increase required mitigation effort if not handled sufficiently carefully.

  9. Robust guaranteed cost tracking control of quadrotor UAV with uncertainties.

    Science.gov (United States)

    Xu, Zhiwei; Nian, Xiaohong; Wang, Haibo; Chen, Yinsheng

    2017-07-01

    In this paper, a robust guaranteed cost controller (RGCC) is proposed for quadrotor UAV system with uncertainties to address set-point tracking problem. A sufficient condition of the existence for RGCC is derived by Lyapunov stability theorem. The designed RGCC not only guarantees the whole closed-loop system asymptotically stable but also makes the quadratic performance level built for the closed-loop system have an upper bound irrespective to all admissible parameter uncertainties. Then, an optimal robust guaranteed cost controller is developed to minimize the upper bound of performance level. Simulation results verify the presented control algorithms possess small overshoot and short setting time, with which the quadrotor has ability to perform set-point tracking task well. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Cost uncertainty for different levels of technology maturity

    International Nuclear Information System (INIS)

    DeMuth, S.F.; Franklin, A.L.

    1996-01-01

    It is difficult at best to apply a single methodology for estimating cost uncertainties related to technologies of differing maturity. While highly mature technologies may have significant performance and manufacturing cost data available, less well developed technologies may be defined in only conceptual terms. Regardless of the degree of technical maturity, often a cost estimate relating to application of the technology may be required to justify continued funding for development. Yet, a cost estimate without its associated uncertainty lacks the information required to assess the economic risk. For this reason, it is important for the developer to provide some type of uncertainty along with a cost estimate. This study demonstrates how different methodologies for estimating uncertainties can be applied to cost estimates for technologies of different maturities. For a less well developed technology an uncertainty analysis of the cost estimate can be based on a sensitivity analysis; whereas, an uncertainty analysis of the cost estimate for a well developed technology can be based on an error propagation technique from classical statistics. It was decided to demonstrate these uncertainty estimation techniques with (1) an investigation of the additional cost of remediation due to beyond baseline, nearly complete, waste heel retrieval from underground storage tanks (USTs) at Hanford; and (2) the cost related to the use of crystalline silico-titanate (CST) rather than the baseline CS100 ion exchange resin for cesium separation from UST waste at Hanford

  11. Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities

    International Nuclear Information System (INIS)

    Benjamin, Serge; Descures, Sylvain; Du Pasquier, Louis; Francois, Patrice; Buonarotti, Stefano; Mariotti, Giovanni; Tarakonov, Jurij; Daniska, Vladimir; Bergh, Niklas; Carroll, Simon; AaSTRoeM, Annika; Cato, Anna; De La Gardie, Fredrik; Haenggi, Hannes; Rodriguez, Jose; Laird, Alastair; Ridpath, Andy; La Guardia, Thomas; O'Sullivan, Patrick; ); Weber, Inge; )

    2017-01-01

    The cost estimation process of decommissioning nuclear facilities has continued to evolve in recent years, with a general trend towards demonstrating greater levels of detail in the estimate and more explicit consideration of uncertainties, the latter of which may have an impact on decommissioning project costs. The 2012 report on the International Structure for Decommissioning Costing (ISDC) of Nuclear Installations, a joint recommendation by the Nuclear Energy Agency (NEA), the International Atomic Energy Agency (IAEA) and the European Commission, proposes a standardised structure of cost items for decommissioning projects that can be used either directly for the production of cost estimates or for mapping of cost items for benchmarking purposes. The ISDC, however, provides only limited guidance on the treatment of uncertainty when preparing cost estimates. Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities, prepared jointly by the NEA and IAEA, is intended to complement the ISDC, assisting cost estimators and reviewers in systematically addressing uncertainties in decommissioning cost estimates. Based on experiences gained in participating countries and projects, the report describes how uncertainty and risks can be analysed and incorporated in decommissioning cost estimates, while presenting the outcomes in a transparent manner

  12. The cost of uncertainty in capacity expansion problems

    Energy Technology Data Exchange (ETDEWEB)

    Jenhung Wang [National Chung Cheng Univ., Dept. of Business Administration, Chia-Yi (Taiwan); Sparrow, F.T. [Purdue Univ., School of Industrial Engineering, West Lafayette, IN (United States)

    1999-07-01

    The goals of this paper are to present a two-stage programming model of the capacity expansion problem under uncertainty of demand and explore the impact of the uncertainty on cost. The model is a mixed integer nonlinear programming (MINLP) model with the consideration of uncertainty used to maximise the expected presented value of utility profits over the planning horizon, under the constraints of rate of return and reserve margin regulation. The results reveal that the uncertainty harms the profit seriously. In this paper both microeconomics and mathematical programming are used to analyse the problem. We try to observe the economic behaviour of the utility with uncertainty involved. We also investigate the influence on the cost of uncertainty of each economic parameter. (Author)

  13. Marketable pollution permits with uncertainty and transaction costs

    International Nuclear Information System (INIS)

    Montero, Juan-Pablo

    1998-01-01

    Increasing interest in the use of marketable permits for pollution control has become evident in recent years. Concern regarding their performance still remains because empirical evidence has shown transaction costs and uncertainty to be significant in past and existing marketable permits programs. In this paper we develop theoretical and numerical models that include transaction costs and uncertainty (in trade approval) to show their effects on market performance (i.e., equilibrium price of permits and trading volume) and aggregate control costs. We also show that in the presence of transaction costs and uncertainty the initial allocation of permits may not be neutral in terms of efficiency. Furthermore, using a numerical model for a hypothetical NO x trading program in which participants have discrete control technology choices, we find that aggregate control costs and the equilibrium price of permits are sensitive to the initial allocation of permits, even for constant marginal transaction costs and certainty

  14. Comparing Cost Of New Supply Chain Designs Under Uncertainty

    DEFF Research Database (Denmark)

    Wæhrens, Brian Vejrum; Kristensen, Jesper; Asmussen, Jesper Normann

    2016-01-01

    Accounting, Operational Modelling and SCM inform decision making for new SCDs. Through four embedded cases, a gap is found between the practice of a global OEM and literature. Results shows complications when assessing SCDs due to limited understanding of the internal activity costs, supply chain dynamics......Companies pursuing improvements to their global supply chain (SC) are challenged with unravelling the true cost of operating with their supply chain design (SCD). This challenge is further intensified as SCs are faced with increasing uncertainty. To rectify this it is investigated how Cost...... and how uncertainties affects the SC cost performance....

  15. Cost-effective conservation of an endangered frog under uncertainty.

    Science.gov (United States)

    Rose, Lucy E; Heard, Geoffrey W; Chee, Yung En; Wintle, Brendan A

    2016-04-01

    How should managers choose among conservation options when resources are scarce and there is uncertainty regarding the effectiveness of actions? Well-developed tools exist for prioritizing areas for one-time and binary actions (e.g., protect vs. not protect), but methods for prioritizing incremental or ongoing actions (such as habitat creation and maintenance) remain uncommon. We devised an approach that combines metapopulation viability and cost-effectiveness analyses to select among alternative conservation actions while accounting for uncertainty. In our study, cost-effectiveness is the ratio between the benefit of an action and its economic cost, where benefit is the change in metapopulation viability. We applied the approach to the case of the endangered growling grass frog (Litoria raniformis), which is threatened by urban development. We extended a Bayesian model to predict metapopulation viability under 9 urbanization and management scenarios and incorporated the full probability distribution of possible outcomes for each scenario into the cost-effectiveness analysis. This allowed us to discern between cost-effective alternatives that were robust to uncertainty and those with a relatively high risk of failure. We found a relatively high risk of extinction following urbanization if the only action was reservation of core habitat; habitat creation actions performed better than enhancement actions; and cost-effectiveness ranking changed depending on the consideration of uncertainty. Our results suggest that creation and maintenance of wetlands dedicated to L. raniformis is the only cost-effective action likely to result in a sufficiently low risk of extinction. To our knowledge we are the first study to use Bayesian metapopulation viability analysis to explicitly incorporate parametric and demographic uncertainty into a cost-effective evaluation of conservation actions. The approach offers guidance to decision makers aiming to achieve cost

  16. Treating acetaminophen overdose: thresholds, costs and uncertainties.

    Science.gov (United States)

    Gosselin, S; Hoffman, R S; Juurlink, D N; Whyte, I; Yarema, M; Caro, J

    2013-03-01

    The United Kingdom's Medicines and Healthcare Products Regulatory Agency (MHRA) modified the indications for N-acetylcysteine therapy of acetaminophen (paracetamol) overdose in September 2012. The new treatment threshold line was lowered to 100 mg/L (662 μmol/L) for a 4 hours acetaminophen concentration from the previous 200 mg/L (1325 μmol/L). This decision has the potential to substantially increase overall costs associated with acetaminophen overdose with unclear benefits from a marginal increase in patients protected from hepatotoxicity, fulminant hepatic failure, death, or transplant. Changing the treatment threshold for acetaminophen overdose also implies that ingestion amounts previously thought not to require acetaminophen concentration measurements would need to be revised. As a result, more individuals will be sent to hospitals in order that everyone with a predicted 4 hours concentration above the 100 mg/L line will have concentrations measured and potentially be treated with N-acetylcysteine. Before others consider adopting this new treatment guideline, formal cost-effectiveness analyses need to be performed to define the appropriate thresholds for referral and treatment.

  17. Introducing nonpoint source transferable quotas in nitrogen trading: The effects of transaction costs and uncertainty.

    Science.gov (United States)

    Zhou, Xiuru; Ye, Weili; Zhang, Bing

    2016-03-01

    Transaction costs and uncertainty are considered to be significant obstacles in the emissions trading market, especially for including nonpoint source in water quality trading. This study develops a nonlinear programming model to simulate how uncertainty and transaction costs affect the performance of point/nonpoint source (PS/NPS) water quality trading in the Lake Tai watershed, China. The results demonstrate that PS/NPS water quality trading is a highly cost-effective instrument for emissions abatement in the Lake Tai watershed, which can save 89.33% on pollution abatement costs compared to trading only between nonpoint sources. However, uncertainty can significantly reduce the cost-effectiveness by reducing trading volume. In addition, transaction costs from bargaining and decision making raise total pollution abatement costs directly and cause the offset system to deviate from the optimal state. While proper investment in monitoring and measuring of nonpoint emissions can decrease uncertainty and save on the total abatement costs. Finally, we show that the dispersed ownership of China's farmland will bring high uncertainty and transaction costs into the PS/NPS offset system, even if the pollution abatement cost is lower than for point sources. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Analysis of automated highway system risks and uncertainties. Volume 5

    Energy Technology Data Exchange (ETDEWEB)

    Sicherman, A.

    1994-10-01

    This volume describes a risk analysis performed to help identify important Automated Highway System (AHS) deployment uncertainties and quantify their effect on costs and benefits for a range of AHS deployment scenarios. The analysis identified a suite of key factors affecting vehicle and roadway costs, capacities and market penetrations for alternative AHS deployment scenarios. A systematic protocol was utilized for obtaining expert judgments of key factor uncertainties in the form of subjective probability percentile assessments. Based on these assessments, probability distributions on vehicle and roadway costs, capacity and market penetration were developed for the different scenarios. The cost/benefit risk methodology and analysis provide insights by showing how uncertainties in key factors translate into uncertainties in summary cost/benefit indices.

  19. Multi-scenario modelling of uncertainty in stochastic chemical systems

    International Nuclear Information System (INIS)

    Evans, R. David; Ricardez-Sandoval, Luis A.

    2014-01-01

    Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo

  20. Is Ignorance Bliss? The Cost of Business Cycle Uncertainty

    NARCIS (Netherlands)

    Brevik, F.; D'Addona, S.

    2013-01-01

    We investigate the cost of business-cycle uncertainty (lack of firm knowledge about the prevailing state of the economy) in a setup where the economy switches between booms and recessions at random intervals. Calibrating an exchange economy model to match the properties of the postwar U.S. data, we

  1. Planning ATES systems under uncertainty

    Science.gov (United States)

    Jaxa-Rozen, Marc; Kwakkel, Jan; Bloemendal, Martin

    2015-04-01

    form a complex adaptive system, for which agent-based modelling provides a useful analysis framework. This study therefore explores the interactions between endogenous ATES adoption processes and the relative performance of different planning schemes, using an agent-based adoption model coupled with a hydrologic model of the subsurface. The models are parameterized to simulate typical operating conditions for ATES systems in a dense urban area. Furthermore, uncertainties relating to planning parameters, adoption processes, and climactic conditions are explicitly considered using exploratory modelling techniques. Results are therefore presented for the performance of different planning policies over a broad range of plausible scenarios.

  2. Relationships for Cost and Uncertainty of Decision Trees

    KAUST Repository

    Chikalov, Igor

    2013-01-01

    This chapter is devoted to the design of new tools for the study of decision trees. These tools are based on dynamic programming approach and need the consideration of subtables of the initial decision table. So this approach is applicable only to relatively small decision tables. The considered tools allow us to compute: 1. Theminimum cost of an approximate decision tree for a given uncertainty value and a cost function. 2. The minimum number of nodes in an exact decision tree whose depth is at most a given value. For the first tool we considered various cost functions such as: depth and average depth of a decision tree and number of nodes (and number of terminal and nonterminal nodes) of a decision tree. The uncertainty of a decision table is equal to the number of unordered pairs of rows with different decisions. The uncertainty of approximate decision tree is equal to the maximum uncertainty of a subtable corresponding to a terminal node of the tree. In addition to the algorithms for such tools we also present experimental results applied to various datasets acquired from UCI ML Repository [4]. © Springer-Verlag Berlin Heidelberg 2013.

  3. Addressing imperfect maintenance modelling uncertainty in unavailability and cost based optimization

    International Nuclear Information System (INIS)

    Sanchez, Ana; Carlos, Sofia; Martorell, Sebastian; Villanueva, Jose F.

    2009-01-01

    Optimization of testing and maintenance activities performed in the different systems of a complex industrial plant is of great interest as the plant availability and economy strongly depend on the maintenance activities planned. Traditionally, two types of models, i.e. deterministic and probabilistic, have been considered to simulate the impact of testing and maintenance activities on equipment unavailability and the cost involved. Both models present uncertainties that are often categorized as either aleatory or epistemic uncertainties. The second group applies when there is limited knowledge on the proper model to represent a problem, and/or the values associated to the model parameters, so the results of the calculation performed with them incorporate uncertainty. This paper addresses the problem of testing and maintenance optimization based on unavailability and cost criteria and considering epistemic uncertainty in the imperfect maintenance modelling. It is framed as a multiple criteria decision making problem where unavailability and cost act as uncertain and conflicting decision criteria. A tolerance interval based approach is used to address uncertainty with regard to effectiveness parameter and imperfect maintenance model embedded within a multiple-objective genetic algorithm. A case of application for a stand-by safety related system of a nuclear power plant is presented. The results obtained in this application show the importance of considering uncertainties in the modelling of imperfect maintenance, as the optimal solutions found are associated with a large uncertainty that influences the final decision making depending on, for example, if the decision maker is risk averse or risk neutral

  4. Addressing imperfect maintenance modelling uncertainty in unavailability and cost based optimization

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez, Ana [Department of Statistics and Operational Research, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain); Carlos, Sofia [Department of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain); Martorell, Sebastian [Department of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain)], E-mail: smartore@iqn.upv.es; Villanueva, Jose F. [Department of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain)

    2009-01-15

    Optimization of testing and maintenance activities performed in the different systems of a complex industrial plant is of great interest as the plant availability and economy strongly depend on the maintenance activities planned. Traditionally, two types of models, i.e. deterministic and probabilistic, have been considered to simulate the impact of testing and maintenance activities on equipment unavailability and the cost involved. Both models present uncertainties that are often categorized as either aleatory or epistemic uncertainties. The second group applies when there is limited knowledge on the proper model to represent a problem, and/or the values associated to the model parameters, so the results of the calculation performed with them incorporate uncertainty. This paper addresses the problem of testing and maintenance optimization based on unavailability and cost criteria and considering epistemic uncertainty in the imperfect maintenance modelling. It is framed as a multiple criteria decision making problem where unavailability and cost act as uncertain and conflicting decision criteria. A tolerance interval based approach is used to address uncertainty with regard to effectiveness parameter and imperfect maintenance model embedded within a multiple-objective genetic algorithm. A case of application for a stand-by safety related system of a nuclear power plant is presented. The results obtained in this application show the importance of considering uncertainties in the modelling of imperfect maintenance, as the optimal solutions found are associated with a large uncertainty that influences the final decision making depending on, for example, if the decision maker is risk averse or risk neutral.

  5. The French biofuels mandates under cost uncertainty - an assessment based on robust optimization

    International Nuclear Information System (INIS)

    Lorne, Daphne; Tchung-Ming, Stephane

    2012-01-01

    This paper investigates the impact of primary energy and technology cost uncertainty on the achievement of renewable and especially biofuel policies - mandates and norms - in France by 2030. A robust optimization technique that allows to deal with uncertainty sets of high dimensionality is implemented in a TIMES-based long-term planning model of the French energy transport and electricity sectors. The energy system costs and potential benefits (GHG emissions abatements, diversification) of the French renewable mandates are assessed within this framework. The results of this systemic analysis highlight how setting norms and mandates allows to reduce the variability of CO 2 emissions reductions and supply mix diversification when the costs of technological progress and prices are uncertain. Beyond that, we discuss the usefulness of robust optimization in complement of other techniques to integrate uncertainty in large-scale energy models. (authors)

  6. Securitization of residential solar photovoltaic assets: Costs, risks and uncertainty

    International Nuclear Information System (INIS)

    Alafita, T.; Pearce, J.M.

    2014-01-01

    Limited access to low-cost financing is an impediment to high-velocity technological diffusion and high grid penetration of solar photovoltaic (PV) technology. Securitization of solar assets provides a potential solution to this problem. This paper assesses the viability of solar asset-backed securities (ABS) as a lower cost financing mechanism and identifies policies that could facilitate implementation of securitization. First, traditional solar financing is examined to provide a baseline for cost comparisons. Next, the securitization process is modeled. The model enables identification of several junctures at which risk and uncertainty influence costs. Next, parameter values are assigned and used to generate cost estimates. Results show that, under reasonable assumptions, securitization of solar power purchase agreements (PPA) can significantly reduce project financing costs, suggesting that securitization is a viable mechanism for improving the financing of PV projects. The clear impediment to the successful launch of a solar ABS is measuring and understanding the riskiness of underlying assets. This study identifies three classes of policy intervention that lower the cost of ABS by reducing risk or by improving the measurement of risk: (i) standardization of contracts and the contracting process, (ii) improved access to contract and equipment performance data, and (iii) geographic diversification. - Highlights: • Limited access to low-cost financing is hampering penetration of solar PV. • Solar asset-backed securities (ABS) provide a low cost financing mechanism. • Results for securitization of solar leases and power purchase agreements (PPA). • Securitization can significantly reduce project financing costs. • Identifies policy intervention that lower cost of ABS by reducing risk

  7. Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation

    Science.gov (United States)

    Schwabe, O.; Shehab, E.; Erkoyuncu, J.

    2015-08-01

    The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis

  8. Stochastic Systems Uncertainty Quantification and Propagation

    CERN Document Server

    Grigoriu, Mircea

    2012-01-01

    Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: ·         A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis   ·          Probabilistic models for random variables an...

  9. Use of probabilistic methods for analysis of cost and duration uncertainties in a decision analysis framework

    International Nuclear Information System (INIS)

    Boak, D.M.; Painton, L.

    1995-01-01

    Probabilistic forecasting techniques have been used in many risk assessment and performance assessment applications on radioactive waste disposal projects such as Yucca Mountain and the Waste Isolation Pilot Plant (WIPP). Probabilistic techniques such as Monte Carlo and Latin Hypercube sampling methods are routinely used to treat uncertainties in physical parameters important in simulating radionuclide transport in a coupled geohydrologic system and assessing the ability of that system to comply with regulatory release limits. However, the use of probabilistic techniques in the treatment of uncertainties in the cost and duration of programmatic alternatives on risk and performance assessment projects is less common. Where significant uncertainties exist and where programmatic decisions must be made despite existing uncertainties, probabilistic techniques may yield important insights into decision options, especially when used in a decision analysis framework and when properly balanced with deterministic analyses. For relatively simple evaluations, these types of probabilistic evaluations can be made using personal computer-based software

  10. Derivative-free optimization under uncertainty applied to costly simulators

    International Nuclear Information System (INIS)

    Pauwels, Benoit

    2016-01-01

    The modeling of complex phenomena encountered in industrial issues can lead to the study of numerical simulation codes. These simulators may require extensive execution time (from hours to days), involve uncertain parameters and even be intrinsically stochastic. Importantly within the context of simulation-based optimization, the derivatives of the outputs with respect to the inputs may be inexistent, inaccessible or too costly to approximate reasonably. This thesis is organized in four chapters. The first chapter discusses the state of the art in derivative-free optimization and uncertainty modeling. The next three chapters introduce three independent - although connected - contributions to the field of derivative-free optimization in the presence of uncertainty. The second chapter addresses the emulation of costly stochastic simulation codes - stochastic in the sense simulations run with the same input parameters may lead to distinct outputs. Such was the matter of the CODESTOCH project carried out at the Summer mathematical research center on scientific computing and its applications (CEMRACS) during the summer of 2013, together with two Ph.D. students from Electricity of France (EDF) and the Atomic Energy and Alternative Energies Commission (CEA). We designed four methods to build emulators for functions whose values are probability density functions. These methods were tested on two toy functions and applied to industrial simulation codes concerned with three complex phenomena: the spatial distribution of molecules in a hydrocarbon system (IFPEN), the life cycle of large electric transformers (EDF) and the repercussions of a hypothetical accidental in a nuclear plant (CEA). Emulation was a preliminary process towards optimization in the first two cases. In the third chapter we consider the influence of inaccurate objective function evaluations on direct search - a classical derivative-free optimization method. In real settings inaccuracy may never vanish

  11. Uncertainty reasoning in expert systems

    Science.gov (United States)

    Kreinovich, Vladik

    1993-01-01

    Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible' into an actual control. To apply this transformation, one must choose appropriate methods for reasoning with uncertainty, i.e., one must: (1) choose the representation for words like 'small', 'big'; (2) choose operations corresponding to 'and' and 'or'; (3) choose a method that transforms the resulting uncertain control recommendations into a precise control strategy. The wrong choice can drastically affect the quality of the resulting control, so the problem of choosing the right procedure is very important. From a mathematical viewpoint these choice problems correspond to non-linear optimization and are therefore extremely difficult. In this project, a new mathematical formalism (based on group theory) is developed that allows us to solve the problem of optimal choice and thus: (1) explain why the existing choices are really the best (in some situations); (2) explain a rather mysterious fact that fuzzy control (i.e., control based on the experts' knowledge) is often better than the control by these same experts; and (3) give choice recommendations for the cases when traditional choices do not work.

  12. Uncertainty in an Interconnected Financial System, Contagion

    OpenAIRE

    Mei Li; Frank Milne; Junfeng Qiu

    2013-01-01

    This paper studies contagion and market freezes caused by uncertainty in financial network structures and provides theoretical guidance for central banks. We establish a formal model to demonstrate that, in a financial system where financial institutions are interconnected, a negative shock to an individual financial institution could spread to other institutions, causing market freezes because of creditors' uncertainty about the financial network structure. Central bank policies to alleviate...

  13. Starling flock networks manage uncertainty in consensus at low cost.

    Directory of Open Access Journals (Sweden)

    George F Young

    Full Text Available Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors. We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks.

  14. Starling Flock Networks Manage Uncertainty in Consensus at Low Cost

    Science.gov (United States)

    Young, George F.; Scardovi, Luca; Cavagna, Andrea; Giardina, Irene; Leonard, Naomi E.

    2013-01-01

    Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors). We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks. PMID:23382667

  15. Photovoltaic System Modeling. Uncertainty and Sensitivity Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, Clifford W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Martin, Curtis E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-08-01

    We report an uncertainty and sensitivity analysis for modeling AC energy from ph otovoltaic systems . Output from a PV system is predicted by a sequence of models. We quantify u ncertainty i n the output of each model using empirical distribution s of each model's residuals. We propagate uncertainty through the sequence of models by sampli ng these distributions to obtain a n empirical distribution of a PV system's output. We consider models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane - of - array irradiance; (2) estimate effective irradiance; (3) predict cell temperature; (4) estimate DC voltage, current and power ; (5) reduce DC power for losses due to inefficient maximum power point tracking or mismatch among modules; and (6) convert DC to AC power . O ur analysis consider s a notional PV system com prising an array of FirstSolar FS - 387 modules and a 250 kW AC inverter ; we use measured irradiance and weather at Albuquerque, NM. We found the uncertainty in PV syste m output to be relatively small, on the order of 1% for daily energy. We found that unce rtainty in the models for POA irradiance and effective irradiance to be the dominant contributors to uncertainty in predicted daily energy. Our analysis indicates that efforts to reduce the uncertainty in PV system output predictions may yield the greatest improvements by focusing on the POA and effective irradiance models.

  16. Historical Analysis of Costs, Risks, and Uncertainties: Moving From a Proprietary to an Open Architected Systems, Open Business Acquisitions Management Approach

    Science.gov (United States)

    2012-04-30

    Service Manager to improve IT staff efficiency, increase application availability, and reduce costs for a global media consulting firm. Retrieved...Using HP Service Manager to integrate environments, increase IT productivity, and reduce user downtime for a leading United States-based

  17. Robustness of dynamic systems with parameter uncertainties

    CERN Document Server

    Balemi, S; Truöl, W

    1992-01-01

    Robust Control is one of the fastest growing and promising areas of research today. In many practical systems there exist uncertainties which have to be considered in the analysis and design of control systems. In the last decade methods were developed for dealing with dynamic systems with unstructured uncertainties such as HOO_ and £I-optimal control. For systems with parameter uncertainties, the seminal paper of V. L. Kharitonov has triggered a large amount of very promising research. An international workshop dealing with all aspects of robust control was successfully organized by S. P. Bhattacharyya and L. H. Keel in San Antonio, Texas, USA in March 1991. We organized the second international workshop in this area in Ascona, Switzer­ land in April 1992. However, this second workshop was restricted to robust control of dynamic systems with parameter uncertainties with the objective to concentrate on some aspects of robust control. This book contains a collection of papers presented at the International W...

  18. Cost benchmarking of railway projects in Europe – dealing with uncertainties in cost estimates

    DEFF Research Database (Denmark)

    Trabo, Inara

    transport infrastructure projects, 9 projects out of 10 came out with budget overruns. As an example of cost overruns is the High Speed 1 in UK, the railway line between London and the British end of the Channel Tunnel. The project was delayed for 11 months and final construction costs were escalated to 80......, Italian projects have productive experiences in constructing and operating high-speed railway lines. The case study for this research is the first Danish high-speed railway line “The New Line Copenhagen-Ringsted”. The project’s aim is to avoid cost overruns and even make lower the final budget outcomes...... results show that the cost values of the projects located in the same geographical zone are slightly the same, e.g. this is explained by the use of the same construction companies presented in the market. However there are still many uncertainties included into received information from the other projects...

  19. Reducing prediction uncertainty of weather controlled systems

    NARCIS (Netherlands)

    Doeswijk, T.G.

    2007-01-01

    In closed agricultural systems the weather acts both as a disturbance and as a resource. By using weather forecasts in control strategies the effects of disturbances can be minimized whereas the resources can be utilized. In this situation weather forecast uncertainty and model based control are

  20. Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models

    Science.gov (United States)

    Errickson, F. C.; Anthoff, D.; Keller, K.

    2016-12-01

    Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty

  1. Systems/cost summary

    International Nuclear Information System (INIS)

    Grand, P.; Danby, G.; Keane, J.; Spiro, J.; Sutter, D.; Cole, F.; Hoyer, E.; Freytag, K.; Burke, R.

    1977-01-01

    The purpose of the meeting was to discuss and develop cost-estimating methods for heavy-ion fusion accelerator systems. The group did not consider that its purpose was to make technical judgements on proposed systems, but to develop methods for making reasonable cost estimates of these systems. Such estimates will, it is hoped, provide material for systems studies, will help in guiding research and development efforts by identifying ''high-leverage'' subsystems (areas that account for a significant part of total system cost and that might be reduced in cost by further technical development) and to begin to provide data to aid in an eventual decision on the optimum type of accelerator for heavy-ion fusion

  2. Sensitivity of LWR fuel cycle costs to uncertainties in detailed thermal cross sections

    International Nuclear Information System (INIS)

    Ryskamp, J.M.; Becker, M.; Harris, D.R.

    1979-01-01

    Cross sections averaged over the thermal energy (< 1 or 2 eV) group have been shown to have an important economic role for light-water reactors. Cost implications of thermal cross section uncertainties at the few-group level were reported earlier. When it has been determined that costs are sensitive to a specific thermal-group cross section, it becomes desirable to determine how specific energy-dependent cross sections influence fuel cycle costs. Multigroup cross-section sensitivity coefficients vary with fuel exposure. By changing the shape of a cross section displayed on a view-tube through an interactive graphics system, one can compute the change in few-group cross section using the exposure dependent sensitivity coefficients. With the changed exposure dependent few-group cross section, a new fuel cycle cost is computed by a sequence of batch depletion, core analysis, and fuel batch cost code modules. Fuel cycle costs are generally most sensitive to cross section uncertainties near the peak of the hardened Maxwellian flux

  3. Uncertainty Analysis of Power Systems Using Collocation

    Science.gov (United States)

    2008-05-01

    sensitivity can be inferred and to construct surrogate models with which interpolation can be used to propagate PDF ?s. These techniques are applied to...with time and use. There is significant environmental interaction in the form of wind and waves; a large wave can partially of fully expose the...Power System We analyze uncertainty in a Simulink model describing the operation of a large pulse load reflecting the power consumption of a rail gun [8

  4. Integrated modelling of risk and uncertainty underlying the selection of cost-effective water quality measures

    NARCIS (Netherlands)

    Brouwer, R.; de Blois, C.

    2008-01-01

    In this paper we present an overview of the most important sources of uncertainty when analysing the least cost way to improve water quality. The estimation of the cost-effectiveness of water quality measures is surrounded by environmental, economic and political uncertainty. These different types

  5. Evaluation of advanced coal gasification combined-cycle systems under uncertainty

    International Nuclear Information System (INIS)

    Frey, H.C.; Rubin, E.S.

    1992-01-01

    Advanced integrated gasification combined cycle (IGCC) systems have not been commercially demonstrated, and uncertainties remain regarding their commercial-scale performance and cost. Therefore, a probabilistic evaluation method has been developed and applied to explicitly consider these uncertainties. The insights afforded by this method are illustrated for an IGCC design featuring a fixed-bed gasifier and a hot gas cleanup system. Detailed case studies are conducted to characterize uncertainties in key measures of process performance and cost, evaluate design trade-offs under uncertainty, identify research priorities, evaluate the potential benefits of additional research, compare results for different uncertainty assumptions, and compare the advanced IGCC system to a conventional system under uncertainty. The implications of probabilistic results for research planning and technology selection are discussed in this paper

  6. Energy supply planning in Iran by using fuzzy linear programming approach (regarding uncertainties of investment costs)

    International Nuclear Information System (INIS)

    Sadeghi, Mehdi; Mirshojaeian Hosseini, Hossein

    2006-01-01

    For many years, energy models have been used in developed or developing countries to satisfy different needs in energy planning. One of major problems against energy planning and consequently energy models is uncertainty, spread in different economic, political and legal dimensions of energy planning. Confronting uncertainty, energy planners have often used two well-known strategies. The first strategy is stochastic programming, in which energy system planners define different scenarios and apply an explicit probability of occurrence to each scenario. The second strategy is Minimax Regret strategy that minimizes regrets of different decisions made in energy planning. Although these strategies have been used extensively, they could not flexibly and effectively deal with the uncertainties caused by fuzziness. 'Fuzzy Linear Programming (FLP)' is a strategy that can take fuzziness into account. This paper tries to demonstrate the method of application of FLP for optimization of supply energy system in Iran, as a case study. The used FLP model comprises fuzzy coefficients for investment costs. Following the mentioned purpose, it is realized that FLP is an easy and flexible approach that can be a serious competitor for other confronting uncertainties approaches, i.e. stochastic and Minimax Regret strategies. (author)

  7. Uncertainty assessment for accelerator-driven systems

    International Nuclear Information System (INIS)

    Finck, P. J.; Gomes, I.; Micklich, B.; Palmiotti, G.

    1999-01-01

    The concept of a subcritical system driven by an external source of neutrons provided by an accelerator ADS (Accelerator Driver System) has been recently revived and is becoming more popular in the world technical community with active programs in Europe, Russia, Japan, and the U.S. A general consensus has been reached in adopting for the subcritical component a fast spectrum liquid metal cooled configuration. Both a lead-bismuth eutectic, sodium and gas are being considered as a coolant; each has advantages and disadvantages. The major expected advantage is that subcriticality avoids reactivity induced transients. The potentially large subcriticality margin also should allow for the introduction of very significant quantities of waste products (minor Actinides and Fission Products) which negatively impact the safety characteristics of standard cores. In the U.S. these arguments are the basis for the development of the Accelerator Transmutation of Waste (ATW), which has significant potential in reducing nuclear waste levels. Up to now, neutronic calculations have not attached uncertainties on the values of the main nuclear integral parameters that characterize the system. Many of these parameters (e.g., degree of subcriticality) are crucial to demonstrate the validity and feasibility of this concept. In this paper we will consider uncertainties related to nuclear data only. The present knowledge of the cross sections of many isotopes that are not usually utilized in existing reactors (like Bi, Pb-207, Pb-208, and also Minor Actinides and Fission Products) suggests that uncertainties in the integral parameters will be significantly larger than for conventional reactor systems, and this raises concerns on the neutronic performance of those systems

  8. Uncertainty in air quality observations using low-cost sensors

    Science.gov (United States)

    Castell, Nuria; Dauge, Franck R.; Dongol, Rozina; Vogt, Matthias; Schneider, Philipp

    2016-04-01

    Air pollution poses a threat to human health, and the WHO has classified air pollution as the world's largest single environmental health risk. In Europe, the majority of the population lives in areas where air quality levels frequently exceed WHO's ambient air quality guidelines. The emergence of low-cost, user-friendly and very compact air pollution platforms allowing observations at high spatial resolution in near real-time, provides us with new opportunities to simultaneously enhance existing monitoring systems as well as enable citizens to engage in more active environmental monitoring (citizen science). However the data sets generated by low-cost sensors show often questionable data quality. For many sensors, neither their error characteristics nor how their measurement capability holds up over time or through a range of environmental conditions, have been evaluated. We have conducted an exhaustive evaluation of the commercial low-cost platform AQMesh (measuring NO, NO2, CO, O3, PM10 and PM2.5) in laboratory and in real-world conditions in the city of Oslo (Norway). Co-locations in field of 24 platforms were conducted over a 6 month period (April to September 2015) allowing to characterize the temporal variability in the performance. Additionally, the field performance included the characterization on different monitoring urban monitoring sites characteristic of both traffic and background conditions. All the evaluations have been conducted against CEN reference method analyzers maintained according to the Norwegian National Reference Laboratory quality system. The results show clearly that a good performance in laboratory does not imply similar performance in real-world outdoor conditions. Moreover, laboratory calibration is not suitable for subsequent measurements in urban environments. In order to reduce the errors, sensors require on-site field calibration. Even after such field calibration, the platforms show a significant variability in the performance

  9. Model Uncertainty for Bilinear Hysteric Systems

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Thoft-Christensen, Palle

    density functions, Veneziano [2]. In general, model uncertainty is the uncertainty connected with mathematical modelling of the physical reality. When structural reliability analysis is related to the concept of a failure surface (or limit state surface) in the n-dimension basic variable space then model......In structural reliability analysis at least three types of uncertainty must be considered, namely physical uncertainty, statistical uncertainty, and model uncertainty (see e.g. Thoft-Christensen & Baker [1]). The physical uncertainty is usually modelled by a number of basic variables by predictive...

  10. Cost implications of uncertainty in CO2 storage resource estimates: A review

    Science.gov (United States)

    Anderson, Steven T.

    2017-01-01

    Carbon capture from stationary sources and geologic storage of carbon dioxide (CO2) is an important option to include in strategies to mitigate greenhouse gas emissions. However, the potential costs of commercial-scale CO2 storage are not well constrained, stemming from the inherent uncertainty in storage resource estimates coupled with a lack of detailed estimates of the infrastructure needed to access those resources. Storage resource estimates are highly dependent on storage efficiency values or storage coefficients, which are calculated based on ranges of uncertain geological and physical reservoir parameters. If dynamic factors (such as variability in storage efficiencies, pressure interference, and acceptable injection rates over time), reservoir pressure limitations, boundaries on migration of CO2, consideration of closed or semi-closed saline reservoir systems, and other possible constraints on the technically accessible CO2 storage resource (TASR) are accounted for, it is likely that only a fraction of the TASR could be available without incurring significant additional costs. Although storage resource estimates typically assume that any issues with pressure buildup due to CO2 injection will be mitigated by reservoir pressure management, estimates of the costs of CO2 storage generally do not include the costs of active pressure management. Production of saline waters (brines) could be essential to increasing the dynamic storage capacity of most reservoirs, but including the costs of this critical method of reservoir pressure management could increase current estimates of the costs of CO2 storage by two times, or more. Even without considering the implications for reservoir pressure management, geologic uncertainty can significantly impact CO2 storage capacities and costs, and contribute to uncertainty in carbon capture and storage (CCS) systems. Given the current state of available information and the scarcity of (data from) long-term commercial-scale CO2

  11. Automatic Voltage Control (AVC) System under Uncertainty from Wind Power

    DEFF Research Database (Denmark)

    Qin, Nan; Abildgaard, Hans; Flynn, Damian

    2016-01-01

    An automatic voltage control (AVC) system maintains the voltage profile of a power system in an acceptable range and minimizes the operational cost by coordinating the regulation of controllable components. Typically, all of the parameters in the optimization problem are assumed to be certain....... The proposed method improves the performance and the robustness of a scenario based approach by estimating the potential voltage variations due to fluctuating wind power production, and introduces a voltage margin to protect the decision against uncertainty for each scenario. The effectiveness of the proposed...

  12. Change and uncertainty in quantum systems

    International Nuclear Information System (INIS)

    Franson, J.D.

    1996-01-01

    A simple inequality shows that any change in the expectation value of an observable quantity must be associated with some degree of uncertainty. This inequality is often more restrictive than the Heisenberg uncertainty principle. copyright 1996 The American Physical Society

  13. Limitations of acceptability curves for presenting uncertainty in cost-effectiveness analysis

    NARCIS (Netherlands)

    Groot Koerkamp, Bas; Hunink, M. G. Myriam; Stijnen, Theo; Hammitt, James K.; Kuntz, Karen M.; Weinstein, Milton C.

    2007-01-01

    Clinical journals increasingly illustrate uncertainty about the cost and effect of health care interventions using cost-effectiveness acceptability curves (CEACs). CEACs present the probability that each competing alternative is optimal for a range of values of the cost-effectiveness threshold. The

  14. Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties

    Directory of Open Access Journals (Sweden)

    Hadis Moradi

    2017-09-01

    Full Text Available A novel method for a day-ahead optimal operation of a hybrid microgrid system including fuel cells, photovoltaic arrays, a microturbine, and battery energy storage in order to fulfill the required load demand is presented in this paper. In the proposed system, the microgrid has access to the main utility grid in order to exchange power when required. Available municipal waste is utilized to produce the hydrogen required for running the fuel cells, and natural gas will be used as the backup source. In the proposed method, an energy scheduling is introduced to optimize the generating unit power outputs for the next day, as well as the power flow with the main grid, in order to minimize the operational costs and produced greenhouse gases emissions. The nature of renewable energies and electric power consumption is both intermittent and unpredictable, and the uncertainty related to the PV array power generation and power consumption has been considered in the next-day energy scheduling. In order to model uncertainties, some scenarios are produced according to Monte Carlo (MC simulations, and microgrid optimal energy scheduling is analyzed under the generated scenarios. In addition, various scenarios created by MC simulations are applied in order to solve unit commitment (UC problems. The microgrid’s day-ahead operation and emission costs are considered as the objective functions, and the particle swarm optimization algorithm is employed to solve the optimization problem. Overall, the proposed model is capable of minimizing the system costs, as well as the unfavorable influence of uncertainties on the microgrid’s profit, by generating different scenarios.

  15. Intrinsic Uncertainties in Modeling Complex Systems.

    Energy Technology Data Exchange (ETDEWEB)

    Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.

    2014-09-01

    Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project #170979, entitled "Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties", which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.

  16. Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming

    DEFF Research Database (Denmark)

    Ren, Jingzheng; Dong, Liang; Sun, Lu

    2015-01-01

    The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered...... model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties...

  17. Approaches for Managing Uncertainty in Learning Management Systems

    OpenAIRE

    Radwan, Nouran M.; Senousy, M. Badr; Riad, Alaa El Din M.

    2016-01-01

    The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and imprecise knowledge. Different uncertainty types which are imprecision, vagueness, ambiguity, and inconsistence need different handling models. Uncertain knowledge representation and analysis is an essential issue.

  18. Estimating the costs of nuclear power: benchmarks and uncertainties

    International Nuclear Information System (INIS)

    Leveque, Francois

    2013-05-01

    The debate on this topic is fairly confusing. Some present electricity production using nuclear power as an affordable solution, others maintain it is too expensive. These widely divergent views prompt fears among consumers and voters that they are being manipulated: each side is just defending its own interests and the true cost of nuclear power is being concealed. Companies and non-government organizations certainly adopt whatever position suits them best. But at the same time, the notion of just one 'true' cost is misleading. As we shall see in this paper there is no such thing as the cost of nuclear power: we must reason in terms of costs and draw a distinction between a private cost and a social cost. The private cost is what an operator examines before deciding whether it is opportune to build a new nuclear power station. This cost varies between different investors, particularly as a function of their attitude to risks. On the other hand the social cost weighs on society, which may take into account the risk of proliferation, or the benefits of avoiding carbon-dioxide emissions, among others. The cost of actually building new plant differs from one country to the next. So deciding whether nuclear power is profitable or not, a benefit for society or not, does not involve determining the real cost, but rather compiling data, developing methods and formulating hypotheses. It is not as easy as inundating the general public with contradictory figures, but it is a more effective way of casting light on economic decisions by industry and government. Without evaluating the costs it is impossible to establish the cost price, required to compare electricity production using nuclear power and rival technologies. Would it be preferable to build a gas-powered plant, a nuclear reactor or a wind farm? Which technology yields the lowest cost per KWh? Under what conditions - financial terms, regulatory framework, carbon pricing - will private investors see an adequate return

  19. Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: An Irish case study

    International Nuclear Information System (INIS)

    Farrell, Niall; Donoghue, Cathal O’; Morrissey, Karyn

    2015-01-01

    Wave Energy Conversion (WEC) devices are at a pre-commercial stage of development with feasibility studies sensitive to uncertainties surrounding assumed input costs. This may affect decision making. This paper analyses the impact these uncertainties may have on investor, developer and policymaker decisions using an Irish case study. Calibrated to data present in the literature, a probabilistic methodology is shown to be an effective means to carry this out. Value at Risk (VaR) and Conditional Value at Risk (CVaR) metrics are used to quantify the certainty of achieving a given cost or return on investment. We analyse the certainty of financial return provided by the proposed Irish Feed-in Tariff (FiT) policy. The influence of cost reduction through bulk discount is also discussed, with cost reduction targets for developers identified. Uncertainty is found to have a greater impact on the profitability of smaller installations and those subject to lower rates of cost reduction. This paper emphasises that a premium is required to account for cost uncertainty when setting FiT rates. By quantifying uncertainty, a means to specify an efficient premium is presented. - Highlights: • Probabilistic model quantifies uncertainty for wave energy feasibility analyses. • Methodology presented and applied to an Irish case study. • A feed-in tariff premium of 3–4 c/kWh required to account for cost uncertainty. • Sensitivity of uncertainty and cost to rates of technological change analysed. • Use of probabilistic model for investors and developers also demonstrated

  20. Using performance indicators to reduce cost uncertainty of China's CO2 mitigation goals

    International Nuclear Information System (INIS)

    Xu, Yuan

    2013-01-01

    Goals on absolute emissions and intensity play key roles in CO 2 mitigation. However, like cap-and-trade policies with price uncertainty, they suffer from significant uncertainty in abatement costs. This article examines whether an indicator could be established to complement CO 2 mitigation goals and help reduce cost uncertainty with a particular focus on China. Performance indicators on CO 2 emissions per unit of energy consumption could satisfy three criteria: compared with the mitigation goals, (i) they are more closely associated with active mitigation efforts and (ii) their baselines have more stable projections from historical trajectories. (iii) Their abatement costs are generally higher than other mitigation methods, particularly energy efficiency and conservation. Performance indicators could be used in the following way: if a CO 2 goal on absolute emissions or intensity is attained, the performance indicator should still reach a lower threshold as a cost floor. If the goal cannot be attained, an upper performance threshold should be achieved as a cost ceiling. The narrower cost uncertainty may encourage wider and greater mitigation efforts. - Highlights: ► CO 2 emissions per unit of energy consumption could act as performance indicators. ► Performance indicators are more closely related to active mitigation activities. ► Performance indicators have more stable historical trajectories. ► Abatement costs are higher for performance indicators than for other activities. ► Performance thresholds could reduce the cost uncertainty of CO 2 mitigation goals.

  1. Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)

    Science.gov (United States)

    2011-12-01

    Linking the BBN to Existing Cost Estimation Models 38 3.8 Mapping BBN Outputs to the COCOMO Inputs 38 3.9 Monte Carlo Simulation in the Cost...been particularly helpful at various stages of our research, including Michael Cullen , Rob Flowe, Jim Judy and Keith Miller. The same is so for Adam...The method described in this report synthesizes scenario building, Bayesian Belief Network (BBN) modeling, and Monte Carlo simulation into an

  2. Revised cost savings estimate with uncertainty for enhanced sludge washing of underground storage tank waste

    Energy Technology Data Exchange (ETDEWEB)

    DeMuth, S.

    1998-09-01

    Enhanced Sludge Washing (ESW) has been selected to reduce the amount of sludge-based underground storage tank (UST) high-level waste at the Hanford site. During the past several years, studies have been conducted to determine the cost savings derived from the implementation of ESW. The tank waste inventory and ESW performance continues to be revised as characterization and development efforts advance. This study provides a new cost savings estimate based upon the most recent inventory and ESW performance revisions, and includes an estimate of the associated cost uncertainty. Whereas the author`s previous cost savings estimates for ESW were compared against no sludge washing, this study assumes the baseline to be simple water washing which more accurately reflects the retrieval activity along. The revised ESW cost savings estimate for all UST waste at Hanford is $6.1 B {+-} $1.3 B within 95% confidence. This is based upon capital and operating cost savings, but does not include development costs. The development costs are assumed negligible since they should be at least an order of magnitude less than the savings. The overall cost savings uncertainty was derived from process performance uncertainties and baseline remediation cost uncertainties, as determined by the author`s engineering judgment.

  3. Uncertainties

    Indian Academy of Sciences (India)

    The imperfect understanding of some of the processes and physics in the carbon cycle and chemistry models generate uncertainties in the conversion of emissions to concentration. To reflect this uncertainty in the climate scenarios, the use of AOGCMs that explicitly simulate the carbon cycle and chemistry of all the ...

  4. Which Costs Matter? Costs Included in Economic Evaluation and their Impact on Decision Uncertainty for Stable Coronary Artery Disease.

    Science.gov (United States)

    Lomas, James; Asaria, Miqdad; Bojke, Laura; Gale, Chris P; Richardson, Gerry; Walker, Simon

    2018-02-14

    Variation exists in the resource categories included in economic evaluations, and National Institute for Health and Care Excellence (NICE) guidance suggests the inclusion only of costs related to the index condition or intervention. However, there is a growing consensus that all healthcare costs should be included in economic evaluations for Health Technology Assessments (HTAs), particularly those related to extended years of life. We aimed to quantify the impact of a range of cost categories on the adoption decision about a hypothetical intervention, and uncertainty around that decision, for stable coronary artery disease (SCAD) based on a dataset comprising 94,966 patients. Three costing scenarios were considered: coronary heart disease (CHD) costs only, cardiovascular disease (CVD) costs and all costs. The first two illustrate different interpretations of what might be regarded as related costs. Employing a 20-year time horizon, the highest mean expected incremental cost was when all costs were included (£2468) and the lowest when CVD costs only were included (£2377). The probability of the treatment being cost effective, estimating health opportunity costs using a ratio of £30,000 per quality-adjusted life-year (QALY), was different for each of the CHD (70%) costs, CVD costs (73%) and all costs (56%) scenarios. The results concern a hypothetical intervention and are illustrative only, as such they cannot necessarily be generalised to all interventions and diseases. Cost categories included in an economic evaluation of SCAD impact on estimates of both cost effectiveness and decision uncertainty. With an aging and co-morbid population, the inclusion of all healthcare costs may have important ramifications for the selection of healthcare provision on economic grounds.

  5. Advice under uncertainty in the marine system

    NARCIS (Netherlands)

    Dankel, D.J.; Aps, R.; Padda, G.; Rockmann, C.; Sluijs, van der J.P.; Wilson, D.C.; Degnbol, P.

    2012-01-01

    There is some uncertainty in the fisheries science–policy interface. Although progress has been made towards more transparency and participation in fisheries science in ICES Areas, routine use of state-of-the-art quantitative and qualitative tools to address uncertainty systematically is still

  6. Optimal Time to Invest Energy Storage System under Uncertainty Conditions

    Directory of Open Access Journals (Sweden)

    Yongma Moon

    2014-04-01

    Full Text Available This paper proposes a model to determine the optimal investment time for energy storage systems (ESSs in a price arbitrage trade application under conditions of uncertainty over future profits. The adoption of ESSs can generate profits from price arbitrage trade, which are uncertain because the future marginal prices of electricity will change depending on supply and demand. In addition, since the investment is optional, an investor can delay adopting an ESS until it becomes profitable, and can decide the optimal time. Thus, when we evaluate this investment, we need to incorporate the investor’s option which is not captured by traditional evaluation methods. In order to incorporate these aspects, we applied real option theory to our proposed model, which provides an optimal investment threshold. Our results concerning the optimal time to invest show that if future profits that are expected to be obtained from arbitrage trade become more uncertain, an investor needs to wait longer to invest. Also, improvement in efficiency of ESSs can reduce the uncertainty of arbitrage profit and, consequently, the reduced uncertainty enables earlier ESS investment, even for the same power capacity. Besides, when a higher rate of profits is expected and ESS costs are higher, an investor needs to wait longer. Also, by comparing a widely used net present value model to our real option model, we show that the net present value method underestimates the value for ESS investment and misleads the investor to make an investment earlier.

  7. Quantifying uncertainty in LCA-modelling of waste management systems

    DEFF Research Database (Denmark)

    Clavreul, Julie; Guyonnet, D.; Christensen, Thomas Højlund

    2012-01-01

    Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present...... the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining...

  8. Planning uncertainties, market risks and new environmental choices: Winning least cost planning combinations

    International Nuclear Information System (INIS)

    Violette, D.; Lang, C.

    1990-01-01

    Utility demand and supply-side planners will face new challenges from environmental regulations. Under current proposals, every ton of pollutant will have a cost to utilities, not just the tons that put them over the allowable limit. Planners will have to account for these new costs. To do this, planners need to start tracking emissions implementation actions today, and begin strategies for future regulatory changes. Current legislative proposals include a tax on the carbon content of fuels to curb emissions of greenhouse gases and substantial reductions in sulfur dioxide and nitrogen oxide emissions. The important issue for planners is the flexible compliance requirements within these regulatory changes. The acid rain proposals, for example, include a market-based emissions trading system for emissions allowances. Whenever there is a competitive market, there are market risks, and potential winners and losers. Utilities need to be prepared to analyze and mitigate these risks. Integrated least cost planing is one way a utility will have to meet this challenge. Planning involves uncertainty and risk. The wide array of compliance choices create countless combinations of strategies for utilities to comply with the new emissions regulations. This paper discusses new compliance strategies, demand-side management (DSM) as a compliance strategy, solutions to DSM traps, and the compliance strategy game

  9. Uncertainties

    Indian Academy of Sciences (India)

    To reflect this uncertainty in the climate scenarios, the use of AOGCMs that explicitly simulate the carbon cycle and chemistry of all the substances are needed. The Hadley Centre has developed a version of the climate model that allows the effect of climate change on the carbon cycle and its feedback into climate, to be ...

  10. Using interpolation to estimate system uncertainty in gene expression experiments.

    Directory of Open Access Journals (Sweden)

    Lee J Falin

    Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.

  11. Model Uncertainty for Bilinear Hysteretic Systems

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Thoft-Christensen, Palle

    1984-01-01

    is related to the concept of a failure surface (or limit state surface) in the n-dimensional basic variable space then model uncertainty is at least due to the neglected variables, the modelling of the failure surface and the computational technique used. A more precise definition is given in section 2...

  12. Advice under uncertainty in the marine system

    DEFF Research Database (Denmark)

    Dankel, Dorothy J.; Aps, Robert; Padda, Gurpreet

    2012-01-01

    lacking. Fisheries science that gives advice to policy-making is plagued by uncertainties; the stakes of the policies are high and value-laden and need therefore to be treated as an example of “post-normal science” (PNS). To achieve robust governance, understanding of the characteristics and implications...

  13. How to deal with climate change uncertainty in the planning of engineering systems

    Science.gov (United States)

    Spackova, Olga; Dittes, Beatrice; Straub, Daniel

    2016-04-01

    The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.

  14. Estimating the uncertainty of damage costs of pollution: A simple transparent method and typical results

    International Nuclear Information System (INIS)

    Spadaro, Joseph V.; Rabl, Ari

    2008-01-01

    Whereas the uncertainty of environmental impacts and damage costs is usually estimated by means of a Monte Carlo calculation, this paper shows that most (and in many cases all) of the uncertainty calculation involves products and/or sums of products and can be accomplished with an analytic solution which is simple and transparent. We present our own assessment of the component uncertainties and calculate the total uncertainty for the impacts and damage costs of the classical air pollutants; results for a Monte Carlo calculation for the dispersion part are also shown. The distribution of the damage costs is approximately lognormal and can be characterized in terms of geometric mean μ g and geometric standard deviation σ g , implying that the confidence interval is multiplicative. We find that for the classical air pollutants σ g is approximately 3 and the 68% confidence interval is [μ g / σ g , μ g σ g ]. Because the lognormal distribution is highly skewed for large σ g , the median is significantly smaller than the mean. We also consider the case where several lognormally distributed damage costs are added, for example to obtain the total damage cost due to all the air pollutants emitted by a power plant, and we find that the relative error of the sum can be significantly smaller than the relative errors of the summands. Even though the distribution for such sums is not exactly lognormal, we present a simple lognormal approximation that is quite adequate for most applications

  15. Japanese Cost Accounting Systems - analysis of the cost accounting systems of the Japanese cost accounting standard

    OpenAIRE

    Peter, Winter

    2005-01-01

    This paper aims at providing an insight into Japanese cost accounting. Firstly, the development of cost accounting in Japan is delineated. Subsequently, the cost accounting systems codified in the Japanese cost accounting standard are analysed based on the classification according to Hoitsch/Schmitz. Lastly, a critical appraisal of the cost accounting systems of the Japanese cost accounting standard as well as a comparison to German and American cost accounting systems are conducted.

  16. Using cost-benefit concepts in design floods improves communication of uncertainty

    Science.gov (United States)

    Ganora, Daniele; Botto, Anna; Laio, Francesco; Claps, Pierluigi

    2017-04-01

    Flood frequency analysis, i.e. the study of the relationships between the magnitude and the rarity of high flows in a river, is the usual procedure adopted to assess flood hazard, preliminary to the plan/design of flood protection measures. It grounds on the fit of a probability distribution to the peak discharge values recorded in gauging stations and the final estimates over a region are thus affected by uncertainty, due to the limited sample availability and of the possible alternatives in terms of the probabilistic model and the parameter estimation methods used. In the last decade, the scientific community dealt with this issue by developing a number of methods to quantify such uncertainty components. Usually, uncertainty is visually represented through confidence bands, which are easy to understand, but are not yet demonstrated to be useful for design purposes: they usually disorient decision makers, as the design flood is no longer univocally defined, making the decision process undetermined. These considerations motivated the development of the uncertainty-compliant design flood estimator (UNCODE) procedure (Botto et al., 2014) that allows one to select meaningful flood design values accounting for the associated uncertainty by considering additional constraints based on cost-benefit criteria. This method suggests an explicit multiplication factor that corrects the traditional (without uncertainty) design flood estimates to incorporate the effects of uncertainty in the estimate at the same safety level. Even though the UNCODE method was developed for design purposes, it can represent a powerful and robust tool to help clarifying the effects of the uncertainty in statistical estimation. As the process produces increased design flood estimates, this outcome demonstrates how uncertainty leads to more expensive flood protection measures, or insufficiency of current defenses. Moreover, the UNCODE approach can be used to assess the "value" of data, as the costs

  17. Sensitivity of nuclear fuel cycle cost to uncertainties in nuclear data

    International Nuclear Information System (INIS)

    Harris, D.R.; Becker, M.; Parvez, A.; Ryskamp, J.M.

    1979-01-01

    A sensitivity analysis system is developed for assessing the economic implications of uncertainties in nuclear data and related computational methods for light water power reactors. Results of the sensitivity analysis indicate directions for worthwhile improvements in data and methods. Benefits from improvements in data and methods are related to reduction of margins provided by designers to ensure meeting reactor and fuel objectives. Sensitivity analyses are carried out using the batch depletion code FASTCELL, the core analysis code FASTCORE, and the reactor cost code COSTR. FASTCELL depletes a cell using methods comparable to industry cell codes except for a few-group treatment of cell flux distribution. FASTCORE is used with the Haling strategy of fixed power sharing among batches in the core. COSTR computes costs using components and techniques as in industry costing codes, except that COSTR uses fixed payment schedules. Sensitivity analyses are carried out for large commercial boiling and pressurized water reactors. Each few-group nuclear parameter is changed, and initial enrichment is also changed so as to keep the end-of-cycle core multiplication factor unchanged, i.e., to preserve cycle time at the demand power. Sensitivities of equilibrium fuel cycle cost are determined with respect to approx. 300 few-group nuclear parameters, both for a normal fuel cycle and for a throwaway fuel cycle. Particularly large dollar implications are found for thermal and resonance range cross sections in fissile and fertile materials. Sensitivities constrained by adjustment of fission neutron yield so as to preserve agreement with zero exposure integral data also are computed

  18. Incorporating uncertainty of management costs in sensitivity analyses of matrix population models.

    Science.gov (United States)

    Salomon, Yacov; McCarthy, Michael A; Taylor, Peter; Wintle, Brendan A

    2013-02-01

    The importance of accounting for economic costs when making environmental-management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population-management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost-efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on

  19. Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

    Science.gov (United States)

    McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

    2015-01-01

    Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding

  20. Cost reduction through system integration

    International Nuclear Information System (INIS)

    Helsing, P.

    1994-01-01

    In resent years cost reduction has been a key issue in the petroleum industry. Several findings are not economically attractive at the current cost level, and for this and other reasons some of the major oil companies require the suppliers to have implemented a cost reduction programme to prequalify for projects. The present paper addresses cost reduction through system design and integration in both product development and working methods. This is to be obtained by the combination of contracts by reducing unnecessary coordination and allow re-use of proven interface designs, improve subsystem integration by ''top down'' system design, and improve communication and exchange of experience. 3 figs

  1. Modeling of uncertainty in atmospheric transport system using hybrid method

    International Nuclear Information System (INIS)

    Pandey, M.; Ranade, Ashok; Brij Kumar; Datta, D.

    2012-01-01

    Atmospheric dispersion models are routinely used at nuclear and chemical plants to estimate exposure to the members of the public and occupational workers due to release of hazardous contaminants into the atmosphere. Atmospheric dispersion is a stochastic phenomenon and in general, the concentration of the contaminant estimated at a given time and at a predetermined location downwind of a source cannot be predicted precisely. Uncertainty in atmospheric dispersion model predictions is associated with: 'data' or 'parameter' uncertainty resulting from errors in the data used to execute and evaluate the model, uncertainties in empirical model parameters, and initial and boundary conditions; 'model' or 'structural' uncertainty arising from inaccurate treatment of dynamical and chemical processes, approximate numerical solutions, and internal model errors; and 'stochastic' uncertainty, which results from the turbulent nature of the atmosphere as well as from unpredictability of human activities related to emissions, The possibility theory based on fuzzy measure has been proposed in recent years as an alternative approach to address knowledge uncertainty of a model in situations where available information is too vague to represent the parameters statistically. The paper presents a novel approach (called Hybrid Method) to model knowledge uncertainty in a physical system by a combination of probabilistic and possibilistic representation of parametric uncertainties. As a case study, the proposed approach is applied for estimating the ground level concentration of hazardous contaminant in air due to atmospheric releases through the stack (chimney) of a nuclear plant. The application illustrates the potential of the proposed approach. (author)

  2. Price setting under cost uncertainty and menu costs - the case of the Danish petrol market

    International Nuclear Information System (INIS)

    Stampe Christensen, M.

    1994-01-01

    This paper derives the optimal pricing policy for a firm facing menu costs and stochastic production cost. The pricing policy is a boundary pricing policy and numerical comparative static analysis shows how exogenous parameters - the drift and variance of the production cost, the discount factor and the menu costs - affect the boundaries. Analyzing daily data for the Danish petrol price illustrates that a boundary pricing policy indeed has been followed for the period 1988-1992, with occasional shifts in both the desired mark-up and more importantly in the width of the bounds. While the theoretical model can say nothing of the shifts in desired mark-up, changes in the width of the bounds are found to be consistent with the implications of the model. (au)

  3. External costs of PM2.5 pollution in Beijing, China: Uncertainty analysis of multiple health impacts and costs

    DEFF Research Database (Denmark)

    Hao, Yin; Pizzol, Massimo; Xu, Linyu

    2017-01-01

    Some cities in China are facing serious air pollution problems including high concentrations of particles, SO2 and NOx. Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society....... The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well...... as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both...

  4. A smart Monte Carlo procedure for production costing and uncertainty analysis

    International Nuclear Information System (INIS)

    Parker, C.; Stremel, J.

    1996-01-01

    Electric utilities using chronological production costing models to decide whether to buy or sell power over the next week or next few weeks need to determine potential profits or losses under a number of uncertainties. A large amount of money can be at stake--often $100,000 a day or more--and one party of the sale must always take on the risk. In the case of fixed price ($/MWh) contracts, the seller accepts the risk. In the case of cost plus contracts, the buyer must accept the risk. So, modeling uncertainty and understanding the risk accurately can improve the competitive edge of the user. This paper investigates an efficient procedure for representing risks and costs from capacity outages. Typically, production costing models use an algorithm based on some form of random number generator to select resources as available or on outage. These algorithms allow experiments to be repeated and gains and losses to be observed in a short time. The authors perform several experiments to examine the capability of three unit outage selection methods and measures their results. Specifically, a brute force Monte Carlo procedure, a Monte Carlo procedure with Latin Hypercube sampling, and a Smart Monte Carlo procedure with cost stratification and directed sampling are examined

  5. Uncertainty and sensitivity analysis for photovoltaic system modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, Clifford W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pohl, Andrew Phillip [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jordan, Dirk [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.

  6. On the role of budget sufficiency, cost efficiency, and uncertainty in species management

    Science.gov (United States)

    van der Burg, Max Post; Bly, Bartholomew B.; Vercauteren, Tammy; Grand, James B.; Tyre, Andrew J.

    2014-01-01

    Many conservation planning frameworks rely on the assumption that one should prioritize locations for management actions based on the highest predicted conservation value (i.e., abundance, occupancy). This strategy may underperform relative to the expected outcome if one is working with a limited budget or the predicted responses are uncertain. Yet, cost and tolerance to uncertainty rarely become part of species management plans. We used field data and predictive models to simulate a decision problem involving western burrowing owls (Athene cunicularia hypugaea) using prairie dog colonies (Cynomys ludovicianus) in western Nebraska. We considered 2 species management strategies: one maximized abundance and the other maximized abundance in a cost-efficient way. We then used heuristic decision algorithms to compare the 2 strategies in terms of how well they met a hypothetical conservation objective. Finally, we performed an info-gap decision analysis to determine how these strategies performed under different budget constraints and uncertainty about owl response. Our results suggested that when budgets were sufficient to manage all sites, the maximizing strategy was optimal and suggested investing more in expensive actions. This pattern persisted for restricted budgets up to approximately 50% of the sufficient budget. Below this budget, the cost-efficient strategy was optimal and suggested investing in cheaper actions. When uncertainty in the expected responses was introduced, the strategy that maximized abundance remained robust under a sufficient budget. Reducing the budget induced a slight trade-off between expected performance and robustness, which suggested that the most robust strategy depended both on one's budget and tolerance to uncertainty. Our results suggest that wildlife managers should explicitly account for budget limitations and be realistic about their expected levels of performance.

  7. Modeling multibody systems with uncertainties. Part II: Numerical applications

    Energy Technology Data Exchange (ETDEWEB)

    Sandu, Corina, E-mail: csandu@vt.edu; Sandu, Adrian; Ahmadian, Mehdi [Virginia Polytechnic Institute and State University, Mechanical Engineering Department (United States)

    2006-04-15

    This study applies generalized polynomial chaos theory to model complex nonlinear multibody dynamic systems operating in the presence of parametric and external uncertainty. Theoretical and computational aspects of this methodology are discussed in the companion paper 'Modeling Multibody Dynamic Systems With Uncertainties. Part I: Theoretical and Computational Aspects .In this paper we illustrate the methodology on selected test cases. The combined effects of parametric and forcing uncertainties are studied for a quarter car model. The uncertainty distributions in the system response in both time and frequency domains are validated against Monte-Carlo simulations. Results indicate that polynomial chaos is more efficient than Monte Carlo and more accurate than statistical linearization. The results of the direct collocation approach are similar to the ones obtained with the Galerkin approach. A stochastic terrain model is constructed using a truncated Karhunen-Loeve expansion. The application of polynomial chaos to differential-algebraic systems is illustrated using the constrained pendulum problem. Limitations of the polynomial chaos approach are studied on two different test problems, one with multiple attractor points, and the second with a chaotic evolution and a nonlinear attractor set. The overall conclusion is that, despite its limitations, generalized polynomial chaos is a powerful approach for the simulation of multibody dynamic systems with uncertainties.

  8. Modeling multibody systems with uncertainties. Part II: Numerical applications

    International Nuclear Information System (INIS)

    Sandu, Corina; Sandu, Adrian; Ahmadian, Mehdi

    2006-01-01

    This study applies generalized polynomial chaos theory to model complex nonlinear multibody dynamic systems operating in the presence of parametric and external uncertainty. Theoretical and computational aspects of this methodology are discussed in the companion paper 'Modeling Multibody Dynamic Systems With Uncertainties. Part I: Theoretical and Computational Aspects .In this paper we illustrate the methodology on selected test cases. The combined effects of parametric and forcing uncertainties are studied for a quarter car model. The uncertainty distributions in the system response in both time and frequency domains are validated against Monte-Carlo simulations. Results indicate that polynomial chaos is more efficient than Monte Carlo and more accurate than statistical linearization. The results of the direct collocation approach are similar to the ones obtained with the Galerkin approach. A stochastic terrain model is constructed using a truncated Karhunen-Loeve expansion. The application of polynomial chaos to differential-algebraic systems is illustrated using the constrained pendulum problem. Limitations of the polynomial chaos approach are studied on two different test problems, one with multiple attractor points, and the second with a chaotic evolution and a nonlinear attractor set. The overall conclusion is that, despite its limitations, generalized polynomial chaos is a powerful approach for the simulation of multibody dynamic systems with uncertainties

  9. An interval-based possibilistic programming method for waste management with cost minimization and environmental-impact abatement under uncertainty.

    Science.gov (United States)

    Li, Y P; Huang, G H

    2010-09-15

    Considerable public concerns have been raised in the past decades since a large amount of pollutant emissions from municipal solid waste (MSW) disposal of processes pose risks on surrounding environment and human health. Moreover, in MSW management, various uncertainties exist in the related costs, impact factors and objectives, which can affect the optimization processes and the decision schemes generated. In this study, an interval-based possibilistic programming (IBPP) method is developed for planning the MSW management with minimized system cost and environmental impact under uncertainty. The developed method can deal with uncertainties expressed as interval values and fuzzy sets in the left- and right-hand sides of constraints and objective function. An interactive algorithm is provided for solving the IBPP problem, which does not lead to more complicated intermediate submodels and has a relatively low computational requirement. The developed model is applied to a case study of planning a MSW management system, where mixed integer linear programming (MILP) technique is introduced into the IBPP framework to facilitate dynamic analysis for decisions of timing, sizing and siting in terms of capacity expansion for waste-management facilities. Three cases based on different waste-management policies are examined. The results obtained indicate that inclusion of environmental impacts in the optimization model can change the traditional waste-allocation pattern merely based on the economic-oriented planning approach. The results obtained can help identify desired alternatives for managing MSW, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty. Copyright 2010 Elsevier B.V. All rights reserved.

  10. Entropic uncertainty measures for large dimensional hydrogenic systems

    NARCIS (Netherlands)

    D. Puertas-Centeno; N.M. Temme (Nico); I.V. Toranzo; J.S. Dehesa

    2017-01-01

    textabstractThe entropic moments of the probability density of a quantum system in position and momentum spaces describe not only some fundamental and/or experimentally accessible quantities of the system but also the entropic uncertainty measures of Rényi type, which allow one to find the most

  11. Costing systems design for sustainability

    Directory of Open Access Journals (Sweden)

    Mihaela TURTUREA

    2013-10-01

    Full Text Available The aim of this article is to present an overall image of the way Accounting responds to nowadays user’s needs in relation to the quantification of the impact companies have towards the environment. Regarding this, there have been analyzed concepts like sustainable development, environmental accounting, environmental costs and there have been presented the main progress towards environmental cost identification and measurement from the perspective of Activity Based Costing system. To provide an overall image of this concepts, there have been used as research methodology methods the documentation from literature review, analysis, synthesis and comparison.

  12. Uncertainty analysis of integrated gasification combined cycle systems based on Frame 7H versus 7F gas turbines.

    Science.gov (United States)

    Zhu, Yunhua; Frey, H Christopher

    2006-12-01

    Integrated gasification combined cycle (IGCC) technology is a promising alternative for clean generation of power and coproduction of chemicals from coal and other feedstocks. Advanced concepts for IGCC systems that incorporate state-of-the-art gas turbine systems, however, are not commercially demonstrated. Therefore, there is uncertainty regarding the future commercial-scale performance, emissions, and cost of such technologies. The Frame 7F gas turbine represents current state-of-practice, whereas the Frame 7H is the most recently introduced advanced commercial gas turbine. The objective of this study was to evaluate the risks and potential payoffs of IGCC technology based on different gas turbine combined cycle designs. Models of entrained-flow gasifier-based IGCC systems with Frame 7F (IGCC-7F) and 7H gas turbine combined cycles (IGCC-7H) were developed in ASPEN Plus. An uncertainty analysis was conducted. Gasifier carbon conversion and project cost uncertainty are identified as the most important uncertain inputs with respect to system performance and cost. The uncertainties in the difference of the efficiencies and costs for the two systems are characterized. Despite uncertainty, the IGCC-7H system is robustly preferred to the IGCC-7F system. Advances in gas turbine design will improve the performance, emissions, and cost of IGCC systems. The implications of this study for decision-making regarding technology selection, research planning, and plant operation are discussed.

  13. Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

    Science.gov (United States)

    Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun

    2015-01-01

    The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. MOUSE (MODULAR ORIENTED UNCERTAINTY SYSTEM): A COMPUTERIZED UNCERTAINTY ANALYSIS SYSTEM (FOR MICRO- COMPUTERS)

    Science.gov (United States)

    Environmental engineering calculations involving uncertainties; either in the model itself or in the data, are far beyond the capabilities of conventional analysis for any but the simplest of models. There exist a number of general-purpose computer simulation languages, using Mon...

  15. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty

    CERN Document Server

    Starczewski, Janusz T

    2013-01-01

    This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic ambiguity resulting from limited perception or lack of knowledge about exact membership functions - lack of attributes or granularity arising from discretization of real data - imprecise description of membership functions - vagueness perceived as fuzzification of conditional attributes. Consequently, the membership uncertainty can be modeled by combining methods of conventional and type-2 fuzzy logic, rough set theory and possibility theory.            In particular, this book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets and presents some basic structures of generalized uncertain fuzzy logic systems, as well as introduces several of methods to generate fuzzy membership uncertainty. It is desirable as a reference book for under-graduates in higher education, master and doctor graduates in the courses of computer science, computational intelligence, or...

  16. Deep uncertainty and broad heterogeneity in country-level social cost of carbon

    Science.gov (United States)

    Ricke, K.; Drouet, L.; Caldeira, K.; Tavoni, M.

    2017-12-01

    The social cost of carbon (SCC) is a commonly employed metric of the expected economic damages expected from carbon dioxide (CO2) emissions. Recent estimates of SCC range from approximately 10/tonne of CO2 to as much as 1000/tCO2, but these have been computed at the global level. While useful in an optimal policy context, a world-level approach obscures the heterogeneous geography of climate damages and vast differences in country-level contributions to global SCC, as well as climate and socio-economic uncertainties, which are much larger at the regional level. For the first time, we estimate country-level contributions to SCC using recent climate and carbon-cycle model projections, empirical climate-driven economic damage estimations, and information from the Shared Socio-economic Pathways. Central specifications show high global SCC values (median: 417 /tCO2, 66% confidence intervals: 168 - 793 /tCO2) with country-level contributions ranging from -11 (-8 - -14) /tCO2 to 86 (50 - 158) /tCO2. We quantify climate-, scenario- and economic damage- driven uncertainties associated with the calculated values of SCC. We find that while the magnitude of country-level social cost of carbon is highly uncertain, the relative positioning among countries is consistent. Countries incurring large fractions of the global cost include India, China, and the United States. The share of SCC distributed among countries is robust, indicating climate change winners and losers from a geopolitical perspective.

  17. Uncertainties in Early Stage Capital Cost Estimation of Process Design – A case study on biorefinery design

    Directory of Open Access Journals (Sweden)

    Gurkan eSin

    2015-02-01

    Full Text Available Capital investment, next to the product demand, sales and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early stage design is a challenging task. This is especially important in biorefinery research, where available information and experiences with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs (a Bootstrapping as a regression method when cost data is available and (b the Monte Carlo technique as an error propagation method based on expert input when cost data is not available. Four well-known models for early stage cost estimation are reviewed an analyzed using the methodology. The significance of uncertainties of cost data for early stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision making under uncertainties. One of the results using an order-of-magnitude estimate shows that the production of diethyl ether and 1,3-butadiene are the most promising with economic risks of 0.24 MM$/a and 4.6 MM$/a due to uncertainties in cost estimations, respectively.

  18. H2 guaranteed cost control of discrete linear systems

    Directory of Open Access Journals (Sweden)

    W. Colmenares

    2000-01-01

    guaranteed cost performance on a discrete linear uncertain system where the uncertainty is of the norm bounded type. The conditions are presented as a collection of linear matrix inequalities.The solution, however requires a search over a scalar parameter space.

  19. Modifications to Replacement Costs System

    International Nuclear Information System (INIS)

    Godec, M.

    1989-01-01

    The purpose of this memorandum is to document the improvements and modifications made to the Replacement Costs of Crude Oil (REPCO) Supply Analysis System. While some of this work was performed under our previous support contract to DOE/ASFE, we are presenting all modifications and improvements are presented here for completeness. The memo primarily documents revisions made to the Lower-48 Onshore Model. Revisions and modifications made to other components and models in the REPCO system which are documented elsewhere are only highlighted in this memo. Generally, the modifications made to the Lower-48 Onshore Model reflect changes that have occurred in domestic drilling, oil field costs, and reserves since 1982, the date of the most recent available data used for the original Replacement Costs report, published in 1985

  20. Groundwater detection monitoring system design under conditions of uncertainty

    NARCIS (Netherlands)

    Yenigül, N.B.

    2006-01-01

    Landfills represent a wide-spread and significant threat to groundwater quality. In this thesis a methodology was developed for the design of optimal groundwater moni-toring system design at landfill sites under conditions of uncertainty. First a decision analysis approach was presented for optimal

  1. A dynamic model to optimize municipal electric power systems by considering carbon emission trading under uncertainty

    International Nuclear Information System (INIS)

    In this study, a FFSP (full-infinite fuzzy stochastic programming) method is developed for planning MEPS (municipal electric power systems) associated with GHG (greenhouse gas) control under uncertainty. FFSP can deal with multiple uncertainties presented in terms of fuzzy sets, functional intervals, and random variables. FFSP is also applied to a case study of Beijing for managing MEPS, and reducing the GHG emission through introducing the EU ETS (European Union greenhouse gas emission trading scheme). The results indicate that reasonable solutions have been generated, which can be used for generating schemes of energy resources, electricity production/allocation, and capacity expansion under various economic costs and GHG reduction requirements. The case study demonstrates that FFSP can increase the abilities of reflecting complexities for dynamics of capacity expansion and interaction of multiple uncertainties in MEPS. The results allow in-depth analyses of trade-offs between GHG mitigation and economic objective as well as those between system cost and decision makers' satisfaction degree. Besides, this study can also provide an example to help China construct domestic carbon trading market at municipal scale for addressing the challenges of global climate change. - Highlights: • A dynamic optimization (FFSP) method is developed for tackling uncertainties. • FFSP is applied to planning MEPS (municipal electric power systems) of Beijing. • CET (Carbon emission trading) is introduced into MEPS for mitigating CO 2 emissions. • Trade-offs occur between system cost and satisfaction degree under uncertainties. • Results can provide an example to construct domestic CET market in China

  2. Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

    Science.gov (United States)

    Groves, Curtis E.

    2013-01-01

    Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around

  3. Sustainable design of complex industrial and energy systems under uncertainty

    Science.gov (United States)

    Liu, Zheng

    Depletion of natural resources, environmental pressure, economic globalization, etc., demand seriously industrial organizations to ensure that their manufacturing be sustainable. On the other hand, the efforts of pursing sustainability also give raise to potential opportunities for improvements and collaborations among various types of industries. Owing to inherent complexity and uncertainty, however, sustainability problems of industrial and energy systems are always very difficult to deal with, which has made industrial practice mostly experience based. For existing research efforts on the study of industrial sustainability, although systems approaches have been applied in dealing with the challenge of system complexity, most of them are still lack in the ability of handling inherent uncertainty. To overcome this limit, there is a research need to develop a new generation of systems approaches by integrating techniques and methods for handling various types of uncertainties. To achieve this objective, this research introduced series of holistic methodologies for sustainable design and decision-making of industrial and energy systems. The introduced methodologies are developed in a systems point of view with the functional components involved in, namely, modeling, assessment, analysis, and decision-making. For different methodologies, the interval-parameter-based, fuzzy-logic-based, and Monte Carlo based methods are selected and applied respectively for handling various types of uncertainties involved, and the optimality of solutions is guaranteed by thorough search or system optimization. The proposed methods are generally applicable for any types of industrial systems, and their efficacy had been successfully demonstrated by the given case studies. Beyond that, a computational tool was designed, which provides functions on the industrial sustainability assessment and decision-making through several convenient and interactive steps of computer operation. This

  4. Evaluation of uncertainty in dosimetry of irradiator system

    International Nuclear Information System (INIS)

    Santos, Gelson P.; Potiens, Maria P.A.; Vivolo, Vitor

    2005-01-01

    This paper describes the study of uncertainties in the estimates of dosimetry irradiator system STS 0B85 of LCI IPEN/CNEN-SP. This study is relevant for determination of best measurement capability when the laboratory performs routine calibrations of measuring radiation next the optimal measures designed to radioprotection. It is also a requirement for obtaining the accreditation of the laboratory by the INMETRO. For this dosimetry was used a reference system of the laboratory composed of a electrometer and a spherical ionization chamber of 1 liter. Measurements were made at five distances selected so to include the whole range of the optical bench tests and using three attenuators filters so as to extend the measurement capability. The magnitude used for evaluation was the rate of air kerma for 1 37C s and 6 0C o beams. Were carried out four series of measurements. It was verified the inverse square law to these series and their sets of uncertainty. Unfiltered, with one and two filters series showed good agreement with the inverse square low and the maximum uncertainty obtained was approximately 1.7%. In series with all the filters was a major deviation of the inverse square law and wide increase in uncertainty to measurements at the end of the optical bench

  5. Quantification of uncertainties in global grazing systems assessment

    Science.gov (United States)

    Fetzel, T.; Havlik, P.; Herrero, M.; Kaplan, J. O.; Kastner, T.; Kroisleitner, C.; Rolinski, S.; Searchinger, T.; Van Bodegom, P. M.; Wirsenius, S.; Erb, K.-H.

    2017-07-01

    Livestock systems play a key role in global sustainability challenges like food security and climate change, yet many unknowns and large uncertainties prevail. We present a systematic, spatially explicit assessment of uncertainties related to grazing intensity (GI), a key metric for assessing ecological impacts of grazing, by combining existing data sets on (a) grazing feed intake, (b) the spatial distribution of livestock, (c) the extent of grazing land, and (d) its net primary productivity (NPP). An analysis of the resulting 96 maps implies that on average 15% of the grazing land NPP is consumed by livestock. GI is low in most of the world's grazing lands, but hotspots of very high GI prevail in 1% of the total grazing area. The agreement between GI maps is good on one fifth of the world's grazing area, while on the remainder, it is low to very low. Largest uncertainties are found in global drylands and where grazing land bears trees (e.g., the Amazon basin or the Taiga belt). In some regions like India or Western Europe, massive uncertainties even result in GI > 100% estimates. Our sensitivity analysis indicates that the input data for NPP, animal distribution, and grazing area contribute about equally to the total variability in GI maps, while grazing feed intake is a less critical variable. We argue that a general improvement in quality of the available global level data sets is a precondition for improving the understanding of the role of livestock systems in the context of global environmental change or food security.

  6. Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

    Science.gov (United States)

    Nguyen, Nhan T.

    2012-01-01

    This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

  7. Optimization under variability and uncertainty: a case study for NOx emissions control for a gasification system.

    Science.gov (United States)

    Chen, Jianjun; Frey, H Christopher

    2004-12-15

    Methods for optimization of process technologies considering the distinction between variability and uncertainty are developed and applied to case studies of NOx control for Integrated Gasification Combined Cycle systems. Existing methods of stochastic optimization (SO) and stochastic programming (SP) are demonstrated. A comparison of SO and SP results provides the value of collecting additional information to reduce uncertainty. For example, an expected annual benefit of 240,000 dollars is estimated if uncertainty can be reduced before a final design is chosen. SO and SP are typically applied to uncertainty. However, when applied to variability, the benefit of dynamic process control is obtained. For example, an annual savings of 1 million dollars could be achieved if the system is adjusted to changes in process conditions. When variability and uncertainty are treated distinctively, a coupled stochastic optimization and programming method and a two-dimensional stochastic programming method are demonstrated via a case study. For the case study, the mean annual benefit of dynamic process control is estimated to be 700,000 dollars, with a 95% confidence range of 500,000 dollars to 940,000 dollars. These methods are expected to be of greatest utility for problems involving a large commitment of resources, for which small differences in designs can produce large cost savings.

  8. Estimation of Model Uncertainties in Closed-loop Systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2008-01-01

    This paper describe a method for estimation of parameters or uncertainties in closed-loop systems. The method is based on an application of the dual YJBK (after Youla, Jabr, Bongiorno and Kucera) parameterization of all systems stabilized by a given controller. The dual YJBK transfer function...... is a measure for the variation in the system seen through the feedback controller. It is shown that it is possible to isolate a certain number of parameters or uncertain blocks in the system exactly. This is obtained by modifying the feedback controller through the YJBK transfer function together with pre...

  9. Buy now, saved later? The critical impact of time-to-pandemic uncertainty on pandemic cost-effectiveness analyses.

    Science.gov (United States)

    Drake, Tom; Chalabi, Zaid; Coker, Richard

    2015-02-01

    Investment in pandemic preparedness is a long-term gamble, with the return on investment coming at an unknown point in the future. Many countries have chosen to stockpile key resources, and the number of pandemic economic evaluations has risen sharply since 2009. We assess the importance of uncertainty in time-to-pandemic (and associated discounting) in pandemic economic evaluation, a factor frequently neglected in the literature to-date. We use a probability tree model and Monte Carlo parameter sampling to consider the cost effectiveness of antiviral stockpiling in Cambodia under parameter uncertainty. Mean elasticity and mutual information (MI) are used to assess the importance of time-to-pandemic compared with other parameters. We also consider the sensitivity to choice of sampling distribution used to model time-to-pandemic uncertainty. Time-to-pandemic and discount rate are the primary drivers of sensitivity and uncertainty in pandemic cost effectiveness models. Base case cost effectiveness of antiviral stockpiling ranged between is US$112 and US$3599 per DALY averted using historical pandemic intervals for time-to-pandemic. The mean elasticities for time-to-pandemic and discount rate were greater than all other parameters. Similarly, the MI scores for time to pandemic and discount rate were greater than other parameters. Time-to-pandemic and discount rate were key drivers of uncertainty in cost-effectiveness results regardless of time-to-pandemic sampling distribution choice. Time-to-pandemic assumptions can "substantially" affect cost-effectiveness results and, in our model, is a greater contributor to uncertainty in cost-effectiveness results than any other parameter. We strongly recommend that cost-effectiveness models include probabilistic analysis of time-to-pandemic uncertainty. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2013; all rights reserved.

  10. Linear collider systems and costs

    International Nuclear Information System (INIS)

    Loew, G.A.

    1993-05-01

    The purpose of this paper is to examine some of the systems and sub-systems involved in so-called ''conventional'' e + e - linear colliders and to study how their design affects the overall cost of these machines. There are presently a total of at least six 500 GeV c. of m. linear collider projects under study in the world. Aside from TESLA (superconducting linac at 1.3 GHz) and CLIC (two-beam accelerator with main linac at 30GHz), the other four proposed e + e - linear colliders can be considered ''conventional'' in that their main linacs use the proven technique of driving room temperature accelerator sections with pulsed klystrons and modulators. The centrally distinguishing feature between these projects is their main linac rf frequency: 3 GHz for the DESY machine, 11.424 GHz for the SLAC and JLC machines, and 14 GHz for the VLEPP machine. The other systems, namely the electron and positron sources, preaccelerators, compressors, damping rings and final foci, are fairly similar from project to project. Probably more than 80% of the cost of these linear colliders will be incurred in the two main linacs facing each other and it is therefore in their design and construction that major savings or extra costs may be found

  11. On the average uncertainty for systems with nonlinear coupling

    Science.gov (United States)

    Nelson, Kenric P.; Umarov, Sabir R.; Kon, Mark A.

    2017-02-01

    The increased uncertainty and complexity of nonlinear systems have motivated investigators to consider generalized approaches to defining an entropy function. New insights are achieved by defining the average uncertainty in the probability domain as a transformation of entropy functions. The Shannon entropy when transformed to the probability domain is the weighted geometric mean of the probabilities. For the exponential and Gaussian distributions, we show that the weighted geometric mean of the distribution is equal to the density of the distribution at the location plus the scale (i.e. at the width of the distribution). The average uncertainty is generalized via the weighted generalized mean, in which the moment is a function of the nonlinear source. Both the Rényi and Tsallis entropies transform to this definition of the generalized average uncertainty in the probability domain. For the generalized Pareto and Student's t-distributions, which are the maximum entropy distributions for these generalized entropies, the appropriate weighted generalized mean also equals the density of the distribution at the location plus scale. A coupled entropy function is proposed, which is equal to the normalized Tsallis entropy divided by one plus the coupling.

  12. Dissertation Defense: Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

    Science.gov (United States)

    Groves, Curtis Edward

    2014-01-01

    Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions

  13. Dissertation Defense Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

    Science.gov (United States)

    Groves, Curtis Edward

    2014-01-01

    Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics

  14. Risk classification and uncertainty propagation for virtual water distribution systems

    International Nuclear Information System (INIS)

    Torres, Jacob M.; Brumbelow, Kelly; Guikema, Seth D.

    2009-01-01

    While the secrecy of real water distribution system data is crucial, it poses difficulty for research as results cannot be publicized. This data includes topological layouts of pipe networks, pump operation schedules, and water demands. Therefore, a library of virtual water distribution systems can be an important research tool for comparative development of analytical methods. A virtual city, 'Micropolis', has been developed, including a comprehensive water distribution system, as a first entry into such a library. This virtual city of 5000 residents is fully described in both geographic information systems (GIS) and EPANet hydraulic model frameworks. A risk classification scheme and Monte Carlo analysis are employed for an attempted water supply contamination attack. Model inputs to be considered include uncertainties in: daily water demand, seasonal demand, initial storage tank levels, the time of day a contamination event is initiated, duration of contamination event, and contaminant quantity. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. High uncertainties in exposure patterns lead to greater resources needed for more effective mitigation strategies.

  15. How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications

    Science.gov (United States)

    McMillan, Hilary; Seibert, Jan; Petersen-Overleir, Asgeir; Lang, Michel; White, Paul; Snelder, Ton; Rutherford, Kit; Krueger, Tobias; Mason, Robert; Kiang, Julie

    2017-07-01

    Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.

  16. State Estimation for Sensor Monitoring System with Uncertainty and Disturbance

    Directory of Open Access Journals (Sweden)

    Jianhong Sun

    2014-10-01

    Full Text Available This paper considers the state estimation problem for the sensor monitoring system which contains system uncertainty and nonlinear disturbance. In the sensor monitoring system, states of each inner sensor node usually contains system uncertainty, and external noise often works as nonlinear item. Besides, information transmission in the system is also time consuming. All mentioned above may arouse in unstable of the monitoring system. In this case, states of sensors could be wrongly sampled. Under this circumstance, a proper mathematical model is proposed and by the use of Lipschitz condition, the nonlinear item is transformed to linear one. In addition, we suppose that all sensor nodes are distributed arranged, no interface occurs with each other. By establishing proper Lyapunov– Krasovskii functional, sufficient conditions are acquired by solving linear matrix inequality to make the error augmented system stable, and the gains of observers are also derived. Finally, an illustrated example is given to show that system observed value tracks system states well, which fully demonstrate the effectiveness of our result.

  17. Risk Intelligence: Making Profit from Uncertainty in Data Processing System

    Directory of Open Access Journals (Sweden)

    Si Zheng

    2014-01-01

    Full Text Available In extreme scale data processing systems, fault tolerance is an essential and indispensable part. Proactive fault tolerance scheme (such as the speculative execution in MapReduce framework is introduced to dramatically improve the response time of job executions when the failure becomes a norm rather than an exception. Efficient proactive fault tolerance schemes require precise knowledge on the task executions, which has been an open challenge for decades. To well address the issue, in this paper we design and implement RiskI, a profile-based prediction algorithm in conjunction with a riskaware task assignment algorithm, to accelerate task executions, taking the uncertainty nature of tasks into account. Our design demonstrates that the nature uncertainty brings not only great challenges, but also new opportunities. With a careful design, we can benefit from such uncertainties. We implement the idea in Hadoop 0.21.0 systems and the experimental results show that, compared with the traditional LATE algorithm, the response time can be improved by 46% with the same system throughput.

  18. Energy Saving Potential, Costs and Uncertainties in the Industry: A Case Study of the Chemical Industry in Germany

    DEFF Research Database (Denmark)

    Bühler, Fabian; Guminski, Andrej; Gruber, Anna

    2017-01-01

    ), which rank these measures according to specific implementation costs. Existing analyses, however, often do not take uncertainties in costs and potentials into account. The aim of this paper is to create a MCC of energy efficiency measures for the chemical industry in Germany, while quantifying...... to 1990. To achieve this ambitious goal, energy planners and industries alike require an overview of the existing energy efficiency measures, their technical potential as well as the costs for realizing this potential. Energy efficiency opportunities are commonly presented in marginal cost curves (MCCs...... the uncertainties of the results and identifying the most influential input parameters. The identification of energy efficiency measures and the quantification of the associated technical potentials and costs are identified based on literature data and own assessments. Based on these findings, a cost curve...

  19. Sustainable infrastructure system modeling under uncertainties and dynamics

    Science.gov (United States)

    Huang, Yongxi

    potential risks caused by feedstock seasonality and demand uncertainty. Facility spatiality, time variation of feedstock yields, and demand uncertainty are integrated into a two-stage stochastic programming (SP) framework. In the study of Transitional Energy System Modeling under Uncertainty, a multistage stochastic dynamic programming is established to optimize the process of building and operating fuel production facilities during the transition. Dynamics due to the evolving technologies and societal changes and uncertainty due to demand fluctuations are the major issues to be addressed.

  20. Electric-power systems planning and greenhouse-gas emission management under uncertainty

    International Nuclear Information System (INIS)

    Li, Y.P.; Huang, G.H.

    2012-01-01

    Highlight: ►A multistage stochastic integer programming model is developed for planning electric-power systems. ►Uncertain and dynamic information can be incorporated within a multilayer scenario tree. ►This can help minimize system cost under random energy demand and greenhouse gas (GHG) abatement goal. ►Results can support decisions of facility expansion, electricity supply and GHG mitigation. - Abstract: In this study, a multistage interval-stochastic integer programming model is formulated for managing greenhouse gas (GHG) emissions and planning electric-power systems under uncertainty. The developed model can reflect dynamic, interactive, and uncertain characteristics of energy systems. Besides, the model can be used for answering questions related to types, times, demands and mitigations of energy systems planning practices, with the objective of minimizing system cost over a long-time planning horizon. The solutions can help generate electricity-generation schemes and capacity-expansion plans under different GHG-mitigation options and electricity-demand levels. Tradeoffs among system cost, energy security, and emission management can also be tackled. A high system cost will increase renewable energy supply and reduce GHG emission, while a desire for a low cost will run into risks of a high energy deficiency and a high GHG emission.

  1. System convergence in transport models: algorithms efficiency and output uncertainty

    DEFF Research Database (Denmark)

    Rich, Jeppe; Nielsen, Otto Anker

    2015-01-01

    of this paper is to analyse convergence performance for the external loop and to illustrate how an improper linkage between the converging parts can lead to substantial uncertainty in the final output. Although this loop is crucial for the performance of large-scale transport models it has not been analysed......-scale in the Danish National Transport Model (DNTM). It is revealed that system convergence requires that either demand or supply is without random noise but not both. In that case, if MSA is applied to the model output with random noise, it will converge effectively as the random effects are gradually dampened...... in the MSA process. In connection to DNTM it is shown that MSA works well when applied to travel-time averaging, whereas trip averaging is generally infected by random noise resulting from the assignment model. The latter implies that the minimum uncertainty in the final model output is dictated...

  2. Least-cost failure diagnosis in uncertain reliability systems

    International Nuclear Information System (INIS)

    Cox, Louis Anthony; Chiu, Steve Y.; Sun Xiaorong

    1996-01-01

    In many textbook solutions, for systems failure diagnosis problems studied using reliability theory and artificial intelligence, the prior probabilities of different failure states can be estimated and used to guide the sequential search for failed components after the whole system fails. In practice, however, both the component failure probabilities and the structure function of the system being examined--i.e., the mapping between the states of its components and the state of the system--may not be known with certainty. At best:, the probabilities of different hypothesized system descriptions, each specifying the component failure probabilities and the system's structure function, may be known to a useful approximation, perhaps based on sample data and previous experience. Cost-effective diagnosis of the system's failure state is then a challenging problem. Although the probabilities of component failures are aleatory, uncertainties about these probabilities and about the system structure function are epistemic. This paper examines how to make best use of both epistemic prior probabilities for system descriptions and the information gleaned from costly inspections of component states after the system fails, to minimize the average cost of identifying the failure state. Two approaches are introduced for systems dominated by aleatory uncertainties, one motivated by information theory and the other based on the idea of trying to prove a hypothesis about the identity of the failure state as efficiently as possible. While the general problem of cost-effective failure diagnosis is computationally intractable (NP-hard), both heuristics provide useful approximations on small to moderate sized problems and optimal results for certain common types of reliability systems, including series, parallel, parallel-series, and k-out-of-n systems. A hybrid heuristic that adaptively chooses which heuristic to apply next after any sequence of observations (component test results

  3. Analysis of Uncertainty in a Middle-Cost Device for 3D Measurements in BIM Perspective

    Directory of Open Access Journals (Sweden)

    Alonso Sánchez

    2016-09-01

    Full Text Available Medium-cost devices equipped with sensors are being developed to get 3D measurements. Some allow for generating geometric models and point clouds. Nevertheless, the accuracy of these measurements should be evaluated, taking into account the requirements of the Building Information Model (BIM. This paper analyzes the uncertainty in outdoor/indoor three-dimensional coordinate measures and point clouds (using Spherical Accuracy Standard (SAS methods for Eyes Map, a medium-cost tablet manufactured by e-Capture Research & Development Company, Mérida, Spain. To achieve it, in outdoor tests, by means of this device, the coordinates of targets were measured from 1 to 6 m and cloud points were obtained. Subsequently, these were compared to the coordinates of the same targets measured by a Total Station. The Euclidean average distance error was 0.005–0.027 m for measurements by Photogrammetry and 0.013–0.021 m for the point clouds. All of them satisfy the tolerance for point cloud acquisition (0.051 m according to the BIM Guide for 3D Imaging (General Services Administration; similar results are obtained in the indoor tests, with values of 0.022 m. In this paper, we establish the optimal distances for the observations in both, Photogrammetry and 3D Photomodeling modes (outdoor and point out some working conditions to avoid in indoor environments. Finally, the authors discuss some recommendations for improving the performance and working methods of the device.

  4. Analysis of Uncertainty in a Middle-Cost Device for 3D Measurements in BIM Perspective.

    Science.gov (United States)

    Sánchez, Alonso; Naranjo, José-Manuel; Jiménez, Antonio; González, Alfonso

    2016-09-22

    Medium-cost devices equipped with sensors are being developed to get 3D measurements. Some allow for generating geometric models and point clouds. Nevertheless, the accuracy of these measurements should be evaluated, taking into account the requirements of the Building Information Model (BIM). This paper analyzes the uncertainty in outdoor/indoor three-dimensional coordinate measures and point clouds (using Spherical Accuracy Standard (SAS) methods) for Eyes Map, a medium-cost tablet manufactured by e-Capture Research & Development Company, Mérida, Spain. To achieve it, in outdoor tests, by means of this device, the coordinates of targets were measured from 1 to 6 m and cloud points were obtained. Subsequently, these were compared to the coordinates of the same targets measured by a Total Station. The Euclidean average distance error was 0.005-0.027 m for measurements by Photogrammetry and 0.013-0.021 m for the point clouds. All of them satisfy the tolerance for point cloud acquisition (0.051 m) according to the BIM Guide for 3D Imaging (General Services Administration); similar results are obtained in the indoor tests, with values of 0.022 m. In this paper, we establish the optimal distances for the observations in both, Photogrammetry and 3D Photomodeling modes (outdoor) and point out some working conditions to avoid in indoor environments. Finally, the authors discuss some recommendations for improving the performance and working methods of the device.

  5. Reliability-Based Marginal Cost Pricing Problem Case with Both Demand Uncertainty and Travelers’ Perception Errors

    Directory of Open Access Journals (Sweden)

    Shaopeng Zhong

    2013-01-01

    Full Text Available Focusing on the first-best marginal cost pricing (MCP in a stochastic network with both travel demand uncertainty and stochastic perception errors within the travelers’ route choice decision processes, this paper develops a perceived risk-based stochastic network marginal cost pricing (PRSN-MCP model. Numerical examples based on an integrated method combining the moment analysis approach, the fitting distribution method, and the reliability measures are also provided to demonstrate the importance and properties of the proposed model. The main finding is that ignoring the effect of travel time reliability and travelers’ perception errors may significantly reduce the performance of the first-best MCP tolls, especially under high travelers’ confidence and network congestion levels. The analysis result could also enhance our understanding of (1 the effect of stochastic perception error (SPE on the perceived travel time distribution and the components of road toll; (2 the effect of road toll on the actual travel time distribution and its reliability measures; (3 the effect of road toll on the total network travel time distribution and its statistics; and (4 the effect of travel demand level and the value of reliability (VoR level on the components of road toll.

  6. Integrative evaluation for sustainable decisions of urban wastewater system management under uncertainty

    Science.gov (United States)

    Hadjimichael, A.; Corominas, L.; Comas, J.

    2017-12-01

    With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by

  7. Uncertainty propagation for systems of conservation laws, stochastic spectral methods

    International Nuclear Information System (INIS)

    Poette, G.

    2009-09-01

    Uncertainty quantification through stochastic spectral methods has been recently applied to several kinds of stochastic PDEs. This thesis deals with stochastic systems of conservation laws. These systems are non linear and develop discontinuities in finite times: these difficulties can trigger the loss of hyperbolicity of the truncated system resulting of the application of sG-gPC (stochastic Galerkin-generalized Polynomial Chaos). We introduce a formalism based on both kinetic theory and moments theory in order to close the truncated system in such a way that the hyperbolicity of the latter is ensured. The idea is to close the truncated system obtained by Galerkin projection via the introduction of an entropy - strictly convex function on the definition domain of our unknowns. In the case this entropy is the mathematical entropy of the non truncated system, the hyperbolicity is ensured. We state several properties of this truncated system from a general non truncated system of conservation laws. We then apply the method to the case of the stochastic inviscid Burgers' equation with random initial conditions and to the stochastic Euler system in one and two space dimensions. In the vicinity of discontinuities, the new method bounds the oscillations due to Gibbs phenomenon to a certain range through the entropy of the system without the use of any adaptative random space discretizations. It is found to be more precise than the stochastic Galerkin method for several test problems. In a last chapter, we present two prospective outlooks: we first suggest an uncertainty propagation method based on the coupling of intrusive and non intrusive methods. We finally emphasize the modelling possibilities of the intrusive Polynomial Chaos methods in order to take into account three dimensional perturbations of a mean one dimensional flow. (author)

  8. The Calculation Process of Channel Uncertainty on Digital System for Integral Reactor

    International Nuclear Information System (INIS)

    Moon, Hee Gun; Kim, Sung Hun; Kim, Jung Seon; Park, Heui Youn; Koo, In Soo

    2005-01-01

    The Channel Uncertainty is very important factor on the Safety Analysis input data because the channel uncertainty is the input data for calculating the trip setpoint and verify the hardware accuracy. But, the instrumentation system is changed to digital system due to technical improvement in these days. So, there are occurred to problems when digital system adopt directly the calculation method of uncertainty on analog system. This paper shows that the difference of the calculation process between analog system and digital system. And also, it presents consideration for calculating the uncertainty on digital system and the calculation process of uncertainty on digital system for Integral Reactor

  9. Maintenance cost models in deregulated power systems under opportunity costs

    International Nuclear Information System (INIS)

    Al-Arfaj, K.; Dahal, K.; Azaiez, M.N.

    2007-01-01

    In a centralized power system, the operator is responsible for scheduling maintenance. There are different types of maintenance, including corrective maintenance; predictive maintenance; preventive maintenance; and reliability-centred maintenance. The main cause of power failures is poor maintenance. As such, maintenance costs play a significant role in deregulated power systems. They include direct costs associated with material and labor costs as well as indirect costs associated with spare parts inventory, shipment, test equipment, indirect labor, opportunity costs and cost of failure. In maintenance scheduling and planning, the cost function is the only component of the objective function. This paper presented the results of a study in which different components of maintenance costs were modeled. The maintenance models were formulated as an optimization problem with single and multiple objectives and a set of constraints. The maintenance costs models could be used to schedule the maintenance activities of power generators more accurately and to identify the best maintenance strategies over a period of time as they consider failure and opportunity costs in a deregulated environment. 32 refs., 4 tabs., 4 figs

  10. Uncertainty analysis in raw material and utility cost of biorefinery synthesis and design

    DEFF Research Database (Denmark)

    Cheali, Peam; Quaglia, Alberto; Gernaey, Krist

    2014-01-01

    are characterized by considerable uncertainty. These uncertainties might have significant impact on the results of the design problem, and therefore need to be carefully evaluated and managed, in order to generate candidates for robust design. In this contribution, we study the effect of data uncertainty (raw...

  11. Sensing risk, fearing uncertainty: systems science approach to change.

    Science.gov (United States)

    Janecka, Ivo P

    2014-01-01

    Medicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases. There are two attributes of systems science that are especially relevant to this research: One-it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two-it gives pre-eminence to sensory input capable to register, evaluate, and react to change. Public domain records of change, during the last 50 years, have been studied in the context of systems science, the dynamic systems model, and various cycles. Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems' relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems. From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.

  12. On-orbit servicing system assessment and optimization methods based on lifecycle simulation under mixed aleatory and epistemic uncertainties

    Science.gov (United States)

    Yao, Wen; Chen, Xiaoqian; Huang, Yiyong; van Tooren, Michel

    2013-06-01

    To assess the on-orbit servicing (OOS) paradigm and optimize its utilities by taking advantage of its inherent flexibility and responsiveness, the OOS system assessment and optimization methods based on lifecycle simulation under uncertainties are studied. The uncertainty sources considered in this paper include both the aleatory (random launch/OOS operation failure and on-orbit component failure) and the epistemic (the unknown trend of the end-used market price) types. Firstly, the lifecycle simulation under uncertainties is discussed. The chronological flowchart is presented. The cost and benefit models are established, and the uncertainties thereof are modeled. The dynamic programming method to make optimal decision in face of the uncertain events is introduced. Secondly, the method to analyze the propagation effects of the uncertainties on the OOS utilities is studied. With combined probability and evidence theory, a Monte Carlo lifecycle Simulation based Unified Uncertainty Analysis (MCS-UUA) approach is proposed, based on which the OOS utility assessment tool under mixed uncertainties is developed. Thirdly, to further optimize the OOS system under mixed uncertainties, the reliability-based optimization (RBO) method is studied. To alleviate the computational burden of the traditional RBO method which involves nested optimum search and uncertainty analysis, the framework of Sequential Optimization and Mixed Uncertainty Analysis (SOMUA) is employed to integrate MCS-UUA, and the RBO algorithm SOMUA-MCS is developed. Fourthly, a case study on the OOS system for a hypothetical GEO commercial communication satellite is investigated with the proposed assessment tool. Furthermore, the OOS system is optimized with SOMUA-MCS. Lastly, some conclusions are given and future research prospects are highlighted.

  13. H 2 guaranteed cost control of discrete linear systems

    Directory of Open Access Journals (Sweden)

    Colmenares W.

    2000-01-01

    Full Text Available This paper presents necessary and sufficient conditions for the existence of a quadratically stabilizing output feedback controller which also assures H 2 guaranteed cost performance on a discrete linear uncertain system where the uncertainty is of the norm bounded type. The conditions are presented as a collection of linear matrix inequalities.The solution, however requires a search over a scalar parameter space.

  14. Sensing risk, fearing uncertainty: Systems science approach to change.

    Directory of Open Access Journals (Sweden)

    Ivo P Janecka

    2014-03-01

    Full Text Available BackgroundMedicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases.There are two attributes of systems science that are especially relevant to this research: One- it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two- it gives pre-eminence to sensory input capable to register, evaluate, and react to change. Material / MethodPublic domain records of change, during the last fifty years, have been studied in the context of systems science, the dynamic systems model, and various cycles. Results / Conclusions Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems’ relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems.From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.

  15. Reducing annotation cost and uncertainty in computer-aided diagnosis through selective iterative classification

    Science.gov (United States)

    Riely, Amelia; Sablan, Kyle; Xiaotao, Thomas; Furst, Jacob; Raicu, Daniela

    2015-03-01

    Medical imaging technology has always provided radiologists with the opportunity to view and keep records of anatomy of the patient. With the development of machine learning and intelligent computing, these images can be used to create Computer-Aided Diagnosis (CAD) systems, which can assist radiologists in analyzing image data in various ways to provide better health care to patients. This paper looks at increasing accuracy and reducing cost in creating CAD systems, specifically in predicting the malignancy of lung nodules in the Lung Image Database Consortium (LIDC). Much of the cost in creating an accurate CAD system stems from the need for multiple radiologist diagnoses or annotations of each image, since there is rarely a ground truth diagnosis and even different radiologists' diagnoses of the same nodule often disagree. To resolve this issue, this paper outlines an method of selective iterative classification that predicts lung nodule malignancy by using multiple radiologist diagnoses only for cases that can benefit from them. Our method achieved 81% accuracy while costing only 46% of the method that indiscriminately used all annotations, which achieved a lower accuracy of 70%, while costing more.

  16. Optimal Sizing of Battery Storage Systems for Industrial Applications when Uncertainties Exist

    Directory of Open Access Journals (Sweden)

    Guido Carpinelli

    2014-01-01

    Full Text Available Demand response (DR can be very useful for an industrial facility, since it allows noticeable reductions in the electricity bill due to the significant value of energy demand. Although most industrial processes have stringent constraints in terms of hourly active power, DR only becomes attractive when performed with the contemporaneous use of battery energy storage systems (BESSs. When this option is used, an optimal sizing of BESSs is desirable, because the investment costs can be significant. This paper deals with the optimal sizing of a BESS installed in an industrial facility to reduce electricity costs. A four-step procedure, based on Decision Theory, was used to obtain a good solution for the sizing problem, even when facing uncertainties; in fact, we think that the sizing procedure must properly take into account the unavoidable uncertainties introduced by the cost of electricity and the load demands of industrial facilities. Three approaches provided by Decision Theory were applied, and they were based on: (1 the minimization of expected cost; (2 the regret felt by the sizing engineer; and (3 a mix of (1 and (2. The numerical applications performed on an actual industrial facility provided evidence of the effectiveness of the proposed procedure.

  17. Resilient guaranteed cost control of a power system

    Science.gov (United States)

    Soliman, Hisham M.; Soliman, Mostafa H.; Hassan, Mohammad. F.

    2013-01-01

    With the development of power system interconnection, the low-frequency oscillation is becoming more and more prominent which may cause system separation and loss of energy to consumers. This paper presents an innovative robust control for power systems in which the operating conditions are changing continuously due to load changes. However, practical implementation of robust control can be fragile due to controller inaccuracies (tolerance of resistors used with operational amplifiers). A new design of resilient (non-fragile) robust control is given that takes into consideration both model and controller uncertainties by an iterative solution of a set of linear matrix inequalities (LMI). Both uncertainties are cast into a norm-bounded structure. A sufficient condition is derived to achieve the desired settling time for damping power system oscillations in face of plant and controller uncertainties. Furthermore, an improved controller design, resilient guaranteed cost controller, is derived to achieve oscillations damping in a guaranteed cost manner. The effectiveness of the algorithm is shown for a single machine infinite bus system, and then, it is extended to multi-area power system. PMID:25685505

  18. Stochastic dynamic analysis of marine risers considering Gaussian system uncertainties

    Science.gov (United States)

    Ni, Pinghe; Li, Jun; Hao, Hong; Xia, Yong

    2018-03-01

    This paper performs the stochastic dynamic response analysis of marine risers with material uncertainties, i.e. in the mass density and elastic modulus, by using Stochastic Finite Element Method (SFEM) and model reduction technique. These uncertainties are assumed having Gaussian distributions. The random mass density and elastic modulus are represented by using the Karhunen-Loève (KL) expansion. The Polynomial Chaos (PC) expansion is adopted to represent the vibration response because the covariance of the output is unknown. Model reduction based on the Iterated Improved Reduced System (IIRS) technique is applied to eliminate the PC coefficients of the slave degrees of freedom to reduce the dimension of the stochastic system. Monte Carlo Simulation (MCS) is conducted to obtain the reference response statistics. Two numerical examples are studied in this paper. The response statistics from the proposed approach are compared with those from MCS. It is noted that the computational time is significantly reduced while the accuracy is kept. The results demonstrate the efficiency of the proposed approach for stochastic dynamic response analysis of marine risers.

  19. Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model

    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.

  20. Robust uncertainty evaluation for system identification on distributed wireless platforms

    Science.gov (United States)

    Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

    2016-04-01

    Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on

  1. Impact of Input Uncertainty on Failure Prognostic Algorithms: Extending the Remaining Useful Life of Nonlinear Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a novel set of uncertainty measures to quantify the impact of input uncertainty on nonlinear prognosis systems. A Particle Filtering-based method...

  2. Implementation of a Cost-Accounting System for Visibility of Weapon Systems Life-Cycle Costs

    National Research Council Canada - National Science Library

    Ugone, Mary

    2001-01-01

    ... costs through activity-based costing and management. The system must deliver timely, integrated data for management purposes to permit understanding of total weapon costs, provide a basis for estimating costs of future systems, and feed other tools for life-cycle cost management.

  3. Reducing uncertainty in nitrogen budgets for African livestock systems

    International Nuclear Information System (INIS)

    Rufino, M C; Brandt, P; Herrero, M; Butterbach-Bahl, K

    2014-01-01

    Livestock is poorly represented in N budgets for the African continent although some studies have examined livestock-related N flows at different levels. Livestock plays an important role in N cycling and therefore on N budgets including livestock-related flows. This study reviews the literature on N budgets for Africa to identify factors contributing to uncertainties. Livestock densities are usually modelled because of the lack of observational spatial data. Even though feed availability and quality varies across seasons, most studies use constant livestock excretion rates, and excreta are usually assumed to be uniformly distributed onto the land. Major uncertainties originate in the fraction of manure managed, and emission factors which may not reflect the situation of Africa. N budgets use coarse assumptions on production, availability, and use of crop residues as livestock feed. No flows between croplands–livestock and rangelands reflect the lack of data. Joint efforts are needed for spatial data collection of livestock data, crowdsourcing appears to be a promising option. The focus of the assessment of N budgets must go beyond croplands to include livestock and crop–livestock flows. We propose a nested systems definition of livestock systems to link local, regional level, and continental level and to increase the usefulness of point measurements of N losses. Scientists working at all levels should generate data to calibrate process-based models. Measurements in the field should not only concentrate on greenhouse gas emissions, but need to include crop and livestock production measurements, soil stock changes and other N loss pathways such as leaching, run-off and volatilization to assess management practices and trade-offs. Compared to the research done in other continents on N flows in livestock systems, there are few data for Africa, and therefore concerted effort will be needed to generate sufficient data for modelling. (paper)

  4. Uncertainties in early-stage capital cost estimation of process design – a case study on biorefinery design

    DEFF Research Database (Denmark)

    Cheali, Peam; Gernaey, Krist; Sin, Gürkan

    2015-01-01

    robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively....... is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable...

  5. Cost Accounting System for fusion studies

    Energy Technology Data Exchange (ETDEWEB)

    Hamilton, W.R.; Keeton, D.C.; Thomson, S.L.

    1985-12-01

    A Cost Accounting System that is applicable to all magnetic fusion reactor design studies has been developed. This system provides: (1) definitions of the elements of cost and methods for the combination of these elements to form a cost estimate; (2) a Code of Accounts that uses a functional arrangement for identification of the plant components; and (3) definitions and methods to analyze actual cost data so that the data can be directly reported into this Cost Accounting System. The purpose of the Cost Accounting System is to provide the structure for the development of a fusion cost data base and for the development of validated cost estimating procedures. This system has been developed through use at the Fusion Engineering Design Center (FEDC) and has been applied to different confinement concepts (tokamaks and tandem mirrors) and to different types of projects (experimental devices and commercial power plants). The use of this Cost Accounting System by all magnetic fusion projects will promote the development of a common cost data base, allow the direct comparison of cost estimates, and ultimately establish the cost credibility of the program.

  6. Cost Accounting System for fusion studies

    International Nuclear Information System (INIS)

    Hamilton, W.R.; Keeton, D.C.; Thomson, S.L.

    1985-12-01

    A Cost Accounting System that is applicable to all magnetic fusion reactor design studies has been developed. This system provides: (1) definitions of the elements of cost and methods for the combination of these elements to form a cost estimate; (2) a Code of Accounts that uses a functional arrangement for identification of the plant components; and (3) definitions and methods to analyze actual cost data so that the data can be directly reported into this Cost Accounting System. The purpose of the Cost Accounting System is to provide the structure for the development of a fusion cost data base and for the development of validated cost estimating procedures. This system has been developed through use at the Fusion Engineering Design Center (FEDC) and has been applied to different confinement concepts (tokamaks and tandem mirrors) and to different types of projects (experimental devices and commercial power plants). The use of this Cost Accounting System by all magnetic fusion projects will promote the development of a common cost data base, allow the direct comparison of cost estimates, and ultimately establish the cost credibility of the program

  7. Quantum uncertainty in critical systems with three spins interaction

    International Nuclear Information System (INIS)

    Carrijo, Thiago M; Avelar, Ardiley T; Céleri, Lucas C

    2015-01-01

    In this article we consider two spin-1/2 chains described, respectively, by the thermodynamic limit of the XY model with the usual two site interaction, and an extension of this model (without taking the thermodynamics limit), called XYT, were a three site interaction term is presented. To investigate the critical behaviour of such systems we employ tools from quantum information theory. Specifically, we show that the local quantum uncertainty, a quantity introduced in order to quantify the minimum quantum share of the variance of a local measurement, can be used to indicate quantum phase transitions presented by these models at zero temperature. Due to the connection of this quantity with the quantum Fisher information, the results presented here may be relevant for quantum metrology and quantum thermodynamics. (paper)

  8. Automated system for calculating the uncertainty of standards

    International Nuclear Information System (INIS)

    Harvel, C.D.

    1990-01-01

    Working Calibration and Test Material (WCTM) solutions are essential as standards in the surveillance of analytical methods, the calibration of equipment and methods, and the training and testing of laboratory personnel. Before the WCTM can be used it must be characterized. That is, the WCTM concentration and its associated uncertainty must be estimated. The characterization of a WCTM is a tedious process. The chemistry and subsequent statistical analysis require a significant amount of care. For a nonstatistician, the statistical analysis of a WCTM characterization can be quite difficult. In addition, the WCTM traceability and characterization must be thoroughly documented as required by DOE Order 5633.3 [1]. An automated system can easily do the statistical analysis and provide the necessary documentation. 3 refs., 2 figs

  9. Vulnerability analysis of power systems considering uncertainty in variables using fuzzy logic type 2

    Directory of Open Access Journals (Sweden)

    Julian Alexander Melo Rodriguez

    2016-09-01

    Full Text Available Objectives: This paper presents a new methodology for analyzing the vulnerability of power systems including uncertainty in some variables. Method: The methodology optimizes a Bi-level mixed integer model. Costs associated with power generation and load shedding are minimized at the lowest level whereas at the higher level the damage in the power system, represented by the load shedding, is maximized. Fuzzy logic type 2 is used to model the uncertainty in both linguistic variables and numeric variables. The linguistic variables model the factors of the geographical environment while numeric variables model parameters of the power system. Results: The methodology was validated by using a modified IEEE RTS-96 test system. The results show that by including particularities of the geographical environment different vulnerabilities are detected in the power system. Moreover, it was possible to identify that the most critical component is the line 112-123 because it had 16 attacks in 18 scenarios, and that the maximum load shedding of the system varies from 145 to 1258 MW. Conclusions: This methodology can be used to coordinate and refine protection plans of the power system infrastructure. Funding: EMC-UN research group.

  10. Influences of system uncertainties on the numerical transfer path analysis of engine systems

    Science.gov (United States)

    Acri, A.; Nijman, E.; Acri, A.; Offner, G.

    2017-10-01

    Practical mechanical systems operate with some degree of uncertainty. In numerical models uncertainties can result from poorly known or variable parameters, from geometrical approximation, from discretization or numerical errors, from uncertain inputs or from rapidly changing forcing that can be best described in a stochastic framework. Recently, random matrix theory was introduced to take parameter uncertainties into account in numerical modeling problems. In particular in this paper, Wishart random matrix theory is applied on a multi-body dynamic system to generate random variations of the properties of system components. Multi-body dynamics is a powerful numerical tool largely implemented during the design of new engines. In this paper the influence of model parameter variability on the results obtained from the multi-body simulation of engine dynamics is investigated. The aim is to define a methodology to properly assess and rank system sources when dealing with uncertainties. Particular attention is paid to the influence of these uncertainties on the analysis and the assessment of the different engine vibration sources. Examples of the effects of different levels of uncertainties are illustrated by means of examples using a representative numerical powertrain model. A numerical transfer path analysis, based on system dynamic substructuring, is used to derive and assess the internal engine vibration sources. The results obtained from this analysis are used to derive correlations between parameter uncertainties and statistical distribution of results. The derived statistical information can be used to advance the knowledge of the multi-body analysis and the assessment of system sources when uncertainties in model parameters are considered.

  11. Predicted costs of environmental controls for a commercial oil shale industry. Volume II. A subjective self-assessment of uncertainty in the predicted costs

    Energy Technology Data Exchange (ETDEWEB)

    Jovanovich, A.P.; Stone, M.L.; Taylor, G.C.

    1979-07-01

    The uncertainties in Volume I without extensive additional engineering effort were identified and quantified. Substantial uncertainty was found in several critical variables, allowing a broad range of possible values. Calculations of the cost impact associated with such broad ranges, however, did not always result in significant differences. Seven major areas of pollution control activity were judged to warrant the assessment effort. Three of these areas were found to contain significant uncertainty and additional research is suggested. These areas are: H/sub 2/S removal from the retort gas stream (Stretford process); organic removal from process wastewaters (bio-oxidation or other alternatives); and slurry backfilling of spent Modified In Situ (MIS) retorts. The overall results of the assessment and analysis process are summarized in Table 1-1 in terms of total cost for pollution control. The distributions have been divided into three ranges in this table. A center range is given which contains 80% to 90% probability, and the costs outside this range with probabilities are given. The full distributions can be found in Section 5.0. The subjective probability distributions are a quantification of opinion. The probability of encountering costs below the low figure or above the high figure for each process and scenario is judged to be nearly zero.

  12. FORMATION OF THE ENTERPRISE COSTS MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Borysiuk Iryna

    2018-01-01

    Full Text Available Introduction. The paper deals with the actual issues of formation of the enterprise management system costs, because in the conditions of an unstable market environment the financial performance depends on the efficiency of the cost management system, competitiveness, financial sustainability and investment attractiveness of any subject of economic activity. Purpose of the article is consolidation of approaches to cost management, theoretical substantiation and development of recommendations regarding the formation of the enterprise cost management system. Results. Development of an enterprise cost management system based on research on the essence and cost management approaches. The goals, tasks, principles, methods, tools, functions and main elements of the cost management system were determined, factors of the external and internal environment of the enterprise, that affect the system of its costs management. Conclusions. Formation of integrated cost management system ensures the successful company operation on the market, production of competitive products based on costs and prices optimization and making a profit, increase of the reasonableness of making managerial decisions.

  13. Total Measurement Uncertainty for the Plutonium Finishing Plant (PFP) Segmented Gamma Scan Assay System

    CERN Document Server

    Fazzari, D M

    2001-01-01

    This report presents the results of an evaluation of the Total Measurement Uncertainty (TMU) for the Canberra manufactured Segmented Gamma Scanner Assay System (SGSAS) as employed at the Hanford Plutonium Finishing Plant (PFP). In this document, TMU embodies the combined uncertainties due to all of the individual random and systematic sources of measurement uncertainty. It includes uncertainties arising from corrections and factors applied to the analysis of transuranic waste to compensate for inhomogeneities and interferences from the waste matrix and radioactive components. These include uncertainty components for any assumptions contained in the calibration of the system or computation of the data. Uncertainties are propagated at 1 sigma. The final total measurement uncertainty value is reported at the 95% confidence level. The SGSAS is a gamma assay system that is used to assay plutonium and uranium waste. The SGSAS system can be used in a stand-alone mode to perform the NDA characterization of a containe...

  14. [Pricing system for costly equipment. Cost allocation adapted to technical operating costs].

    Science.gov (United States)

    Alies-Patin, A

    1990-10-01

    1. Our study consists on analysing annual technical operating costs (excluding professional fees) of computed tomography and extracorporeal lithotripsy in order to define a pricing system able to provide proper reimbursements of technical costs for costly equipment. 2. Economic and utilization data have been collected from physicians responsible for facilities and from equipment current manufacturers. Annual charges are assessed in function of annual volume of procedures. 3. Definition of mean costs (total mean cost, mean cost of one more procedure) and mean cost distribution analysis according to annual volume of procedures lead to propose a method for financing costly technical medical activities based on a two-price rate: until a defined number of procedures is reached, a full-rate reimbursement is applied and then, it is replaced by a reduced-rate reimbursement. 4. Such a pricing system is easy to manage and allows to fit annual technical receipts to annual technical expenditure on a wide range of patient procedure volume.

  15. Uncertainty-accounting environmental policy and management of water systems.

    Science.gov (United States)

    Baresel, Christian; Destouni, Georgia

    2007-05-15

    Environmental policies for water quality and ecosystem management do not commonly require explicit stochastic accounts of uncertainty and risk associated with the quantification and prediction of waterborne pollutant loads and abatement effects. In this study, we formulate and investigate a possible environmental policy that does require an explicit stochastic uncertainty account. We compare both the environmental and economic resource allocation performance of such an uncertainty-accounting environmental policy with that of deterministic, risk-prone and risk-averse environmental policies under a range of different hypothetical, yet still possible, scenarios. The comparison indicates that a stochastic uncertainty-accounting policy may perform better than deterministic policies over a range of different scenarios. Even in the absence of reliable site-specific data, reported literature values appear to be useful for such a stochastic account of uncertainty.

  16. Planning low-carbon electricity systems under uncertainty considering operational flexibility and smart grid technologies.

    Science.gov (United States)

    Moreno, Rodrigo; Street, Alexandre; Arroyo, José M; Mancarella, Pierluigi

    2017-08-13

    Electricity grid operators and planners need to deal with both the rapidly increasing integration of renewables and an unprecedented level of uncertainty that originates from unknown generation outputs, changing commercial and regulatory frameworks aimed to foster low-carbon technologies, the evolving availability of market information on feasibility and costs of various technologies, etc. In this context, there is a significant risk of locking-in to inefficient investment planning solutions determined by current deterministic engineering practices that neither capture uncertainty nor represent the actual operation of the planned infrastructure under high penetration of renewables. We therefore present an alternative optimization framework to plan electricity grids that deals with uncertain scenarios and represents increased operational details. The presented framework is able to model the effects of an array of flexible, smart grid technologies that can efficiently displace the need for conventional solutions. We then argue, and demonstrate via the proposed framework and an illustrative example, that proper modelling of uncertainty and operational constraints in planning is key to valuing operationally flexible solutions leading to optimal investment in a smart grid context. Finally, we review the most used practices in power system planning under uncertainty, highlight the challenges of incorporating operational aspects and advocate the need for new and computationally effective optimization tools to properly value the benefits of flexible, smart grid solutions in planning. Such tools are essential to accelerate the development of a low-carbon energy system and investment in the most appropriate portfolio of renewable energy sources and complementary enabling smart technologies.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

  17. Uncertainty Measurement of kVp Output of the X-ray System using Spectrometry System

    International Nuclear Information System (INIS)

    Wan Hazlinda Ismail; Norhayati Abdullah; Muhammad Jamal Mohd Isa

    2011-01-01

    This study was carried out to determine the uncertainty of kVp output of the x-ray tube used in the calibration of non-invasive kVp meters. A non-invasive method was used to measure the spectrum of the x-ray output using Amptek XR-100T-CdTe spectrometry system. While an invasive high voltage divider (dynalyser) coupled to the x-ray system measures the true kilo voltage supplied to the x-ray tube with uncertainty of 2.5 % (k=2). The consistency of the kVp output was monitored daily at 9 points ranging between 40 kV-120 kV with interval steps of 10 kV from the dynalyser system. While the x-ray output spectrum of the 9 points were measured once a year. The uncertainty was determined from the consistency x-ray output, dynalyser system uncertainty, the spectrometry system accuracy, error and variation. The test results showed that kVp output measured by the dynalyser system everyday is consistent with coefficient of variations of not more than 0.89 %. The kVp output via dynalyser system and Spectrometry system shows good agreement with standard error of not more than 2.48 %. The total uncertainty of kVp output of the x-ray system using the spectrometry system is not more than 6.2 % (k=2). As a conclusion, the factors influencing the quality and quantity of the x-ray output also influence the uncertainty of the kVp output. (author)

  18. Accounting for Epistemic and Aleatory Uncertainty in Early System Design, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — This project extends Probability Bounds Analysis to model epistemic and aleatory uncertainty during early design of engineered systems in an Integrated Concurrent...

  19. Accounting for Epistemic and Aleatory Uncertainty in Early System Design, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed work extends Probability Bounds Analysis to model epistemic and aleatory uncertainty during early design of engineered systems in an Integrated...

  20. Evaluation of Spatial Uncertainties In Modeling of Cadastral Systems

    Science.gov (United States)

    Fathi, Morteza; Teymurian, Farideh

    2013-04-01

    Cadastre plays an essential role in sustainable development especially in developing countries like Iran. A well-developed Cadastre results in transparency of estates tax system, transparency of data of estate, reduction of action before the courts and effective management of estates and natural sources and environment. Multipurpose Cadastre through gathering of other related data has a vital role in civil, economic and social programs and projects. Iran is being performed Cadastre for many years but success in this program is subject to correct geometric and descriptive data of estates. Since there are various sources of data with different accuracy and precision in Iran, some difficulties and uncertainties are existed in modeling of geometric part of Cadastre such as inconsistency between data in deeds and Cadastral map which cause some troubles in execution of cadastre and result in losing national and natural source, rights of nation. Now there is no uniform and effective technical method for resolving such conflicts. This article describes various aspects of such conflicts in geometric part of cadastre and suggests a solution through some modeling tools of GIS.

  1. Quantification of Uncertainties in Integrated Spacecraft System Models, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort is to investigate a novel uncertainty quantification (UQ) approach based on non-intrusive polynomial chaos (NIPC) for computationally efficient...

  2. Quantification of Uncertainties in Integrated Spacecraft System Models, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective for the Phase II effort will be to develop a comprehensive, efficient, and flexible uncertainty quantification (UQ) framework implemented within a...

  3. Cost-effectiveness of preventive treatment of intracranial aneurysms New data and uncertainties

    NARCIS (Netherlands)

    Greving, Jacoba P.; Rinkel, Gabriel J. E.; Buskens, Erik; Algra, Ale

    2009-01-01

    Background: Previous modeling studies on treatment of unruptured intracranial aneurysms largely disregarded detailed data on treatment risks and omitted several factors that could influence cost-effectiveness. We performed a cost-effectiveness analysis of surgical and endovascular treatment of

  4. Costing the OMNIUM-G system 7500

    Science.gov (United States)

    Fortgang, H. R.

    1980-05-01

    A complete OMNIUM-G System 7500 was cost analyzed for annual production quantities ranging from 25 to 10,000 units per year. Parts and components were subjected to in-depth scrutiny to determine optimum manufacturing processes, coupled with make or buy decisions on materials and small parts. When production quantities increase both labor and material costs reduce substantially. A redesign of the system that was analyzed could result in lower costs when annual production runs approach 100,000 units/year. Material and labor costs for producing 25, 100, 25,000 and 100,00 units are given for 17 subassembly units.

  5. Quantifying Uncertainty from Computational Factors in Simulations of a Model Ballistic System

    Science.gov (United States)

    2017-08-01

    Ballistic System by Daniel J Hornbaker Approved for public release; distribution is unlimited. NOTICES...Uncertainty from Computational Factors in Simulations of a Model Ballistic System by Daniel J Hornbaker Weapons and Materials Research...November 2016 4. TITLE AND SUBTITLE Quantifying Uncertainty from Computational Factors in Simulations of a Model Ballistic System 5a. CONTRACT NUMBER

  6. The Launch Systems Operations Cost Model

    Science.gov (United States)

    Prince, Frank A.; Hamaker, Joseph W. (Technical Monitor)

    2001-01-01

    One of NASA's primary missions is to reduce the cost of access to space while simultaneously increasing safety. A key component, and one of the least understood, is the recurring operations and support cost for reusable launch systems. In order to predict these costs, NASA, under the leadership of the Independent Program Assessment Office (IPAO), has commissioned the development of a Launch Systems Operations Cost Model (LSOCM). LSOCM is a tool to predict the operations & support (O&S) cost of new and modified reusable (and partially reusable) launch systems. The requirements are to predict the non-recurring cost for the ground infrastructure and the recurring cost of maintaining that infrastructure, performing vehicle logistics, and performing the O&S actions to return the vehicle to flight. In addition, the model must estimate the time required to cycle the vehicle through all of the ground processing activities. The current version of LSOCM is an amalgamation of existing tools, leveraging our understanding of shuttle operations cost with a means of predicting how the maintenance burden will change as the vehicle becomes more aircraft like. The use of the Conceptual Operations Manpower Estimating Tool/Operations Cost Model (COMET/OCM) provides a solid point of departure based on shuttle and expendable launch vehicle (ELV) experience. The incorporation of the Reliability and Maintainability Analysis Tool (RMAT) as expressed by a set of response surface model equations gives a method for estimating how changing launch system characteristics affects cost and cycle time as compared to today's shuttle system. Plans are being made to improve the model. The development team will be spending the next few months devising a structured methodology that will enable verified and validated algorithms to give accurate cost estimates. To assist in this endeavor the LSOCM team is part of an Agency wide effort to combine resources with other cost and operations professionals to

  7. Cost of photovoltaic energy systems as determined by balance-of-system costs

    Science.gov (United States)

    Rosenblum, L.

    1978-01-01

    The effect of the balance-of-system (BOS), i.e., the total system less the modules, on photo-voltaic energy system costs is discussed for multikilowatt, flat-plate systems. Present BOS costs are in the range of 10 to 16 dollars per peak watt (1978 dollars). BOS costs represent approximately 50% of total system cost. The possibility of future BOS cost reduction is examined. It is concluded that, given the nature of BOS costs and the lack of comprehensive national effort focussed on cost reduction, it is unlikely that BOS costs will decline greatly in the next several years. This prognosis is contrasted with the expectations of the Department of Energy National Photovoltaic Program goals and pending legislation in the Congress which require a BOS cost reduction of an order of magnitude or more by the mid-1980s.

  8. Assessing uncertainty in the burden of hepatitis C virus: Comparison of estimated disease burden and treatment costs in the UK.

    Science.gov (United States)

    Gubay, F; Staunton, R; Metzig, C; Abubakar, I; White, P J

    2017-12-23

    Hepatitis C virus (HCV) is a major and growing public health concern. We need to know the expected health burden and treatment cost, and understand uncertainty in those estimates, to inform policymaking and future research. Two models that have been important in informing treatment guidelines and assessments of HCV burden were compared by simulating cohorts of individuals with chronic HCV infection initially aged 20, 35 and 50 years. One model predicts that health losses (measured in quality-adjusted life-years [QALYs]) and treatment costs decrease with increasing initial age of the patients, whilst the other model predicts that below 40 years, costs increase and QALY losses change little with age, and above 40 years, they decline with increasing age. Average per-patient costs differ between the models by up to 38%, depending on the patients' initial age. One model predicts double the total number, and triple the peak annual incidence, of liver transplants compared to the other model. One model predicts 55%-314% more deaths than the other, depending on the patients' initial age. The main sources of difference between the models are estimated progression rates between disease states and rates of health service utilization associated with different disease states and, in particular, the age dependency of these parameters. We conclude that decision-makers need to be aware that uncertainties in the health burden and economic cost of HCV disease have important consequences for predictions of future need for care and cost-effectiveness of interventions to avert HCV transmission, and further quantification is required to inform decisions. © 2017 The Authors. Journal of Viral Hepatitis published by John Wiley & Sons Ltd.

  9. Cost effectiveness of recycling: A systems model

    Energy Technology Data Exchange (ETDEWEB)

    Tonjes, David J., E-mail: david.tonjes@stonybrook.edu [Department of Technology and Society, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794-3560 (United States); Waste Reduction and Management Institute, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000 (United States); Center for Bioenergy Research and Development, Advanced Energy Research and Technology Center, Stony Brook University, 1000 Innovation Rd., Stony Brook, NY 11794-6044 (United States); Mallikarjun, Sreekanth, E-mail: sreekanth.mallikarjun@stonybrook.edu [Department of Technology and Society, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794-3560 (United States)

    2013-11-15

    Highlights: • Curbside collection of recyclables reduces overall system costs over a range of conditions. • When avoided costs for recyclables are large, even high collection costs are supported. • When avoided costs for recyclables are not great, there are reduced opportunities for savings. • For common waste compositions, maximizing curbside recyclables collection always saves money. - Abstract: Financial analytical models of waste management systems have often found that recycling costs exceed direct benefits, and in order to economically justify recycling activities, externalities such as household expenses or environmental impacts must be invoked. Certain more empirically based studies have also found that recycling is more expensive than disposal. Other work, both through models and surveys, have found differently. Here we present an empirical systems model, largely drawn from a suburban Long Island municipality. The model accounts for changes in distribution of effort as recycling tonnages displace disposal tonnages, and the seven different cases examined all show that curbside collection programs that manage up to between 31% and 37% of the waste stream should result in overall system savings. These savings accrue partially because of assumed cost differences in tip fees for recyclables and disposed wastes, and also because recycling can result in a more efficient, cost-effective collection program. These results imply that increases in recycling are justifiable due to cost-savings alone, not on more difficult to measure factors that may not impact program budgets.

  10. Cost effectiveness of recycling: A systems model

    International Nuclear Information System (INIS)

    Tonjes, David J.; Mallikarjun, Sreekanth

    2013-01-01

    Highlights: • Curbside collection of recyclables reduces overall system costs over a range of conditions. • When avoided costs for recyclables are large, even high collection costs are supported. • When avoided costs for recyclables are not great, there are reduced opportunities for savings. • For common waste compositions, maximizing curbside recyclables collection always saves money. - Abstract: Financial analytical models of waste management systems have often found that recycling costs exceed direct benefits, and in order to economically justify recycling activities, externalities such as household expenses or environmental impacts must be invoked. Certain more empirically based studies have also found that recycling is more expensive than disposal. Other work, both through models and surveys, have found differently. Here we present an empirical systems model, largely drawn from a suburban Long Island municipality. The model accounts for changes in distribution of effort as recycling tonnages displace disposal tonnages, and the seven different cases examined all show that curbside collection programs that manage up to between 31% and 37% of the waste stream should result in overall system savings. These savings accrue partially because of assumed cost differences in tip fees for recyclables and disposed wastes, and also because recycling can result in a more efficient, cost-effective collection program. These results imply that increases in recycling are justifiable due to cost-savings alone, not on more difficult to measure factors that may not impact program budgets

  11. Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

    Science.gov (United States)

    Groves, Curtis; Ilie, Marcel; Schallhorn, Paul

    2014-01-01

    Spacecraft components may be damaged due to airflow produced by Environmental Control Systems (ECS). There are uncertainties and errors associated with using Computational Fluid Dynamics (CFD) to predict the flow field around a spacecraft from the ECS System. This paper describes an approach to estimate the uncertainty in using CFD to predict the airflow speeds around an encapsulated spacecraft.

  12. The costs of uncertainty: regulating health and safety in the Canadian uranium industry

    International Nuclear Information System (INIS)

    Robinson, I.

    1982-04-01

    Federalism, and particularly federal/provincial jurisdictional relationships, have led to considerable uncertainty in the regulation of occupational health and safety and of environmental protection in the Canadian uranium mining industry. The two principal uranium producing provinces in Canada are Saskatchewan and Ontario. Since 1978, in an attempt to avoid constitutional issues, both these provinces and the federal government as well have proceeded unilaterally with health and safety reforms for the industry. In Saskatchewan this has resulted in areas of overlapping jurisdiction, which have led to uncertainty over the legal enforceability of the provincial regulations. In Ontario, the province has left significant gaps in the protection of both workers and the environment. Little progress can be expected in eliminating these gaps and overlaps until the current administrative and jurisdictional arrangements are understood

  13. Technical and governance considerations for advanced metering infrastructure/smart meters: Technology, security, uncertainty, costs, benefits, and risks

    International Nuclear Information System (INIS)

    McHenry, Mark P.

    2013-01-01

    The fundamental role of policymakers when considering Advanced Metering Infrastructure (AMI), or ‘smart meters for energy and water infrastructure is to investigate a broad range of complex interrelated issues. These include alternative technical and non-technical options and deployment needs, the cost and benefits of the infrastructure (risks and mitigation measures), and the impact of a number of stakeholders: consumers, distributors, retailers, competitive market operators, competing technology companies, etc. The scale and number of potential variables in the AMI space is an almost unprecedented challenge to policymakers, with the anticipation of new ancillary products and services, associated market contestability, related regulatory and policy amendments, and the adequacy of consumer protection, education, and safety considerations requiring utmost due-diligence. Embarking on AMI investment entails significant technical, implementation, and strategic risk for governments and administering bodies, and an active effort is required to ensure AMI governance and planning maximises the potential benefits, and minimise uncertainties, costs, and risks to stakeholders. This work seeks to clarify AMI fundamentals and discusses the technical and related governance considerations from a dispassionate perspective, yet acknowledges many stakeholders tend to dichotomise debate, and obfuscate both advantages and benefits, and the converse. - Highlights: • AMI presents an almost unprecedented technical and governance policy challenge. • AMI enables vertical integration of electricity, gas, water, IT, and telco entities • AMI investments involve major technical, implementation, and strategic decisions. • Adequacy of consumer education, safety, privacy, and protection is paramount. • Policy must maximise AMI benefits and minimise uncertainties, costs, and risks

  14. Minimum Cost Nanosatellite Launch System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Delta Velocity Corporation proposes the development of a very low cost, highly responsive nanosat launch system. We propose to develop an integrated propulsion...

  15. Propagation of Uncertainty in System Parameters of a LWR Model by Sampling MCNPX Calculations - Burnup Analysis

    Science.gov (United States)

    Campolina, Daniel de A. M.; Lima, Claubia P. B.; Veloso, Maria Auxiliadora F.

    2014-06-01

    For all the physical components that comprise a nuclear system there is an uncertainty. Assessing the impact of uncertainties in the simulation of fissionable material systems is essential for a best estimate calculation that has been replacing the conservative model calculations as the computational power increases. The propagation of uncertainty in a simulation using a Monte Carlo code by sampling the input parameters is recent because of the huge computational effort required. In this work a sample space of MCNPX calculations was used to propagate the uncertainty. The sample size was optimized using the Wilks formula for a 95th percentile and a two-sided statistical tolerance interval of 95%. Uncertainties in input parameters of the reactor considered included geometry dimensions and densities. It was showed the capacity of the sampling-based method for burnup when the calculations sample size is optimized and many parameter uncertainties are investigated together, in the same input.

  16. Low-cost image analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Lassahn, G.D.

    1995-01-01

    The author has developed an Automatic Target Recognition system based on parallel processing using transputers. This approach gives a powerful, fast image processing system at relatively low cost. This system scans multi-sensor (e.g., several infrared bands) image data to find any identifiable target, such as physical object or a type of vegetation.

  17. A comparative analysis of methods to represent uncertainty in estimating the cost of constructing wastewater treatment plants.

    Science.gov (United States)

    Chen, Ho-Wen; Chang, Ni-Bin

    2002-08-01

    Prediction of construction cost of wastewater treatment facilities could be influential for the economic feasibility of various levels of water pollution control programs. However, construction cost estimation is difficult to precisely evaluate in an uncertain environment and measured quantities are always burdened with different types of cost structures. Therefore, an understanding of the previous development of wastewater treatment plants and of the related construction cost structures of those facilities becomes essential for dealing with an effective regional water pollution control program. But deviations between the observed values and the estimated values are supposed to be due to measurement errors only in the conventional regression models. The inherent uncertainties of the underlying cost structure, where the human estimation is influential, are rarely explored. This paper is designed to recast a well-known problem of construction cost estimation for both domestic and industrial wastewater treatment plants via a comparative framework. Comparisons were made for three technologies of regression analyses, including the conventional least squares regression method, the fuzzy linear regression method, and the newly derived fuzzy goal regression method. The case study, incorporating a complete database with 48 domestic wastewater treatment plants and 29 industrial wastewater treatment plants being collected in Taiwan, implements such a cost estimation procedure in an uncertain environment. Given that the fuzzy structure in regression estimation may account for the inherent human complexity in cost estimation, the fuzzy goal regression method does exhibit more robust results in terms of some criteria. Moderate economy of scale exists in constructing both the domestic and industrial wastewater treatment plants. Findings indicate that the optimal size of a domestic wastewater treatment plant is approximately equivalent to 15,000 m3/day (CMD) and higher in Taiwan

  18. Development of cost-benefit analysis system

    International Nuclear Information System (INIS)

    Shiba, Tsuyoshi; Mishima, Tetsuya; Yuyama, Tomonori; Suzuki, Atsushi

    2001-01-01

    In order to promote the FDR development, it is necessary to see various benefits brought by introduction of FBR from multiple perspectives and have a good grasp of such benefits quantitatively and an adequate R and D investment scale which corresponds with them. In this study, the structured prototype in the previous study was improved to be able to perform cost-benefit analysis. An example of improvement made in the system is addition of subroutine used for comparison between new energy and benefits brought by introduction of FBR with special emphasis on addition of logic for analyzing externality about the new energy. Other improvement examples are modification of the Conventional Year Expense Ratio method of power generation cost to Average Durable Year Cost method, addition of database function and turning input data into database, and reviewing idea on cost by the type of waste material and price of uranium. The cost-benefit analysis system was also restructured utilizing Microsoft ACCESS so that it should have a data base function. As the result of the improvement mentioned above, we expect that the improved cost-benefit analysis system will have higher generality than the system before; therefore, great deal of benefits brought by application of the system in the future is expected. (author)

  19. Propagation Delay Uncertainty in Time-Of Systems

    Science.gov (United States)

    Feehrer, John Ross

    1995-01-01

    This dissertation presents a study of how propagation delay uncertainty affects the performance of time-of-flight synchronized digital circuits. Time-of-flight synchronization is a new timing method suitable for technologies such as optoelectronics having highly controllable propagation delay. No bistable memory elements are required, and synchronization is accomplished by precise adjustments of interconnect lengths. Delay is distributed over connections so that, nominally, pulses arrive at a common destination simultaneously. Clock gating and pulse stretching are used to restore timing of pulses. Time multiplexing is used to increase computational throughput, whereby a major cycle is divided into a number of minor cycles, each representing an independent virtual machine. What limits the amount of multiplexing that is feasible is the controllability of delay. The principle focus of this research is methods for computing the minimum feasible minor cycle and the amount of stretch needed to prevent synchronization errors. Due to the unique circuit features, timing analysis differs significantly from analysis of conventional digital circuits. Models of delay uncertainty accounting for static and dynamic effects are discussed for discrete and integrated implementations. Methods for placing a minimal set of clock gates necessary for a functional circuit are presented. The minimum feasible major cycle is computed using nominal delays. A method for computing the arrival time and pulse width uncertainty at each node in the circuit is presented. The circuit graph is traversed and device uncertainty functions operating on worst-case input pulse parameters are applied at vertices. Using pulse timing parameters obtained from the traversal, timing constraints are generated. A constrained minimization problem to find the minimum feasible minor cycle is then presented and solved. Two variations on this problem are presented. Circuit structural issues that affect the accuracy of

  20. Optimal operation method coping with uncertainty in multi-area small power systems

    Directory of Open Access Journals (Sweden)

    Shota Tobaru

    2017-07-01

    Full Text Available Japan contains a vast number of isolated islands. Majority of these islands are poweredby diesel generators (DGs, which are operationally not economical. Therefore, the introduction of renewableenergy systems (RESs into these area is very much vital. However, the variability of RESs asa result of weather condition as well as load demand , battery energy storage system (BESS is broughtinto play. Demand response (DR programs have also been so attractive in the energy management systemsfor the past decades. Among them, the real-time pricing (RTP has been one of the most effectivedemand response program being utilized. This program encourages the customer to increase or reducethe load consumption by varying the electricity price. Also, due to the increase in power transactionmarket, Japan electric power exchange (JEPX has established spot (day-ahead, intraday hour-ahead,and forward market programs. This paper utilizes day-ahead and hour-ahead markets, since these marketscan make it possible to deal with uncertainty related to generated power fluctuations. Therefore,this paper presents the optimal operation method coping with the uncertainties of RESs in multi-areasmall power systems. The proposed method enables flexibility to correspond to the forecasting error byproviding two kinds of power markets among multi-area small power systems and trading the shortageand surplus powers. Furthermore, it accomplishes a stable power supply and demand by RTP. Thus, theproposed method was able to reduce operational cost for multi-area small power systems. The processof creating operational plan for RTP, power trading at the markets and the unit commitment of DGs arealso presented in this paper. Simulation results corroborate the merit of the proposed program.

  1. Uncertainty evaluation for a three dimensional rotary measuring system by Markov chain Monte Carlo method

    Science.gov (United States)

    Chen, Bo; Zhang, Xiangchao; Zhang, Hao; He, Xiaoying; Xu, Min

    2013-10-01

    Uncertainty evaluation, which is an effort to set reasonable bounds for the measurement results, is important for assessing the performances of precision measuring systems. The three dimensional measurement is affected by a large number of error sources. The distributions of the primary error sources are analyzed in this paper. The multiple-try Metropolis (MTM) algorithm is applied for sampling and propagation of uncertainty for these error sources due to its advantage in dealing with large dimensional problems. The uncertainties of the three coordinates of a measured point on the workpiece r, z, and θ are evaluated before and after error separation, respectively. The differences between the two types of uncertainties are compared to find out the influence of the error separation to the uncertainty. Finally, numerical experiments are implemented to demonstrate the uncertainty assessment process.

  2. Accounting for data uncertainties in comparing risks from energy systems

    International Nuclear Information System (INIS)

    Hauptmanns, Ulrich

    1998-01-01

    Data and models for risk comparisons are uncertain and this is true all the more the larger the time horizon contemplated. Statistical methods are presented for dealing with data uncertainties thus providing a broader foundation for decisions. Nevertheless, it has to be borne in mind that no method exists to account for the 'unforeseeable' which is always present in decision making with respect to the far future. (author)

  3. INTEGRATION OF SYSTEM COMPONENTS AND UNCERTAINTY ANALYSIS - HANFORD EXAMPLES

    International Nuclear Information System (INIS)

    Wood, M.I.

    2009-01-01

    (sm b ullet) Deterministic 'One Off' analyses as basis for evaluating sensitivity and uncertainty relative to reference case (sm b ullet) Spatial coverage identical to reference case (sm b ullet) Two types of analysis assumptions - Minimax parameter values around reference case conditions - 'What If' cases that change reference case condition and associated parameter values (sm b ullet) No conclusions about likelihood of estimated result other than' qualitative expectation that actual outcome should tend toward reference case estimate

  4. Observation of quantum-memory-assisted entropic uncertainty relation under open systems, and its steering

    Science.gov (United States)

    Chen, Peng-Fei; Sun, Wen-Yang; Ming, Fei; Huang, Ai-Jun; Wang, Dong; Ye, Liu

    2018-01-01

    Quantum objects are susceptible to noise from their surrounding environments, interaction with which inevitably gives rise to quantum decoherence or dissipation effects. In this work, we examine how different types of local noise under an open system affect entropic uncertainty relations for two incompatible measurements. Explicitly, we observe the dynamics of the entropic uncertainty in the presence of quantum memory under two canonical categories of noisy environments: unital (phase flip) and nonunital (amplitude damping). Our study shows that the measurement uncertainty exhibits a non-monotonic dynamical behavior—that is, the amount of the uncertainty will first inflate, and subsequently decrease, with the growth of decoherence strengths in the two channels. In contrast, the uncertainty decreases monotonically with the growth of the purity of the initial state shared in prior. In order to reduce the measurement uncertainty in noisy environments, we put forward a remarkably effective strategy to steer the magnitude of uncertainty by means of a local non-unitary operation (i.e. weak measurement) on the qubit of interest. It turns out that this non-unitary operation can greatly reduce the entropic uncertainty, upon tuning the operation strength. Our investigations might thereby offer an insight into the dynamics and steering of entropic uncertainty in open systems.

  5. Bottom-up uncertainty estimates of global ammonia emissions from global agricultural production systems

    NARCIS (Netherlands)

    Beusen, A.H.W.; Bouwman, A.F.; Heuberger, P.S.C.; Drecht, van G.; Hoek, van der K.W.

    2008-01-01

    Here we present an uncertainty analysis of NH3 emissions from agricultural production systems based on a global NH3 emission inventory with a 5×5 min resolution. Of all results the mean is given with a range (10% and 90% percentile). The uncertainty range for the global NH3 emission from

  6. Users manual for the FORSS sensitivity and uncertainty analysis code system

    International Nuclear Information System (INIS)

    Lucius, J.L.; Weisbin, C.R.; Marable, J.H.; Drischler, J.D.; Wright, R.Q.; White, J.E.

    1981-01-01

    FORSS is a code system used to study relationships between nuclear reaction cross sections, integral experiments, reactor performance parameter predictions and associated uncertainties. This report describes the computing environment and the modules currently used to implement FORSS Sensitivity and Uncertainty Methodology

  7. using fuzzy-robust approach for minimizing transportation and fuel costs in location problem under uncertainty

    Directory of Open Access Journals (Sweden)

    hasan hosseini nasab

    2016-02-01

    Full Text Available Operations research is a commonly used method in many subjects nowadays. One applicable domain of operation research is the problem of facility layout and location. In this paper, a new mathematical programing model is developed for an optimal facility location and assignment. The model includes two objective functions. The first one minimizes the total material handling and fixed costs of facility location. Because of the importance of energy and the main role of fossil fuel in transportation, the second objective function, minimizes the total cost of fuel consumption. To consider the real condition in the proposed model, the cost of fuel, is considered to increase stepwise gradually. In the proposed model the coefficients of objective function are considered to be probabilistic and some of constraints to be fuzzy variables. Using a new approach, this model can be changed to a robust model. To prove the applicability of the model, it is examined for a real condition of facility location.

  8. Accounting for uncertainty in the quantification of the environmental impacts of Canadian pig farming systems.

    Science.gov (United States)

    Mackenzie, S G; Leinonen, I; Ferguson, N; Kyriazakis, I

    2015-06-01

    The objective of the study was to develop a life cycle assessment (LCA) for pig farming systems that would account for uncertainty and variability in input data and allow systematic environmental impact comparisons between production systems. The environmental impacts of commercial pig production for 2 regions in Canada (Eastern and Western) were compared using a cradle-to-farm gate LCA. These systems had important contrasting characteristics such as typical feed ingredients used, herd performance, and expected emission factors from manure management. The study used detailed production data supplied by the industry and incorporated uncertainty/variation in all major aspects of the system including life cycle inventory data for feed ingredients, animal performance, energy inputs, and emission factors. The impacts were defined using 5 metrics-global warming potential, acidification potential, eutrophication potential (EP), abiotic resource use, and nonrenewable energy use-and were expressed per kilogram carcass weight at farm gate. Eutrophication potential was further separated into marine EP (MEP) and freshwater EP (FEP). Uncertainties in the model inputs were separated into 2 types: uncertainty in the data used to describe the systemuncertainties) and uncertainty in impact calculations or background data that affects all systems equally (β uncertainties). The impacts of pig production in the 2 regions were systematically compared based on the differences in the systemsuncertainties). The method of ascribing uncertainty influenced the outcomes. In eastern systems, EP, MEP, and FEP were lower (P < 0.05) when assuming that all uncertainty in the emission factors for leaching from manure application was β. This was mainly due to increased EP resulting from field emissions for typical ingredients in western diets. When uncertainty in these emission factors was assumed to be α, only FEP was lower in eastern systems (P < 0.05). The environmental impacts for

  9. Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

    Directory of Open Access Journals (Sweden)

    Ryusuke Konishi

    2018-01-01

    Full Text Available In deregulated electricity markets, minimizing the procurement costs of electricity is a critical problem for procurement agencies (PAs. However, uncertainty is inevitable for PAs and includes multiple factors such as market prices, photovoltaic system (PV output and demand. This study focuses on settlements in multi-period markets (a day-ahead market and a real-time market and the installation of energy storage systems (ESSs. ESSs can be utilized for time arbitrage in the day-ahead market and to reduce the purchasing/selling of electricity in the real-time market. However, the high costs of an ESS mean the size of the system needs to be minimized. In addition, when determining the size of an ESS, it is important to identify the size appropriate for each role. Therefore, we employ the concept of a “slow” and a “fast” ESS to quantify the size of a system’s role, based on the values associated with the various uncertainties. Because the problem includes nonlinearity and non-convexity, we solve it within a realistic computational burden by reformulating the problem using reasonable assumptions. Therefore, this study identifies the optimal sizes of ESSs and procurement, taking into account the uncertainties of prices in multi-period markets, PV output and demand.

  10. Reduction of entropic uncertainty in entangled qubits system by local PT-symmetric operation

    International Nuclear Information System (INIS)

    Zhang Shi-Yang; Fang Mao-Fa; Zhang Yan-Liang; Guo You-Neng; Zhao Yan-Jun; Tang Wu-Wei

    2015-01-01

    We investigate the quantum-memory-assisted entropic uncertainty for an entangled two-qubit system in a local quantum noise channel with -symmetric operation performing on one of the two particles. Our results show that the quantum-memory-assisted entropic uncertainty in the qubits system can be reduced effectively by the local -symmetric operation. Physical explanations for the behavior of the quantum-memory-assisted entropic uncertainty are given based on the property of entanglement of the qubits system and the non-locality induced by the re-normalization procedure for the non-Hermitian -symmetric operation. (paper)

  11. [Relationship between cost systems and hospital expenditure].

    Science.gov (United States)

    García-Cornejo, Beatriz; Pérez-Méndez, José A

    To analyze the relationship between the degree of development of hospital cost systems (CS) implemented by the regional health services (RHS) and the variation in unit cost of hospitals in Spanish National Health Service (NHS) between 2010 and 2013 and to identify other explanatory factors of this variation. A database of NHS hospitals was constructed from exclusively public sources. Using a multilevel regression model, explaining factors of the variation in unit cost (cost per weighted unit of activity [WAU]) of a sample of 170 hospitals were analyzed. The variables representative of the degree of development of CS are associated in a negative and significant way with the variation of the cost per WAU. It is observed that if a high-level development CS is used the cost variation per WAU would be reduced by close to 3.2%. There is also a negative and significant relationship between the variation in the cost per WAU and the variations in the percentage of high technology and the hospital occupancy rate. On the other hand, the variations in the average cost of personnel and in the number of workers per 100 beds are associated in a positive and significant way with the variation of the cost per WAU. In the period analysed, during which the main health expenditure adjustment was made, the control in hospital unit cost is associated not only with spending cuts but also with aspects related to their management, such as the implementation of more developed CS. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

  12. Verification and uncertainty evaluation of HELIOS/MASTER nuclear design system

    Energy Technology Data Exchange (ETDEWEB)

    Song, Jae Seung; Kim, J. C.; Cho, B. O. [Korea Atomic Energy Research Institute, Taejon (Korea)

    1999-03-01

    A nuclear design system HELIOS/MASTER was established and core follow calculations were performed for Yonggwang Unit 1 cycles 1 through 7 and Yonggwang Unit 3 cycles 1 through 2. The accuracy of HELIOS/MASTER system was evaluated by estimations of uncertainties of reactivity and peaking factors and by comparisons of the maximum differences of isothermal temperature coefficient, inverse boron worth and control rod worth with the CASMO-3/MASTER uncertainties. The reactivity uncertainty was estimated by 362 pcm, and the uncertainties of three-dimensional, axially integrated radial, and planar peaking factors were evaluated by 0.048, 0.034, and 0.044 in relative power unit, respectively. The maximum differences of isothermal temperature coefficient, inverse boron worth and control rod worth were within the CASMO-3/MASTER uncertainties. 17 refs., 17 figs., 10 tabs. (Author)

  13. Final Report: Hydrogen Storage System Cost Analysis

    Energy Technology Data Exchange (ETDEWEB)

    James, Brian David [Strategic Analysis Inc., Arlington, VA (United States); Houchins, Cassidy [Strategic Analysis Inc., Arlington, VA (United States); Huya-Kouadio, Jennie Moton [Strategic Analysis Inc., Arlington, VA (United States); DeSantis, Daniel A. [Strategic Analysis Inc., Arlington, VA (United States)

    2016-09-30

    The Fuel Cell Technologies Office (FCTO) has identified hydrogen storage as a key enabling technology for advancing hydrogen and fuel cell power technologies in transportation, stationary, and portable applications. Consequently, FCTO has established targets to chart the progress of developing and demonstrating viable hydrogen storage technologies for transportation and stationary applications. This cost assessment project supports the overall FCTO goals by identifying the current technology system components, performance levels, and manufacturing/assembly techniques most likely to lead to the lowest system storage cost. Furthermore, the project forecasts the cost of these systems at a variety of annual manufacturing rates to allow comparison to the overall 2017 and “Ultimate” DOE cost targets. The cost breakdown of the system components and manufacturing steps can then be used to guide future research and development (R&D) decisions. The project was led by Strategic Analysis Inc. (SA) and aided by Rajesh Ahluwalia and Thanh Hua from Argonne National Laboratory (ANL) and Lin Simpson at the National Renewable Energy Laboratory (NREL). Since SA coordinated the project activities of all three organizations, this report includes a technical description of all project activity. This report represents a summary of contract activities and findings under SA’s five year contract to the US Department of Energy (Award No. DE-EE0005253) and constitutes the “Final Scientific Report” deliverable. Project publications and presentations are listed in the Appendix.

  14. Distribution system costs associated with the deployment of photovoltaic systems

    Energy Technology Data Exchange (ETDEWEB)

    Horowitz, Kelsey A. W.; Palmintier, Bryan; Mather, Barry; Denholm, Paul

    2018-07-01

    The broadening of our energy system to include increasing amounts of wind and solar has led to significant debate about the total costs and benefits associated with different types of generators - with potentially far-reaching policy implications. This has included debate about the cost associated with integrating these generators onto the electric grid. For photovoltaics (PV), this encompasses costs incurred on both the bulk power and distribution systems, as well as the value provided to them. These costs and benefits, in particular those associated with integrating PV onto the distribution system, are not well understood. We seek to advance the state of understanding of 'grid integration costs' for the distribution system by reviewing prior literature and outlining a transparent, bottom-up approach that can be used to calculate these costs. We provide a clear delineation of costs to integrate PV in to the distribution system within the larger context of total costs and benefits associated with PV generators. We emphasize that these costs are situationally dependent, and that a single 'cost of integration' cannot be obtained. We additionally emphasize that benefits must be considered when evaluating the competitiveness of the technology in a given situation.

  15. Integrated waste management system costs in a MPC system

    International Nuclear Information System (INIS)

    Supko, E.M.

    1995-01-01

    The impact on system costs of including a centralized interim storage facility as part of an integrated waste management system based on multi-purpose canister (MPC) technology was assessed in analyses by Energy Resources International, Inc. A system cost savings of $1 to $2 billion occurs if the Department of Energy begins spent fuel acceptance in 1998 at a centralized interim storage facility. That is, the savings associated with decreased utility spent fuel management costs will be greater than the cost of constructing and operating a centralized interim storage facility

  16. Development of Uncertainty Analysis Method for SMART Digital Core Protection and Monitoring System

    International Nuclear Information System (INIS)

    Koo, Bon Seung; In, Wang Kee; Hwang, Dae Hyun

    2012-01-01

    The Korea Atomic Energy Research Institute has developed a system-integrated modular advanced reactor (SMART) for a seawater desalination and electricity generation. Online digital core protection and monitoring systems, called SCOPS and SCOMS respectively were developed. SCOPS calculates minimum DNBR and maximum LPD based on the several online measured system parameters. SCOMS calculates the variables of limiting conditions for operation. KAERI developed overall uncertainty analysis methodology which is used statistically combining uncertainty components of SMART core protection and monitoring system. By applying overall uncertainty factors in on-line SCOPS/SCOMS calculation, calculated LPD and DNBR are conservative with a 95/95 probability/confidence level. In this paper, uncertainty analysis method is described for SMART core protection and monitoring system

  17. Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-09-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique

  18. Multi-objective optimization for hybrid fuel cells power system under uncertainty

    Science.gov (United States)

    Subramanyan, Karthik; Diwekar, Urmila M.; Goyal, Amit

    One of the major applications of fuel cells is as onsite stationary electric power plants. Several types of configurations have been hypothesized and tested for these kinds of applications at the conceptual level but hybrid power plants are one of the most efficient. These are designs that combine a fuel cell cycle with other thermodynamic cycles to provide higher efficiency. Generally, the heat rejected by the fuel cell at a higher temperature is used in a bottoming cycle to generate steam. In this work we are considering a conceptual design of a solid oxide fuel cell-proton exchange membrane (SOFC-PEM) fuel cell hybrid power plant [R. Geisbrecht, Compact Electrochemical Reformer Based on SOFC Technology, AIChE Spring National Meeting, Atlanta, GA, 2000] in which the high temperature SOFC fuel cell acts both as electricity producer and fuel reformer for the low temperature PEM fuel cell (PEMFC). The exhaust from the PEM fuel cell goes to a waste hydrogen burner and heat recovery steam generator that produces steam for further utilizations. Optimizing this conceptual design involves consideration of a number of objectives. The process should have low pollutant emissions as well as cost competitive with the existing technology. The solution of a multi-objective optimization problem is not a single solution but a complete non-dominated or Pareto set, which includes the alternatives representing potential compromise solutions among the objectives. This makes a range of choice available to decision makers and provides them with the trade-off information among the multiple objectives effectively. This paper presents the optimal trade-off design solutions or the Pareto set for this hybrid power plant through a multi-objective optimization framework. This hybrid technology is new and the system level models used for fuel cells performance have significant uncertainties in them. In this paper, we characterize these uncertainties and study the effect of these uncertainties

  19. Using cost/risk uncertainty spheres to make better environmental restoration decisions

    International Nuclear Information System (INIS)

    Shangraw, R.F.; Cheney, C.S.; Shangraw, W.R.

    1994-01-01

    The process of balancing cost expenditures and risk reductions during environmental restoration (ER) activities (and as part of other environmental programs such as waste management and facility transition) is the critical policy decision facing DOE site decisionmakers and associated stakeholders (including regulators). The ground rules for this process are specified formally in the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), as amended, the Resource Conservation and Recovery Act, as amended, the subsequent regulations (e.g., National Contingency Plan) and policies that EPA and State agencies have issued to implement these programs, and (increasingly) interagency agreements and orders. Clearly, as Federal resources to meet environmental commitments become more constrained, cost and risk management tradeoffs will become even more needed and their results pronounced

  20. Propagation of uncertainty in system parameters of a LWR model by sampling MCNPX calculations - Burnup analysis

    International Nuclear Information System (INIS)

    Campolina, D. de A. M.; Lima, C.P.B.; Veloso, M.A.F.

    2013-01-01

    For all the physical components that comprise a nuclear system there is an uncertainty. Assessing the impact of uncertainties in the simulation of fissionable material systems is essential for a best estimate calculation that has been replacing the conservative model calculations as the computational power increases. The propagation of uncertainty in a simulation using a Monte Carlo code by sampling the input parameters is recent because of the huge computational effort required. In this work a sample space of MCNPX calculations was used to propagate the uncertainty. The sample size was optimized using the Wilks formula for a 95. percentile and a two-sided statistical tolerance interval of 95%. Uncertainties in input parameters of the reactor considered included geometry dimensions and densities. It was showed the capacity of the sampling-based method for burnup when the calculations sample size is optimized and many parameter uncertainties are investigated together, in the same input. Particularly it was shown that during the burnup, the variances when considering all the parameters uncertainties is equivalent to the sum of variances if the parameter uncertainties are sampled separately

  1. Filmless versus film-based systems in radiographic examination costs: an activity-based costing method

    OpenAIRE

    Muto, Hiroshi; Tani, Yuji; Suzuki, Shigemasa; Yokooka, Yuki; Abe, Tamotsu; Sase, Yuji; Terashita, Takayoshi; Ogasawara, Katsuhiko

    2011-01-01

    Abstract Background Since the shift from a radiographic film-based system to that of a filmless system, the change in radiographic examination costs and costs structure have been undetermined. The activity-based costing (ABC) method measures the cost and performance of activities, resources, and cost objects. The purpose of this study is to identify the cost structure of a radiographic examination comparing a filmless system to that of a film-based system using the ABC method. Methods We calc...

  2. Roles of nuclear power system in the presence of uncertainties from global warming

    International Nuclear Information System (INIS)

    Kiriyama, Eriko; Iwata, Shuichi

    2005-01-01

    Environmental 'bads' like carbon dioxide are not simply incorporated in the market system. The costs involved, however, do not really reflect the inherent value of the environment, or what it is worth to them. This study focuses on the uncertainty of CO 2 emission credits. Assigning economic values to environmental goods and services is complex, but it is an area that is receiving considerable attention from environmental economists. The purpose of this study is to analyze the value of an investment in power generation assets that do not emit CO 2 . To deal with the CO 2 emission credit, we built new models based on the real option model by Pindyck (2000). In the modern, market-based financial systems that dominate the global economy, the value of a resource is represented by the price that an individual or a group is willing to pay for it. Managing CO 2 emission limitations will be a critical aspect of power generation systems. And it will be increasingly so as the emphasis on global environmental issues continues to rise. In order to secure the effectiveness of measures against global warming, we should reconsider the role of nuclear power systems. (author)

  3. Cost estimating issues in the Russian integrated system planning context

    International Nuclear Information System (INIS)

    Allentuck, J.

    1996-01-01

    An important factor in the credibility of an optimal capacity expansion plan is the accuracy of cost estimates given the uncertainty of future economic conditions. This paper examines the problems associated with estimating investment and operating costs in the Russian nuclear power context over the period 1994 to 2010

  4. The relationship between cost system complexity, purposes of use, and cost system effectiveness

    NARCIS (Netherlands)

    Schoute, M.

    2009-01-01

    This paper uses survey data from 133 Dutch, medium-sized manufacturing firms to examine the associations between cost system complexity (in terms of the applied overhead absorption procedures), purposes of use, and cost system effectiveness. First, factor analysis identifies two underlying

  5. Preliminary Uncertainty Analysis for SMART Digital Core Protection and Monitoring System

    International Nuclear Information System (INIS)

    Koo, Bon Seung; In, Wang Kee; Hwang, Dae Hyun

    2012-01-01

    The Korea Atomic Energy Research Institute (KAERI) developed on-line digital core protection and monitoring systems, called SCOPS and SCOMS as a part of SMART plant protection and monitoring system. SCOPS simplified the protection system by directly connecting the four RSPT signals to each core protection channel and eliminated the control element assembly calculator (CEAC) hardware. SCOMS adopted DPCM3D method in synthesizing core power distribution instead of Fourier expansion method being used in conventional PWRs. The DPCM3D method produces a synthetic 3-D power distribution by coupling a neutronics code and measured in-core detector signals. The overall uncertainty analysis methodology which is used statistically combining uncertainty components of SMART core protection and monitoring system was developed. In this paper, preliminary overall uncertainty factors for SCOPS/SCOMS of SMART initial core were evaluated by applying newly developed uncertainty analysis method

  6. A new system to quantify uncertainties in LEO satellite position determination due to space weather events

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop a new system for quantitative assessment of uncertainties in LEO satellite position caused by storm time changes in space environmental...

  7. Understanding uncertainty propagation in life cycle assessments of waste management systems

    DEFF Research Database (Denmark)

    Bisinella, Valentina; Conradsen, Knut; Christensen, Thomas Højlund

    2015-01-01

    Uncertainty analysis in Life Cycle Assessments (LCAs) of waste management systems often results obscure and complex, with key parameters rarely determined on a case-by-case basis. The paper shows an application of a simplified approach to uncertainty coupled with a Global Sensitivity Analysis (GSA......) perspective on three alternative waste management systems for Danish single-family household waste. The approach provides a fast and systematic method to select the most important parameters in the LCAs, understand their propagation and contribution to uncertainty....

  8. Risk aversion and uncertainty in cost-effectiveness analysis: the expected-utility, moment-generating function approach.

    Science.gov (United States)

    Elbasha, Elamin H

    2005-05-01

    The availability of patient-level data from clinical trials has spurred a lot of interest in developing methods for quantifying and presenting uncertainty in cost-effectiveness analysis (CEA). Although the majority has focused on developing methods for using sample data to estimate a confidence interval for an incremental cost-effectiveness ratio (ICER), a small strand of the literature has emphasized the importance of incorporating risk preferences and the trade-off between the mean and the variance of returns to investment in health and medicine (mean-variance analysis). This paper shows how the exponential utility-moment-generating function approach is a natural extension to this branch of the literature for modelling choices from healthcare interventions with uncertain costs and effects. The paper assumes an exponential utility function, which implies constant absolute risk aversion, and is based on the fact that the expected value of this function results in a convenient expression that depends only on the moment-generating function of the random variables. The mean-variance approach is shown to be a special case of this more general framework. The paper characterizes the solution to the resource allocation problem using standard optimization techniques and derives the summary measure researchers need to estimate for each programme, when the assumption of risk neutrality does not hold, and compares it to the standard incremental cost-effectiveness ratio. The importance of choosing the correct distribution of costs and effects and the issues related to estimation of the parameters of the distribution are also discussed. An empirical example to illustrate the methods and concepts is provided. Copyright 2004 John Wiley & Sons, Ltd

  9. Uncertainty in prediction and simulation of flow in sewer systems

    DEFF Research Database (Denmark)

    Breinholt, Anders

    were obtained. The Akaike’s (AIC) and the Bayesian (BIC) information criteria were used to identify preferred models for the one-step prediction whereas a skill scoring criterion addressing both the reliability and the sharpness of the confidence bounds was used when assessing the forecasting...... autocorrelation remained in the simulation case. A skill scoring comparison of a simulation and a prediction model showed that a major improvement is gained by updating the model states continuously, i.e. updating of model states results in much lower forecasting uncertainty at shorter prediction steps....... In the GLUE methodology there are no requirements to the residuals. Nevertheless the aim is the same as for the stochastic simulation models, namely to cover a proportion of observations consistent with the considered quantile with maximum sharpness, i.e. to minimise the skill score. In one calibration case...

  10. Activity-Based Costing Systems for Higher Education.

    Science.gov (United States)

    Day, Dennis H.

    1993-01-01

    Examines traditional costing models utilized in higher education and pinpoints shortcomings related to proper identification of costs. Describes activity-based costing systems as a superior alternative for cost identification, measurement, and allocation. (MLF)

  11. Number-phase entropic uncertainty relations and Wigner functions for solvable quantum systems with discrete spectra

    Energy Technology Data Exchange (ETDEWEB)

    Honarasa, G.R., E-mail: honarasa@sutech.ac.i [Atomic and Molecular Group, Faculty of Physics, Yazd University, Yazd (Iran, Islamic Republic of); Tavassoly, M.K., E-mail: mktavassoly@yazduni.ac.i [Atomic and Molecular Group, Faculty of Physics, Yazd University, Yazd (Iran, Islamic Republic of); Hatami, M., E-mail: mhatami@yazduni.ac.i [Atomic and Molecular Group, Faculty of Physics, Yazd University, Yazd (Iran, Islamic Republic of)

    2009-10-19

    In this Letter, the 'number-phase entropic uncertainty relation' and the 'number-phase Wigner function' of generalized coherent states associated to a few solvable quantum systems with non-degenerate spectra are studied. We also investigate time evolution of 'number-phase entropic uncertainty' and 'Wigner function' of the considered physical systems with the help of temporally stable Gazeau-Klauder coherent states.

  12. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  13. Computing the uncertainty associated with the control of ecological and biological systems

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2013-09-01

    Full Text Available Recently, I showed that ecological and biological networks can be controlled by coupling their dynamics to evolutionary modelling. This provides numerous solutions to the goal of guiding a system's behaviour towards the desired result. In this paper, I face another important question: how reliable is the achieved solution? In other words, which is the degree of uncertainty about getting the desired result if values of edges and nodes were a bit different from optimized ones? This is a pivotal question, because it's not assured that while managing a certain system we are able to impose to nodes and edges exactly the optimized values we would need in order to achieve the desired results. In order to face this topic, I have formulated here a 3-parts framework (network dynamics - genetic optimization - stochastic simulations and, using an illustrative example, I have been able to detect the most reliable solution to the goal of network control. The proposed framework could be used to: a counteract damages to ecological and biological networks, b safeguard rare and endangered species, c manage systems at the least possible cost, and d plan optimized bio-manipulations.

  14. 78 FR 7718 - Review of the General Purpose Costing System

    Science.gov (United States)

    2013-02-04

    .... EP 431 (Sub-No. 4)] Review of the General Purpose Costing System AGENCY: Surface Transportation Board... Transportation Board (Board) is proposing certain changes to its general purpose costing system, the Uniform... general purpose costing system. Adoption of the Unif. R.R. Costing Sys. as a Gen. Purpose Costing Sys. for...

  15. An H∞ suboptimal robust control approach for systems with uncertainties and data dropouts

    Science.gov (United States)

    Jurado, Isabel; Ortega, Manuel G.; Quevedo, Daniel E.; Rubio, Francisco R.

    2015-08-01

    This paper studies the design of control systems subject to plant uncertainties and data losses in the channel connecting the plant sensor with the controller. The controller design has two main objectives. The first one is to robustify the control law against plant uncertainties. The other one is to achieve good performance by minimising the variance of the error signal. Data losses are modelled as an independent and identically distributed sequence of Bernoulli random variables. For analysis and design, this random variable is replaced by an additive noise plus gain channel model. To cope with structural uncertainties in the model of the plant, an H∞ control technique is employed. The controller is synthesised in order to make the closed-loop system robust against structural uncertainties of the nominal model, while achieving optimal performance of the system in the presence of dropouts.

  16. Using finite mixture models in thermal-hydraulics system code uncertainty analysis

    Energy Technology Data Exchange (ETDEWEB)

    Carlos, S., E-mail: scarlos@iqn.upv.es [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Sánchez, A. [Department d’Estadística Aplicada i Qualitat, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Ginestar, D. [Department de Matemàtica Aplicada, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Martorell, S. [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain)

    2013-09-15

    Highlights: • Best estimate codes simulation needs uncertainty quantification. • The output variables can present multimodal probability distributions. • The analysis of multimodal distribution is performed using finite mixture models. • Two methods to reconstruct output variable probability distribution are used. -- Abstract: Nuclear Power Plant safety analysis is mainly based on the use of best estimate (BE) codes that predict the plant behavior under normal or accidental conditions. As the BE codes introduce uncertainties due to uncertainty in input parameters and modeling, it is necessary to perform uncertainty assessment (UA), and eventually sensitivity analysis (SA), of the results obtained. These analyses are part of the appropriate treatment of uncertainties imposed by current regulation based on the adoption of the best estimate plus uncertainty (BEPU) approach. The most popular approach for uncertainty assessment, based on Wilks’ method, obtains a tolerance/confidence interval, but it does not completely characterize the output variable behavior, which is required for an extended UA and SA. However, the development of standard UA and SA impose high computational cost due to the large number of simulations needed. In order to obtain more information about the output variable and, at the same time, to keep computational cost as low as possible, there has been a recent shift toward developing metamodels (model of model), or surrogate models, that approximate or emulate complex computer codes. In this way, there exist different techniques to reconstruct the probability distribution using the information provided by a sample of values as, for example, the finite mixture models. In this paper, the Expectation Maximization and the k-means algorithms are used to obtain a finite mixture model that reconstructs the output variable probability distribution from data obtained with RELAP-5 simulations. Both methodologies have been applied to a separated

  17. Reliability/Cost Evaluation on Power System connected with Wind Power for the Reserve Estimation

    DEFF Research Database (Denmark)

    Lee, Go-Eun; Cha, Seung-Tae; Shin, Je-Seok

    2012-01-01

    Wind power is ideally a renewable energy with no fuel cost, but has a risk to reduce reliability of the whole system because of uncertainty of the output. If the reserve of the system is increased, the reliability of the system may be improved. However, the cost would be increased. Therefore...... the reserve needs to be estimated considering the trade-off between reliability and economic aspects. This paper suggests a methodology to estimate the appropriate reserve, when wind power is connected to the power system. As a case study, when wind power is connected to power system of Korea, the effects...

  18. Quantifying Uncertainty in Early Lifecycle Cost Estimation for DOD Major Defense Acquisition Programs

    Science.gov (United States)

    2012-10-31

    Prod uc F22 cond 1 Contract cond 2 Function cond 3 CONOPS For C2 systems, how often does Strategic Vision change? Records show that...System De cond 3 CapDef JTRS cond 1 InterOpera cond 2 Prod uctio F22 cond 1 Contract cond 2 Functional cond 3 CONOPS The Materiel

  19. Uncertainty analysis technique of dynamic response and cumulative damage properties of piping system

    International Nuclear Information System (INIS)

    Suzuki, Kohei; Aoki, Shigeru; Hara, Fumio; Hanaoka, Masaaki; Yamashita, Tadashi.

    1982-01-01

    It is a technologically important subject to establish the method of uncertainty analysis statistically examining the variation of the earthquake response and damage properties of equipment and piping system due to the change of input load and the parameters of structural system, for evaluating the aseismatic capability and dynamic structural reliability of these systems. The uncertainty in the response and damage properties when equipment and piping system are subjected to excessive vibration load is mainly dependent on the irregularity of acting input load such as the unsteady vibration of earthquakes, and structural uncertainty in forms and dimensions. This study is the basic one to establish the method for evaluating the uncertainty in the cumulative damage property at the time of resonant vibration of piping system due to the disperse of structural parameters with a simple model. First, the piping models with simple form were broken by resonant vibration, and the uncertainty in the cumulative damage property was evaluated. Next, the response analysis using an elasto-plastic mechanics model was performed by numerical simulation. Finally, the method of uncertainty analysis for response and damage properties by the perturbation method utilizing equivalent linearization was proposed, and its propriety was proved. (Kako, I.)

  20. Cost effectiveness of recycling: a systems model.

    Science.gov (United States)

    Tonjes, David J; Mallikarjun, Sreekanth

    2013-11-01

    Financial analytical models of waste management systems have often found that recycling costs exceed direct benefits, and in order to economically justify recycling activities, externalities such as household expenses or environmental impacts must be invoked. Certain more empirically based studies have also found that recycling is more expensive than disposal. Other work, both through models and surveys, have found differently. Here we present an empirical systems model, largely drawn from a suburban Long Island municipality. The model accounts for changes in distribution of effort as recycling tonnages displace disposal tonnages, and the seven different cases examined all show that curbside collection programs that manage up to between 31% and 37% of the waste stream should result in overall system savings. These savings accrue partially because of assumed cost differences in tip fees for recyclables and disposed wastes, and also because recycling can result in a more efficient, cost-effective collection program. These results imply that increases in recycling are justifiable due to cost-savings alone, not on more difficult to measure factors that may not impact program budgets. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Working paper : the ITS cost data repository at Mitretek Systems

    Science.gov (United States)

    1998-11-30

    Mitretek Systems has been tasked by the Intelligent Transportation Systems (ITS) Joint Program Office (JPO) to collect available information on ITS costs and maintain the information in a cost database, which serves as the ITS Cost Data Repository. T...

  2. PLACE OF PRODUCTION COSTS SYSTEM ANALYSIS IN SYSTEM ANALYSIS

    Directory of Open Access Journals (Sweden)

    Mariia CHEREDNYCHENKO

    2016-12-01

    Full Text Available Current economic conditions require the development and implementation of an adequate system of production costs, which would ensure a steady profit growth and production volumes in a highly competitive, constantly increasing input prices and tariffs. This management system must be based on an integrated production costs system analysis (PCSA, which would provide all operating costs management subsystems necessary information to design and make better management decisions. It provides a systematic analysis of more opportunities in knowledge, creating conditions of integrity mechanism knowledge object consisting of elements that show intersystem connections, each of which has its own defined and limited objectives, relationship with the environment.

  3. [Method for optimal sensor placement in water distribution systems with nodal demand uncertainties].

    Science.gov (United States)

    Liu, Shu-Ming; Wu, Xue; Ouyang, Le-Yan

    2013-08-01

    The notion of identification fitness was proposed for optimizing sensor placement in water distribution systems. Nondominated Sorting Genetic Algorithm II was used to find the Pareto front between minimum overlap of possible detection times of two events and the best probability of detection, taking nodal demand uncertainties into account. This methodology was applied to an example network. The solutions show that the probability of detection and the number of possible locations are not remarkably affected by nodal demand uncertainties, but the sources identification accuracy declines with nodal demand uncertainties.

  4. Using the sampling method to propagate uncertainties of physical parameters in systems with fissile material

    International Nuclear Information System (INIS)

    Campolina, Daniel de Almeida Magalhães

    2015-01-01

    There is an uncertainty for all the components that comprise the model of a nuclear system. Assessing the impact of uncertainties in the simulation of fissionable material systems is essential for a realistic calculation that has been replacing conservative model calculations as the computational power increases. The propagation of uncertainty in a simulation using a Monte Carlo code by sampling the input parameters is recent because of the huge computational effort required. By analyzing the propagated uncertainty to the effective neutron multiplication factor (k eff ), the effects of the sample size, computational uncertainty and efficiency of a random number generator to represent the distributions that characterize physical uncertainty in a light water reactor was investigated. A program entitled GB s ample was implemented to enable the application of the random sampling method, which requires an automated process and robust statistical tools. The program was based on the black box model and the MCNPX code was used in and parallel processing for the calculation of particle transport. The uncertainties considered were taken from a benchmark experiment in which the effects in k eff due to physical uncertainties is done through a conservative method. In this work a script called GB s ample was implemented to automate the sampling based method, use multiprocessing and assure the necessary robustness. It has been found the possibility of improving the efficiency of the random sampling method by selecting distributions obtained from a random number generator in order to obtain a better representation of uncertainty figures. After the convergence of the method is achieved, in order to reduce the variance of the uncertainty propagated without increase in computational time, it was found the best number o components to be sampled. It was also observed that if the sampling method is used to calculate the effect on k eff due to physical uncertainties reported by

  5. Unit Commitment: Computational Performance, System Representation and Wind Uncertainty Management

    NARCIS (Netherlands)

    Morales Espana, G.

    2014-01-01

    In recent years, high penetration of variable generating sources, such as wind power, has challenged independent system operators (ISO) in keeping a cheap and reliable power system operation. Any deviation between expected and real wind production must be absorbed by the power system resources

  6. Multilevel Production Systems with Dependent Demand with Uncertainty of Lead Times

    Directory of Open Access Journals (Sweden)

    Haibatolah Sadeghi

    2016-01-01

    Full Text Available This study considers a multilevel assembly system with several components in each sublevel. It is assumed that actual lead time for all components is probabilistic; and periodic order quantity (POQ policy for ordering is utilized. If at a certain level a job is not received at the expected time, a delay is incurred at the delivery of production at this level and this may result in backorders of the finished product. It is assumed in this case that a fixed percentage of the shortage is backlogged and other sales are lost. In the real situation, some but not all customers will wait for backlogged components during a period of shortage, such as for fashionable commodities or high-tech products with the short product life cycle. The objective of this study is to find the planned lead time and periodicity for the total components in order to minimize the expected fixed ordering, holding, and partial backlogging costs for the finished product. In this study, it is assumed that a percentage of components at each level are scrap. A general mathematical model is suggested and the method developed can be used for optimization planned lead time and periodicity for such an MRP system under lead time uncertainties.

  7. MODELLING OF UNCERTAINTY IN MINIMISING THE COST OF INVENTORY FOR DISASTER RELIEF

    Directory of Open Access Journals (Sweden)

    E. Van Wyk

    2012-01-01

    Full Text Available ENGLISH ABSTRACT: Natural disasters – and even those caused by people – are largely unpredictable. So disasters need to be researched and their impact fully understood, so that the aid supplies required to ensure survival during and after disaster events will be available. The member states of the Southern African Development Community (SADC are the countries of interest for this paper, as insufficient research has been conducted into inventory pre-positioning for disaster response in these countries. It is vital to anticipate the needs of disaster victims in potential disasters. These needs are evaluated according to the types and amounts of aid supplies required. This paper proposes a stochastic inventory model that can be applied in a generic way to any SADC country, providing a means to improve disaster preparedness through keeping aid supplies in pre-positioned facilities in the SADC region, at reasonable and affordable cost.

    AFRIKAANSE OPSOMMING: Natuurlike en mensgemaakte rampe is grootliks onvoorspelbaar. Gevolglik moet rampe nagevors en hul impak ten volle begryp word, sodat noodvoorrade wat benodig word vir oorlewing doeltreffend beplan kan word vir aanwending tydens en na rampgebeure. Die lede van die Suid-Afrikaanse Ontwikkelingsgemeenskap (SAOG is die lande van belang vir hierdie artikel omrede navorsing oor voorraadhouding vir rampreaksie in hierdie betrokke lande tot nog toe onvoldoende was. Dit is noodsaaklik om doeltreffend in die behoeftes van rampslagoffers te voorsien. Hierdie behoeftes word beoordeel na aanleiding van die aard en hoeveelhede van noodvoorrade wat benodig mag word in ramptoestande. Hierdie artikel stel ’n stochastiese voorraadmodel voor vir toepassing op ’n generiese wyse in enige SAOG land, om sodoende ’n metode te verskaf om rampvoorbereiding te verbeter deur die opgaar van noodvoorrade in vooraf-geïdentifiseerde fasiliteite binne die SAOG, teen redelike en bekostigbare koste.

     

  8. Approach for Visualization of Uncertainty in CAD-Systems based on Ontologies

    OpenAIRE

    Mosch, Lucia; Sprenger, André; Anderl, Reiner

    2010-01-01

    In this paper an approach for controlling uncertainties in load-carrying systems in virtual product development during the phase of product design will be presented. In design, manufacturing and usage of technical products uncertainties arise according to process properties and they influence products properties. Many of these properties impact each other. These facts lead to deviation of expected property values which are shown for example in the approximation of stress and strength. In case...

  9. Managing Model Data Introduced Uncertainties in Simulator Predictions for Generation IV Systems via Optimum Experimental Design

    International Nuclear Information System (INIS)

    Turinsky, Paul J.; Abdel-Khalik, Hany S.; Stover, Tracy E.

    2011-01-01

    An optimization technique has been developed to select optimized experimental design specifications to produce data specifically designed to be assimilated to optimize a given reactor concept. Data from the optimized experiment is assimilated to generate posteriori uncertainties on the reactor concept's core attributes from which the design responses are computed. The reactor concept is then optimized with the new data to realize cost savings by reducing margin. The optimization problem iterates until an optimal experiment is found to maximize the savings. A new generation of innovative nuclear reactor designs, in particular fast neutron spectrum recycle reactors, are being considered for the application of closing the nuclear fuel cycle in the future. Safe and economical design of these reactors will require uncertainty reduction in basic nuclear data which are input to the reactor design. These data uncertainty propagate to design responses which in turn require the reactor designer to incorporate additional safety margin into the design, which often increases the cost of the reactor. Therefore basic nuclear data needs to be improved and this is accomplished through experimentation. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment which will provide the data needed for uncertainty reduction such that a reactor design concept can meet its target accuracies or to allow savings to be realized by reducing the margin required due to uncertainty propagated from basic nuclear data. However, this optimization is coupled to the reactor design itself because with improved data the reactor concept can be re-optimized itself. It is thus desired to find the experiment that gives the best optimized reactor design. Methods are first established to model both the reactor concept and the experiment and to efficiently propagate the basic nuclear data uncertainty through these models to outputs. The representativity of the experiment

  10. Managing Model Data Introduced Uncertainties in Simulator Predictions for Generation IV Systems via Optimum Experimental Design

    Energy Technology Data Exchange (ETDEWEB)

    Turinsky, Paul J [North Carolina State Univ., Raleigh, NC (United States); Abdel-Khalik, Hany S [North Carolina State Univ., Raleigh, NC (United States); Stover, Tracy E [North Carolina State Univ., Raleigh, NC (United States)

    2011-03-01

    An optimization technique has been developed to select optimized experimental design specifications to produce data specifically designed to be assimilated to optimize a given reactor concept. Data from the optimized experiment is assimilated to generate posteriori uncertainties on the reactor concept’s core attributes from which the design responses are computed. The reactor concept is then optimized with the new data to realize cost savings by reducing margin. The optimization problem iterates until an optimal experiment is found to maximize the savings. A new generation of innovative nuclear reactor designs, in particular fast neutron spectrum recycle reactors, are being considered for the application of closing the nuclear fuel cycle in the future. Safe and economical design of these reactors will require uncertainty reduction in basic nuclear data which are input to the reactor design. These data uncertainty propagate to design responses which in turn require the reactor designer to incorporate additional safety margin into the design, which often increases the cost of the reactor. Therefore basic nuclear data needs to be improved and this is accomplished through experimentation. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment which will provide the data needed for uncertainty reduction such that a reactor design concept can meet its target accuracies or to allow savings to be realized by reducing the margin required due to uncertainty propagated from basic nuclear data. However, this optimization is coupled to the reactor design itself because with improved data the reactor concept can be re-optimized itself. It is thus desired to find the experiment that gives the best optimized reactor design. Methods are first established to model both the reactor concept and the experiment and to efficiently propagate the basic nuclear data uncertainty through these models to outputs. The representativity of the experiment

  11. Uncertainties in different level assessments of domestic ventilation systems

    NARCIS (Netherlands)

    Bokel, R.M.J.; Yang, Z.; Cauberg, J.J.M.

    2013-01-01

    In order to improve the quality of ventilation systems, assessments are widely used. In this paper, 3 main assessment levels are distinguished based on the number of ventilation systems to be assessed and the assessment objective. The main assessment levels distinguished in this paper are global

  12. ENVIRONMENTAL SYSTEMS MANAGEMENT, SUSTAINABILITY THEORY, AND THE CHALLENGE OF UNCERTAINTY

    Science.gov (United States)

    Environmental Systems Management is the management of environmental problems at the systems level fully accounting fo rthe multi-dimensional nature of the environment. This includes socio-economic dimensions as well s the usual physical and life science aspects. This is important...

  13. Uncertainty analysis methods for estimation of reliability of passive system of VHTR

    International Nuclear Information System (INIS)

    Han, S.J.

    2012-01-01

    An estimation of reliability of passive system for the probabilistic safety assessment (PSA) of a very high temperature reactor (VHTR) is under development in Korea. The essential approach of this estimation is to measure the uncertainty of the system performance under a specific accident condition. The uncertainty propagation approach according to the simulation of phenomenological models (computer codes) is adopted as a typical method to estimate the uncertainty for this purpose. This presentation introduced the uncertainty propagation and discussed the related issues focusing on the propagation object and its surrogates. To achieve a sufficient level of depth of uncertainty results, the applicability of the propagation should be carefully reviewed. For an example study, Latin-hypercube sampling (LHS) method as a direct propagation was tested for a specific accident sequence of VHTR. The reactor cavity cooling system (RCCS) developed by KAERI was considered for this example study. This is an air-cooled type passive system that has no active components for its operation. The accident sequence is a low pressure conduction cooling (LPCC) accident that is considered as a design basis accident for the safety design of VHTR. This sequence is due to a large failure of the pressure boundary of the reactor system such as a guillotine break of coolant pipe lines. The presentation discussed the obtained insights (benefit and weakness) to apply an estimation of reliability of passive system

  14. Cost effective robust rule calibration system

    Directory of Open Access Journals (Sweden)

    Greeff P.

    2014-01-01

    Full Text Available One of the main calibration services of African NMIs (National Metrology Institutes is the measurement of tapes and rules. This is mainly regulated by legal metrology and OIML (International Organisation of Legal Metrology specifications are therefore referenced. Specifically, OIML R-35 is the standard to which rules or line scales must conform. The accuracy of most African NMIs systems however, cannot prove conformance to this specification. This article will detail the development of a new, cost effective, line scale calibration system, which will have accuracy better than the specification prescribed. The system was locally developed and its design is based on off-the-shelf components and open source software. It is also ready-for-upgrade to an absolute system. The system and details of the line detection algorithm will be presented.

  15. Increased accuracy of cost-estimation using product configuration systems

    DEFF Research Database (Denmark)

    Rasmussen, Jeppe Bredahl; Hvam, Lars; Mortensen, Niels Henrik

    This article describes an approach for utilizing Product Configuration Systems (PCS) for quantifying project costs in project-based companies. It presents a case study demonstrating a method of quantifying costs in a way that makes it possible to configure cost- and time estimates. Piecework costs......, material costs and sub-supplier costs are used as principle cost elements and linked to structural and process elements to facilitate configuration. The cost data are used by the PCS to generate fast and accurate cost-estimates, quotations, time estimates and cost summaries. The described cost...

  16. A low-cost EDXRF analysis system

    International Nuclear Information System (INIS)

    Kahdeman, J.E.; Watson, W.

    1984-01-01

    The article deals with an EDXRF (Energy Dispersive X-ray Fluorescence) system, the Spectrace (sup TM) 4020 (Tractor X-ray). The Spectra analysis software is both powerful and flexible enough to handle a wide variety of applications. The instrument was designed to be economical by integrating the major system components into a single unit. This practical approach to hardware has cut the cost per unit. The software structure of the Spectra 4020 is presented in a flow chart. The article also contains a diagram of the hardware configuration of the instrument

  17. Calculation of the uncertainty of HP (10) evaluation for a thermoluminescent dosimetry system

    International Nuclear Information System (INIS)

    Ferreira, M.S.; Silva, E.R.; Mauricio, C.L.P.

    2016-01-01

    Full interpretation of dose assessment only can be performed when the uncertainty of the measurement is known. The aim of this study is to calculate the uncertainty of the TL dosimetry system of the LDF/IRD for evaluation of H P (10) for photons. It has been done by experimental measurements, extraction of information from documents and calculation of uncertainties based on ISO GUM. Energy and angular dependence is the most important source to the combined u c (y) and expanded (U) uncertainty. For 10 mSv, it was obtained u c (y) = 1,99 mSv and U = 3,98 mSv for 95% of coverage interval. (author)

  18. Actuator Saturation and Control Design for Buildings Structural Systems with Improved Uncertainty Description

    Directory of Open Access Journals (Sweden)

    Y.C. Ding

    2013-01-01

    Full Text Available The problem of robustly active vibration control for a class of earthquake-excited structural systems with time-delay and saturation in the control input channel and parameter uncertainties appearing in all the mass, damping and stiffness matrices is concerned in this paper. The objective of the designing controllers is to guarantee the robust stability of the closed-loop system and attenuate the disturbance from earthquake excitation. Firstly, by using the linear combination of some matrices to deal with the system's uncertainties, a new system uncertainties description, namely rank-1 uncertainty description, is presented. Then, by introducing a linear varying parameter, the input saturation model is described as a linear parameter varying model. Furthermore, based on parameter-dependent Lyapunov theory and linear matrix inequality (LMI technique, the LMIs-based conditions for the closed-loop system to be stable are deduced. By solving those conditions, the controller, considering the actuator saturation, input delay and parameters uncertainties, is obtained. Finally, a three-storey linear building structure under earthquake excitation is considered and simulation results are given to show the effectiveness of the proposed controllers.

  19. A multi-fuel management model for a community-level district heating system under multiple uncertainties

    International Nuclear Information System (INIS)

    Fu, D.Z.; Zheng, Z.Y.; Shi, H.B.; Xiao, Rui; Huang, G.H.; Li, Y.P.

    2017-01-01

    In this study, an interval two-stage double-stochastic single-sided fuzzy chance-constrained programming model is developed for supporting fuel management of a community-level district heating system (DHS) fed with both traditional fossil fuels and renewable biofuels under multiple uncertainties. The proposed model is based on the integration of interval parameter programming and single-sided fuzzy chance-constrained programming within an improved stochastic programming framework to tackle the uncertainties expressed as crisp intervals, fuzzy relationship, and probability distributions. Through transforming and solving the model, the related fuzzy and stochastic information can be effectively reflected in the generated solutions. A real fuel management case of a DHS located in Junpu New District of Dalian is utilized to demonstrate the model applicability. The obtained solutions provides an effective linkage in terms of both ‘‘quality’’ and ‘‘quantity’’ aspects for fuel management under various scenarios associated with multiple factors, and thus can help the decision makers to identify desired fuel allotment patterns. Moreover, this study is also useful for decision makers to address the other challenges (e.g. the imbalance between fuel supply and demand, the contradiction between air-pollution emission and environmental protection, as well as the tradeoff between the total heating cost and system satisfaction degree) generated in the fuel management processes. - Highlights: • A feasible two-stage stochastic programming method is improved. • A multi-fuel management model is developed under multiple uncertainties. • The fuel supply pattern for a district heating system can be obtained. • The variation tendencies of the pollutant emissions are examined. • Tradeoff analyses between system satisfaction degree and cost are carried out.

  20. Role Of Environment Uncertainty On Management Information System-Literature Approach

    Directory of Open Access Journals (Sweden)

    Christine Dwi Karya Susilawati

    2015-08-01

    Full Text Available The purpose of this research is to find role of environmental uncertainty on the quality of management information system with the literature review. Environmental uncertainty is the inability of the individual to capture the environmental factors from outside the company who are not sure which affect the companies that will impact on the quality of management information system application when it lowered the individuals inability to capture the environmental factors from outside uncertain it will improve the quality of management information system application.

  1. Filmless versus film-based systems in radiographic examination costs: an activity-based costing method.

    Science.gov (United States)

    Muto, Hiroshi; Tani, Yuji; Suzuki, Shigemasa; Yokooka, Yuki; Abe, Tamotsu; Sase, Yuji; Terashita, Takayoshi; Ogasawara, Katsuhiko

    2011-09-30

    Since the shift from a radiographic film-based system to that of a filmless system, the change in radiographic examination costs and costs structure have been undetermined. The activity-based costing (ABC) method measures the cost and performance of activities, resources, and cost objects. The purpose of this study is to identify the cost structure of a radiographic examination comparing a filmless system to that of a film-based system using the ABC method. We calculated the costs of radiographic examinations for both a filmless and a film-based system, and assessed the costs or cost components by simulating radiographic examinations in a health clinic. The cost objects of the radiographic examinations included lumbar (six views), knee (three views), wrist (two views), and other. Indirect costs were allocated to cost objects using the ABC method. The costs of a radiographic examination using a filmless system are as follows: lumbar 2,085 yen; knee 1,599 yen; wrist 1,165 yen; and other 1,641 yen. The costs for a film-based system are: lumbar 3,407 yen; knee 2,257 yen; wrist 1,602 yen; and other 2,521 yen. The primary activities were "calling patient," "explanation of scan," "take photographs," and "aftercare" for both filmless and film-based systems. The cost of these activities cost represented 36.0% of the total cost for a filmless system and 23.6% of a film-based system. The costs of radiographic examinations using a filmless system and a film-based system were calculated using the ABC method. Our results provide clear evidence that the filmless system is more effective than the film-based system in providing greater value services directly to patients.

  2. A complete low cost radon detection system

    International Nuclear Information System (INIS)

    Bayrak, A.; Barlas, E.; Emirhan, E.; Kutlu, Ç.; Ozben, C.S.

    2013-01-01

    Monitoring the 222 Rn activity through the 1200 km long Northern Anatolian fault line, for the purpose of earthquake precursory, requires large number of cost effective radon detectors. We have designed, produced and successfully tested a low cost radon detection system (a radon monitor). In the detector circuit of this monitor, First Sensor PS100-7-CER-2 windowless PIN photodiode and a custom made transempedence/shaping amplifier were used. In order to collect the naturally ionized radon progeny to the surface of the PIN photodiode, a potential of 3500 V was applied between the conductive hemi-spherical shell and the PIN photodiode. In addition to the count rate of the radon progeny, absolute pressure, humidity and temperature were logged during the measurements. A GSM modem was integrated to the system for transferring the measurements from the remote locations to the data process center. - Author-Highlights: • Low cost radon detection. • Integrated GSM modem for early warning of radon anomalies. • Radon detection in environment

  3. 48 CFR 252.215-7002 - Cost estimating system requirements.

    Science.gov (United States)

    2010-10-01

    ... historical costs, and other analyses used to generate cost estimates. (b) General. The Contractor shall... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Cost estimating system... of Provisions And Clauses 252.215-7002 Cost estimating system requirements. As prescribed in 215.408...

  4. Visualization of uncertainty in spatial decision support systems

    NARCIS (Netherlands)

    Aerts, J.C.J.H.; Clarke, L.A.; Keuper, A.D.

    2003-01-01

    Many land allocation issues, such as land-use planning, require input from extensive spatial databases and involve complex decision-making. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of land allocation

  5. AES, Automated Construction Cost Estimation System

    International Nuclear Information System (INIS)

    Holder, D.A.

    1995-01-01

    A - Description of program or function: AES (Automated Estimating System) enters and updates the detailed cost, schedule, contingency, and escalation information contained in a typical construction or other project cost estimates. It combines this information to calculate both un-escalated and escalated and cash flow values for the project. These costs can be reported at varying levels of detail. AES differs from previous versions in at least the following ways: The schedule is entered at the WBS-Participant, Activity level - multiple activities can be assigned to each WBS-Participant combination; the spending curve is defined at the schedule activity level and a weighing factor is defined which determines percentage of cost for the WBS-Participant applied to the schedule activity; Schedule by days instead of Fiscal Year/Quarter; Sales Tax is applied at the Line Item Level- a sales tax codes is selected to indicate Material, Large Single Item, or Professional Services; a 'data filter' has been added to allow user to define data the report is to be generated for. B - Method of solution: Average Escalation Rate: The average escalation for a Bill of is calculated in three steps. 1. A table of quarterly escalation factors is calculated based on the base fiscal year and quarter of the project entered in the estimate record and the annual escalation rates entered in the Standard Value File. 2. The percentage distribution of costs by quarter for the Bill of Material is calculated based on the schedule entered and the curve type. 3. The percent in each fiscal year and quarter in the distribution is multiplied by the escalation factor for the fiscal year and quarter. The sum of these results is the average escalation rate for that Bill of Material. Schedule by curve: The allocation of costs to specific time periods is dependent on three inputs, starting schedule date, ending schedule date, and the percentage of costs allocated to each quarter. Contingency Analysis: The

  6. Managing the complexity and uncertainties of load, generation and markets in system development planning

    International Nuclear Information System (INIS)

    2008-01-01

    System planners face today unique challenges to accommodate the new uncertainties in markets, loads and generation and to develop system plans that balance reliability, economy and risk. The report summarizes a survey of the methods used worldwide. In addition, case examples are provided to illustrate in more detail these methods

  7. Managing the complexity and uncertainties of load, generation and markets in system development planning

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2008-07-01

    System planners face today unique challenges to accommodate the new uncertainties in markets, loads and generation and to develop system plans that balance reliability, economy and risk. The report summarizes a survey of the methods used worldwide. In addition, case examples are provided to illustrate in more detail these methods

  8. Robust H-2 Performance Analysis for Systems with Nonlinear Parametric Uncertainties,

    DEFF Research Database (Denmark)

    Zhao, K.-Y.; Grimble, M.J.; Stoustrup, Jakob

    1997-01-01

    In this paper algorithms for calculating the maximal perturbation bounds under H-2 performance constraints for systems with parametric uncertainties are presented. A family of systems is considered, described by state space models which depend nonlinearly on real uncertain parameters. The stability...

  9. Sensing risk, fearing uncertainty: systems science approach to change

    OpenAIRE

    Janecka, Ivo P.

    2014-01-01

    BackgroundMedicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in o...

  10. Introducing uncertainty analysis of nucleation and crystal growth models in Process Analytical Technology (PAT) system design of crystallization processes

    DEFF Research Database (Denmark)

    Abdul Samad, Noor Asma Fazli Bin; Sin, Gürkan; Gernaey, Krist

    2013-01-01

    This paper presents the application of uncertainty and sensitivity analysis as part of a systematic modelbased process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty...

  11. Plug and Play Robust Distributed Control with Ellipsoidal Parametric Uncertainty System

    Directory of Open Access Journals (Sweden)

    Hong Wang-jian

    2016-01-01

    Full Text Available We consider a continuous linear time invariant system with ellipsoidal parametric uncertainty structured into subsystems. Since the design of a local controller uses only information on a subsystem and its neighbours, we combine the plug and play idea and robust distributed control to propose one distributed control strategy for linear system with ellipsoidal parametric uncertainty. Firstly for linear system with ellipsoidal parametric uncertainty, a necessary and sufficient condition for robust state feedback control is proposed by means of linear matrix inequality. If this necessary and sufficient condition is satisfied, this robust state feedback gain matrix can be easily derived to guarantee robust stability and prescribed closed loop performance. Secondly the plug and play idea is introduced in the design process. Finally by one example of aircraft flutter model parameter identification, the efficiency of the proposed control strategy can be easily realized.

  12. An Economic Assessment of Local Farm Multi-Purpose Surface Water Retention Systems under Future Climate Uncertainty

    Directory of Open Access Journals (Sweden)

    Pamela Berry

    2017-03-01

    Full Text Available Regions dependent on agricultural production are concerned about the uncertainty associated with climate change. Extreme drought and flooding events are predicted to occur with greater frequency, requiring mitigation strategies to reduce their negative impacts. Multi-purpose local farm water retention systems can reduce water stress during drought periods by supporting irrigation. The retention systems’ capture of excess spring runoff and extreme rainfall events also reduces flood potential downstream. Retention systems may also be used for biomass production and nutrient retention. A sub-watershed scale retention system was analysed using a dynamic simulation model to predict the economic advantages in the future. Irrigated crops using water from the downstream reservoir at Pelly’s Lake, Manitoba, Canada, experienced a net decrease in gross margin in the future due to the associated irrigation and reservoir infrastructure costs. However, the multi-purpose benefits of the retention system at Pelly’s Lake of avoided flood damages, nutrient retention, carbon sequestration, and biomass production provide an economic benefit of $25,507.00/hectare of retention system/year. Multi-purpose retention systems under future climate uncertainty provide economic and environmental gains when used to avoid flood damages, for nutrient retention and carbon sequestration, and biomass production. The revenue gained from these functions can support farmers willing to invest in irrigation while providing economic and environmental benefits to the region.

  13. Spatial and temporal distribution of long term public policy costs under uncertainty, the case of climate change

    International Nuclear Information System (INIS)

    Lecocq, F.

    2000-07-01

    Because of the inertia of the climate system, policy makers cannot avoid making early decisions regarding climate change in a sea of uncertainties. In this context, the very legitimacy of economic analysis to tackle such questions, and in particular the underlying equity issues (who pays for climate mitigation? when?) faces widespread skepticism. This thesis aims at demonstrating how public economy still remains a powerful tool to try and put some rationale into the debate, by checking the internal consistency of the different discourses, and by providing robust insights, if not definitive answers, into climate decisions. We use a set of compact integrated climate policy optimization models to progressively introduce, articulate, and assess numerically the prominent issues at stake. We obtain three main results. We first demonstrate that the so-called timing debate between short term and long term action cannot be reduced to a mere dispute over discount rate. Given the high uncertainties surrounding climate change indeed, the margins of freedom we pass on to future generations, and in particular the technical and institutional systems we transmit, become more important than the discount rate value. Secondly, we apply the various emission quota allocation rules proposed in the literature for the enlargement of annex B to developing economies. We show that the distributive outcome of these rules depends critically on ex ante assumptions about future economic and emission growth. Therefrom, we conclude that a careful design of the institutions surrounding the tradable permits market is a necessary condition to enhance the systems robustness. Last, on a broader perspective, this thesis illustrates the complementarity between ethics and economics: though the economist does not have per se a superior word about what is fair, his toolbox is powerful enough to show how some intuitively appealing ideas, such as a zero discount rate to take care of both present and future

  14. The role of social cost-benefit analysis in societal decision-making under large uncertainties with application to robbery at a cash depot

    International Nuclear Information System (INIS)

    Jones-Lee, M.; Aven, T.

    2009-01-01

    Social cost-benefit analysis is a well-established method for guiding decisions about safety investments, particularly in situations in which it is possible to make accurate predictions of future performance. However, its direct applicability to situations involving large degrees of uncertainty is less obvious and this raises the question of the extent to which social cost-benefit analysis can provide a useful input to the decision framework that has been explicitly developed to deal with safety decisions in which uncertainty is a major factor, namely risk analysis. This is the main focus of the arguments developed in this paper. In particular, we provide new insights by examining the fundamentals of both approaches and our principal conclusion is that social cost-benefit analysis and risk analysis represent complementary input bases to the decision-making process, and even in the case of large uncertainties social cost-benefit analysis may provide very useful decision support. What is required is the establishment of a proper contextual framework which structures and gives adequate weight to the uncertainties. An application to the possibility of a robbery at a cash depot is examined as a practical example.

  15. The uncertainty of atmospheric processes in planning a hybrid renewable energy system for a non-connected island

    Science.gov (United States)

    Daniil, Vasiliki; Pouliasis, George; Zacharopoulou, Eleni; Demetriou, Evangelos; Manou, Georgia; Chalakatevaki, Maria; Parara, Iliana; Georganta, Xristina; Stamou, Paraskevi; Karali, Sophia; Hadjimitsis, Evanthis; Koudouris, Giannis; Moschos, Evangelos; Roussis, Dimitrios; Papoulakos, Konstantinos; Koskinas, Aristotelis; Pollakis, Giorgos; Gournari, Panagiota; Sakellari, Katerina; Moustakis, Yiannis

    2017-04-01

    Non-connected islands to the electric gird are often depending on oil-fueled power plants with high unit cost. A hybrid energy system with renewable resources such as wind and solar plants could reduce this cost and also offer more environmental friendly solutions. However, atmospheric processes are characterized by high uncertainty that does not permit harvesting and utilizing full of their potential. Therefore, a more sophisticated framework that somehow incorporates this uncertainty could improve the performance of the system. In this context, we describe several stochastic and financial aspects of this framework. Particularly, we investigate the cross-correlation between several atmospheric processes and the energy demand, the possibility of mixing renewable resources with the conventional ones and in what degree of reliability, and critical financial subsystems such as weather derivatives. A pilot application of the above framework is also presented for a remote island in the Aegean Sea. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly. *The "Stochastics in Energy Resources Management (NTUA)" Team: Nikos Mamasis, Andreas Efstratiadis, Hristos Tyralis, Panayiotis Dimitriadis, Theano Iliopoulou, Georgios Karakatsanis, Katerina Tzouka, Ilias Deligiannis, Vicky Tsoukala, Panos Papanicolaou and Demetris Koutsoyiannis

  16. Cost Optimal System Identification Experiment Design

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning

    A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....

  17. Large-Scale Transport Model Uncertainty and Sensitivity Analysis: Distributed Sources in Complex Hydrogeologic Systems

    International Nuclear Information System (INIS)

    Sig Drellack, Lance Prothro

    2007-01-01

    The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result of the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The

  18. Uncertainty modeling in vibration, control and fuzzy analysis of structural systems

    CERN Document Server

    Halder, Achintya; Ayyub, Bilal M

    1997-01-01

    This book gives an overview of the current state of uncertainty modeling in vibration, control, and fuzzy analysis of structural and mechanical systems. It is a coherent compendium written by leading experts and offers the reader a sampling of exciting research areas in several fast-growing branches in this field. Uncertainty modeling and analysis are becoming an integral part of system definition and modeling in many fields. The book consists of ten chapters that report the work of researchers, scientists and engineers on theoretical developments and diversified applications in engineering sy

  19. Development of a decision support tool for seasonal water supply management incorporating system uncertainties and operational constraints

    Science.gov (United States)

    Wang, H.; Asefa, T.

    2017-12-01

    A real-time decision support tool (DST) for water supply system would consider system uncertainties, e.g., uncertain streamflow and demand, as well as operational constraints and infrastructure outage (e.g., pump station shutdown, an offline reservoir due to maintenance). Such DST is often used by water managers for resource allocation and delivery for customers. Although most seasonal DST used by water managers recognize those system uncertainties and operational constraints, most use only historical information or assume deterministic outlook of water supply systems. This study presents a seasonal DST that incorporates rainfall/streamflow uncertainties, seasonal demand outlook and system operational constraints. Large scale climate-information is captured through a rainfall simulator driven by a Bayesian non-homogeneous Markov Chain Monte Carlo model that allows non-stationary transition probabilities contingent on Nino 3.4 index. An ad-hoc seasonal demand forecasting model considers weather conditions explicitly and socio-economic factors implicitly. Latin Hypercube sampling is employed to effectively sample probability density functions of flow and demand. Seasonal system operation is modelled as a mixed-integer optimization problem that aims at minimizing operational costs. It embeds the flexibility of modifying operational rules at different components, e.g., surface water treatment plants, desalination facilities, and groundwater pumping stations. The proposed framework is illustrated at a wholesale water supplier in Southeastern United States, Tampa Bay Water. The use of the tool is demonstrated in proving operational guidance in a typical drawdown and refill cycle of a regional reservoir. The DST provided: 1) probabilistic outlook of reservoir storage and chance of a successful refill by the end of rainy season; 2) operational expectations for large infrastructures (e.g., high service pumps and booster stations) throughout the season. Other potential use

  20. Nonlinear control for systems containing input uncertainty via a Lyapunov-based approach

    Science.gov (United States)

    Mackunis, William

    Controllers are often designed based on the assumption that a control actuation can be directly applied to the system. This assumption may not be valid, however, for systems containing parametric input uncertainty or unmodeled actuator dynamics. In this dissertation, a tracking control methodology is proposed for aircaft and aerospace systems for which the corresponding dynamic models contain uncertainty in the control actuation. The dissertation will focus on five problems of interest: (1) adaptive CMG-actuated satellite attitude control in the presence of inertia uncertainty and uncertain CMG gimbal friction; (2) adaptive neural network (NN)-based satellite attitude control for CMG-actuated small-sats in the presence of uncertain satellite inertia, nonlinear disturbance torques, uncertain CMG gimbal friction, and nonlinear electromechanical CMG actuator disturbances; (3) dynamic inversion (DI) control for aircraft systems containing parametric input uncertainty and additive, nonlinearly parameterizable (non-LP) disturbances; (4) adaptive dynamic inversion (ADI) control for aircraft systems as described in (3); and (5) adaptive output feedback control for aircraft systems as described in (3) and (4).

  1. A hybrid multi-level optimization approach for the dynamic synthesis/design and operation/control under uncertainty of a fuel cell system

    International Nuclear Information System (INIS)

    Kim, Kihyung; Spakovsky, Michael R. von; Wang, M.; Nelson, Douglas J.

    2011-01-01

    During system development, large-scale, complex energy systems require multi-disciplinary efforts to achieve system quality, cost, and performance goals. As systems become larger and more complex, the number of possible system configurations and technologies, which meet the designer's objectives optimally, increases greatly. In addition, both transient and environmental effects may need to be taken into account. Thus, the difficulty of developing the system via the formulation of a single optimization problem in which the optimal synthesis/design and operation/control of the system are achieved simultaneously is great and rather problematic. This difficulty is further heightened with the introduction of uncertainty analysis, which transforms the problem from a purely deterministic one into a probabilistic one. Uncertainties, system complexity and nonlinearity, and large numbers of decision variables quickly render the single optimization problem unsolvable by conventional, single-level, optimization strategies. To address these difficulties, the strategy adopted here combines a dynamic physical decomposition technique for large-scale optimization with a response sensitivity analysis method for quantifying system response uncertainties to given uncertainty sources. The feasibility of such a hybrid approach is established by applying it to the synthesis/design and operation/control of a 5 kW proton exchange membrane (PEM) fuel cell system.

  2. Principles and methods of managerial cost-accounting systems.

    Science.gov (United States)

    Suver, J D; Cooper, J C

    1988-01-01

    An introduction to cost-accounting systems for pharmacy managers is provided; terms are defined and examples of specific applications are given. Cost-accounting systems determine, record, and report the resources consumed in providing services. An effective cost-accounting system must provide the information needed for both internal and external reports. In accounting terms, cost is the value given up to secure an asset. In determining how volumes of activity affect costs, fixed costs and variable costs are calculated; applications include pricing strategies, cost determinations, and break-even analysis. Also discussed are the concepts of direct and indirect costs, opportunity costs, and incremental and sunk costs. For most pharmacy department services, process costing, an accounting of intermediate outputs and homogeneous units, is used; in determining the full cost of providing a product or service (e.g., patient stay), job-order costing is used. Development of work-performance standards is necessary for monitoring productivity and determining product costs. In allocating pharmacy department costs, a ratio of costs to charges can be used; this method is convenient, but microcosting (specific identification of the costs of products) is more accurate. Pharmacy managers can use cost-accounting systems to evaluate the pharmacy's strategies, policies, and services and to improve budgets and reports.

  3. Cost benefit risk - a concept for management of integrated urban wastewater systems?

    DEFF Research Database (Denmark)

    Hauger, Mikkel B.; Rauch, W.; Linde, Jens Jørgen

    2002-01-01

    the most feasible improvement alternative for an urban wastewater system. The most feasible alternative in this context is the alternative that has the best performance, meaning that the alternative has the lowest sum of costs, benefits and risks. The sum is expressed as the Net Present Cost (NPC). To use......Urban wastewater systems should be evaluated and analysed from an integrated point of view, taking all parts of the system, that is sewer system, wastewater treatment plant and receiving waters into consideration. Risk and parameter uncertainties are aspects that hardly ever have been addressed...... in the evaluation and design of urban wastewater systems. In this paper we present and discuss a probabilistic approach for evaluation of the performance of urban wastewater systems. Risk analysis together with the traditional cost-benefit analysis is a special variant of multi-criteria analysis that seeks to find...

  4. ASSESSMENT OF UNCERTAINTY IN THE RADIATION DOSES FOR THE TECHA RIVER DOSIMETRY SYSTEM

    Energy Technology Data Exchange (ETDEWEB)

    Napier, Bruce A.; Degteva, M. O.; Anspaugh, L. R.; Shagina, N. B.

    2009-10-23

    In order to provide more accurate and precise estimates of individual dose (and thus more precise estimates of radiation risk) for the members of the ETRC, a new dosimetric calculation system, the Techa River Dosimetry System-2009 (TRDS-2009) has been prepared. The deterministic version of the improved dosimetry system TRDS-2009D was basically completed in April 2009. Recent developments in evaluation of dose-response models in light of uncertain dose have highlighted the importance of different types of uncertainties in the development of individual dose estimates. These include uncertain parameters that may be either shared or unshared within the dosimetric cohort, and also the nature of the type of uncertainty as aleatory or epistemic and either classical or Berkson. This report identifies the nature of the various input parameters and calculational methods incorporated in the Techa River Dosimetry System (based on the TRDS-2009D implementation), with the intention of preparing a stochastic version to estimate the uncertainties in the dose estimates. This report reviews the equations, databases, and input parameters, and then identifies the author’s interpretations of their general nature. It presents the approach selected so that the stochastic, Monte-Carlo, implementation of the dosimetry System - TRDS-2009MC - will provide useful information regarding the uncertainties of the doses.

  5. The National Ecosystem Services Classification System: A Framework for Identifying and Reducing Relevant Uncertainties

    Science.gov (United States)

    Rhodes, C. R.; Sinha, P.; Amanda, N.

    2013-12-01

    In recent years the gap between what scientists know and what policymakers should appreciate in environmental decision making has received more attention, as the costs of the disconnect have become more apparent to both groups. Particularly for water-related policies, the EPA's Office of Water has struggled with benefit estimates held low by the inability to quantify ecological and economic effects that theory, modeling, and anecdotal or isolated case evidence suggest may prove to be larger. Better coordination with ecologists and hydrologists is being explored as a solution. The ecosystem services (ES) concept now nearly two decades old links ecosystem functions and processes to the human value system. But there remains no clear mapping of which ecosystem goods and services affect which individual or economic values. The National Ecosystem Services Classification System (NESCS, 'nexus') project brings together ecologists, hydrologists, and social scientists to do this mapping for aquatic and other ecosystem service-generating systems. The objective is to greatly reduce the uncertainty in water-related policy making by mapping and ultimately quantifying the various functions and products of aquatic systems, as well as how changes to aquatic systems impact the human economy and individual levels of non-monetary appreciation for those functions and products. Primary challenges to fostering interaction between scientists, social scientists, and policymakers are lack of a common vocabulary, and the need for a cohesive comprehensive framework that organizes concepts across disciplines and accommodates scientific data from a range of sources. NESCS builds the vocabulary and the framework so both may inform a scalable transdisciplinary policy-making application. This talk presents for discussion the process and progress in developing both this vocabulary and a classifying framework capable of bridging the gap between a newer but existing ecosystem services classification

  6. Total costs of injury from accidents in the home and during education, sports and leisure activities: estimates for Norway with assessment of uncertainty.

    Science.gov (United States)

    Veisten, Knut; Nossum, Ase; Akhtar, Juned

    2009-07-01

    Injury accidents occurring in the home, during educational, sports or leisure activities were estimated from samples of hospital data, combined with fatality data from vital statistics. Uncertainty of estimated figures was assessed in simulation-based analysis. Total economic costs to society from injuries and fatalities due to such accidents were estimated at approximately NOK 150 billion per year. The estimated costs reveal the scale of the public health problem and lead to arguments for the establishment of a proper injury register for the identification of preventive measures to reduce the costs to society.

  7. H∞ Loop Shaping Control of Input Saturated Systems with Norm-Bounded Parametric Uncertainty

    Directory of Open Access Journals (Sweden)

    Renan Lima Pereira

    2015-01-01

    Full Text Available This paper proposes a gain-scheduling control design strategy for a class of linear systems with the presence of both input saturation constraints and norm-bounded parametric uncertainty. LMI conditions are derived in order to obtain a gain-scheduled controller that ensures the robust stability and performance of the closed loop system. The main steps to obtain such a controller are given. Differently from other gain-scheduled approaches in the literature, this one focuses on the problem of H∞ loop shaping control design with input saturation nonlinearity and norm-bounded uncertainty to reduce the effect of the disturbance input on the controlled outputs. Here, the design problem has been formulated in the four-block H∞ synthesis framework, in which it is possible to describe the parametric uncertainty and the input saturation nonlinearity as perturbations to normalized coprime factors of the shaped plant. As a result, the shaped plant is represented as a linear parameter-varying (LPV system while the norm-bounded uncertainty and input saturation are incorporated. This procedure yields a linear parameter-varying structure for the controller that ensures the stability of the polytopic LPV shaped plant from the vertex property. Finally, the effectiveness of the method is illustrated through application to a physical system: a VTOL “vertical taking-off landing” helicopter.

  8. Modelling sensitivity and uncertainty in a LCA model for waste management systems - EASETECH

    DEFF Research Database (Denmark)

    Damgaard, Anders; Clavreul, Julie; Baumeister, Hubert

    2013-01-01

    In the new model, EASETECH, developed for LCA modelling of waste management systems, a general approach for sensitivity and uncertainty assessment for waste management studies has been implemented. First general contribution analysis is done through a regular interpretation of inventory and impact...

  9. Performance of Counter Flow Heat Recovery Ventilation Systems in Dwellings Considering the Influence of Uncertainties

    NARCIS (Netherlands)

    Yang, Z.; Cauberg, J.J.M.; Tenpierik, M.J.

    2012-01-01

    Both critical and optimistic claims have been made regarding the performance of heat recovery ventilation systems (HRVS) in dwellings. Such arguments are raised partly because two key aspects are not fully clarified, i.e. the performance criteria and the influence of uncertainties. In the current

  10. Synchronization of chaotic systems with parameter uncertainties via variable structure control

    International Nuclear Information System (INIS)

    Etemadi, Shahram; Alasty, Aria; Salarieh, Hassan

    2006-01-01

    The Letter introduces a robust control design method to synchronize a pair of different uncertain chaotic systems. The technique is based on sliding-mode and variable structure control theories. Comparison of proposed method with previous works is performed during simulations. It is shown that the proposed controller while appearing in a faster response, is able to overcome random uncertainties of all model parameters

  11. Knowledge management system for risk mitigation in supply chain uncertainty: case from automotive battery supply chain

    Science.gov (United States)

    Marie, I. A.; Sugiarto, D.; Surjasa, D.; Witonohadi, A.

    2018-01-01

    Automotive battery supply chain include battery manufacturer, sulphuric acid suppliers, polypropylene suppliers, lead suppliers, transportation service providers, warehouses, retailers and even customers. Due to the increasingly dynamic condition of the environment, supply chain actors were required to improve their ability to overcome various uncertainty issues in the environment. This paper aims to describe the process of designing a knowledge management system for risk mitigation in supply chain uncertainty. The design methodology began with the identification of the knowledge needed to solve the problems associated with uncertainty and analysis of system requirements. The design of the knowledge management system was described in the form of a data flow diagram. The results of the study indicated that key knowledge area that needs to be managed were the knowledge to maintain the stability of process in sulphuric acid process and knowledge to overcome the wastes in battery manufacturing process. The system was expected to be a media acquisition, dissemination and storage of knowledge associated with the uncertainty in the battery supply chain and increase the supply chain performance.

  12. Scenario-based fitted Q-iteration for adaptive control of water reservoir systems under uncertainty

    Science.gov (United States)

    Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

    2017-04-01

    Over recent years, mathematical models have largely been used to support planning and management of water resources systems. Yet, the increasing uncertainties in their inputs - due to increased variability in the hydrological regimes - are a major challenge to the optimal operations of these systems. Such uncertainty, boosted by projected changing climate, violates the stationarity principle generally used for describing hydro-meteorological processes, which assumes time persisting statistical characteristics of a given variable as inferred by historical data. As this principle is unlikely to be valid in the future, the probability density function used for modeling stochastic disturbances (e.g., inflows) becomes an additional uncertain parameter of the problem, which can be described in a deterministic and set-membership based fashion. This study contributes a novel method for designing optimal, adaptive policies for controlling water reservoir systems under climate-related uncertainty. The proposed method, called scenario-based Fitted Q-Iteration (sFQI), extends the original Fitted Q-Iteration algorithm by enlarging the state space to include the space of the uncertain system's parameters (i.e., the uncertain climate scenarios). As a result, sFQI embeds the set-membership uncertainty of the future inflow scenarios in the action-value function and is able to approximate, with a single learning process, the optimal control policy associated to any scenario included in the uncertainty set. The method is demonstrated on a synthetic water system, consisting of a regulated lake operated for ensuring reliable water supply to downstream users. Numerical results show that the sFQI algorithm successfully identifies adaptive solutions to operate the system under different inflow scenarios, which outperform the control policy designed under historical conditions. Moreover, the sFQI policy generalizes over inflow scenarios not directly experienced during the policy design

  13. Incorporating uncertainty into mercury-offset decisions with a probabilistic network for National Pollutant Discharge Elimination System permit holders: an interim report

    Science.gov (United States)

    Wood, Alexander

    2004-01-01

    deterministic methods for Hg TMDL decision support, one that is fully compatible with an adaptive management approach. This alternative approach uses empirical data and informed judgment to provide a scientific and technical basis for helping National Pollutant Discharge Elimination System (NPDES) permit holders make management decisions. An Hg-offset system would be an option if a wastewater-treatment plant could not achieve NPDES permit requirements for HgT reduction. We develop a probabilistic decision-analytical model consisting of three submodels for HgT loading, MeHg, and cost mitigation within a Bayesian network that integrates information of varying rigor and detail into a simple model of a complex system. Hg processes are identified and quantified by using a combination of historical data, statistical models, and expert judgment. Such an integrated approach to uncertainty analysis allows easy updating of prediction and inference when observations of model variables are made. We demonstrate our approach with data from the Cache Creek watershed (a subbasin of the Sacramento River watershed). The empirical models used to generate the needed probability distributions are based on the same empirical models currently being used by the Central Valley Regional Water Quality Control Cache Creek Hg TMDL working group. The significant difference is that input uncertainty and error are explicitly included in the model and propagated throughout its algorithms. This work demonstrates how to integrate uncertainty into the complex and highly uncertain Hg TMDL decisionmaking process. The various sources of uncertainty are propagated as decision risk that allows decisionmakers to simultaneously consider uncertainties in remediation/implementation costs while attempting to meet environmental/ecologic targets. We must note that this research is on going. As more data are collected, the HgT and cost-mitigation submodels are updated and the uncer

  14. Costing for the Future: Exploring Cost Estimation With Unmanned Autonomous Systems

    Science.gov (United States)

    2016-04-30

    ownership of this new breed of systems. Singularly applying traditional software and hardware cost models do not provide this capability because the...various types of costs into their respective phases to demonstrate Total Cost of Ownership . Cost Estimation Methods The exploration of new cost...vehicle; or if it is an attack/reconnaissance system—it needs to support munitions, missiles, or gun platforms. Although many more areas can be

  15. An Overview of Physical Layer Security in Wireless Communication Systems With CSIT Uncertainty

    KAUST Repository

    Hyadi, Amal

    2016-09-21

    The concept of physical layer security builds on the pivotal idea of turning the channel\\'s imperfections, such as noise and fading, into a source of security. This is established through appropriately designed coding techniques and signal processing strategies. In this vein, it has been shown that fading channels can enhance the transmission of confidential information and that a secure communication can be achieved even when the channel to the eavesdropper is better than the main channel. However, to fully benefit from what fading has to offer, the knowledge of the channel state information at the transmitter (CSIT) is of primordial importance. In practical wireless communication systems, CSIT is usually obtained, prior to data transmission, through CSI feedback sent by the receivers. The channel links over which this feedback information is sent can be either noisy, rate-limited, or delayed, leading to CSIT uncertainty. In this paper, we present a comprehensive review of recent and ongoing research works on physical layer security with CSIT uncertainty. We focus on both information theoretic and signal processing approaches to the topic when the uncertainty concerns the channel to the wiretapper or the channel to the legitimate receiver. Moreover, we present a classification of the research works based on the considered channel uncertainty. Mainly, we distinguish between the cases when the uncertainty comes from an estimation error of the CSIT, from a CSI feedback link with limited capacity, or from an outdated CSI.

  16. UNCERTAINTY PROPAGATION ANALYSIS FOR YONGGWANG NUCLEAR UNIT 4 BY MCCARD/MASTER CORE ANALYSIS SYSTEM

    Directory of Open Access Journals (Sweden)

    HO JIN PARK

    2014-06-01

    Full Text Available This paper concerns estimating uncertainties of the core neutronics design parameters of power reactors by direct sampling method (DSM calculations based on the two-step McCARD/MASTER design system in which McCARD is used to generate the fuel assembly (FA homogenized few group constants (FGCs while MASTER is used to conduct the core neutronics design computation. It presents an extended application of the uncertainty propagation analysis method originally designed for uncertainty quantification of the FA FGCs as a way to produce the covariances between the FGCs of any pair of FAs comprising the core, or the covariance matrix of the FA FGCs required for random sampling of the FA FGCs input sets into direct sampling core calculations by MASTER. For illustrative purposes, the uncertainties of core design parameters such as the effective multiplication factor (keff, normalized FA power densities, power peaking factors, etc. for the beginning of life (BOL core of Yonggwang nuclear unit 4 (YGN4 at the hot zero power and all rods out are estimated by the McCARD/MASTER-based DSM computations. The results are compared with those from the uncertainty propagation analysis method based on the McCARD-predicted sensitivity coefficients of nuclear design parameters and the cross section covariance data.

  17. Cost optimization for buildings with hybrid ventilation systems

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Kun; Lu, Yan

    2018-02-13

    A method including: computing a total cost for a first zone in a building, wherein the total cost is equal to an actual energy cost of the first zone plus a thermal discomfort cost of the first zone; and heuristically optimizing the total cost to identify temperature setpoints for a mechanical heating/cooling system and a start time and an end time of the mechanical heating/cooling system, based on external weather data and occupancy data of the first zone.

  18. 18 CFR 301.7 - Average System Cost methodology functionalization.

    Science.gov (United States)

    2010-04-01

    ... SYSTEM COST METHODOLOGY FOR SALES FROM UTILITIES TO BONNEVILLE POWER ADMINISTRATION UNDER NORTHWEST POWER ACT § 301.7 Average System Cost methodology functionalization. (a) Functionalization of each Account... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Average System Cost...

  19. Uncertainty propagation and sensitivity analysis in system reliability assessment via unscented transformation

    International Nuclear Information System (INIS)

    Rocco Sanseverino, Claudio M.; Ramirez-Marquez, José Emmanuel

    2014-01-01

    The reliability of a system, notwithstanding it intended function, can be significantly affected by the uncertainty in the reliability estimate of the components that define the system. This paper implements the Unscented Transformation to quantify the effects of the uncertainty of component reliability through two approaches. The first approach is based on the concept of uncertainty propagation, which is the assessment of the effect that the variability of the component reliabilities produces on the variance of the system reliability. This assessment based on UT has been previously considered in the literature but only for system represented through series/parallel configuration. In this paper the assessment is extended to systems whose reliability cannot be represented through analytical expressions and require, for example, Monte Carlo Simulation. The second approach consists on the evaluation of the importance of components, i.e., the evaluation of the components that most contribute to the variance of the system reliability. An extension of the UT is proposed to evaluate the so called “main effects” of each component, as well to assess high order component interaction. Several examples with excellent results illustrate the proposed approach. - Highlights: • Simulation based approach for computing reliability estimates. • Computation of reliability variance via 2n+1 points. • Immediate computation of component importance. • Application to network systems

  20. Optimized production planning model for a multi-plant cultivation system under uncertainty

    Science.gov (United States)

    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.

  1. Incremental cost analysis of advanced concept CAES systems

    Energy Technology Data Exchange (ETDEWEB)

    Knutsen, C.A.

    1979-09-01

    The costs of compressed air energy storage (CAES) systems using thermal energy storage (TES) are compared to the costs of CAES systems without TES and simple cycle gas turbine systems. Comparisons are made in terms of the system energy costs levelized over the operating life of the systems. These are in 1985 price levels which is the assumed first year of operation for the systems.

  2. A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Afif Monrat, Ahmed; Hasan, Mamun

    2016-01-01

    to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema...... in this BRBES. The study shows that the results generated by BRBES are more reliable than that of Fuzzy Rule-based expert system and from a human expert....

  3. A new costing model in hospital management: time-driven activity-based costing system.

    Science.gov (United States)

    Öker, Figen; Özyapıcı, Hasan

    2013-01-01

    Traditional cost systems cause cost distortions because they cannot meet the requirements of today's businesses. Therefore, a new and more effective cost system is needed. Consequently, time-driven activity-based costing system has emerged. The unit cost of supplying capacity and the time needed to perform an activity are the only 2 factors considered by the system. Furthermore, this system determines unused capacity by considering practical capacity. The purpose of this article is to emphasize the efficiency of the time-driven activity-based costing system and to display how it can be applied in a health care institution. A case study was conducted in a private hospital in Cyprus. Interviews and direct observations were used to collect the data. The case study revealed that the cost of unused capacity is allocated to both open and laparoscopic (closed) surgeries. Thus, by using the time-driven activity-based costing system, managers should eliminate the cost of unused capacity so as to obtain better results. Based on the results of the study, hospital management is better able to understand the costs of different surgeries. In addition, managers can easily notice the cost of unused capacity and decide how many employees to be dismissed or directed to other productive areas.

  4. A COST ORIENTED SYSTEM FOR HOLE MAKING PROCESSES

    OpenAIRE

    Uğur PAMUKOĞLU; Cevdet GÖLOĞLU

    2004-01-01

    A knowledge based system for manufacturing of various hole making processes has been developed. In the system, selection of machining methods, determination of sequences based on cutting tools for each process, determination of process time and cost analysis have been conducted. In the procedure, all available processes have been taken in to account regarding their costs and the most suitable in cost was chosen. The system generated helps facilitate determination of process time and the cost...

  5. Optimizing Capacities of Distributed Generation and Energy Storage in a Small Autonomous Power System Considering Uncertainty in Renewables

    Directory of Open Access Journals (Sweden)

    Ying-Yi Hong

    2015-03-01

    Full Text Available This paper explores real power generation planning, considering distributed generation resources and energy storage in a small standalone power system. On account of the Kyoto Protocol and Copenhagen Accord, wind and photovoltaic (PV powers are considered as clean and renewable energies. In this study, a genetic algorithm (GA was used to determine the optimal capacities of wind-turbine-generators, PV, diesel generators and energy storage in a small standalone power system. The investment costs (installation, unit and maintenance costs of the distributed generation resources and energy storage and the cost of fuel for the diesel generators were minimized while the reliability requirement and CO2 emission limit were fulfilled. The renewable sources and loads were modeled by random variables because of their uncertainties. The equality and inequality constraints in the genetic algorithms were treated by cumulant effects and cumulative probability of random variables, respectively. The IEEE reliability data for an 8760 h load profile with a 150 kW peak load were used to demonstrate the applicability of the proposed method.

  6. Bottom-up uncertainty estimates of global ammonia emissions from global agricultural production systems

    Science.gov (United States)

    Beusen, A. H. W.; Bouwman, A. F.; Heuberger, P. S. C.; Van Drecht, G.; Van Der Hoek, K. W.

    Here we present an uncertainty analysis of NH 3 emissions from agricultural production systems based on a global NH 3 emission inventory with a 5×5 min resolution. Of all results the mean is given with a range (10% and 90% percentile). The uncertainty range for the global NH 3 emission from agricultural systems is 27-38 (with a mean of 32) Tg NH 3-N yr -1, N fertilizer use contributing 10-12 (11) Tg yr -1 and livestock production 16-27 (21) Tg yr -1. Most of the emissions from livestock production come from animal houses and storage systems (31-55%); smaller contributions come from the spreading of animal manure (23-38%) and grazing animals (17-37%). This uncertainty analysis allows for identifying and improving those input parameters with a major influence on the results. The most important determinants of the uncertainty related to the global agricultural NH 3 emission comprise four parameters (N excretion rates, NH 3 emission rates for manure in animal houses and storage, the fraction of the time that ruminants graze and the fraction of non-agricultural use of manure) specific to mixed and landless systems, and total animal stocks. Nitrogen excretion rates and NH 3 emission rates from animal houses and storage systems are shown consistently to be the most important parameters in most parts of the world. Input parameters for pastoral systems are less relevant. However, there are clear differences between world regions and individual countries, reflecting the differences in livestock production systems.

  7. Robust framework for PET image reconstruction incorporating system and measurement uncertainties.

    Directory of Open Access Journals (Sweden)

    Huafeng Liu

    Full Text Available In Positron Emission Tomography (PET, an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts.

  8. A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty.

    Science.gov (United States)

    Hossain, Mohammad Shahadat; Ahmed, Faisal; Fatema-Tuj-Johora; Andersson, Karl

    2017-03-01

    The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and symptoms cannot be measured with 100 % certainty since they are associated with various types of uncertainties such as vagueness, imprecision, randomness, ignorance and incompleteness. Consequently, traditional primary diagnosis, based on these signs and symptoms, which is carried out by the physicians, cannot deliver reliable results. Therefore, this article presents the design, development and applications of a Belief Rule Based Expert System (BRBES) with the ability to handle various types of uncertainties to diagnose TB. The knowledge base of this system is constructed by taking experts' suggestions and by analyzing historical data of TB patients. The experiments, carried out, by taking the data of 100 patients demonstrate that the BRBES's generated results are more reliable than that of human expert as well as fuzzy rule based expert system.

  9. Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation & Uncertainty Quantification

    Energy Technology Data Exchange (ETDEWEB)

    Tsao, Jeffrey Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kleban, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Curtis M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Mark A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flanagan, Tatiana Paz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gabert, Kasimir Georg [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lave, Matthew Samuel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Chen, Wei [Northwestern Univ., Evanston, IL (United States); DeLaurentis, Daniel [Purdue Univ., West Lafayette, IN (United States); Hubler, Alfred [Univ. of Illinois, Urbana, IL (United States); Oberkampf, Bill [WLO Consulting, Austin, TX (United States)

    2016-08-01

    This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?

  10. Subsystem cost data for the tritium systems test assembly

    International Nuclear Information System (INIS)

    Bartlit, J.R.; Anderson, J.L.; Rexroth, V.G.

    1983-01-01

    Details of subsystem costs are among the questions most frequently asked about the $14.4 million Tritium Systems Test Assembly (TSTA) at Los Alamos National Laboratory. This paper presents a breakdown of cost components for each of the 20 major subsystems of TSTA. Also included are details to aid in adjusting the costs to other years, contracting conditions, or system sizes

  11. Subsystem cost data for the tritium systems test assembly

    Energy Technology Data Exchange (ETDEWEB)

    Bartlit, J.R.; Anderson, J.L.; Rexroth, V.G.

    1983-01-01

    Details of subsystem costs are among the questions most frequently asked about the $14.4 million Tritium Systems Test Assembly (TSTA) at Los Alamos National Laboratory. This paper presents a breakdown of cost components for each of the 20 major subsystems of TSTA. Also included are details to aid in adjusting the costs to other years, contracting conditions, or system sizes.

  12. Deterministic sensitivity and uncertainty methodology for best estimate system codes applied in nuclear technology

    International Nuclear Information System (INIS)

    Petruzzi, A.; D'Auria, F.; Cacuci, D.G.

    2009-01-01

    Nuclear Power Plant (NPP) technology has been developed based on the traditional defense in depth philosophy supported by deterministic and overly conservative methods for safety analysis. In the 1970s [1], conservative hypotheses were introduced for safety analyses to address existing uncertainties. Since then, intensive thermal-hydraulic experimental research has resulted in a considerable increase in knowledge and consequently in the development of best-estimate codes able to provide more realistic information about the physical behaviour and to identify the most relevant safety issues allowing the evaluation of the existing actual margins between the results of the calculations and the acceptance criteria. However, the best-estimate calculation results from complex thermal-hydraulic system codes (like Relap5, Cathare, Athlet, Trace, etc..) are affected by unavoidable approximations that are un-predictable without the use of computational tools that account for the various sources of uncertainty. Therefore the use of best-estimate codes (BE) within the reactor technology, either for design or safety purposes, implies understanding and accepting the limitations and the deficiencies of those codes. Taking into consideration the above framework, a comprehensive approach for utilizing quantified uncertainties arising from Integral Test Facilities (ITFs, [2]) and Separate Effect Test Facilities (SETFs, [3]) in the process of calibrating complex computer models for the application to NPP transient scenarios has been developed. The methodology proposed is capable of accommodating multiple SETFs and ITFs to learn as much as possible about uncertain parameters, allowing for the improvement of the computer model predictions based on the available experimental evidences. The proposed methodology constitutes a major step forward with respect to the generally used expert judgment and statistical methods as it permits a) to establish the uncertainties of any parameter

  13. Cost Analysis Of Broadband Service Delivery Systems

    Science.gov (United States)

    Dunn, Donald A.; Johnson, M. Gens

    1990-01-01

    Costs for active double-star fiber networks for local exchange service are compared with the costs of copper twisted-pair single-star networks and copper coaxial-line tree networks with switching at the customer's premises. For both existing and new neighborhoods, it appears that delivery of broadband services through tree networks (possibly using fiber) and delivery of narrow band services through copper twisted-pair star networks will be the minimum cost approach for low market penetrations of the broadband service market. For near 100 percent market penetrations there is relatively little difference in the costs of the two approaches.

  14. Visualizing uncertainties in a storm surge ensemble data assimilation and forecasting system

    KAUST Repository

    Hollt, Thomas

    2015-01-15

    We present a novel integrated visualization system that enables the interactive visual analysis of ensemble simulations and estimates of the sea surface height and other model variables that are used for storm surge prediction. Coastal inundation, caused by hurricanes and tropical storms, poses large risks for today\\'s societies. High-fidelity numerical models of water levels driven by hurricane-force winds are required to predict these events, posing a challenging computational problem, and even though computational models continue to improve, uncertainties in storm surge forecasts are inevitable. Today, this uncertainty is often exposed to the user by running the simulation many times with different parameters or inputs following a Monte-Carlo framework in which uncertainties are represented as stochastic quantities. This results in multidimensional, multivariate and multivalued data, so-called ensemble data. While the resulting datasets are very comprehensive, they are also huge in size and thus hard to visualize and interpret. In this paper, we tackle this problem by means of an interactive and integrated visual analysis system. By harnessing the power of modern graphics processing units for visualization as well as computation, our system allows the user to browse through the simulation ensembles in real time, view specific parameter settings or simulation models and move between different spatial and temporal regions without delay. In addition, our system provides advanced visualizations to highlight the uncertainty or show the complete distribution of the simulations at user-defined positions over the complete time series of the prediction. We highlight the benefits of our system by presenting its application in a real-world scenario using a simulation of Hurricane Ike.

  15. Development of a System Analysis Toolkit for Sensitivity Analysis, Uncertainty Propagation, and Estimation of Parameter Distribution

    International Nuclear Information System (INIS)

    Heo, Jaeseok; Kim, Kyung Doo

    2015-01-01

    Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM

  16. Stability Optimization of a Disc Brake System with Hybrid Uncertainties for Squeal Reduction

    Directory of Open Access Journals (Sweden)

    Hui Lü

    2016-01-01

    Full Text Available A hybrid uncertain model is introduced to deal with the uncertainties existing in a disc brake system in this paper. By the hybrid uncertain model, the uncertain parameters of the brake with enough sampling data are treated as probabilistic variables, while the uncertain parameters with limited data are treated as interval probabilistic variables whose distribution parameters are expressed as interval variables. Based on the hybrid uncertain model, the reliability-based design optimization (RBDO of a disc brake with hybrid uncertainties is proposed to explore the optimal design for squeal reduction. In the optimization, the surrogate model of the real part of domain unstable eigenvalue of the brake system is established, and the upper bound of its expectation is adopted as the optimization objective. The lower bounds of the functions related to system stability, the mass, and the stiffness of design component are adopted as the optimization constraints. The combinational algorithm of Genetic Algorithm and Monte-Carlo method is employed to perform the optimization. The results of a numerical example demonstrate the effectiveness of the proposed optimization on improving system stability and reducing squeal propensity of a disc brake under hybrid uncertainties.

  17. ADAPTIVE OUTPUT CONTROL OF MULTICHANNEL LINEAR STATIONARY SYSTEMS UNDER PARAMETRIC UNCERTAINTY

    Directory of Open Access Journals (Sweden)

    Aleksei A. Bobtsov

    2014-11-01

    Full Text Available The paper deals with the problem of adaptive control for multi-channel linear stationary plants under parametric uncertainty with arbitrary relative degree of each local subsystem. The synthesized regulator provides stabilization of control plant on condition that for each local subsystem only output variables are measured with known relative degrees, but the order of linear differential equations is unknown. We consider the synthesis of control system for two-channel system for simplification of the synthesis method. The "serial compensator" algorithm is chosen as basic approach with A.L. Fradkov's passification theorem and additional filters containing high gain constants in their structure. Durability of the closed system in the group of pointed types of regulators is analyzed and the necessary and sufficient conditions for exponential convergence properties are considered. We suggest adaptive version of the "serial compensator" method from the practical point of view, where customization of the gain constant is based on the integral type algorithm. We show the results of computer simulation for the third and second order subsystems under parametric uncertainty to illustrate the proposed approach workability. It is shown that the proposed technique makes it possible to synthesize control algorithms for multichannel systems under parametric uncertainty with minimal dynamical order as compared to known foreign and domestic counterparts.

  18. Novel adaptive feedback synchronization scheme for a class of chaotic systems with and without parametric uncertainty

    International Nuclear Information System (INIS)

    Handa, Himesh; Sharma, B.B.

    2016-01-01

    Highlights: • New adaptive control design strategy to address chaotic system synchronization in master-slave configuration. • To derive control structure using model reference adaptive control like approach. • Extension of results to address general case with known and unknown system parameters. • Application of proposed strategy to chaotic systems. - Abstract: In this paper, a new adaptive feedback control design technique for the synchronization of a class of chaotic systems in master–slave configuration is proposed. The controller parameters are assumed to be unknown and are evolved using adaptation laws so as to achieve synchronization. To replicate real system operation, uncertainties are considered in both master as well as salve system parameters and adaptation laws for uncertain parameters are analytically derived using Lyapunov stability theory. The proposed strategy is derived by mimicking model reference adaptive control like structure for synchronization problem. To validate the methodology, two Genesio–Tesi systems and two Rossler's Prototype-4 systems are considered in master–slave configuration for synchronization. The analysis is done first with known system parameters and then uncertainties in system parameters are considered. Finally, detailed simulation results are provided to illustrate the effectiveness of the proposed results.

  19. Verification and uncertainty evaluation of CASMO-3/MASTER nuclear analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Song, Jae Seung; Cho, Byung Oh; Joo, Han Kyu; Zee, Sung Quun; Lee, Chung Chan; Park, Sang Yoon

    2000-06-01

    MASTER is a nuclear design code developed by KAERI. It uses group constants generated by CASMO-3 developed by Studsvik. In this report the verification and evaluation of uncertainty were performed for the code system application in nuclear reactor core analysis and design. The verification is performed via various benchmark comparisons for static and transient core condition, and core follow calculations with startup physics test predictions of total 14 cycles of pressurized water reactors. Benchmark calculation include comparisons with reference solutions of IAEA and OECA/NEA problems and critical experiment measurements. The uncertainty evaluation is focused to safety related parameters such as power distribution, reactivity coefficients, control rod worth and core reactivity. It is concluded that CASMO-3/MASTER can be applied for PWR core nuclear analysis and design without any bias factors. Also, it is verified that the system can be applied for SMART core, via supplemental comparisons with reference calculations by MCNP which is a probabilistic nuclear calculation code.

  20. Estimating angle-dependent systematic error and measurement uncertainty for a conoscopic holography measurement system

    Science.gov (United States)

    Paviotti, Anna; Carmignato, Simone; Voltan, Alessandro; Laurenti, Nicola; Cortelazzo, Guido M.

    2009-01-01

    The aim of this study is to assess angle-dependent systematic errors and measurement uncertainties for a conoscopic holography laser sensor mounted on a Coordinate Measuring Machine (CMM). The main contribution of our work is the definition of a methodology for the derivation of point-sensitive systematic and random errors, which must be determined in order to evaluate the accuracy of the measuring system. An ad hoc three dimensional artefact has been built for the task. The experimental test has been designed so as to isolate the effects of angular variations from those of other influence quantities that might affect the measurement result. We have found the best measurand to assess angle-dependent errors, and found some preliminary results on the expression of the systematic error and measurement uncertainty as a function of the zenith angle for the chosen measurement system and sample material.

  1. Leader-follower synchronisation for networked Lagrangian systems with uncertainties: a learning approach

    Science.gov (United States)

    Yang, Shiping; Xu, Jian-Xin

    2016-03-01

    This article addresses a leader-follower synchronisation problem of networked Lagrangian systems with uncertainties by an iterative learning control approach. The inherent properties of the systems are fully utilised in the controller design, and a directed acyclic graph is sufficient for communication among subsystems. The developed controller contains a proportional-plus-derivative (PD) term and two learning terms. The PD term drives the tracking error to zero, one learning term compensates for the model uncertainties, and the other one is used for disturbance rejection. It is shown that the synchronisation task can be achieved by the proposed controller, and all internal signals are either bounded or norm bounded. The theoretical results are supported by a numerical study.

  2. Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

    Science.gov (United States)

    He, Yuning; Davies, Misty Dawn

    2014-01-01

    The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

  3. Uncertainties in calculations of nuclear design code system for the high temperature engineering test reactor (HTTR)

    International Nuclear Information System (INIS)

    Shindo, R.; Yamashita, K.; Murata, I.

    1991-01-01

    The nuclear design code system for the HTTR consists of one dimensional cell burnup computer code, developed in JAERI and the TWOTRAN-2 transport code. In order to satisfy related design criteria, uncertainty of the calculation was investigated by comparing the calculated and experimental results. The experiments were performed with a graphite moderated critical assembly. It was confirmed that discrepancies between calculations and experiments were small enough to be allowed in the nuclear design of HTTR. 8 refs, 6 figs

  4. Quantifying uncertainties of a Soil-Foundation Structure-Interaction System under Seismic Excitation

    Energy Technology Data Exchange (ETDEWEB)

    Tong, C

    2008-04-07

    We applied a spectrum of uncertainty quantification (UQ) techniques to the study of a two-dimensional soil-foundation-structure-interaction (2DSFSI) system (obtained from Professor Conte at UCSD) subjected to earthquake excitation. In the process we varied 19 uncertain parameters describing material properties of the structure and the soil. We present in detail the results for the different stages of our UQ analyses.

  5. SWEPP PAN assay system uncertainty analysis: Passive mode measurements of graphite waste

    International Nuclear Information System (INIS)

    Blackwood, L.G.; Harker, Y.D.; Meachum, T.R.; Yoon, Woo Y.

    1997-07-01

    The Idaho National Engineering and Environmental Laboratory is being used as a temporary storage facility for transuranic waste generated by the U.S. Nuclear Weapons program at the Rocky Flats Plant (RFP) in Golden, Colorado. Currently, there is a large effort in progress to prepare to ship this waste to the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. In order to meet the TRU Waste Characterization Quality Assurance Program Plan nondestructive assay compliance requirements and quality assurance objectives, it is necessary to determine the total uncertainty of the radioassay results produced by the Stored Waste Examination Pilot Plant (SWEPP) Passive Active Neutron (PAN) radioassay system. To this end a modified statistical sampling and verification approach has been developed to determine the total uncertainty of a PAN measurement. In this approach the total performance of the PAN nondestructive assay system is simulated using computer models of the assay system and the resultant output is compared with the known input to assess the total uncertainty. This paper is one of a series of reports quantifying the results of the uncertainty analysis of the PAN system measurements for specific waste types and measurement modes. In particular this report covers passive mode measurements of weapons grade plutonium-contaminated graphite molds contained in 208 liter drums (waste code 300). The validity of the simulation approach is verified by comparing simulated output against results from measurements using known plutonium sources and a surrogate graphite waste form drum. For actual graphite waste form conditions, a set of 50 cases covering a statistical sampling of the conditions exhibited in graphite wastes was compiled using a Latin hypercube statistical sampling approach

  6. Applicability of the MCNP-ACAB system to inventory prediction in high-burnup fuels: sensitivity/uncertainty estimates

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Herranz, N.; Cabellos, O. [Madrid Polytechnic Univ., Dept. of Nuclear Engineering (Spain); Cabellos, O.; Sanz, J. [Madrid Polytechnic Univ., 2 Instituto de Fusion Nuclear (Spain); Sanz, J. [Univ. Nacional Educacion a Distancia, Dept. of Power Engineering, Madrid (Spain)

    2005-07-01

    We present a new code system which combines the Monte Carlo neutron transport code MCNP-4C and the inventory code ACAB as a suitable tool for high burnup calculations. Our main goal is to show that the system, by means of ACAB capabilities, enables us to assess the impact of neutron cross section uncertainties on the inventory and other inventory-related responses in high burnup applications. The potential impact of nuclear data uncertainties on some response parameters may be large, but only very few codes exist which can treat this effect. In fact, some of the most reported effective code systems in dealing with high burnup problems, such as CASMO-4, MCODE and MONTEBURNS, lack this capability. As first step, the potential of our system, ruling out the uncertainty capability, has been compared with that of those code systems, using a well referenced high burnup pin-cell benchmark exercise. It is proved that the inclusion of ACAB in the system allows to obtain results at least as reliable as those obtained using other inventory codes, such as ORIGEN2. Later on, the uncertainty analysis methodology implemented in ACAB, including both the sensitivity-uncertainty method and the uncertainty analysis by the Monte Carlo technique, is applied to this benchmark problem. We estimate the errors due to activation cross section uncertainties in the prediction of the isotopic content up to the high-burnup spent fuel regime. The most relevant uncertainties are remarked, and some of the most contributing cross sections to those uncertainties are identified. For instance, the most critical reaction for Am{sup 242m} is Am{sup 241}(n,{gamma}-m). At 100 MWd/kg, the cross-section uncertainty of this reaction induces an error of 6.63% on the Am{sup 242m} concentration.The uncertainties in the inventory of fission products reach up to 30%.

  7. Uncertainty in hyperthermia treatment planning: the need for robust system design

    International Nuclear Information System (INIS)

    De Greef, M; Kok, H P; Correia, D; Borsboom, P-P; Bel, A; Crezee, J

    2011-01-01

    Hyperthermia treatment planning (HTP) is an important tool to improve the quality of hyperthermia treatment. It is a practical way of designing new hyperthermia systems and can be used to optimize the phase and amplitude settings to achieve optimal heating. One of the main challenges to be dealt with however is the uncertainty in the modeling parameters. The role of dielectric and combined dielectric and perfusion uncertainty on optimization was investigated by means of HTP for six different systems: the 70 MHz AMC-4 (AMC: Academic Medical Center) and AMC-8 system, a 130 MHz version of the AMC-8 system, a three-ring AMC-12 system operating at 130 MHz, the BSD SigmaEye applicator and a dipole applicator with three rings each containing six dipole pairs operated at 150 MHz. For five patients with cervix uteri carcinoma, a patient model was created based on a hyperthermia planning CT. Variation of tissue parameters resulted in 16 dielectric models for every patient. In addition, four thermal models were created to study the combined effect of perfusion and dielectric uncertainty. The impact of dielectric uncertainty on optimization is found to be clearly dependent on the number of channels and increased from 0.5 deg. C for four channels to 1.5 deg. C for the 18-channel system. As a result, the potential gain relative to the AMC-4 system for the 70 MHz AMC-8 system was found to be largely compromised, while for the remaining systems a robust improvement in T 90 was observed. The dipole applicator showed the best target heating for two out of five patients, while for three others heating efficacy was comparable to the 130 MHz AMC-12 system or the 130 MHz AMC-8 system (one patient). Considering the increase in complexity when the number of channels is increased from 12 to 18, the AMC-12 system is considered as a good compromise between heating efficacy and robustness while still being a manageable heating system in clinical practice.

  8. Uncertainty in hyperthermia treatment planning: the need for robust system design

    Science.gov (United States)

    de Greef, M.; Kok, H. P.; Correia, D.; Borsboom, P.-P.; Bel, A.; Crezee, J.

    2011-06-01

    Hyperthermia treatment planning (HTP) is an important tool to improve the quality of hyperthermia treatment. It is a practical way of designing new hyperthermia systems and can be used to optimize the phase and amplitude settings to achieve optimal heating. One of the main challenges to be dealt with however is the uncertainty in the modeling parameters. The role of dielectric and combined dielectric and perfusion uncertainty on optimization was investigated by means of HTP for six different systems: the 70 MHz AMC-4 (AMC: Academic Medical Center) and AMC-8 system, a 130 MHz version of the AMC-8 system, a three-ring AMC-12 system operating at 130 MHz, the BSD SigmaEye applicator and a dipole applicator with three rings each containing six dipole pairs operated at 150 MHz. For five patients with cervix uteri carcinoma, a patient model was created based on a hyperthermia planning CT. Variation of tissue parameters resulted in 16 dielectric models for every patient. In addition, four thermal models were created to study the combined effect of perfusion and dielectric uncertainty. The impact of dielectric uncertainty on optimization is found to be clearly dependent on the number of channels and increased from 0.5 °C for four channels to 1.5 °C for the 18-channel system. As a result, the potential gain relative to the AMC-4 system for the 70 MHz AMC-8 system was found to be largely compromised, while for the remaining systems a robust improvement in T90 was observed. The dipole applicator showed the best target heating for two out of five patients, while for three others heating efficacy was comparable to the 130 MHz AMC-12 system or the 130 MHz AMC-8 system (one patient). Considering the increase in complexity when the number of channels is increased from 12 to 18, the AMC-12 system is considered as a good compromise between heating efficacy and robustness while still being a manageable heating system in clinical practice.

  9. Probabilistic Approach to Enable Extreme-Scale Simulations under Uncertainty and System Faults. Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Knio, Omar [Duke Univ., Durham, NC (United States). Dept. of Mechanical Engineering and Materials Science

    2017-05-05

    The current project develops a novel approach that uses a probabilistic description to capture the current state of knowledge about the computational solution. To effectively spread the computational effort over multiple nodes, the global computational domain is split into many subdomains. Computational uncertainty in the solution translates into uncertain boundary conditions for the equation system to be solved on those subdomains, and many independent, concurrent subdomain simulations are used to account for this bound- ary condition uncertainty. By relying on the fact that solutions on neighboring subdomains must agree with each other, a more accurate estimate for the global solution can be achieved. Statistical approaches in this update process make it possible to account for the effect of system faults in the probabilistic description of the computational solution, and the associated uncertainty is reduced through successive iterations. By combining all of these elements, the probabilistic reformulation allows splitting the computational work over very many independent tasks for good scalability, while being robust to system faults.

  10. Experimental findings on the underwater measurements uncertainty of speed of sound and the alignment system

    Science.gov (United States)

    Santos, T. Q.; Alvarenga, A. V.; Oliveira, D. P.; Mayworm, R. C.; Souza, R. M.; Costa-Félix, R. P. B.

    2016-07-01

    Speed of sound is an important quantity to characterize reference materials for ultrasonic applications, for instance. The alignment between the transducer and the test body is an key activity in order to perform reliable and consistent measurement. The aim of this work is to evaluate the influence of the alignment system to the expanded uncertainty of such measurement. A stainless steel cylinder was previously calibrated on an out of water system typically used for calibration of non-destructive blocks. Afterwards, the cylinder was calibrated underwater with two distinct alignment system: fixed and mobile. The values were statistically compared to the out-of-water measurement, considered the golden standard for such application. For both alignment systems, the normalized error was less than 0.8, leading to conclude that the both measurement system (under and out-of-water) do not diverge significantly. The gold standard uncertainty was 2.7 m-s-1, whilst the fixed underwater system resulted in 13 m-s-1, and the mobile alignment system achieved 6.6 m-s-1. After the validation of the underwater system for speed of sound measurement, it will be applied to certify Encapsulated Tissue Mimicking Material as a reference material for biotechnology application.

  11. Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty

    International Nuclear Information System (INIS)

    Wattanapongskorn, Naruemon; Coit, David W.

    2007-01-01

    In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed

  12. Estimation of the Influence of Power System Mathematical Model Parameter Uncertainty on PSS2A System Stabilizers

    Directory of Open Access Journals (Sweden)

    Adrian Nocoń

    2015-09-01

    Full Text Available This paper presents an analysis of the influence of uncertainty of power system mathematical model parameters on optimised parameters of PSS2A system stabilizers. Optimisation of power system stabilizer parameters was based on polyoptimisation (multi-criteria optimisation. Optimisation criteria were determined for disturbances occurring in a multi-machine power system, when taking into account transient waveforms associated with electromechanical swings (instantaneous power, angular speed and terminal voltage waveforms of generators. A genetic algorithm with floating-point encoding, tournament selection, mean crossover and perturbative mutations, modified for the needs of investigations, was used for optimisation. The impact of uncertainties on the quality of operation of power system stabilizers with optimised parameters has been evaluated using various deformation factors.

  13. Lens refracting cost effective photovoltaic solar energy concentrating systems

    International Nuclear Information System (INIS)

    Pilawjian, G.A.

    2014-01-01

    The overall cost reduction task is studied for photovoltaic (PV) solar energy systems. For that purpose, a new, cost effective lens refracting system is developed. The concentrating system consists of Fresnel lenses placed under different facet angles refracting the sun light onto the solar cells placed along a line. The developed photovoltaic concentrating system uses the mathematical model of Fresnel lens concentrating optics for photovoltaic systems used to optimize the system by cost. A computer program FLCPVSys2.1 for the new concentrating system is developed allowing to design a photovoltaic system of the required power with the minimum cost. The program can be used for designing a cost effective photovoltaic solar concentrating system

  14. An Ounce of Prevention, a Pound of Uncertainty: The Cost-Effectiveness of School-Based Drug Prevention Programs.

    Science.gov (United States)

    Caulkins, Jonathan P.; Rydell, C. Peter; Everingham, Susan S.; Chiesa, James; Bushway, Shawn

    This book describes an analysis of the cost-effectiveness of model school-based drug prevention programs at reducing cocaine consumption. It compares prevention's cost-effectiveness with that of several enforcement programs and with that of treating heavy cocaine users. It also assesses the cost of nationwide implementation of model prevention…

  15. Cost and performance analysis of physical security systems

    Energy Technology Data Exchange (ETDEWEB)

    Hicks, M.J. [Sandia National Lab., Albuquerque, NM (United States); Yates, D.; Jago, W.H. [Tecolote Research, Inc., Santa Barbara, CA (United States)] [and others

    1997-06-01

    CPA - Cost and Performance Analysis - is a prototype integration of existing PC-based cost and performance analysis tools: ACEIT (Automated Cost Estimating Integrated Tools) and ASSESS (Analytic System and Software for Evaluating Safeguards and Security). ACE is an existing DOD PC-based tool that supports cost analysis over the full life cycle of a system; that is, the cost to procure, operate, maintain and retire the system and all of its components. ASSESS is an existing DOE PC-based tool for analysis of performance of physical protection systems. Through CPA, the cost and performance data are collected into Excel workbooks, making the data readily available to analysts and decision makers in both tabular and graphical formats and at both the system and subsystem levels. The structure of the cost spreadsheets incorporates an activity-based approach to cost estimation. Activity-based costing (ABC) is an accounting philosophy used by industry to trace direct and indirect costs to the products or services of a business unit. By tracing costs through security sensors and procedures and then mapping the contributions of the various sensors and procedures to system effectiveness, the CPA architecture can provide security managers with information critical for both operational and strategic decisions. The architecture, features and applications of the CPA prototype are presented. 5 refs., 3 figs.

  16. Cost and performance analysis of physical security systems

    International Nuclear Information System (INIS)

    Hicks, M.J.; Yates, D.; Jago, W.H.

    1997-01-01

    CPA - Cost and Performance Analysis - is a prototype integration of existing PC-based cost and performance analysis tools: ACEIT (Automated Cost Estimating Integrated Tools) and ASSESS (Analytic System and Software for Evaluating Safeguards and Security). ACE is an existing DOD PC-based tool that supports cost analysis over the full life cycle of a system; that is, the cost to procure, operate, maintain and retire the system and all of its components. ASSESS is an existing DOE PC-based tool for analysis of performance of physical protection systems. Through CPA, the cost and performance data are collected into Excel workbooks, making the data readily available to analysts and decision makers in both tabular and graphical formats and at both the system and subsystem levels. The structure of the cost spreadsheets incorporates an activity-based approach to cost estimation. Activity-based costing (ABC) is an accounting philosophy used by industry to trace direct and indirect costs to the products or services of a business unit. By tracing costs through security sensors and procedures and then mapping the contributions of the various sensors and procedures to system effectiveness, the CPA architecture can provide security managers with information critical for both operational and strategic decisions. The architecture, features and applications of the CPA prototype are presented. 5 refs., 3 figs

  17. High-quality Wind Power Scenario Forecasts for Decision-making Under Uncertainty in Power Systems

    DEFF Research Database (Denmark)

    Delikaraoglou, Stefanos; Pinson, Pierre

    2014-01-01

    The large scale integration of wind generation in existing power systems requires novel operational strategies and market clearing mechanisms to account for the variable nature of this energy source. An efficient method to cope with this uncertainty is stochastic optimization which however requires......-valued and probabilistic predictions as well as scenarios representing the spatio-temporal dependence structure of forecast errors. The applicability of the proposed framework is demonstrated with a small-scale stochastic unit commitment model....... high-quality forecasts in the form of scenarios. The main goal of this work is to release a public dataset of wind power forecasts to be used as a reference for future research. To that extent, we provide a complete framework to describe wind power uncertainty in terms of single...

  18. Cost analysis of energy storage systems for electric utility applications

    Energy Technology Data Exchange (ETDEWEB)

    Akhil, A. [Sandia National Lab., Albuquerque, NM (United States); Swaminathan, S.; Sen, R.K. [R.K. Sen & Associates, Inc., Bethesda, MD (United States)

    1997-02-01

    Under the sponsorship of the Department of Energy, Office of Utility Technologies, the Energy Storage System Analysis and Development Department at Sandia National Laboratories (SNL) conducted a cost analysis of energy storage systems for electric utility applications. The scope of the study included the analysis of costs for existing and planned battery, SMES, and flywheel energy storage systems. The analysis also identified the potential for cost reduction of key components.

  19. Effects of the uncertainty of energy price and water availability forecasts on the operation of Alpine hydropower reservoir systems

    Science.gov (United States)

    Anghileri, D.; Castelletti, A.; Burlando, P.

    2016-12-01

    European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow

  20. Factors Associated with Photovoltaic System Costs (Topical Issues Brief)

    Energy Technology Data Exchange (ETDEWEB)

    Mortensen, J.

    2001-06-12

    A variety of factors can affect the cost of photovoltaic systems. This report analyses the relationship among such factors by using information entered into a voluntary registry of PV systems and performing regression analyses. The results showed statistically significant relationships between photovoltaic system cost and (a) grid connection, (b) installation year, (c) areas where the utility had entered into volume purchasing agreements.

  1. The cost system of GSI - heavy ion facility in Darmstadt

    International Nuclear Information System (INIS)

    1979-01-01

    The paper gives an overview about the organization and the research program of the GSI (Heavy Ion Facility in Darmstadt). The cost accounting system is discussed in detail, financing, cost center accounting and cost unit accounting are described. (A.N.)

  2. Is the system really the solution? Operating costs in hospital systems.

    Science.gov (United States)

    Burns, Lawton Robert; McCullough, Jeffrey S; Wholey, Douglas R; Kruse, Gregory; Kralovec, Peter; Muller, Ralph

    2015-06-01

    Hospital system formation has recently accelerated. Executives emphasize scale economies that lower operating costs, a claim unsupported in academic research. Do systems achieve lower costs than freestanding facilities, and, if so, which system types? We test hypotheses about the relationship of cost with membership in systems, larger systems, and centralized and local hub-and-spoke systems. We also test whether these relationships have changed over time. Examining 4,000 U.S. hospitals during 1998 to 2010, we find no evidence that system members exhibit lower costs. However, members of smaller systems are lower cost than larger systems, and hospitals in centralized systems are lower cost than everyone else. There is no evidence that the system's spatial configuration is associated with cost, although national system hospitals exhibit higher costs. Finally, these results hold over time. We conclude that while systems in general may not be the solution to lower costs, some types of systems are. © The Author(s) 2015.

  3. System Approach of Logistic Costs Optimization Solution in Supply Chain

    OpenAIRE

    Majerčák, Peter; Masárová, Gabriela; Buc, Daniel; Majerčáková, Eva

    2013-01-01

    This paper is focused on the possibility of using the costs simulation in supply chain, which are on relative high level. Our goal is to determine the costs using logistic costs optimization which must necessarily be used in business activities in the supply chain management. The paper emphasizes the need to perform not isolated optimization in the whole supply chain. Our goal is to compare classic approach, when every part tracks its costs isolated, a try to minimize them, with the system (l...

  4. Embracing uncertainty, managing complexity: applying complexity thinking principles to transformation efforts in healthcare systems.

    Science.gov (United States)

    Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney

    2018-03-21

    Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By

  5. Mental health services costs within the Alberta criminal justice system.

    Science.gov (United States)

    Jacobs, Philip; Moffatt, Jessica; Dewa, Carolyn S; Nguyen, Thanh; Zhang, Ting; Lesage, Alain

    2016-01-01

    Mental illness has been widely cited as a driver of costs in the criminal justice system. The objective of this paper is to estimate the additional mental health service costs incurred within the criminal justice system that are incurred because of people with mental illnesses who go through the system. Our focus is on costs in Alberta. We set up a model of the flow of all persons through the criminal justice system, including police, court, and corrections components, and for mental health diversion, review, and forensic services. We estimate the transitional probabilities and costs that accrue as persons who have been charged move through the system. Costs are estimated for the Alberta criminal justice system as a whole, and for the mental illness component. Public expenditures for each person diverted or charged in Alberta in the criminal justice system, including mental health costs, were $16,138. The 95% range of this estimate was from $14,530 to $19,580. Of these costs, 87% were for criminal justice services and 13% were for mental illness-related services. Hospitalization for people with mental illness who were reviewed represented the greatest additional cost associated with mental illnesses. Treatment costs stemming from mental illnesses directly add about 13% onto those in the criminal justice system. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Cost-effectiveness of insulin analogs from the perspective of the Brazilian public health system

    Directory of Open Access Journals (Sweden)

    Maurílio de Souza Cazarim

    2017-11-01

    Full Text Available ABSTRACT Human insulin is provided by the Brazilian Public Health System (BPHS for the treatment of diabetes, however, legal proceedings to acquire insulin analogs have burdened the BPHS health system. The aim of this study was to perform a cost-effectiveness analysis to compare insulin analogs and human insulins. This is a pharmacoeconomic study of cost-effectiveness. The direct medical cost related to insulin extracted from the Ministry of Health drug price list was considered. The clinical results, i.e. reduction in glycated hemoglobin (HbA1c, were extracted by meta-analysis. Different scenarios were structured to measure the uncertainties regarding the costs and reduction in HbA1c. Decision tree was developed for sensitivity of Incremental Cost Effectiveness Ratio (ICER. A total of fifteen scenarios were structured. Given the best-case scenario for the insulin analogs, the insulins aspart, lispro, glargine and detemir showed an ICER of R$ 1,768.59; R$ 3,308.54; R$ 11,718.75 and R$ 2,685.22, respectively. In all scenarios in which the minimum effectiveness was proposed, lispro, glargine and detemir were dominant strategies. Sensitivity analysis showed that the aspart had R$ 3,066.98 [95 % CI: 2339.22; 4418.53] and detemir had R$ 6,163.97 [95% CI: 3919.29; 11401.57] for incremental costs. We concluded there was evidence that the insulin aspart is the most cost-effective.

  7. Probabilistic Mass Growth Uncertainties

    Science.gov (United States)

    Plumer, Eric; Elliott, Darren

    2013-01-01

    Mass has been widely used as a variable input parameter for Cost Estimating Relationships (CER) for space systems. As these space systems progress from early concept studies and drawing boards to the launch pad, their masses tend to grow substantially, hence adversely affecting a primary input to most modeling CERs. Modeling and predicting mass uncertainty, based on historical and analogous data, is therefore critical and is an integral part of modeling cost risk. This paper presents the results of a NASA on-going effort to publish mass growth datasheet for adjusting single-point Technical Baseline Estimates (TBE) of masses of space instruments as well as spacecraft, for both earth orbiting and deep space missions at various stages of a project's lifecycle. This paper will also discusses the long term strategy of NASA Headquarters in publishing similar results, using a variety of cost driving metrics, on an annual basis. This paper provides quantitative results that show decreasing mass growth uncertainties as mass estimate maturity increases. This paper's analysis is based on historical data obtained from the NASA Cost Analysis Data Requirements (CADRe) database.

  8. Uncertainty analysis of an integrated energy system based on information theory

    International Nuclear Information System (INIS)

    Fu, Xueqian; Sun, Hongbin; Guo, Qinglai; Pan, Zhaoguang; Xiong, Wen; Wang, Li

    2017-01-01

    Currently, a custom-designed configuration of different renewable technologies named the integrated energy system (IES) has become popular due to its high efficiency, benefiting from complementary multi-energy technologies. This paper proposes an information entropy approach to quantify uncertainty in an integrated energy system based on a stochastic model that drives a power system model derived from an actual network on Barry Island. Due to the complexity of co-behaviours between generators, a copula-based approach is utilized to articulate the dependency structure of the generator outputs with regard to such factors as weather conditions. Correlation coefficients and mutual information, which are effective for assessing the dependence relationships, are applied to judge whether the stochastic IES model is correct. The calculated information values can be used to analyse the impacts of the coupling of power and heat on power flows and heat flows, and this approach will be helpful for improving the operation of IES. - Highlights: • The paper explores uncertainty of an integrated energy system. • The dependent weather model is verified from the perspective of correlativity. • The IES model considers the dependence between power and heat. • The information theory helps analyse the complexity of IES operation. • The application of the model is studied using an operational system on Barry Island.

  9. Uncertainty analyses of the countermeasures module of the program system UFOMOD

    International Nuclear Information System (INIS)

    Fischer, F.; Ehrhardt, J.; Burkart, K.

    1989-10-01

    This report refers to uncertainty analyses of the countermeasures submodule of the program system UFOMOD, version NE 87/1, whose important input parameters are linked with probability distributions derived from expert judgement. Uncertainty bands show how much variability exists, sensitivity measures determine what causes this variability in consequences. Results are presented as confidence bands of complementary cumulative frequency distributions (CCFDs) of individual acute organ doses (lung, bone marrow), individual risks (pulmonary and hematopoietic syndrome) and the corresponding number of early fatalities, partially as a function of distance from the site. In addition the ranked influence of the uncertain parameters on the different consequence types is shown. For the estimation of confidence bands a model parameter sample size of n=60 equal to 3 times the number of uncertain model parameters is chosen. For a reduced set of nine model parameters a sample size of n=50 is selected. A total of 20 uncertain parameters is considered. The most sensitive parameters of the countermeasures submodule of UFOMOD appeared to be the initial delay of emergency actions in a keyhole shaped area A and the fractions of the population evacuating area A spontaneously during the sheltering period or staying outdoors. Under the conditions of the source term the influence on the overall uncertainty in the consequence variables - individual acute organ doses, individual risks and early fatalities - of driving times to leave the evacuation area is small. (orig./HP) [de

  10. Uncertainty and sensitivity analyses of the complete program system UFOMOD and of selected submodels

    International Nuclear Information System (INIS)

    Fischer, F.; Ehrhardt, J.; Hasemann, I.

    1990-09-01

    Uncertainty and sensitivity studies with the program system UFOMOD have been performed since several years on a submodel basis to get a deeper insight into the propagation of parameter uncertainties through the different modules and to quantify their contribution to the confidence bands of the intermediate and final results of an accident consequence assessment. In a series of investigations with the atmospheric dispersion module, the models describing early protective actions, the models calculating short-term organ doses and the health effects model of the near range subsystem NE of UFOMOD, a great deal of experience has been gained with methods and evaluation techniques for uncertainty and sensitivity analyses. Especially the influence on results of different sampling techniques and sample sizes, parameter distributions and correlations could be quantified and the usefulness of sensitivity measures for the interpretation of results could be demonstrated. In each submodel investigation, the (5%, 95%)-confidende bounds of the complementary cumulative frequency distributions (CCFDs) of various consequence types (activity concentrations of I-131 and Cs-137, individual acute organ doses, individual risks of nonstochastic health effects, and the number of early deaths) were calculated. The corresponding sensitivity analyses for each of these endpoints led to a list of parameters contributing significantly to the variation of mean values and 99% - fractiles. The most important parameters were extracted and combined for the final overall analysis. (orig.) [de

  11. Review of storage battery system cost estimates

    Energy Technology Data Exchange (ETDEWEB)

    Brown, D.R.; Russell, J.A.

    1986-04-01

    Cost analyses for zinc bromine, sodium sulfur, and lead acid batteries were reviewed. Zinc bromine and sodium sulfur batteries were selected because of their advanced design nature and the high level of interest in these two technologies. Lead acid batteries were included to establish a baseline representative of a more mature technology.

  12. [Cost of therapy for neurodegenerative diseases. Applying an activity-based costing system].

    Science.gov (United States)

    Sánchez-Rebull, María-Victoria; Terceño Gómez, Antonio; Travé Bautista, Angeles

    2013-01-01

    To apply the activity based costing (ABC) model to calculate the cost of therapy for neurodegenerative disorders in order to improve hospital management and allocate resources more efficiently. We used the case study method in the Francolí long-term care day center. We applied all phases of an ABC system to quantify the cost of the activities developed in the center. We identified 60 activities; the information was collected in June 2009. The ABC system allowed us to calculate the average cost per patient with respect to the therapies received. The most costly and commonly applied technique was psycho-stimulation therapy. Focusing on this therapy and on others related to the admissions process could lead to significant cost savings. ABC costing is a viable method for costing activities and therapies in long-term day care centers because it can be adapted to their structure and standard practice. This type of costing allows the costs of each activity and therapy, or combination of therapies, to be determined and aids measures to improve management. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.

  13. Cost of radon-barrier systems for uranium mill tailings

    International Nuclear Information System (INIS)

    Baker, E.G.; Hartley, J.N.

    1982-08-01

    This report deals specifically with the cost of three types of radon barrier systems, earthen covers, asphalt emulsion covers, and multilayer covers, which could meet standards proposed by the Environmental Protection Agency to stabilize uranium mill tailings located primarily in the western US. In addition, the report includes a sensitivity analysis of various factors which significantly effect the overall cost of the three systems. These analyses were based on a generic disposal site. Four different 3m thick earthen covers were tested and cost an average of $27/m 2 . The least expensive earthen cover cost was about $21/m 2 . The asphalt cover system (6 to 7 cm of asphalt topped with 0.6m of overburden) cost about $28/m 2 . The four multilayer covers averaged $57/m 2 , but materials handling problems encountered during the test inflated this cost above what was anticipated and significant cost reductions should be possible. The least expensive multilayer cover cost $43/m 2 . Based on the results of the Grand Junction field test we estimated the cost of covering the tailings from three high priority sites, Durango, Shiprock, and Salt Lake City (Vitro). The cost of a 3m earthen cover ranged from $18 to 33/m 2 for the seven disposal sites (two or three at each location) studied. The cost of asphalt cover systems were $23 to 28/m 2 and the multilayer cover costs were between $31 to 36/m 2 . The earthen cover costs are less than the Grand Junction field test cost primarily because cover material is available at or near most of the disposal sites selected. Earthen material was imported from 6 to 10 miles for the field test. Assuming more efficienct utilization of materials significantly reduced the cost of the multilayer covers

  14. Space construction system analysis. Part 2: Cost and programmatics

    Science.gov (United States)

    Vonflue, F. W.; Cooper, W.

    1980-01-01

    Cost and programmatic elements of the space construction systems analysis study are discussed. The programmatic aspects of the ETVP program define a comprehensive plan for the development of a space platform, the construction system, and the space shuttle operations/logistics requirements. The cost analysis identified significant items of cost on ETVP development, ground, and flight segments, and detailed the items of space construction equipment and operations.

  15. Concentrated photovoltaics system costs and learning curve analysis

    Science.gov (United States)

    Haysom, Joan E.; Jafarieh, Omid; Anis, Hanan; Hinzer, Karin

    2013-09-01

    An extensive set of costs in /W for the installed costs of CPV systems has been amassed from a range of public sources, including both individual company prices and market reports. Cost reductions over time are very evident, with current prices for 2012 in the range of 3.0 ± 0.7 /W and a predicted cost of 1.5 /W for 2020. Cost data is combined with deployment volumes in a learning curve analysis, providing a fitted learning rate of either 18.5% or 22.3% depending on the methodology. This learning rate is compared to that of PV modules and PV installed systems, and the influence of soft costs is discussed. Finally, if an annual growth rate of 39% is assumed for deployed volumes, then, using the learning rate of 20%, this would predict the achievement of a cost point of 1.5 /W by 2016.

  16. Labor costing for HANDI 2000 business management system

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, D.

    1998-08-24

    Costing labor in the Financial Data System has traditionally been done using standard rates based on type of employee by organization. This methodology will change with the implementation of the PeopleSoft financial system. Labor in the new environment will be cost against actual dollars and marked up with an employee adder, to cover absences and fringe benefits.

  17. Extreme Cost Reductions with Multi-Megawatt Centralized Inverter Systems

    Energy Technology Data Exchange (ETDEWEB)

    Schwabe, Ulrich [Alencon LLC; Fishman, Oleg [Alencon LLC

    2015-03-20

    The objective of this project was to fully develop, demonstrate, and commercialize a new type of utility scale PV system. Based on patented technology, this includes the development of a truly centralized inverter system with capacities up to 100MW, and a high voltage, distributed harvesting approach. This system promises to greatly impact both the energy yield from large scale PV systems by reducing losses and increasing yield from mismatched arrays, as well as reduce overall system costs through very cost effective conversion and BOS cost reductions enabled by higher voltage operation.

  18. Evolutionary systems biology of amino acid biosynthetic cost in yeast.

    Directory of Open Access Journals (Sweden)

    Michael D Barton

    2010-08-01

    Full Text Available Every protein has a biosynthetic cost to the cell based on the synthesis of its constituent amino acids. In order to optimise growth and reproduction, natural selection is expected, where possible, to favour the use of proteins whose constituents are cheaper to produce, as reduced biosynthetic cost may confer a fitness advantage to the organism. Quantifying the cost of amino acid biosynthesis presents challenges, since energetic requirements may change across different cellular and environmental conditions. We developed a systems biology approach to estimate the cost of amino acid synthesis based on genome-scale metabolic models and investigated the effects of the cost of amino acid synthesis on Saccharomyces cerevisiae gene expression and protein evolution. First, we used our two new and six previously reported measures of amino acid cost in conjunction with codon usage bias, tRNA gene number and atomic composition to identify which of these factors best predict transcript and protein levels. Second, we compared amino acid cost with rates of amino acid substitution across four species in the genus Saccharomyces. Regardless of which cost measure is used, amino acid biosynthetic cost is weakly associated with transcript and protein levels. In contrast, we find that biosynthetic cost and amino acid substitution rates show a negative correlation, but for only a subset of cost measures. In the economy of the yeast cell, we find that the cost of amino acid synthesis plays a limited role in shaping transcript and protein expression levels compared to that of translational optimisation. Biosynthetic cost does, however, appear to affect rates of amino acid evolution in Saccharomyces, suggesting that expensive amino acids may only be used when they have specific structural or functional roles in protein sequences. However, as there appears to be no single currency to compute the cost of amino acid synthesis across all cellular and environmental

  19. Cost Engineering Techniques and Their Applicability for Cost Estimation of Organic Rankine Cycle Systems

    Directory of Open Access Journals (Sweden)

    Sanne Lemmens

    2016-06-01

    Full Text Available The potential of organic Rankine cycle (ORC systems is acknowledged by both considerable research and development efforts and an increasing number of applications. Most research aims at improving ORC systems through technical performance optimization of various cycle architectures and working fluids. The assessment and optimization of technical feasibility is at the core of ORC development. Nonetheless, economic feasibility is often decisive when it comes down to considering practical instalments, and therefore an increasing number of publications include an estimate of the costs of the designed ORC system. Various methods are used to estimate ORC costs but the resulting values are rarely discussed with respect to accuracy and validity. The aim of this paper is to provide insight into the methods used to estimate these costs and open the discussion about the interpretation of these results. A review of cost engineering practices shows there has been a long tradition of industrial cost estimation. Several techniques have been developed, but the expected accuracy range of the best techniques used in research varies between 10% and 30%. The quality of the estimates could be improved by establishing up-to-date correlations for the ORC industry in particular. Secondly, the rapidly growing ORC cost literature is briefly reviewed. A graph summarizing the estimated ORC investment costs displays a pattern of decreasing costs for increasing power output. Knowledge on the actual costs of real ORC modules and projects remains scarce. Finally, the investment costs of a known heat recovery ORC system are discussed and the methodologies and accuracies of several approaches are demonstrated using this case as benchmark. The best results are obtained with factorial estimation techniques such as the module costing technique, but the accuracies may diverge by up to +30%. Development of correlations and multiplication factors for ORC technology in particular is

  20. Cost Effectiveness Analysis of System Safety

    Science.gov (United States)

    1987-03-01

    determine the most desirable smog control device for automobiles. Similarly, the agency might also want to evaluate the comparative merits of expending funds...best allocation of available resoruces among the alternative opportunities. Conducting a cost-effectiveness evaluation to determine the best smog ...evaluation. Admittedly, not all complex problems can be solved by simple techni- ques , but disallusion to the mathematical sophistica- tion of the analytical

  1. External costs and taxes in heat supply systems

    International Nuclear Information System (INIS)

    Karlsson, Aasa; Gustavsson, Leif

    2003-01-01

    A systems approach was used to compare different heating systems from a consumer perspective. The whole energy system was considered from natural resources to the required energy services. District heating, electric heat pumps, electric boilers, natural-gas-, oil- or pellet-fired local boilers were considered when supplying heat to a detached house. The district heat production included wood-chip-fired and natural-gas-fired cogeneration plants. Electricity other than cogenerated electricity was produced in wood-chip- and natural-gas-fired stand-alone power plants. The analysis includes four tax scenarios, as well as the external cost of environmental and health damage arising from energy conversion emission based on the ExternE study of the European Commission. The most cost-efficient systems were the natural-gas and oil boiler systems, followed by the heat pump and district heating systems, when the external cost and taxes were excluded. When including the external costs of CO 2 emission, the wood-fuel-based systems were much more cost efficient than the fossil-fuel-based systems, also when CO 2 capture and storage were applied. The external costs are, however, highly uncertain. Taxes steer towards lowering energy use and lowering CO 2 emission if they are levied solely on all the fossil-fuel-related emission and fuel use in the systems. If consumer electricity and heat taxes are used, the taxes have an impact on the total cost, regardless of the fuel used, thereby benefiting fuel-based local heating systems. The heat pump systems were the least affected by taxes, due to their high energy efficiency. The electric boiler systems were the least cost-efficient systems, also when the external cost and taxes were included

  2. Estimation of Nonlinear Functions of State Vector for Linear Systems with Time-Delays and Uncertainties

    Directory of Open Access Journals (Sweden)

    Il Young Song

    2015-01-01

    Full Text Available This paper focuses on estimation of a nonlinear function of state vector (NFS in discrete-time linear systems with time-delays and model uncertainties. The NFS represents a multivariate nonlinear function of state variables, which can indicate useful information of a target system for control. The optimal nonlinear estimator of an NFS (in mean square sense represents a function of the receding horizon estimate and its error covariance. The proposed receding horizon filter represents the standard Kalman filter with time-delays and special initial horizon conditions described by the Lyapunov-like equations. In general case to calculate an optimal estimator of an NFS we propose using the unscented transformation. Important class of polynomial NFS is considered in detail. In the case of polynomial NFS an optimal estimator has a closed-form computational procedure. The subsequent application of the proposed receding horizon filter and nonlinear estimator to a linear stochastic system with time-delays and uncertainties demonstrates their effectiveness.

  3. EOS Operations Systems: EDOS Implemented Changes to Reduce Operations Costs

    Science.gov (United States)

    Cordier, Guy R.; Gomez-Rosa, Carlos; McLemore, Bruce D.

    2007-01-01

    The authors describe in this paper the progress achieved to-date with the reengineering of the Earth Observing System (EOS) Data and Operations System (EDOS), the experience gained in the process and the ensuing reduction of ground systems operations costs. The reengineering effort included a major methodology change, applying to an existing schedule driven system, a data-driven system approach.

  4. Introducing uncertainty analysis of nucleation and crystal growth models in Process Analytical Technology (PAT) system design of crystallization processes.

    Science.gov (United States)

    Samad, Noor Asma Fazli Abdul; Sin, Gürkan; Gernaey, Krist V; Gani, Rafiqul

    2013-11-01

    This paper presents the application of uncertainty and sensitivity analysis as part of a systematic model-based process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty, while for sensitivity analysis, global methods including the standardized regression coefficients (SRC) and Morris screening are used to identify the most significant parameters. The potassium dihydrogen phosphate (KDP) crystallization process is used as a case study, both in open-loop and closed-loop operation. In the uncertainty analysis, the impact on the predicted output of uncertain parameters related to the nucleation and the crystal growth model has been investigated for both a one- and two-dimensional crystal size distribution (CSD). The open-loop results show that the input uncertainties lead to significant uncertainties on the CSD, with appearance of a secondary peak due to secondary nucleation for both cases. The sensitivity analysis indicated that the most important parameters affecting the CSDs are nucleation order and growth order constants. In the proposed PAT system design (closed-loop), the target CSD variability was successfully reduced compared to the open-loop case, also when considering uncertainty in nucleation and crystal growth model parameters. The latter forms a strong indication of the robustness of the proposed PAT system design in achieving the target CSD and encourages its transfer to full-scale implementation. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Managing social-ecological systems under uncertainty: implementation in the real world

    Directory of Open Access Journals (Sweden)

    Ana Nuno

    2014-06-01

    Full Text Available Management decisions for natural resources are not made in a vacuum; the environmental and ecological conditions as well as the socioeconomic and political contexts affect goals, the choice of interventions, their feasibility, and which outcomes are obtained. Although uncertainty is recognized as a feature of natural resource management, little attention has been given to the uncertainty generated by institutional settings, historical contingency, and individual people's influence. These implementation uncertainties, related to the translation of policy into practice, make it difficult to predict the outcomes of management interventions within social-ecological systems. Using the conservation of species hunted for bushmeat in the Serengeti as a case study, we investigated the challenges and potential barriers to successful implementation of natural resource management policies. We used a mixed-methods approach, combining semistructured interviews with scenario building, social network, and institutional analysis exercises. Using a management strategy evaluation (MSE conceptual framework, we obtained insights into the constraints and opportunities for fulfilling stakeholder aspirations for the social-ecological system, analyzed the multiple roles played by different institutions in the system, and described the interactions between different actor types. We found that the respondents had generally similar views about the current and future status of the Serengeti but disagreed about how to address issues of conservation concern and were more uncertain about the actual outcomes of management interventions. Improving conservation implementation (rather than research, monitoring, or status assessment was perceived as the key priority to be addressed. Institutional barriers were perceived as an important challenge given that the decision-making and implementation processes were broadly distributed across a number of institutions. Conservation social

  6. Economics of human performance and systems total ownership cost.

    Science.gov (United States)

    Onkham, Wilawan; Karwowski, Waldemar; Ahram, Tareq Z

    2012-01-01

    Financial costs of investing in people is associated with training, acquisition, recruiting, and resolving human errors have a significant impact on increased total ownership costs. These costs can also affect the exaggerate budgets and delayed schedules. The study of human performance economical assessment in the system acquisition process enhances the visibility of hidden cost drivers which support program management informed decisions. This paper presents the literature review of human total ownership cost (HTOC) and cost impacts on overall system performance. Economic value assessment models such as cost benefit analysis, risk-cost tradeoff analysis, expected value of utility function analysis (EV), growth readiness matrix, multi-attribute utility technique, and multi-regressions model were introduced to reflect the HTOC and human performance-technology tradeoffs in terms of the dollar value. The human total ownership regression model introduces to address the influencing human performance cost component measurement. Results from this study will increase understanding of relevant cost drivers in the system acquisition process over the long term.

  7. Cost evaluation of clinical laboratory in Taiwan's National Health System by using activity-based costing.

    Science.gov (United States)

    Su, Bin-Guang; Chen, Shao-Fen; Yeh, Shu-Hsing; Shih, Po-Wen; Lin, Ching-Chiang

    2016-11-01

    To cope with the government's policies to reduce medical costs, Taiwan's healthcare service providers are striving to survive by pursuing profit maximization through cost control. This article aimed to present the results of cost evaluation using activity-based costing performed in the laboratory in order to throw light on the differences between costs and the payment system of National Health Insurance (NHI). This study analyzed the data of costs and income of the clinical laboratory. Direct costs belong to their respective sections of the department. The department's shared costs, including public expenses and administrative assigned costs, were allocated to the department's respective sections. A simple regression equation was created to predict profit and loss, and evaluate the department's break-even point, fixed cost, and contribution margin ratio. In clinical chemistry and seroimmunology sections, the cost per test was lower than the NHI payment and their major laboratory tests had revenues with the profitability ratio of 8.7%, while the other sections had a higher cost per test than the NHI payment and their major tests were in deficit. The study found a simple linear regression model as follows: "Balance=-84,995+0.543×income (R2=0.544)". In order to avoid deficit, laboratories are suggested to increase test volumes, enhance laboratory test specialization, and become marginal scale. A hospital could integrate with regional medical institutions through alliances or OEM methods to increase volumes to reach marginal scale and reduce laboratory costs, enhancing the level and quality of laboratory medicine.

  8. Cost and Systems Analysis of Innovative Fuel Resources Concepts

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Erich [Univ. of Texas, Austin, TX (United States). Nuclear and Radiation Engineering Program; Byers, M. [Univ. of Texas, Austin, TX (United States). Nuclear and Radiation Engineering Program

    2017-05-04

    Economically recovered uranium from seawater can have a transformative effect on the way policy makers view the long-term viability of uranium based fuel cycles. Seawater uranium, even when estimated to cost more than terrestrially mined uranium, is integral in establishing an economic backstop, thus reducing uncertainty in future nuclear power costs. While a passive recovery scheme relying on a field of polymer adsorbents prepared via radiation induced grafting has long been considered the leading technology for full scale deployment, non-trivial cost and logistical barriers persist. Consequently, university partners of the nation-wide consortium for seawater uranium recovery have developed variants of this technology, each aiming to address a substantial weakness. The focus of this NEUP project is the economic impacts of the proposed variant technologies. The team at University of Alabama has pursued an adsorbent synthesis method that replaces the synthetic fiber backbone with a natural waste product. Chitin fibers suitable for ligand grafting have been prepared from shrimp shell waste. These environmental benefits could be realized at a comparable cost to the reference fiber so long as the uptake can be increased or the chemical consumption cost decreased.

  9. Probabilistic cost-benefit seismic design criterion for a dedicated shutdown heat removal system

    International Nuclear Information System (INIS)

    Lee, Y.T.; Okrent, D.

    1985-01-01

    A probabilistic methodology is developed for assessing the risk reduction potential and cost-benefit tradeoff of a Dedicated Shutdown Heat Removal System (DSHRS) for a PWR as a function of its seismic design capability. The option of coping with a very small LOCA is included. The annual seismic risk of a plant and a similar hypothetical plant having a proposed DSHRS with various seismic strengths are computed. The difference in the annual seismic risks is the annual seismic risk reduction benefit for having the system. The present value of the future risk reduction benefit is then compared to the cost of building a DSHRS and the incremental seismic cost associated with building the system to withstand a stronger earthquake. A reactor like Zion was used for application of the method due to the availability of data. Studies were performed to investigate the sensitivity of the results to the assumed seismic hazard, probability of occurrence of seismic-induced accident initiating events, equipment seismic fragility, accident costs, and discount rate. The incremental seismic risk reduction benefit computed in these studies ranges from Dollar 207 million for a DSHRS with a median seismic capacity of 1.70g (i.e. 10 x SSE) in a new plant built at the site. The total cost of a DSHRS is crudely estimated to be Dollar 25 million or more, if it were built to withstand the current SSE of the plant (for which the system probably would have a median seismic capacicty of 0.85g or more due to various design and construction conservatisms). The cost associated with the seismic design aspect of such a system is estimated to be approximately Dollar 2.5 million and it may be doubled if the seismic design capability of the system is tripled. The cost/benefit results and their inherent large uncertainties are not definitive but indicate that probabilistic seismic design of a DSHRS should be examined in further detail. (orig.)

  10. SCATS: SRB Cost Accounting and Tracking System handbook

    Science.gov (United States)

    Zorv, R. B.; Stewart, R. D.; Coley, G.; Higginbotham, M.

    1978-01-01

    The Solid Rocket Booster Cost Accounting and Tracking System (SCATS) which is an automatic data processing system designed to keep a running account of the number, description, and estimated cost of Level 2, 3, and 4 changes is described. Although designed specifically for the Space Shuttle Solid Rocket Booster Program, the ADP system can be used for any other program that has a similar structure for recording, reporting, and summing numbers and costs of changes. The program stores the alpha-numeric designators for changes, government estimated costs, proposed costs, and negotiated value in a MIRADS (Marshall Information Retrieval and Display System) format which permits rapid access, manipulation, and reporting of current change status. Output reports listing all changes, totals of each level, and totals of all levels, can be derived for any calendar interval period.

  11. A COST ORIENTED SYSTEM FOR HOLE MAKING PROCESSES

    Directory of Open Access Journals (Sweden)

    Uğur PAMUKOĞLU

    2004-01-01

    Full Text Available A knowledge based system for manufacturing of various hole making processes has been developed. In the system, selection of machining methods, determination of sequences based on cutting tools for each process, determination of process time and cost analysis have been conducted. In the procedure, all available processes have been taken in to account regarding their costs and the most suitable in cost was chosen. The system generated helps facilitate determination of process time and the costs of features to be manufactured. It is especially useful for quick cost estimation. In addition to these, the system helps people who are naïve in manufacturing operations so that people could be used for the related manufacturing stages.

  12. Using systems gaming to explore decision-making under uncertainty in natural hazard crises

    Science.gov (United States)

    McCaughey, Jamie W.; Finnigan, David

    2017-04-01

    Faced with uncertain scientific forecasts of a potential hazard, it is perhaps natural to wait and see. As we wait, uncertainties do decrease, but so do our options to minimise impacts of the hazard. This tradeoff is fundamental to preparing for natural hazards, yet difficult to communicate. Interactive systems gaming is one promising way forward. We are developing in-person interactive games, drawing on role-playing and other table-top scenario exercises in natural hazards, as well as on game-based modeling of complex systems. Our games model an unfolding natural hazard crisis (such as volcanic unrest or an approaching typhoon) as a complex social-physical system. Participants take on the roles of diverse stakeholder groups (including government, scientists, media, farmers, city residents, and others) with differing expertise, responsibilities, and priorities. Interactions among these groups play out in a context of decreasing scientific uncertainty and decreasing options for actions to reduce societal risk. Key design challenges are (1) to engage players without trivialising the real-world context; (2) to provide the right level of guidance for players to navigate the system; and (3) to enable players to face realistic tradeoffs and see realistic consequences of their choices, without feeling frustrated that the game is set up for them to fail. We will first prototype the games with general public and secondary-school participants, then adjust this for specialist groups working in disaster management. We will illustrate participatory systems gaming techniques in our presentation 'A toolkit of systems gaming techniques' in the companion EGU session EOS6: 'Perform! A platform to discuss art & science projects with live presentation'.

  13. Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

    Directory of Open Access Journals (Sweden)

    Douglas Domingues Bueno

    2008-01-01

    Full Text Available This paper deals with the study of algorithms for robust active vibration control in flexible structures considering uncertainties in system parameters. It became an area of enormous interest, mainly due to the countless demands of optimal performance in mechanical systems as aircraft, aerospace, and automotive structures. An important and difficult problem for designing active vibration control is to get a representative dynamic model. Generally, this model can be obtained using finite element method (FEM or an identification method using experimental data. Actuators and sensors may affect the dynamics properties of the structure, for instance, electromechanical coupling of piezoelectric material must be considered in FEM formulation for flexible and lightly damping structure. The nonlinearities and uncertainties involved in these structures make it a difficult task, mainly for complex structures as spatial truss structures. On the other hand, by using an identification method, it is possible to obtain the dynamic model represented through a state space realization considering this coupling. This paper proposes an experimental methodology for vibration control in a 3D truss structure using PZT wafer stacks and a robust control algorithm solved by linear matrix inequalities.

  14. Waste management facilities cost information: System cost model product description. Revision 2

    International Nuclear Information System (INIS)

    Lundeen, A.S.; Hsu, K.M.; Shropshire, D.E.

    1996-02-01

    In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors developed the System Cost Model (SCM) application. The SCM estimates life-cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, transuranic, and mixed transuranic waste. The SCM uses parametric cost functions to estimate life-cycle costs for various treatment, storage, and disposal modules which reflect planned and existing facilities at DOE installations. In addition, SCM can model new facilities based on capacity needs over the program life cycle. The SCM also provides transportation costs for DOE wastes. Transportation costs are provided for truck and rail and include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction costs, operation management, and decommissioning these waste management facilities

  15. The System Cost Model: A tool for life cycle cost and risk analysis

    International Nuclear Information System (INIS)

    Hsu, K.; Lundeen, A.; Shropshire, D.; Sherick, M.

    1996-01-01

    In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors began development of the System Cost Model (SCM) application. The SCM estimates life cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, and transuranic waste. The SCM uses parametric cost functions to estimate life cycle costs for various treatment, storage, and disposal modules which reflect planned and existing waste management facilities at DOE installations. In addition, SCM can model new TSD facilities based on capacity needs over the program life cycle. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction, operations and maintenance, and decommissioning these waste management facilities. The SCM also provides transportation costs for DOE wastes. Transportation costs are provided for truck and rail and include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. A complement to the SCM is the System Cost Model-Risk (SCM-R) model, which provides relative Environmental, Safety, and Health (ES and H) risk information. A relative ES and H risk basis has been developed and applied by LITCO at the INEL. The risk basis is now being automated in the SCM-R to facilitate rapid risk analysis of system alternatives. The added risk functionality will allow combined cost and risk evaluation of EM alternatives

  16. Model-based verification method for solving the parameter uncertainty in the train control system

    International Nuclear Information System (INIS)

    Cheng, Ruijun; Zhou, Jin; Chen, Dewang; Song, Yongduan

    2016-01-01

    This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. - Highlights: • We solve the parameters uncertainty problem by using model-based method. • We acquire the parameter constraint sets by verifying linear hybrid automata models. • Online verification algorithms are designed to monitor the high-speed trains. • We analyze the correlation of key parameters and uncritical parameters. • The transient probabilities are obtained by using reliability analysis.

  17. Radiometer uncertainty equation research of 2D planar scanning PMMW imaging system

    Science.gov (United States)

    Hu, Taiyang; Xu, Jianzhong; Xiao, Zelong

    2009-07-01

    With advances in millimeter-wave technology, passive millimeter-wave (PMMW) imaging technology has received considerable concerns, and it has established itself in a wide range of military and civil practical applications, such as in the areas of remote sensing, blind landing, precision guidance and security inspection. Both the high transparency of clothing at millimeter wavelengths and the spatial resolution required to generate adequate images combine to make imaging at millimeter wavelengths a natural approach of screening people for concealed contraband detection. And at the same time, the passive operation mode does not present a safety hazard to the person who is under inspection. Based on the description to the design and engineering implementation of a W-band two-dimensional (2D) planar scanning imaging system, a series of scanning methods utilized in PMMW imaging are generally compared and analyzed, followed by a discussion on the operational principle of the mode of 2D planar scanning particularly. Furthermore, it is found that the traditional radiometer uncertainty equation, which is derived from a moving platform, does not hold under this 2D planar scanning mode due to the fact that there is no absolute connection between the scanning rates in horizontal direction and vertical direction. Consequently, an improved radiometer uncertainty equation is carried out in this paper, by means of taking the total time spent on scanning and imaging into consideration, with the purpose of solving the problem mentioned above. In addition, the related factors which affect the quality of radiometric images are further investigated under the improved radiometer uncertainty equation, and ultimately some original results are presented and analyzed to demonstrate the significance and validity of this new methodology.

  18. Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

    Directory of Open Access Journals (Sweden)

    Stephan Birle

    2016-01-01

    Full Text Available In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the

  19. Effects of Uncertainty and Spatial Variability on Seepage into Drifts in the Yucca Mountain Total system Performance Assessment Model

    International Nuclear Information System (INIS)

    Kalinich, D. A.; Wilson, M. L.

    2001-01-01

    Seepage into the repository drifts is an important factor in total-system performance. Uncertainty and spatial variability are considered in the seepage calculations. The base-case results show 13.6% of the waste packages (WPs) have seepage. For 5th percentile uncertainty, 4.5% of the WPs have seepage and the seepage flow decreased by a factor of 2. For 95th percentile uncertainty, 21.5% of the WPs have seepage and the seepage flow increased by a factor of 2. Ignoring spatial variability resulted in seepage on 100% of the WPs, with a factor of 3 increase in the seepage flow

  20. Cost-Effectiveness of Surgery, Stereotactic Body Radiation Therapy, and Systemic Therapy for Pulmonary Oligometastases

    Energy Technology Data Exchange (ETDEWEB)

    Lester-Coll, Nataniel H., E-mail: nataniel.lester-coll@yale.edu [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Rutter, Charles E.; Bledsoe, Trevor J. [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Goldberg, Sarah B. [Department of Medicine (Medical Oncology), Yale University School of Medicine, New Haven, Connecticut (United States); Decker, Roy H.; Yu, James B. [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States)

    2016-06-01

    Introduction: Pulmonary oligometastases have conventionally been managed with surgery and/or systemic therapy. However, given concerns about the high cost of systemic therapy and improvements in local treatment of metastatic cancer, the optimal cost-effective management of these patients is unclear. Therefore, we sought to assess the cost-effectiveness of initial management strategies for pulmonary oligometastases. Methods and Materials: A cost-effectiveness analysis using a Markov modeling approach was used to compare average cumulative costs, quality adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) among 3 initial disease management strategies: video-assisted thoracic surgery (VATS) wedge resection, stereotactic body radiation therapy (SBRT), and systemic therapy among 5 different cohorts of patient disease: (1) melanoma; (2) non-small cell lung cancer adenocarcinoma without an EGFR mutation (NSCLC AC); (3) NSCLC with an EGFR mutation (NSCLC EGFRm AC); (4) NSCLC squamous cell carcinoma (NSCLC SCC); and (5) colon cancer. One-way sensitivity analyses and probabilistic sensitivity analyses were performed to analyze uncertainty with regard to model parameters. Results: In the base case, SBRT was cost effective for melanoma, with costs/net QALYs of $467,787/0.85. In patients with NSCLC, the most cost-effective strategies were SBRT for AC ($156,725/0.80), paclitaxel/carboplatin for SCC ($123,799/0.48), and erlotinib for EGFRm AC ($147,091/1.90). Stereotactic body radiation therapy was marginally cost-effective for EGFRm AC compared to erlotinib with an incremental cost-effectiveness ratio of $126,303/QALY. For colon cancer, VATS wedge resection ($147,730/2.14) was the most cost-effective strategy. Variables with the greatest influence in the model were erlotinib-associated progression-free survival (EGFRm AC), toxicity (EGFRm AC), cost of SBRT (NSCLC SCC), and patient utilities (all histologies). Conclusions: Video-assisted thoracic

  1. Cost-Effectiveness of Surgery, Stereotactic Body Radiation Therapy, and Systemic Therapy for Pulmonary Oligometastases.

    Science.gov (United States)

    Lester-Coll, Nataniel H; Rutter, Charles E; Bledsoe, Trevor J; Goldberg, Sarah B; Decker, Roy H; Yu, James B

    2016-06-01

    Pulmonary oligometastases have conventionally been managed with surgery and/or systemic therapy. However, given concerns about the high cost of systemic therapy and improvements in local treatment of metastatic cancer, the optimal cost-effective management of these patients is unclear. Therefore, we sought to assess the cost-effectiveness of initial management strategies for pulmonary oligometastases. A cost-effectiveness analysis using a Markov modeling approach was used to compare average cumulative costs, quality adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) among 3 initial disease management strategies: video-assisted thoracic surgery (VATS) wedge resection, stereotactic body radiation therapy (SBRT), and systemic therapy among 5 different cohorts of patient disease: (1) melanoma; (2) non-small cell lung cancer adenocarcinoma without an EGFR mutation (NSCLC AC); (3) NSCLC with an EGFR mutation (NSCLC EGFRm AC); (4) NSCLC squamous cell carcinoma (NSCLC SCC); and (5) colon cancer. One-way sensitivity analyses and probabilistic sensitivity analyses were performed to analyze uncertainty with regard to model parameters. In the base case, SBRT was cost effective for melanoma, with costs/net QALYs of $467,787/0.85. In patients with NSCLC, the most cost-effective strategies were SBRT for AC ($156,725/0.80), paclitaxel/carboplatin for SCC ($123,799/0.48), and erlotinib for EGFRm AC ($147,091/1.90). Stereotactic body radiation therapy was marginally cost-effective for EGFRm AC compared to erlotinib with an incremental cost-effectiveness ratio of $126,303/QALY. For colon cancer, VATS wedge resection ($147,730/2.14) was the most cost-effective strategy. Variables with the greatest influence in the model were erlotinib-associated progression-free survival (EGFRm AC), toxicity (EGFRm AC), cost of SBRT (NSCLC SCC), and patient utilities (all histologies). Video-assisted thoracic surgery wedge resection or SBRT can be cost-effective in select

  2. Determination of the components of uncertainty for a dosimetry system in radiation protection

    International Nuclear Information System (INIS)

    Lopez, F.; Cabral, T.S.; Peixoto, J.G.

    2013-01-01

    This work is about the theoretical calculation of uncertainties associated to the dosimetry of photons of a 137 Cs source that will be used in a Dosimetry Laboratory. In this case recognition of the influence quantities that provide most uncertainty and the right choice of resolution of auxiliary equipment to obtain the smallest uncertainties according to the laboratory. (author)

  3. Parametric cost model for solar space power and DIPS systems

    International Nuclear Information System (INIS)

    Meisl, C.J.

    1993-01-01

    A detailed cost model has been developed to parametrically determine the program development and production cost of (1) photovoltaic, (2) solar dynamic and (3) dynamic isotope (DIPS) space power systems. The model is applicable in the net electrical power range of 3 to 300 kWe for solar power, and 0.5 to 10 kWe for DIPS. Application of the cost model allows spacecraft or space-based power system architecture and design trade studies or budgetary forecasting and cost benefit analyses. The cost model considers all major power subsystems (i.e., power generation, power conversion, energy storage, thermal management, and power management/distribution/control). It also considers system cost effects such as integration, testing, management, etc. The cost breakdown structure, model assumptions, ground rules, bases, Cost Estimation Relationship (CER) format and rationale are presented, and the application of the cost model to 100-kWe solar space power plants and to a 1.0-kWe DIPS are demonstrated

  4. The importance of fixed costs in animal health systems.

    Science.gov (United States)

    Tisdell, C A; Adamson, D

    2017-04-01

    In this paper, the authors detail the structure and optimal management of health systems as influenced by the presence and level of fixed costs. Unlike variable costs, fixed costs cannot be altered, and are thus independent of the level of veterinary activity in the short run. Their importance is illustrated by using both single-period and multi-period models. It is shown that multi-stage veterinary decision-making can often be envisaged as a sequence of fixed-cost problems. In general, it becomes clear that, the higher the fixed costs, the greater the net benefit of veterinary activity must be, if such activity is to be economic. The authors also assess the extent to which it pays to reduce fixed costs and to try to compensate for this by increasing variable costs. Fixed costs have major implications for the industrial structure of the animal health products industry and for the structure of the private veterinary services industry. In the former, they favour market concentration and specialisation in the supply of products. In the latter, they foster increased specialisation. While cooperation by individual farmers may help to reduce their individual fixed costs, the organisational difficulties and costs involved in achieving this cooperation can be formidable. In such cases, the only solution is government provision of veterinary services. Moreover, international cooperation may be called for. Fixed costs also influence the nature of the provision of veterinary education.

  5. A Cost Effective System Design Approach for Critical Space Systems

    Science.gov (United States)

    Abbott, Larry Wayne; Cox, Gary; Nguyen, Hai

    2000-01-01

    NASA-JSC required an avionics platform capable of serving a wide range of applications in a cost-effective manner. In part, making the avionics platform cost effective means adhering to open standards and supporting the integration of COTS products with custom products. Inherently, operation in space requires low power, mass, and volume while retaining high performance, reconfigurability, scalability, and upgradability. The Universal Mini-Controller project is based on a modified PC/104-Plus architecture while maintaining full compatibility with standard COTS PC/104 products. The architecture consists of a library of building block modules, which can be mixed and matched to meet a specific application. A set of NASA developed core building blocks, processor card, analog input/output card, and a Mil-Std-1553 card, have been constructed to meet critical functions and unique interfaces. The design for the processor card is based on the PowerPC architecture. This architecture provides an excellent balance between power consumption and performance, and has an upgrade path to the forthcoming radiation hardened PowerPC processor. The processor card, which makes extensive use of surface mount technology, has a 166 MHz PowerPC 603e processor, 32 Mbytes of error detected and corrected RAM, 8 Mbytes of Flash, and I Mbytes of EPROM, on a single PC/104-Plus card. Similar densities have been achieved with the quad channel Mil-Std-1553 card and the analog input/output cards. The power management built into the processor and its peripheral chip allows the power and performance of the system to be adjusted to meet the requirements of the application, allowing another dimension to the flexibility of the Universal Mini-Controller. Unique mechanical packaging allows the Universal Mini-Controller to accommodate standard COTS and custom oversized PC/104-Plus cards. This mechanical packaging also provides thermal management via conductive cooling of COTS boards, which are typically

  6. Optimization under Uncertainty

    KAUST Repository

    Lopez, Rafael H.

    2016-01-06

    The goal of this poster is to present the main approaches to optimization of engineering systems in the presence of uncertainties. We begin by giving an insight about robust optimization. Next, we detail how to deal with probabilistic constraints in optimization, the so called the reliability based design. Subsequently, we present the risk optimization approach, which includes the expected costs of failure in the objective function. After that the basic description of each approach is given, the projects developed by CORE are presented. Finally, the main current topic of research of CORE is described.

  7. Development of an integrated model for energy systems planning and carbon dioxide mitigation under uncertainty - Tradeoffs between two-level decision makers.

    Science.gov (United States)

    Jin, S W; Li, Y P; Xu, L P

    2018-07-01

    A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO 2 ) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO 2 emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty. Copyright © 2018 Elsevier Inc. All rights reserved.

  8. Evaluation of Uncertainties in the Design Process of Complex Mechanical Systems

    Directory of Open Access Journals (Sweden)

    Francesco Villecco

    2017-09-01

    Full Text Available In this paper, the problem of the evaluation of the uncertainties that originate in the complex design process of a new system is analyzed, paying particular attention to multibody mechanical systems. To this end, the Wiener-Shannon’s axioms are extended to non-probabilistic events and a theory of information for non-repetitive events is used as a measure of the reliability of data. The selection of the solutions consistent with the values of the design constraints is performed by analyzing the complexity of the relation matrix and using the idea of information in the metric space. Comparing the alternatives in terms of the amount of entropy resulting from the various distribution, this method is capable of finding the optimal solution that can be obtained with the available resources. In the paper, the algorithmic steps of the proposed method are discussed and an illustrative numerical example is provided.

  9. Analysis of costs-benefits tradeoffs of complex security systems

    Energy Technology Data Exchange (ETDEWEB)

    Hicks, M.J. [Sandia National Labs., Albuquerque, NM (United States). Security Systems Analysis and Development Dept.

    1996-12-31

    Essential to a systems approach to design of security systems is an analysis of the cost effectiveness of alternative designs. While the concept of analysis of costs and benefits is straightforward, implementation can be at the least tedious and, for complex designs and alternatives, can become nearly intractable without the help of structured analysis tools. PACAIT--Performance and Cost Analysis Integrated Tools--is a prototype tool. The performance side of the analysis collates and reduces data from ASSESS, and existing DOE PC-based security systems performance analysis tool. The costs side of the analysis uses ACE, an existing DOD PC-based costs analysis tool. Costs are reported over the full life-cycle of the system, that is, the costs to procure, operate, maintain and retire the system and all of its components. Results are collected in Microsoft{reg_sign} Excel workbooks and are readily available to analysts and decision makers in both tabular and graphical formats and at both the system and path-element levels.

  10. Analysis of costs-benefits tradeoffs of complex security systems

    International Nuclear Information System (INIS)

    Hicks, M.J.

    1996-01-01

    Essential to a systems approach to design of security systems is an analysis of the cost effectiveness of alternative designs. While the concept of analysis of costs and benefits is straightforward, implementation can be at the least tedious and, for complex designs and alternatives, can become nearly intractable without the help of structured analysis tools. PACAIT--Performance and Cost Analysis Integrated Tools--is a prototype tool. The performance side of the analysis collates and reduces data from ASSESS, and existing DOE PC-based security systems performance analysis tool. The costs side of the analysis uses ACE, an existing DOD PC-based costs analysis tool. Costs are reported over the full life-cycle of the system, that is, the costs to procure, operate, maintain and retire the system and all of its components. Results are collected in Microsoft reg-sign Excel workbooks and are readily available to analysts and decision makers in both tabular and graphical formats and at both the system and path-element levels

  11. Cost analysis of hot-air solar-heating systems

    Science.gov (United States)

    Hawkins, B. J.; Stewart, R. D.

    1979-01-01

    Report describes results of study of two operational test sites (Huntsville, Alabama and Carlsbad, New Mexico) furnishing stimates of actual costs and potential cost savings of new and retrofit hot-air solar heating and hot-water system for single family dwellings.

  12. Mirror Fusion Test Facility: Superconducting magnet system cost analysis

    Energy Technology Data Exchange (ETDEWEB)

    1977-07-01

    At the request of Victor Karpenko, Project manager for LLL`s Mirror Fusion Test Facility, EG&G has prepared this independent cost analysis for the proposed MFTF Superconducting Magnet System. The analysis has attempted to show sufficient detail to provide adequate definition for a basis of estimating costs.

  13. Power distribution system diagnosis with uncertainty information based on rough sets and clouds model

    Science.gov (United States)

    Sun, Qiuye; Zhang, Huaguang

    2006-11-01

    During the distribution system fault period, usually the explosive growth signals including fuzziness and randomness are too redundant to make right decision for the dispatcher. The volume of data with a few uncertainties overwhelms classic information systems in the distribution control center and exacerbates the existing knowledge acquisition process of expert systems. So intelligent methods must be developed to aid users in maintaining and using this abundance of information effectively. An important issue in distribution fault diagnosis system (DFDS) is to allow the discovered knowledge to be as close as possible to natural languages to satisfy user needs with tractability, and to offer DFDS robustness. At this junction, the paper describes a systematic approach for detecting superfluous data. The approach therefore could offer user both the opportunity to learn about the data and to validate the extracted knowledge. It is considered as a "white box" rather than a "black box" like in the case of neural network. The cloud theory is introduced and the mathematical description of cloud has effectively integrated the fuzziness and randomness of linguistic terms in a unified way. Based on it, a method of knowledge representation in DFDS is developed which bridges the gap between quantitative knowledge and qualitative knowledge. In relation to classical rough set, the cloud-rough method can deal with the uncertainty of the attribute and make a soft discretization for continuous ones (such as the current and the voltage). A novel approach, including discretization, attribute reduction, rule reliability computation and equipment reliability computation, is presented. The data redundancy is greatly reduced based on an integrated use of cloud theory and rough set theory. Illustrated with a power distribution DFDS shows the effectiveness and practicality of the proposed approach.

  14. Towards uncertainty estimates in global operational forecasts of trace gases in the Copernicus Atmosphere Monitoring System

    Science.gov (United States)

    Huijnen, V.; Bouarar, I.; Chabrillat, S. H.; Christophe, Y.; Thierno, D.; Karydis, V.; Marecal, V.; Pozzer, A.; Flemming, J.

    2017-12-01

    Operational atmospheric composition analyses and forecasts such as developed in the Copernicus Atmosphere Monitoring Service (CAMS) rely on modules describing emissions, chemical conversion, transport and removal processing, as well as data assimilation methods. The CAMS forecasts can be used to drive regional air quality models across the world. Critical analyses of uncertainties in any of these processes are continuously needed to advance the quality of such systems on a global scale, ranging from the surface up to the stratosphere. With regard to the atmospheric chemistry to describe the fate of trace gases, the operational system currently relies on a modified version of the CB05 chemistry scheme for the troposphere combined with the Cariolle scheme to describe stratospheric ozone, as integrated in ECMWF's Integrated Forecasting System (IFS). It is further constrained by assimilation of satellite observations of CO, O3 and NO2. As part of CAMS we have recently developed three fully independent schemes to describe the chemical conversion throughout the atmosphere. These parameterizations originate from parent model codes in MOZART, MOCAGE and a combination of TM5/BASCOE. In this contribution we evaluate the correspondence and elemental differences in the performance of the three schemes in an otherwise identical model configuration (excluding data-assimilation) against a large range of in-situ and satellite-based observations of ozone, CO, VOC's and chlorine-containing trace gases for both troposphere and stratosphere. This analysis aims to provide a measure of model uncertainty in the operational system for tracers that are not, or poorly, constrained by data assimilation. It aims also to provide guidance on the directions for further model improvement with regard to the chemical conversion module.

  15. State Tracking and Fault Diagnosis for Dynamic Systems Using Labeled Uncertainty Graph.

    Science.gov (United States)

    Zhou, Gan; Feng, Wenquan; Zhao, Qi; Zhao, Hongbo

    2015-11-05

    Cyber-physical systems such as autonomous spacecraft, power plants and automotive systems become more vulnerable to unanticipated failures as their complexity increases. Accurate tracking of system dynamics and fault diagnosis are essential. This paper presents an efficient state estimation method for dynamic systems modeled as concurrent probabilistic automata. First, the Labeled Uncertainty Graph (LUG) method in the planning domain is introduced to describe the state tracking and fault diagnosis processes. Because the system model is probabilistic, the Monte Carlo technique is employed to sample the probability distribution of belief states. In addition, to address the sample impoverishment problem, an innovative look-ahead technique is proposed to recursively generate most likely belief states without exhaustively checking all possible successor modes. The overall algorithms incorporate two major steps: a roll-forward process that estimates system state and identifies faults, and a roll-backward process that analyzes possible system trajectories once the faults have been detected. We demonstrate the effectiveness of this approach by applying it to a real world domain: the power supply control unit of a spacecraft.

  16. Managing uncertainty: a review of food system scenario analysis and modelling.

    Science.gov (United States)

    Reilly, Michael; Willenbockel, Dirk

    2010-09-27

    Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address.

  17. The MIT Integrated Global System Model: A facility for Assessing and Communicating Climate Change Uncertainty (Invited)

    Science.gov (United States)

    Prinn, R. G.

    2013-12-01

    The world is facing major challenges that create tensions between human development and environmental sustenance. In facing these challenges, computer models are invaluable tools for addressing the need for probabilistic approaches to forecasting. To illustrate this, I use the MIT Integrated Global System Model framework (IGSM; http://globalchange.mit.edu ). The IGSM consists of a set of coupled sub-models of global economic and technological development and resultant emissions, and physical, dynamical and chemical processes in the atmosphere, land, ocean and ecosystems (natural and managed). Some of the sub-models have both complex and simplified versions available, with the choice of which version to use being guided by the questions being addressed. Some sub-models (e.g.urban air pollution) are reduced forms of complex ones created by probabilistic collocation with polynomial chaos bases. Given the significant uncertainties in the model components, it is highly desirable that forecasts be probabilistic. We achieve this by running 400-member ensembles (Latin hypercube sampling) with different choices for key uncertain variables and processes within the human and natural system model components (pdfs of inputs estimated by model-observation comparisons, literature surveys, or expert elicitation). The IGSM has recently been used for probabilistic forecasts of climate, each using 400-member ensembles: one ensemble assumes no explicit climate mitigation policy and others assume increasingly stringent policies involving stabilization of greenhouse gases at various levels. These forecasts indicate clearly that the greatest effect of these policies is to lower the probability of extreme changes. The value of such probability analyses for policy decision-making lies in their ability to compare relative (not just absolute) risks of various policies, which are less affected by the earth system model uncertainties. Given the uncertainties in forecasts, it is also clear that

  18. Evaluating Uncertainty in GHG Emission Scenarios: Mapping IAM Outlooks With an Energy System Phase Space

    Science.gov (United States)

    Ritchie, W. J.; Dowlatabadi, H.

    2017-12-01

    Climate change modeling relies on projections of future greenhouse gas emissions and other phenomena leading to changes in planetary radiative forcing (RF). Pathways for long-run fossil energy use that map to total forcing outcomes are commonly depicted with integrated assessment models (IAMs). IAMs structure outlooks for 21st-century emissions with various theories for developments in demographics, economics, land-use, energy markets and energy service demands. These concepts are applied to understand global changes in two key factors relevant for scenarios of carbon emissions: total energy use (E) this century and the carbon intensity of that energy (F/E). A simple analytical and graphical approach can also illustrate the full range of outcomes for these variables to determine if IAMs provide sufficient coverage of the uncertainty space for future energy use. In this talk, we present a method for understanding uncertainties relevant to RF scenario components in a phase space. The phase space of a dynamic system represents significant factors as axes to capture the full range of physically possible states. A two-dimensional phase space of E and F/E presents the possible system states that can lead to various levels of total 21st-century carbon emissions. Once defined in this way, a phase space of these energy system coordinates allows for rapid characterization of large IAM scenario sets with machine learning techniques. This phase space method is applied to the levels of RF described by the Representative Concentration Pathways (RCPs). The resulting RCP phase space identifies characteristics of the baseline energy system outlooks provided by IAMs for IPCC Working Group III. We conduct a k-means cluster analysis to distinguish the major features of IAM scenarios for each RCP range. Cluster analysis finds the IAM scenarios in AR5 illustrate RCPs with consistent combinations of energy resources. This suggests IAM scenarios understate uncertainty ranges for future

  19. Interactive Photochemistry in Earth System Models to Assess Uncertainty in Ozone and Greenhouse Gases. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Prather, Michael J. [Univ. of California, Irvine, CA (United States); Hsu, Juno [Univ. of California, Irvine, CA (United States); Nicolau, Alex [Univ. of California, Irvine, CA (United States); Veidenbaum, Alex [Univ. of California, Irvine, CA (United States); Smith, Philip Cameron [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bergmann, Dan [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-11-07

    Atmospheric chemistry controls the abundances and hence climate forcing of important greenhouse gases including N2O, CH4, HFCs, CFCs, and O3. Attributing climate change to human activities requires, at a minimum, accurate models of the chemistry and circulation of the atmosphere that relate emissions to abundances. This DOE-funded research provided realistic, yet computationally optimized and affordable, photochemical modules to the Community Earth System Model (CESM) that augment the CESM capability to explore the uncertainty in future stratospheric-tropospheric ozone, stratospheric circulation, and thus the lifetimes of chemically controlled greenhouse gases from climate simulations. To this end, we have successfully implemented Fast-J (radiation algorithm determining key chemical photolysis rates) and Linoz v3.0 (linearized photochemistry for interactive O3, N2O, NOy and CH4) packages in LLNL-CESM and for the first time demonstrated how change in O2 photolysis rate within its uncertainty range can significantly impact on the stratospheric climate and ozone abundances. From the UCI side, this proposal also helped LLNL develop a CAM-Superfast Chemistry model that was implemented for the IPCC AR5 and contributed chemical-climate simulations to CMIP5.

  20. Space Launch System Booster Separation Aerodynamic Database Development and Uncertainty Quantification

    Science.gov (United States)

    Chan, David T.; Pinier, Jeremy T.; Wilcox, Floyd J., Jr.; Dalle, Derek J.; Rogers, Stuart E.; Gomez, Reynaldo J.

    2016-01-01

    The development of the aerodynamic database for the Space Launch System (SLS) booster separation environment has presented many challenges because of the complex physics of the ow around three independent bodies due to proximity e ects and jet inter- actions from the booster separation motors and the core stage engines. This aerodynamic environment is dicult to simulate in a wind tunnel experiment and also dicult to simu- late with computational uid dynamics. The database is further complicated by the high dimensionality of the independent variable space, which includes the orientation of the core stage, the relative positions and orientations of the solid rocket boosters, and the thrust lev- els of the various engines. Moreover, the clearance between the core stage and the boosters during the separation event is sensitive to the aerodynamic uncertainties of the database. This paper will present the development process for Version 3 of the SLS booster separa- tion aerodynamic database and the statistics-based uncertainty quanti cation process for the database.

  1. Building uncertainty into cost-effectiveness rankings: portfolio risk-return tradeoffs and implications for decision rules.

    Science.gov (United States)

    O'Brien, B J; Sculpher, M J

    2000-05-01

    Current principles of cost-effectiveness analysis emphasize the rank ordering of programs by expected economic return (eg, quality-adjusted life-years gained per dollar expended). This criterion ignores the variance associated with the cost-effectiveness of a program, yet variance is a common measure of risk when financial investment options are appraised. Variation in health care program return is likely to be a criterion of program selection for health care managers with fixed budgets and outcome performance targets. Characterizing health care resource allocation as a risky investment problem, we show how concepts of portfolio analysis from financial economics can be adopted as a conceptual framework for presenting cost-effectiveness data from multiple programs as mean-variance data. Two specific propositions emerge: (1) the current convention of ranking programs by expected return is a special case of the portfolio selection problem in which the decision maker is assumed to be indifferent to risk, and (2) for risk-averse decision makers, the degree of joint risk or covariation in cost-effectiveness between programs will create incentives to diversify an investment portfolio. The conventional normative assumption of risk neutrality for social-level public investment decisions does not apply to a large number of health care resource allocation decisions in which health care managers seek to maximize returns subject to budget constraints and performance targets. Portfolio theory offers a useful framework for studying mean-variance tradeoffs in cost-effectiveness and offers some positive predictions (and explanations) of actual decision making in the health care sector.

  2. Construction of VLCC marine oil storage cost index system

    Science.gov (United States)

    Li, Yuan; Li, Yule; Lu, Jinshu; Wu, Wenfeng; Zhu, Faxin; Chen, Tian; Qin, Beichen

    2018-04-01

    VLCC as the research object, the basic knowledge of VLCC is summarized. According to the phenomenon that VLCC is applied to offshore oil storage gradually, this paper applies the theoretical analysis method to analyze the excess capacity from VLCC, the drop of oil price, the aging VLCC is more suitable for offshore storage The paper analyzes the reason of VLCC offshore oil storage from three aspects, analyzes the cost of VLCC offshore storage from the aspects of manpower cost and shipping cost, and constructs the cost index system of VLCC offshore oil storage.

  3. A critical evaluation of deterministic methods in size optimisation of reliable and cost effective standalone hybrid renewable energy systems

    International Nuclear Information System (INIS)

    Maheri, Alireza

    2014-01-01

    Reliability of a hybrid renewable energy system (HRES) strongly depends on various uncertainties affecting the amount of power produced by the system. In the design of systems subject to uncertainties, both deterministic and nondeterministic design approaches can be adopted. In a deterministic design approach, the designer considers the presence of uncertainties and incorporates them indirectly into the design by applying safety factors. It is assumed that, by employing suitable safety factors and considering worst-case-scenarios, reliable systems can be designed. In fact, the multi-objective optimisation problem with two objectives of reliability and cost is reduced to a single-objective optimisation problem with the objective of cost only. In this paper the competence of deterministic design methods in size optimisation of reliable standalone wind–PV–battery, wind–PV–diesel and wind–PV–battery–diesel configurations is examined. For each configuration, first, using different values of safety factors, the optimal size of the system components which minimises the system cost is found deterministically. Then, for each case, using a Monte Carlo simulation, the effect of safety factors on the reliability and the cost are investigated. In performing reliability analysis, several reliability measures, namely, unmet load, blackout durations (total, maximum and average) and mean time between failures are considered. It is shown that the traditional methods of considering the effect of uncertainties in deterministic designs such as design for an autonomy period and employing safety factors have either little or unpredictable impact on the actual reliability of the designed wind–PV–battery configuration. In the case of wind–PV–diesel and wind–PV–battery–diesel configurations it is shown that, while using a high-enough margin of safety in sizing diesel generator leads to reliable systems, the optimum value for this margin of safety leading to a

  4. Novel surface measurement system reading cost savings

    Energy Technology Data Exchange (ETDEWEB)

    Sword, M.

    1996-05-01

    A new state-of-the-art data acquisition system for the oil and natural gas industries is being marketed by OPSCO`92 Industries Ltd. The unit is portable, it measures surface data which is calibrated to bottom-hole conditions and designed to measure temperature and pressure information without the necessity of sending testing equipment downhole. The Surface Data System (SDS) uses silicon-crystal technology, is mounted in a suitcase size carrying case, and runs off a 12-volt battery enclosure which can be backed up by a small solar panel. The first generation system can handle 16 different channels of information input on a laptop computer. Pressure, pressure differential, temperature, frequency and pulse signals for flow meter measurements are handled by standard sensors. Areas of application include build-up and fall-off tests, pipeline evaluation, pre-frac tests, underbalanced drilling and gas well evaluation. 1 fig., 1 photo.

  5. Some uncertainty results obtained by the statistical version of the KARATE code system related to core design and safety analysis

    Energy Technology Data Exchange (ETDEWEB)

    Panka, Istvan; Hegyi, Gyoergy; Maraczy, Csaba; Temesvari, Emese [Hungarian Academy of Sciences, Budapest (Hungary). Reactor Analysis Dept.

    2017-11-15

    The best-estimate KARATE code system has been widely used for core design calculations and simulations of slow transients of VVER reactors. Recently there has been an increasing need for assessing the uncertainties of such calculations by propagating the basic input uncertainties of the models through the full calculation chain. In order to determine the uncertainties of quantities of interest during the burnup, the statistical version of the KARATE code system has been elaborated. In the first part of the paper, the main features of the new code system are discussed. The applied statistical method is based on Monte-Carlo sampling of the considered input data taking into account mainly the covariance matrices of the cross sections and/or the technological uncertainties. In the second part of the paper, only the uncertainties of cross sections are considered and an equilibrium cycle related to a VVER-440 type reactor is investigated. The burnup dependence of the uncertainties of some safety related parameters (e.g. critical boron concentration, rod worth, feedback coefficients, assembly-wise radial power and burnup distribution) are discussed and compared to the recently used limits.

  6. The health system cost of postabortion care in Ethiopia.

    Science.gov (United States)

    Vlassoff, Michael; Fetters, Tamara; Kumbi, Solomon; Singh, Susheela

    2012-09-01

    To address the knowledge gap that exists in costing unsafe abortion in Ethiopia, estimates were derived of the cost to the health system of providing postabortion care (PAC), based on research conducted in 2008. Fourteen public and private health facilities were selected, representing 3 levels of health care. Cost information on drugs, supplies, material, personnel time, and out-of-pocket expenses was collected using an ingredients approach. Sensitivity analysis was used to determine the most likely range of costs. The average direct cost per client, across 5 types of abortion complications, was US $36.21. The annual direct cost nationally ranged from US $6.5 to US $8.9 million. Including indirect costs and satisfying all demand increased the annual national cost to US $47 million. PAC consumes a large portion of the total expenditure in reproductive health in Ethiopia. Investing more resources in family planning programs to prevent unwanted pregnancies would be cost-beneficial to the health system. Copyright © 2012 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

  7. Low Cost Vision Based Personal Mobile Mapping System

    Science.gov (United States)

    Amami, M. M.; Smith, M. J.; Kokkas, N.

    2014-03-01

    Mobile mapping systems (MMS) can be used for several purposes, such as transportation, highway infrastructure mapping and GIS data collecting. However, the acceptance of these systems is not wide spread and their use is still limited due the high cost and dependency on the Global Navigation Satellite System (GNSS). A low cost vision based personal MMS has been produced with an aim to overcome these limitations. The system has been designed to depend mainly on cameras and use of low cost GNSS and inertial sensors to provide a bundle adjustment solution with initial values. The system has the potential to be used indoor and outdoor. The system has been tested indoors and outdoors with different GPS coverage, surrounded features, and narrow and curvy paths. Tests show that the system is able to work in such environments providing 3D coordinates of better than 10 cm accuracy.

  8. Low Cost Vision Based Personal Mobile Mapping System

    Directory of Open Access Journals (Sweden)

    M. M. Amami

    2014-03-01

    Full Text Available Mobile mapping systems (MMS can be used for several purposes, such as transportation, highway infrastructure mapping and GIS data collecting. However, the acceptance of these systems is not wide spread and their use is still limited due the high cost and dependency on the Global Navigation Satellite System (GNSS. A low cost vision based personal MMS has been produced with an aim to overcome these limitations. The system has been designed to depend mainly on cameras and use of low cost GNSS and inertial sensors to provide a bundle adjustment solution with initial values. The system has the potential to be used indoor and outdoor. The system has been tested indoors and outdoors with different GPS coverage, surrounded features, and narrow and curvy paths. Tests show that the system is able to work in such environments providing 3D coordinates of better than 10 cm accuracy.

  9. Healthcare Utilization and Costs of Systemic Lupus Erythematosus in Medicaid

    Directory of Open Access Journals (Sweden)

    Hong J. Kan

    2013-01-01

    Full Text Available Objective. Healthcare utilization and costs associated with systemic lupus erythematosus (SLE in a US Medicaid population were examined. Methods. Patients ≥ 18 years old with SLE diagnosis (ICD-9-CM 710.0x were extracted from a large Medicaid database 2002–2009. Index date was date of the first SLE diagnosis. Patients with and without SLE were matched. All patients had a variable length of followup with a minimum of 12 months. Annualized healthcare utilization and costs associated with SLE and costs of SLE flares were assessed during the followup period. Multivariate regressions were conducted to estimate incremental healthcare utilization and costs associated with SLE. Results. A total of 14,777 SLE patients met the study criteria, and 14,262 were matched to non-SLE patients. SLE patients had significantly higher healthcare utilization per year than their matched controls. The estimated incremental annual cost associated with SLE was $10,984, with the highest increase in inpatient costs (P<0.001. Cost per flare was $11,716 for severe flares, $562 for moderate flares, and $129 for mild flares. Annual total costs for patients with severe flares were $49,754. Conclusions. SLE patients had significantly higher healthcare resource utilization and costs than non-SLE patients. Patients with severe flares had the highest costs.

  10. Spoken language interaction with model uncertainty: an adaptive human-robot interaction system

    Science.gov (United States)

    Doshi, Finale; Roy, Nicholas

    2008-12-01

    Spoken language is one of the most intuitive forms of interaction between humans and agents. Unfortunately, agents that interact with people using natural language often experience communication errors and do not correctly understand the user's intentions. Recent systems have successfully used probabilistic models of speech, language and user behaviour to generate robust dialogue performance in the presence of noisy speech recognition and ambiguous language choices, but decisions made using these probabilistic models are still prone to errors owing to the complexity of acquiring and maintaining a complete model of human language and behaviour. In this paper, a decision-theoretic model for human-robot interaction using natural language is described. The algorithm is based on the Partially Observable Markov Decision Process (POMDP), which allows agents to choose actions that are robust not only to uncertainty from noisy or ambiguous speech recognition but also unknown user models. Like most dialogue systems, a POMDP is defined by a large number of parameters that may be difficult to specify a priori from domain knowledge, and learning these parameters from the user may require an unacceptably long training period. An extension to the POMDP model is described that allows the agent to acquire a linguistic model of the user online, including new vocabulary and word choice preferences. The approach not only avoids a training period of constant questioning as the agent learns, but also allows the agent actively to query for additional information when its uncertainty suggests a high risk of mistakes. The approach is demonstrated both in simulation and on a natural language interaction system for a robotic wheelchair application.

  11. Low-cost panoramic infrared surveillance system

    Science.gov (United States)

    Kecskes, Ian; Engel, Ezra; Wolfe, Christopher M.; Thomson, George

    2017-05-01

    A nighttime surveillance concept consisting of a single surface omnidirectional mirror assembly and an uncooled Vanadium Oxide (VOx) longwave infrared (LWIR) camera has been developed. This configuration provides a continuous field of view spanning 360° in azimuth and more than 110° in elevation. Both the camera and the mirror are readily available, off-the-shelf, inexpensive products. The mirror assembly is marketed for use in the visible spectrum and requires only minor modifications to function in the LWIR spectrum. The compactness and portability of this optical package offers significant advantages over many existing infrared surveillance systems. The developed system was evaluated on its ability to detect moving, human-sized heat sources at ranges between 10 m and 70 m. Raw camera images captured by the system are converted from rectangular coordinates in the camera focal plane to polar coordinates and then unwrapped into the users azimuth and elevation system. Digital background subtraction and color mapping are applied to the images to increase the users ability to extract moving items from background clutter. A second optical system consisting of a commercially available 50 mm f/1.2 ATHERM lens and a second LWIR camera is used to examine the details of objects of interest identified using the panoramic imager. A description of the components of the proof of concept is given, followed by a presentation of raw images taken by the panoramic LWIR imager. A description of the method by which these images are analyzed is given, along with a presentation of these results side-by-side with the output of the 50 mm LWIR imager and a panoramic visible light imager. Finally, a discussion of the concept and its future development are given.

  12. The 2008 IDA Cost Research Workshop: Contractor Data Reporting Systems

    National Research Council Canada - National Science Library

    Balut, Stephen J; Cloos, John J; Roark, Lance M

    2008-01-01

    Several Department of Defense (DoD) offices are responsible for estimating and monitoring the costs of defense systems and forces in support of planning, programming, budgeting, and acquisition decisions...

  13. Costs and benefits of MDOT intelligent transportation system deployments.

    Science.gov (United States)

    2015-07-01

    This report analyses costs and benefits of Intelligent Transportation Systems (ITS) deployed by : the Michigan Department of Transportation (MDOT). MDOT ITS focuses on traffic incident : management and also provide Freeway Courtesy Patrol services. A...

  14. Airport Visibility Measuring Systems Elements of Deployment Cost Analysis

    Science.gov (United States)

    1976-09-01

    This report analyzes the deployment cost for different visibility measuring systems necessary to satisfy CAT I, II, and II operations. The analysis is based on airport operational requirements and data for commercially available visibility measuring ...

  15. Impact of Platon ETC system on intercity trucking cost

    Directory of Open Access Journals (Sweden)

    Pogotovkina Natalya

    2017-01-01

    Full Text Available In 2015 Platon ETC System, a system of charging trucks with gross vehicle weight exceeding 12 tons, was implemented in Russia. The payment is collected as a compensation fo0 the damage caused to the federal public roads. Platon system is an additional source of financing for the road sector. However, its implementation made the carriers face the increasing costs. This paper presents the first results of the system functioning and the problems, associated with it. We consider the foreign systems of truck charging. The results of calculations, which show the effect of the toll collection on the prime cost of road freight transportation, are also presented.

  16. Uncertainty management in telecommunications uninterruptible power supply systems and on their network by utilizing human reasoning methodology

    Energy Technology Data Exchange (ETDEWEB)

    Suntio, T.

    1992-01-01

    The uninterruptible power supply (UPS) systems are used to supply quality power to critical systems such as computers, telephone exchanges, etc. The lack of energy in public power lines is of concern and has to be rectified. Quality power is, therefore, a flow of energy containing controlled amount of uncertainty about its continuity. The reserve energy stored in the UPS system carries out the basic reduction of the uncertainty caused by public power lines. The physical structure of the UPS system and the people maintaining the power system will increase the uncertainty. The main objectives of uncertainty management are to ensure that there is enough reserve energy and to minimize the additional uncertainties. This task can be carried out by optimally utilizing both the human beings and machines. The philosophy of the suggested management scheme is based on distributed decision making and centralized verification of these decisions. The on-site supervision facilities take care of distributed decision making by utilizing human reasoning. The alarm messages contain the most probable explanation of the available evidence. The network management facilities of her information in such a form that supports the human way of reasoning and thereby, effectively enables the centralized verification of the situation in the power system. The credibility of alarm issuing is of prime concern and it can be maintained by utilizing human reasoning. Uncertainty management is studied especially in Telecommunications domain, but most of the results obtained are applicable to computer domain also. The sources of the uncertainties are systematically identified and studied by using reliability techniques and finally a network wide solution is suggested.

  17. A Cost Benefit Analysis of an Accelerator Driven Transmutation System

    International Nuclear Information System (INIS)

    Westlen, D.; Gudowski, W.; Wallenius, J.; Tucek, K.

    2002-01-01

    This paper estimates the economical costs and benefits associated with a nuclear waste transmutation strategy. An 800 MWth, fast neutron spectrum, subcritical core design has been used in the study (the so called Sing-Sing Core). Three different fuel cycle scenarios have been compared. The main purpose of the paper has been to identify the cost drivers of a partitioning and transmutation strategy, and to estimate the cost of electricity generated in a nuclear park with operating accelerator driven systems. It has been found that directing all transuranic discharges from spent light water reactor (LWR) uranium oxide (UOX) fuel to accelerator driven systems leads to a cost increase for nuclear power of 50±15%, while introduction of a mixed oxide (MOX) burning step in the LWRs diminishes the cost penalty to 35±10%. (authors)

  18. DRG systems in Europe: variations in cost accounting systems among 12 countries.

    Science.gov (United States)

    Tan, Siok Swan; Geissler, Alexander; Serdén, Lisbeth; Heurgren, Mona; van Ineveld, B Martin; Redekop, W Ken; Hakkaart-van Roijen, Leona

    2014-12-01

    Diagnosis-related group (DRG)-based hospital payment systems have gradually become the principal means of reimbursing hospitals in many European countries. Owing to the absence or inaccuracy of costs related to DRGs, these countries have started to routinely collect cost accounting data. The aim of the present article was to compare the cost accounting systems of 12 European countries. A standardized questionnaire was developed to guide comprehensive cost accounting system descriptions for each of the 12 participating countries. The cost accounting systems of European countries vary widely by the share of hospital costs reimbursed through DRG payment, the presence of mandatory cost accounting and/or costing guidelines, the share of cost collecting hospitals, costing methods and data checks on reported cost data. Each of these aspects entails a trade-off between accuracy of the cost data and feasibility constraints. Although a 'best' cost accounting system does not exist, our cross-country comparison gives insight into international differences and may help regulatory authorities and hospital managers to identify and improve areas of weakness in their cost accounting systems. Moreover, it may help health policymakers to underpin the development of a cost accounting system. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

  19. Superconductors Enable Lower Cost MRI Systems

    Science.gov (United States)

    2013-01-01

    The future looks bright, light, and green, especially where aircraft are concerned. The division of NASA s Fundamental Aeronautics Program called the Subsonic Fixed Wing Project is aiming to reach new heights by 2025-2035, improving the efficiency and environmental impact of air travel by developing new capabilities for cleaner, quieter, and more fuel efficient aircraft. One of the many ways NASA plans to reach its aviation goals is by combining new aircraft configurations with an advanced turboelectric distributed propulsion (TeDP) system. Jeff Trudell, an engineer at Glenn Research Center, says, "The TeDP system consists of gas turbines generating electricity to power a large number of distributed motor-driven fans embedded into the airframe." The combined effect increases the effective bypass ratio and reduces drag to meet future goals. "While room temperature components may help reduce emissions and noise in a TeDP system, cryogenic superconducting electric motors and generators are essential to reduce fuel burn," says Trudell. Superconductors provide significantly higher current densities and smaller and lighter designs than room temperature equivalents. Superconductors are also able to conduct direct current without resistance (loss of energy) below a critical temperature and applied field. Unfortunately, alternating current (AC) losses represent the major part of the heat load and depend on the frequency of the current and applied field. A refrigeration system is necessary to remove the losses and its weight increases with decreasing temperature. In 2001, a material called magnesium diboride (MgB2) was discovered to be superconducting. The challenge, however, has been learning to manufacture MgB2 inexpensively and in long lengths to wind into large coils while meeting the application requirements.

  20. Flexible interval mixed-integer bi-infinite programming for environmental systems management under uncertainty.

    Science.gov (United States)

    He, L; Huang, G H; Lu, H W

    2009-04-01

    A number of inexact programming methods have been developed for municipal solid waste management under uncertainty. However, most of them do not allow the parameters in the objective and constraints of a programming problem to be functional intervals (i.e., the lower and upper bounds of the intervals are functions of impact factors). In this study, a flexible interval mixed-integer bi-infinite programming (FIMIBIP) method is developed in response to the above concern. A case study is also conducted; the solutions are then compared with those obtained from interval mixed-integer bi-infinite programming (IMIBIP) and fuzzy interval mixed-integer programming (FIMIP) methods. It is indicated that the solutions through FIMIBIP can provide decision support for cost-effectively diverting municipal solid waste, and for sizing, timing and siting the facilities' expansion during the entire planning horizon. These schemes are more flexible than those identified through IMIBIP since the tolerance intervals are introduced to measure the level of constraints satisfaction. The FIMIBIP schemes may also be robust since the solutions are "globally-optimal" under all scenarios caused by the fluctuation of gas/energy prices, while the conventional ones are merely "locally-optimal" under a certain scenario.

  1. Optimum capacity determination of stand-alone hybrid generation system considering cost and reliability

    International Nuclear Information System (INIS)

    Chen, Hung-Cheng

    2013-01-01

    Highlights: ► This paper presents a methodology for the installation capacity optimization. ► Hybrid generation system is optimized by application of adaptive genetic algorithm. ► A cost investigation is made under various conditions and component characteristics. ► The optimization scheme is validated to meet the annual power load demand. -- Abstract: The aim of this work is to present an optimization methodology for the installation capacity of a stand-alone hybrid generation system, taking into consideration the cost and reliability. Firstly, on the basis of derived steady state models of a wind generator (WG), a photovoltaic array (PV), a battery and an inverter, the hybrid generation system is modeled for the purpose of capacity optimization. Secondly, the power system is analyzed for determining both the system structure and the operation control strategy. Thirdly, according to hourly weather database of wind speed, temperature and solar irradiation, annual power generation capacity is estimated for the system match design in order that an annual power load demand can be met. The capacity determination of a hybrid generation system becomes complicated as a result of the uncertainty in the renewable energy together with load demand and the nonlinearity of system components. Aimed at the power system reliability and the cost minimization, the capacity of a hybrid generation system is optimized by application of an adaptive genetic algorithm (AGA) to individual power generation units. A total cost investigation is made under various conditions, such as wind generator power curves, battery discharge depth and the loss of load probability (LOLP). At the end of this work, the capacity of a hybrid generation system is optimized at two installation sites, namely the offshore Orchid Island and Wuchi in Taiwan. The optimization scheme is validated to optimize power capacities of a photovoltaic array, a battery and a wind turbine generator with a relative

  2. Development of LLW and VLLW disposal business cost estimation system

    International Nuclear Information System (INIS)

    Koibuchi, Hiroko; Ishiguro, Hideharu; Matsuda, Kenji

    2004-01-01

    In order to undertake the LLW and VLLW disposal business, various examinations are carried out in RANDEC. Since it is important in undertaking this business to secure funds, a disposal cost must be calculated by way of trial. However, at present, there are many unknown factors such as the amount of wastes, a disposal schedule, the location of a disposal site, and so on, and the cost cannot be determined. Meanwhile, the cost depends on complicated relations among these factors. Then, a 'LLW and VLLW disposal business cost estimation system' has been developed to calculate the disposal cost easily. This system can calculate an annual balance of payments by using a construction and operation cost of disposal facilities, considering economic parameters of tax, inflation rate, interest rate and so on. And the system can calculate internal reserves to assign to next-stage upkeep of the disposal facilities after the disposal operation. A model of disposal site was designed based on assumption of some preconditions and a study was carried out to make a trial calculation by using the system. Moreover, it will be required to reduce construction cost by rationalizing the facility and to make flat an annual business spending by examining the business schedule. (author)

  3. Sliding Mode Control of Fractional-Order Delayed Memristive Chaotic System with Uncertainty and Disturbance

    Science.gov (United States)

    Ding, Da-Wei; Liu, Fang-Fang; Chen, Hui; Wang, Nian; Liang, Dong

    2017-12-01

    In this paper, a simplest fractional-order delayed memristive chaotic system is proposed in order to control the chaos behaviors via sliding mode control strategy. Firstly, we design a sliding mode control strategy for the fractional-order system with time delay to make the states of the system asymptotically stable. Then, we obtain theoretical analysis results of the control method using Lyapunov stability theorem which guarantees the asymptotic stability of the non-commensurate order and commensurate order system with and without uncertainty and an external disturbance. Finally, numerical simulations are given to verify that the proposed sliding mode control method can eliminate chaos and stabilize the fractional-order delayed memristive system in a finite time. Supported by the National Nature Science Foundation of China under Grant No. 61201227, Funding of China Scholarship Council, the Natural Science Foundation of Anhui Province under Grant No. 1208085M F93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B

  4. Practical impulsive synchronization of chaotic systems with parametric uncertainty and mismatch

    International Nuclear Information System (INIS)

    Wen, C.Y.; Ji, Y.; Li, Z.G.

    2007-01-01

    Recently, there has been increasing interest in the synchronization of two chaotic systems and some significant results have been reported. In these results, a strong assumption that the two chaotic systems should be identical, i.e., without any mismatch, is imposed. Furthermore, system parameters are also assumed known exactly. Clearly, these are impractical. In this Letter, pure impulsive synchronization is considered. We quantitatively establish a relationship between a pre-specified bound of the synchronization error and the length of impulsive intervals in the presence of both parametric uncertainties and mismatch between the two systems. This is the first available result in the area, to the knowledge of the authors. With such a relationship as a guideline to choose impulsive intervals, a practical impulsive synchronization scheme is obtained. With the proposed scheme, the magnitude of the synchronization error is theoretically ensured to approach to and stay within the pre-specified bound which can be arbitrarily small. Simulation studies on the Lorenz system also verify the effectiveness of the proposed scheme

  5. Density meter algorithm and system for estimating sampling/mixing uncertainty

    International Nuclear Information System (INIS)

    Shine, E.P.

    1986-01-01

    The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statisical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses

  6. A PCE-based multiscale framework for the characterization of uncertainties in complex systems

    Science.gov (United States)

    Mehrez, Loujaine; Fish, Jacob; Aitharaju, Venkat; Rodgers, Will R.; Ghanem, Roger

    2018-02-01

    This paper presents a framework for the modeling and analysis of material systems that exhibit uncertainties in their constituents at all scales. The framework integrates multiscale formalism with a polynomial chaos construction enabling an explicit representation of quantities of interests, at any scale, in terms of any form of underlying uncertain parameters, a key feature to model multiscale dependencies. It is demonstrated how the framework can successfully tackle settings where a hierarchy of scales must be explicitly modeled. The application of this framework is illustrated in the construction of stochastic models of mesoscale and macroscale properties of non-crimp fabric composites. Joint statistical properties of upscaled components of the composite, including properties of tow, laminae and laminate, are computed.

  7. Human subjects concerns in ground based ECLSS testing - Managing uncertainty in closely recycled systems

    Science.gov (United States)

    Crump, William J.; Janik, Daniel S.; Thomas, L. Dale

    1990-01-01

    U.S. space missions have to this point used water either made on board or carried from earth and discarded after use. For Space Station Freedom, long duration life support will include air and water recycling using a series of physical-chemical subsystems. The Environmental Control and Life Support System (ECLSS) designed for this application must be tested extensively at all stages of hardware maturity. Human test subjects are required to conduct some of these tests, and the risks associated with the use of development hardware must be addressed. Federal guidelines for protection of human subjects require careful consideration of risks and potential benefits by an Institutional Review Board (IRB) before and during testing. This paper reviews the ethical principles guiding this consideration, details the problems and uncertainties inherent in current hardware testing, and presents an incremental approach to risk assessment for ECLSS testing.

  8. Uncertainties affecting fund collection, management and final utilisation

    International Nuclear Information System (INIS)

    Soederberg, Olof

    2006-01-01

    The paper presents, on a general level, major uncertainties in financing systems aiming at providing secure funding for future costs for decommissioning. The perspective chosen is that of a fund collector/manager. The paper also contains a description of how these uncertainties are dealt within the Swedish financing system and particularly from the perspective of the Board of the Swedish Nuclear Waste Fund. It is concluded that existing uncertainties are a good reason not to postpone decommissioning activities to a distant future. This aspect is important also when countries have in place financing systems that have been constructed in order to be robust against identified uncertainties. (author)

  9. Sensitivity analysis and uncertainties simulation of the migration of radionuclide in the system of geological disposal-CRP-GEORC model

    International Nuclear Information System (INIS)

    Su Rui; Wang Ju; Chen Weiming; Zong Zihua; Zhao Honggang

    2008-01-01

    CRP-GEORC concept model is an artificial system of geological disposal for High-Level radioactive waste. Sensitivity analysis and uncertainties simulation of the migration of radionuclide Se-79 and I-129 in the far field of this system by using GoldSim Code have been conducted. It can be seen from the simulation results that variables used to describe the geological features and characterization of groundwater flow are sensitive variables of whole geological disposal system. The uncertainties of parameters have remarkable influence on the simulation results. (authors)

  10. An Interactive Fuzzy Programming Approach for Designing a Multi-Echelon, Multi-Product, Multi-Period Supply Chain Network Under Uncertainty Considering Cost and Time

    Directory of Open Access Journals (Sweden)

    Mohammad Amirkhan

    2015-09-01

    Full Text Available The supply chain network design has attracted the attention of many researchers during recent years. This paper presents a new bi-objective mixed-integer linear programming (MILP model to integrate procurement, production and distribution planning under uncertainty. This model is set up for the network of a multi-echelon, multi-product, multi-channel, multi-period supply chain with regard to two conflicting objectives, which minimize the costs and minimize the sum of backorders and surpluses of products in all periods using “activity-based costing and the total cost of ownership” and “JIT” concepts, respectively. To solve the presented model, an interactive fuzzy approach is used. The associated results show the amount of purchasing of each supplier, the quantity of producing, the inventory of raw materials and products, backorder or surplus delivery of goods, the mode of transportation, the amount of goods transported between facilities and suppliers used in each period. In addition, a numerical example is presented to demonstrate the applicability of the presented model and exhibit the efficiency of the proposed interactive fuzzy approach. Finally, the results and conclusion are provided.

  11. Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

    Science.gov (United States)

    Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

    2006-01-01

    There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

  12. Entropic Measure of Epistemic Uncertainties in Multibody System Models by Axiomatic Design

    Directory of Open Access Journals (Sweden)

    Francesco Villecco

    2017-06-01

    Full Text Available In this paper, the use of the MaxInf Principle in real optimization problems is investigated for engineering applications, where the current design solution is actually an engineering approximation. In industrial manufacturing, multibody system simulations can be used to develop new machines and mechanisms by using virtual prototyping, where an axiomatic design can be employed to analyze the independence of elements and the complexity of connections forming a general mechanical system. In the classic theories of Fisher and Wiener-Shannon, the idea of information is a measure of only probabilistic and repetitive events. However, this idea is broader than the probability alone field. Thus, the Wiener-Shannon’s axioms can be extended to non-probabilistic events and it is possible to introduce a theory of information for non-repetitive events as a measure of the reliability of data for complex mechanical systems. To this end, one can devise engineering solutions consistent with the values of the design constraints analyzing the complexity of the relation matrix and using the idea of information in the metric space. The final solution gives the entropic measure of epistemic uncertainties which can be used in multibody system models, analyzed with an axiomatic design.

  13. Natural gas price uncertainty and the cost-effectiveness of hedging against low hydropower revenues caused by drought

    Science.gov (United States)

    Kern, Jordan D.; Characklis, Gregory W.; Foster, Benjamin T.

    2015-04-01

    Prolonged periods of low reservoir inflows (droughts) significantly reduce a hydropower producer's ability to generate both electricity and revenues. Given the capital intensive nature of the electric power industry, this can impact hydropower producers' ability to pay down outstanding debt, leading to credit rating downgrades, higher interests rates on new debt, and ultimately, greater infrastructure costs. One potential tool for reducing the financial exposure of hydropower producers to drought is hydrologic index insurance, in particular, contracts structured to payout when streamflows drop below a specified level. An ongoing challenge in developing this type of insurance, however, is minimizing contracts' "basis risk," that is, the degree to which contract payouts deviate in timing and/or amount from actual damages experienced by policyholders. In this paper, we show that consideration of year-to-year changes in the value of hydropower (i.e., the cost of replacing it with an alternative energy source during droughts) is critical to reducing contract basis risk. In particular, we find that volatility in the price of natural gas, a key driver of peak electricity prices, can significantly degrade the performance of index insurance unless contracts are designed to explicitly consider natural gas prices when determining payouts. Results show that a combined index whose value is derived from both seasonal streamflows and the spot price of natural gas yields contracts that exhibit both lower basis risk and greater effectiveness in terms of reducing financial exposure.

  14. Optimal Sizing of Battery Storage Systems for Industrial Applications when Uncertainties Exist

    OpenAIRE

    Guido Carpinelli; Anna Rita di Fazio; Shahab Khormali; Fabio Mottola

    2014-01-01

    Demand response (DR) can be very useful for an industrial facility, since it allows noticeable reductions in the electricity bill due to the significant value of energy demand. Although most industrial processes have stringent constraints in terms of hourly active power, DR only becomes attractive when performed with the contemporaneous use of battery energy storage systems (BESSs). When this option is used, an optimal sizing of BESSs is desirable, because the investment costs can be signific...

  15. The cost of systemic therapy for metastatic colorectal carcinoma in Slovenia: discrepancy analysis between cost and reimbursement.

    Science.gov (United States)

    Mesti, Tanja; Boshkoska, Biljana Mileva; Kos, Mitja; Tekavčič, Metka; Ocvirk, Janja

    2015-06-01

    The aim of the study was to estimate the direct medical costs of metastatic colorectal cancer (mCRC) treated at the Institute of Oncology Ljubljana and to question the healthcare payment system in Slovenia. Using an internal patient database, the costs of mCRC patients were estimated in 2009 by examining (1) mCRC direct medical related costs, and (2) the cost difference between payment received by Slovenian health insurance and actual mCRC costs. Costs were analysed in the treatment phase of the disease by assessing the direct medical costs of hospital treatment with systemic therapy together with hospital treatment of side effects, without assessing radiotherapy or surgical treatment. Follow-up costs, indirect medical costs, and nonmedical costs were not included. A total of 209 mCRC patients met all eligibility criteria. The direct medical costs of mCRC hospitalization with systemic therapy in Slovenia for 2009 were estimated as the cost of medications (cost of systemic therapy + cost of drugs for premedication) + labor cost (the cost of carrying out systemic treatment) + cost of lab tests + cost of imaging tests + KRAS testing cost + cost of hospital treatment due to side effects of mCRC treatment, and amounted to €3,914,697. The difference between the cost paid by health insurance and actual costs, estimated as direct medical costs of hospitalization of mCRC patients treated with systemic therapy at the Institute of Oncology Ljubljana in 2009, was €1,900,757.80. The costs paid to the Institute of Oncology Ljubljana by health insurance for treating mCRC with systemic therapy do not match the actual cost of treatment. In fact, the difference between the payment and the actual cost estimated as direct medical costs of hospitalization of mCRC patients treated with systemic therapy at the Institute of Oncology Ljubljana in 2009 was €1,900,757.80. The model Australian Refined Diagnosis Related Groups (AR-DRG) for cost assessment in oncology being currently used

  16. Attributes of system testing which promote cost-effectiveness

    International Nuclear Information System (INIS)

    Martin, L.C.

    1975-01-01

    A brief overview of conventional EMP testing activity examines attributes of overall systems tests which promote cost-effectiveness. The general framework represents an EMP-oriented systems test as a portion of a planned program to design, produce, and field system elements. As such, all so-called system tests should play appropriate cost-effective roles in this program, and the objective here is to disclose such roles. The intrinsic worth of such tests depends not only upon placing proper values on the outcomes, but also upon the possible eventual consequences of not doing tests. A relative worth measure is required. Attributes of EMP system testing over the range of potential activity which encompasses research and development, production, field handling, verification, evaluation, and others are reviewed and examined. Thus, the relative worth, in a cost-effective sense, is provided by relating such attributes to the overall program objectives so that values can be placed on the outcomes for tradeoff purposes

  17. The promise--and peril--of integrated cost systems.

    Science.gov (United States)

    Cooper, R; Kaplan, R S

    1998-01-01

    Recent advances in managerial accounting have helped executives get the information they need to make good strategic decisions. But today's enterprise resource planning systems promise even greater benefits--the chance to integrate activity-based costing, operational-control, and financial reporting systems. But managers need to approach integration very thoughtfully, or they could end up with a system that drives decision making in the wrong direction. Operational-control and ABC systems have fundamentally different purposes. Their requirements for accuracy, timeliness, and aggregation are so different that no single, fully integrated approach can be adequate for both purposes. If an integrated system used real-time cost data instead of standard rates in its ABC subsystem, for example, the result would be dangerously distorted messages about individual product profitability--and that's precisely the problem ABC systems were originally designed to address. Proper linkage and feedback between the two systems is possible, however. Through activity-based budgeting, the ABC system is linked directly to operations control: managers can determine the supply and practical capacity of resources in forthcoming periods. Linking operational control to ABC is also possible. The activity-based portion of an operational control system collects information that, while it mustn't be fed directly into the activity-based strategic cost system, can be extremely useful once it's been properly analyzed. Finally, ABC and operational control can be linked to financial reporting to generate cost of goods sold and inventory valuations--but again, with precautions.

  18. The Paleoclimate Uncertainty Cascade: Tracking Proxy Errors Via Proxy System Models.

    Science.gov (United States)

    Emile-Geay, J.; Dee, S. G.; Evans, M. N.; Adkins, J. F.

    2014-12-01

    Paleoclimatic observations are, by nature, imperfect recorders of climate variables. Empirical approaches to their calibration are challenged by the presence of multiple sources of uncertainty, which may confound the interpretation of signals and the identifiability of the noise. In this talk, I will demonstrate the utility of proxy system models (PSMs, Evans et al, 2013, 10.1016/j.quascirev.2013.05.024) to quantify the impact of all known sources of uncertainty. PSMs explicitly encode the mechanistic knowledge of the physical, chemical, biological and geological processes from which paleoclimatic observations arise. PSMs may be divided into sensor, archive and observation components, all of which may conspire to obscure climate signals in actual paleo-observations. As an example, we couple a PSM for the δ18O of speleothem calcite to an isotope-enabled climate model (Dee et al, submitted) to analyze the potential of this measurement as a proxy for precipitation amount. A simple soil/karst model (Partin et al, 2013, 10.1130/G34718.1) is used as sensor model, while a hiatus-permitting chronological model (Haslett & Parnell, 2008, 10.1111/j.1467-9876.2008.00623.x) is used as part of the observation model. This subdivision allows us to explicitly model the transformation from precipitation amount to speleothem calcite δ18O as a multi-stage process via a physical and chemical sensor model, and a stochastic archive model. By illustrating the PSM's behavior within the context of the climate simulations, we show how estimates of climate variability may be affected by each submodel's transformation of the signal. By specifying idealized climate signals(periodic vs. episodic, slow vs. fast) to the PSM, we investigate how frequency and amplitude patterns are modulated by sensor and archive submodels. To the extent that the PSM and the climate models are representative of real world processes, then the results may help us more accurately interpret existing paleodata

  19. Comparison of high-speed rail and maglev system costs

    Energy Technology Data Exchange (ETDEWEB)

    Rote, D.M.

    1998-07-01

    This paper compares the two modes of transportation, and notes important similarities and differences in the technologies and in how they can be implemented to their best advantage. Problems with making fair comparisons of the costs and benefits are discussed and cost breakdowns based on data reported in the literature are presented and discussed in detail. Cost data from proposed and actual construction projects around the world are summarized and discussed. Results from the National Maglev Initiative and the recently-published Commercial Feasibility Study are included in the discussion. Finally, estimates will be given of the expected cost differences between HSR and maglev systems implemented under simple and complex terrain conditions. The extent to which the added benefits of maglev technology offset the added costs is examined.

  20. The assessment of damages due to climate change in a situation of uncertainty: the contribution of adaptation cost modelling

    International Nuclear Information System (INIS)

    Dumas, P.

    2006-01-01

    The aim of this research is to introduce new elements for the assessment of damages due to climate changes within the frame of compact models aiding the decision. Two types of methodologies are used: sequential optimisation stochastic models and simulation stochastic models using optimal assessment methods. The author first defines the damages, characterizes their different categories, and reviews the existing assessments. Notably, he makes the distinction between damages due to climate change and damages due to its rate. Then, he presents the different models used in this study, the numerical solutions, and gives a rough estimate of the importance of the considered phenomena. By introducing a new category of capital in an optimal growth model, he tries to establish a framework allowing the representation of adaptation and of its costs. He introduces inertia in macro-economical evolutions, climatic variability, detection of climate change and damages due to climate hazards

  1. Semi-active control for vibration mitigation of structural systems incorporating uncertainties

    International Nuclear Information System (INIS)

    Miah, Mohammad S; Chatzi, Eleni N; Weber, Felix

    2015-01-01

    This study introduces a novel semi-active control scheme, where the linear-quadratic regulator (LQR) is combined with an unscented Kalman filter (UKF) observer, for the real-time mitigation of structural vibration. Due to a number of factors, such as environmental effects and ageing processes, the controlled system may be characterized by uncertainties. The UKF, which comprises a nonlinear observer, is employed herein for devising an adaptive semi-active control scheme capable of tackling such a challenge. This is achieved through the real-time realization of joint state and parameter estimation during the structural control process via the proposed LQR-UKF approach. The behavior of the introduced scheme is exemplified through two numerical applications. The efficacy of the devised methodology is firstly compared against the standard LQR-KF approach in a linear benchmark application where the system model is assumed known a priori, and secondly, the method is validated on a joint state and parameter estimation problem where the system model is assumed uncertain, formulated as nonlinear, and updated in real-time. (paper)

  2. Air Force Reusable Booster System: A Quick-look, Design Focused Modeling and Cost Analysis Study

    Science.gov (United States)

    Zapata, Edgar

    2011-01-01

    . Design and technology features bear special relevance to early program research and development directions. Given the uncertainties involved in both their actual performance promise and their relation to costs of operational systems, this later relationship is also given special attention.

  3. Uncertainties in the measured quantities of water leaving waste Tank 241-C-106 via the ventilation system

    Energy Technology Data Exchange (ETDEWEB)

    Minteer, D.J.

    1995-01-23

    The purpose of this analysis is to estimate the uncertainty in the measured quantity of water which typically leaves Tank 241-C-106 via the ventilation system each month. Such measurements are essential for heat removal estimation and tank liquid level verification purposes. The uncertainty associated with the current, infrequent, manual method of measurement (involves various psychrometric and pressure measurements) is suspected to be unreasonably high. Thus, the possible reduction of this uncertainty using a continuous, automated method of measurement will also be estimated. There are three major conclusions as a result of this analysis: (1) the uncertainties associated with the current (infrequent, manual) method of measuring the water which typically leaves Tank 241-C-106 per month via the ventilation system are indeed quite high (80% to 120%); (2) given the current psychrometric and pressure measurement methods and any tank which loses considerable moisture through active ventilation, such as Tank 241-C-106, significant quantities of liquid can actually leak from the tank before a leak can be positively identified via liquid level measurement; (3) using improved (continuous, automated) methods of taking the psychrometric and pressure measurements, the uncertainty in the measured quantity of water leaving Tank 241-C-106 via the ventilation system can be reduced by approximately an order of magnitude.

  4. Uncertainties in the measured quantities of water leaving waste Tank 241-C-106 via the ventilation system

    International Nuclear Information System (INIS)

    Minteer, D.J.

    1995-01-01

    The purpose of this analysis is to estimate the uncertainty in the measured quantity of water which typically leaves Tank 241-C-106 via the ventilation system each month. Such measurements are essential for heat removal estimation and tank liquid level verification purposes. The uncertainty associated with the current, infrequent, manual method of measurement (involves various psychrometric and pressure measurements) is suspected to be unreasonably high. Thus, the possible reduction of this uncertainty using a continuous, automated method of measurement will also be estimated. There are three major conclusions as a result of this analysis: (1) the uncertainties associated with the current (infrequent, manual) method of measuring the water which typically leaves Tank 241-C-106 per month via the ventilation system are indeed quite high (80% to 120%); (2) given the current psychrometric and pressure measurement methods and any tank which loses considerable moisture through active ventilation, such as Tank 241-C-106, significant quantities of liquid can actually leak from the tank before a leak can be positively identified via liquid level measurement; (3) using improved (continuous, automated) methods of taking the psychrometric and pressure measurements, the uncertainty in the measured quantity of water leaving Tank 241-C-106 via the ventilation system can be reduced by approximately an order of magnitude

  5. Internal Logistics System Selection with Total Cost of Ownership Analysis

    Science.gov (United States)

    Araújo, Inês; Pimentel, Carina; Godina, Radu; Matias, João C. O.

    2017-06-01

    In this paper a methodology was followed in order to support the decision-making of one industrial unit regarding its internal logistics system. The addressed factory was facing issues with their internal logistics approach. Some alternatives were pointed out and a proper total cost of ownership (TCO) analysis was developed. This analysis was taken in order to demonstrate the more cost-effective solution for the internal logistics system. This tool is more and more valued by the companies, due to their willing to reduce the costs that are associated with the way of doing business. Despite the proposal of the best choice for the internal logistics system of the enterprise, this study also intends to present some conclusions about the match between the nature of the industrial unit and the logistics systems that best fit the requirements of those.

  6. Assessment of structural model and parameter uncertainty with a multi-model system for soil water balance models

    Science.gov (United States)

    Michalik, Thomas; Multsch, Sebastian; Frede, Hans-Georg; Breuer, Lutz

    2016-04-01

    Water for agriculture is strongly limited in arid and semi-arid regions and often of low quality in terms of salinity. The application of saline waters for irrigation increases the salt load in the rooting zone and has to be managed by leaching to maintain a healthy soil, i.e. to wash out salts by additional irrigation. Dynamic simulation models are helpful tools to calculate the root zone water fluxes and soil salinity content in order to investigate best management practices. However, there is little information on structural and parameter uncertainty for simulations regarding the water and salt balance of saline irrigation. Hence, we established a multi-model system with four different models (AquaCrop, RZWQM, SWAP, Hydrus1D/UNSATCHEM) to analyze the structural and parameter uncertainty by using the Global Likelihood and Uncertainty Estimation (GLUE) method. Hydrus1D/UNSATCHEM and SWAP were set up with multiple sets of different implemented functions (e.g. matric and osmotic stress for root water uptake) which results in a broad range of different model structures. The simulations were evaluated against soil water and salinity content observations. The posterior distribution of the GLUE analysis gives behavioral parameters sets and reveals uncertainty intervals for parameter uncertainty. Throughout all of the model sets, most parameters accounting for the soil water balance show a low uncertainty, only one or two out of five to six parameters in each model set displays a high uncertainty (e.g. pore-size distribution index in SWAP and Hydrus1D/UNSATCHEM). The differences between the models and model setups reveal the structural uncertainty. The highest structural uncertainty is observed for deep percolation fluxes between the model sets of Hydrus1D/UNSATCHEM (~200 mm) and RZWQM (~500 mm) that are more than twice as high for the latter. The model sets show a high variation in uncertainty intervals for deep percolation as well, with an interquartile range (IQR) of

  7. Trading-off tolerable risk with climate change adaptation costs in water supply systems

    Science.gov (United States)

    Borgomeo, Edoardo; Mortazavi-Naeini, Mohammad; Hall, Jim W.; O'Sullivan, Michael J.; Watson, Tim

    2016-02-01

    Choosing secure water resource management plans inevitably requires trade-offs between risks (for a variety of stakeholders), costs, and other impacts. We have previously argued that water resources planning should focus upon metrics of risk of water restrictions, accompanied by extensive simulation and scenario-based exploration of uncertainty. However, the results of optimization subject to risk constraints can be sensitive to the specification of tolerable risk, which may not be precisely or consistently defined by different stakeholders. In this paper, we recast the water resources planning problem as a multiobjective optimization problem to identify least cost schemes that satisfy a set of criteria for tolerable risk, where tolerable risk is defined in terms of the frequency of water use restrictions of different levels of severity. Our proposed method links a very large ensemble of climate model projections to a water resource system model and a multiobjective optimization algorithm to identify a Pareto optimal set of water resource management plans across a 25 years planning period. In a case study application to the London water supply system, we identify water resources management plans that, for a given financial cost, maximize performance with respect to one or more probabilistic criteria. This illustrates trade-offs between financial costs of plans and risk, and between risk criteria for four different severities of water use restrictions. Graphical representation of alternative sequences of investments in the Pareto set helps to identify water management options for which there is a robust case for including them in the plan.

  8. Transmission embedded cost allocation methodology with consideration of system reliability

    International Nuclear Information System (INIS)

    Hur, D.; Park, J.-K.; Yoo, C.-I.; Kim, B.H.

    2004-01-01

    In a vertically integrated utility industry, the cost of reliability, as a separate service, has not received much rigorous analysis. However, as a cornerstone of restructuring the industry, the transmission service pricing must change to be consistent with, and supportive of, competitive wholesale electricity markets. This paper focuses on the equitable allocation of transmission network embedded costs including the transmission reliability cost based on the contributions of each generator to branch flows under normal conditions as well as the line outage impact factor under a variety of load levels. A numerical example on a six-bus system is given to illustrate the applications of the proposed methodology. (author)

  9. Long Term Cost Efficiency through Green Management Control Systems

    OpenAIRE

    Vukania Adda, Nancy; Qin, Xiaochen

    2012-01-01

    Title: Long term cost efficiency through green management control systems.Authors: Nancy Vukania &Xiaochen QinSupervisor: Åsa Karin-EngstrandBackground: The worldwide financial crisis of 2008 has reconfigured the economic turf leading to a more uncertain and turbulent playing field – a greater challenge for business strategy and the quest for optimization- The oil price hike of 2008 (Furlong 2010)1 caused its rippling effect to affect various cost categories including energy, labor and lo...

  10. Cost Effective and Affordable Guidance and Control Systems.

    Science.gov (United States)

    1985-02-01

    FACTORY SUPORIT COST, . PODUCTION TEST & TEST EQUIPMENT COSTS SYSTEM DTPSESIG APROC BLOCK DIAGRAM r A CONFIGU RAEI1 TARGET~~~~~ADI COMMITTEES M...peut Atre rdduit en utilisant des circuits dlectroniques adaptds pour treiter les franges d’interfdrence. Bens ce cas, mmse avec: des gyrolasers de 6...warehouse of parts, and an editing and testing facility. The Japanese have reportedly achieved up to an 85% reuse rate in their software factories by using

  11. Waste Management facilities cost information: System Cost Model Software Quality Assurance Plan. Revision 2

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, B.L.; Lundeen, A.S.

    1996-02-01

    In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors developed the System Cost Model (SCM) application. The SCM estimates life-cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, transuranic, and mixed transuranic waste. The SCM uses parametric cost functions to estimate life-cycle costs for various treatment, storage, and disposal modules which reflect planned and existing facilities at DOE installations. In addition, SCM can model new facilities based on capacity needs over the program life cycle. The SCM also provides transportation costs for truck and rail, which include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation`s generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction costs, operation management, and decommissioning these waste management facilities. For the product to be effective and useful the SCM users must have a high level of confidence in the data generated by the software model. The SCM Software Quality Assurance Plan is part of the overall SCM project management effort to ensure that the SCM is maintained as a quality product and can be relied on to produce viable planning data. This document defines tasks and deliverables to ensure continued product integrity, provide increased confidence in the accuracy of the data generated, and meet the LITCO`s quality standards during the software maintenance phase. 8 refs., 1 tab.

  12. Waste Management facilities cost information: System Cost Model Software Quality Assurance Plan. Revision 2

    International Nuclear Information System (INIS)

    Peterson, B.L.; Lundeen, A.S.

    1996-02-01

    In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors developed the System Cost Model (SCM) application. The SCM estimates life-cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, transuranic, and mixed transuranic waste. The SCM uses parametric cost functions to estimate life-cycle costs for various treatment, storage, and disposal modules which reflect planned and existing facilities at DOE installations. In addition, SCM can model new facilities based on capacity needs over the program life cycle. The SCM also provides transportation costs for truck and rail, which include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction costs, operation management, and decommissioning these waste management facilities. For the product to be effective and useful the SCM users must have a high level of confidence in the data generated by the software model. The SCM Software Quality Assurance Plan is part of the overall SCM project management effort to ensure that the SCM is maintained as a quality product and can be relied on to produce viable planning data. This document defines tasks and deliverables to ensure continued product integrity, provide increased confidence in the accuracy of the data generated, and meet the LITCO's quality standards during the software maintenance phase. 8 refs., 1 tab

  13. The Almajiri educational system in Nigeria: cost and challenges ...

    African Journals Online (AJOL)

    This paper highlights the cost and challenges of the Almajiri system of education in Nigeria. The paper theoretically examines pertinent issues arising from its conduct and administration. Although the Almajiri system of education in Nigeria has attracted very large number of children in the Northern part of the country, it has ...

  14. Systems Analysis for Program Planning and Cost Effectiveness. (An Application).

    Science.gov (United States)

    van Gigch, John P.; Hill, Richard E.

    This paper describes an effort to implement a cost-effectiveness program using systems analysis in an elementary school district, the Rio Linda Union School District in California. The systems design cycle employed has three phases, policy-making evaluation, and action-implementation. During the first phase, the general philosophy or mission of…

  15. Cost-effective treatment of existing guardrail systems.

    Science.gov (United States)

    2013-05-01

    A cost-effective means for upgrading existing guardrail systems with deviations from current practice (i.e., low-rail heights, antiquated end : treatments, and improper installation) does not exist. As a result these systems remain on U.S. highways. ...

  16. Latency and Criticality of Uncertainties in the Development of Product-Service Systems

    DEFF Research Database (Denmark)

    Ramirez Hernandez, Tabea; Kreye, Melanie; Pigosso, Daniela Cristina Antelmi

    2018-01-01

    to the high levels of uncertainty caused by the novelty and complexity of developing the product and the service in parallel. Uncertainty is further increased through mostly long life cycles of PSS and organisational complexity caused by a high degree of stakeholder involvement (Wolfenstetter et al., 2015...

  17. Uncertainty modelling and analysis of environmental systems: a river sediment yield example

    NARCIS (Netherlands)

    Keesman, K.J.; Koskela, J.; Guillaume, J.H.; Norton, J.P.; Croke, B.; Jakeman, A.

    2011-01-01

    Abstract: Throughout the last decades uncertainty analysis has become an essential part of environmental model building (e.g. Beck 1987; Refsgaard et al., 2007). The objective of the paper is to introduce stochastic and setmembership uncertainty modelling concepts, which basically differ in the

  18. Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application

    International Nuclear Information System (INIS)

    Baraldi, Piero; Podofillini, Luca; Mkrtchyan, Lusine; Zio, Enrico; Dang, Vinh N.

    2015-01-01

    The use of expert systems can be helpful to improve the transparency and repeatability of assessments in areas of risk analysis with limited data available. In this field, human reliability analysis (HRA) is no exception, and, in particular, dependence analysis is an HRA task strongly based on analyst judgement. The analysis of dependence among Human Failure Events refers to the assessment of the effect of an earlier human failure on the probability of the subsequent ones. This paper analyses and compares two expert systems, based on Bayesian Belief Networks and Fuzzy Logic (a Fuzzy Expert System, FES), respectively. The comparison shows that a BBN approach should be preferred in all the cases characterized by quantifiable uncertainty in the input (i.e. when probability distributions can be assigned to describe the input parameters uncertainty), since it provides a satisfactory representation of the uncertainty and its output is directly interpretable for use within PSA. On the other hand, in cases characterized by very limited knowledge, an analyst may feel constrained by the probabilistic framework, which requires assigning probability distributions for describing uncertainty. In these cases, the FES seems to lead to a more transparent representation of the input and output uncertainty. - Highlights: • We analyse treatment of uncertainty in two expert systems. • We compare a Bayesian Belief Network (BBN) and a Fuzzy Expert System (FES). • We focus on the input assessment, inference engines and output assessment. • We focus on an application problem of interest for human reliability analysis. • We emphasize the application rather than math to reach non-BBN or FES specialists

  19. Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

    Science.gov (United States)

    Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

    2012-06-01

    It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

  20. The system of account and control of logistics costs

    Directory of Open Access Journals (Sweden)

    Khayrullin Rustam Zinnatullovich

    Full Text Available The process of organization of civil engineering provides the delivery of construction materials, equipment to the civil engineering objects in the required quantities at the specified time. Effective tool for solving this problem is logistics. The basic components of logistics costs, which occupy the largest share in the sum of all logistics costs, are transportation costs and storage costs. The civil engineering industry is very promising for the use of outsourcing. The main part of works on providing material and technical resources in most cases is transferred to the outsourcing of other companies, including the group of companies forming the holding. In large holding companies the chain of movement of materials, goods and productions: purchase of materials and goods, completion materials, production structures, storage, movement, transportation, etc. may include several companies belonging in holding. The goods can be moved from one warehouse to another, with or without change of the owner of goods. Each company is obliged to show each movement of goods in their financial accounting. During the goods’ movement within a group of companies from one storage to another, from one owner to another, the total costs of the goods rise. Sales within a group of companies lead, as a rule, to a gain by one of the companies and the logistic expenses of another company. Selling to a consumer provides a profit to the seller company. Therefore, the problem of adequate allocation of logistics expenses and profits between separate legal entity and the task of continuous accounting and control of logistics costs and earnings in large companies, is vital. The automated system for accounting and controlling of logistics costs is suggested. The developed system allows controlling logistics costs of refining, storage and transportation for each ton, pieces, linear or square meters of the shipped cargoes. The System is based on complex algorithms of distribution

  1. New Approaches in Reuseable Booster System Life Cycle Cost Modeling

    Science.gov (United States)

    Zapata, Edgar

    2013-01-01

    This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model

  2. New Approaches in Reusable Booster System Life Cycle Cost Modeling

    Science.gov (United States)

    Zapata, Edgar

    2013-01-01

    This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model

  3. Automatic Threshold Setting and Its Uncertainty Quantification in Wind Turbine Condition Monitoring System

    DEFF Research Database (Denmark)

    Marhadi, Kun Saptohartyadi; Skrimpas, Georgios Alexandros

    2015-01-01

    Setting optimal alarm thresholds in vibration based condition monitoring system is inherently difficult. There are no established thresholds for many vibration based measurements. Most of the time, the thresholds are set based on statistics of the collected data available. Often times the underly......Setting optimal alarm thresholds in vibration based condition monitoring system is inherently difficult. There are no established thresholds for many vibration based measurements. Most of the time, the thresholds are set based on statistics of the collected data available. Often times...... the underlying probability distribution that describes the data is not known. Choosing an incorrect distribution to describe the data and then setting up thresholds based on the chosen distribution could result in sub-optimal thresholds. Moreover, in wind turbine applications the collected data available may...... not represent the whole operating conditions of a turbine, which results in uncertainty in the parameters of the fitted probability distribution and the thresholds calculated. In this study, Johnson, Normal, and Weibull distributions are investigated; which distribution can best fit vibration data collected...

  4. muView: A Visual Analysis System for Exploring Uncertainty in Myocardial Ischemia Simulations

    KAUST Repository

    Rosen, Paul

    2016-05-23

    In this paper we describe the Myocardial Uncertainty Viewer (muView or μView) system for exploring data stemming from the simulation of cardiac ischemia. The simulation uses a collection of conductivity values to understand how ischemic regions effect the undamaged anisotropic heart tissue. The data resulting from the simulation is multi-valued and volumetric, and thus, for every data point, we have a collection of samples describing cardiac electrical properties. μView combines a suite of visual analysis methods to explore the area surrounding the ischemic zone and identify how perturbations of variables change the propagation of their effects. In addition to presenting a collection of visualization techniques, which individually highlight different aspects of the data, the coordinated view system forms a cohesive environment for exploring the simulations. We also discuss the findings of our study, which are helping to steer further development of the simulation and strengthening our collaboration with the biomedical engineers attempting to understand the phenomenon.

  5. Basin entropy: a new tool to analyze uncertainty in dynamical systems

    Science.gov (United States)

    Daza, Alvar; Wagemakers, Alexandre; Georgeot, Bertrand; Guéry-Odelin, David; Sanjuán, Miguel A. F.

    2016-01-01

    In nonlinear dynamics, basins of attraction link a given set of initial conditions to its corresponding final states. This notion appears in a broad range of applications where several outcomes are possible, which is a common situation in neuroscience, economy, astronomy, ecology and many other disciplines. Depending on the nature of the basins, prediction can be difficult even in systems that evolve under deterministic rules. From this respect, a proper classification of this unpredictability is clearly required. To address this issue, we introduce the basin entropy, a measure to quantify this uncertainty. Its application is illustrated with several paradigmatic examples that allow us to identify the ingredients that hinder the prediction of the final state. The basin entropy provides an efficient method to probe the behavior of a system when different parameters are varied. Additionally, we provide a sufficient condition for the existence of fractal basin boundaries: when the basin entropy of the boundaries is larger than log2, the basin is fractal. PMID:27514612

  6. Peak Load Regulation and Cost Optimization for Microgrids by Installing a Heat Storage Tank and a Portable Energy System

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2018-04-01

    Full Text Available With the rapid growth of electricity demands, many traditional distributed networks cannot cover their peak demands, especially in the evening. Additionally, with the interconnection of distributed electrical and thermal grids, system operational flexibility and energy efficiency can be affected as well. Therefore, by adding a portable energy system and a heat storage tank to the traditional distributed system, this paper proposes a newly defined distributed network to deal with the aforementioned problems. Simulation results show that by adding a portable energy system, fossil fuel energy consumption and daily operation cost can be reduced by 8% and 28.29%, respectively. Moreover, system peak load regulating capacity can be significantly improved. However, by introducing the portable energy system to the grid, system uncertainty can be increased to some extent. Therefore, chance constrained programming is proposed to control the system while considering system uncertainty. By applying Particle Swarm Optimization—Monte Carlo to solve the chance constrained programming, results show that power system economy and uncertainty can be compromised by selecting appropriate confidence levels α and β. It is also reported that by installing an extra heat storage tank, combined heat and power energy efficiency can be significantly improved and the installation capacity of the battery can be reduced.

  7. A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response

    International Nuclear Information System (INIS)

    Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui

    2016-01-01

    Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could

  8. Optimized low-cost-array field designs for photovoltaic systems

    Science.gov (United States)

    Post, H. N.; Carmichael, D. C.; Castle, J. A.

    A comprehensive program to define and develop array field subsystems which can achieve the lowest possible lifecycle costs is discussed. The major activity of this program is described, namely, the design and development of optimized, modular array fields for photovoltaic (PV) systems. As part of this activity, design criteria and performance requirements for specific array subsystems including support structures, foundations, intermodule connections, field wiring, lightning protection, system grounding, site preparation, and monitoring and control were defined and evaluated. Similarly, fully integrated flat-panel array field designs, optimized for lowest lifecycle costs, were developed for system sizes ranging from 20 to 500 kW sub p. Key features, subsystem requirements, and projected costs for these array field designs are presented and discussed.

  9. Prototyping low-cost and flexible vehicle diagnostic systems

    Directory of Open Access Journals (Sweden)

    Marisol GARCÍA-VALLS

    2016-12-01

    Full Text Available Diagnostic systems are software and hardware-based equipment that interoperate with an external monitored system. Traditionally, they have been expensive equipment running test algorithms to monitor physical properties of, e.g., vehicles, or civil infrastructure equipment, among others. As computer hardware is increasingly powerful (whereas its cost and size is decreasing and communication software becomes easier to program and more run-time efficient, new scenarios are enabled that yield to lower cost monitoring solutions. This paper presents a low cost approach towards the development of a diagnostic systems relying on a modular component-based approach and running on a resource limited embedded computer. Results on a prototype implementation are shown that validate the presented design, its flexibility, performance, and communication latency.

  10. Uncertainties in the daily operation of a district heating plant

    DEFF Research Database (Denmark)

    Sorknæs, Peter

    , such as CHP. It will therefore likely be increasingly important to increase the value per operation hour. The value can be increased by offering balancing for the electricity system. This in turn increases the uncertainties in the daily operation planning of the DH system. In this paper the Danish DH plant...... Ringkøbing District Heating is used as a case to investigate what costs market uncertainties can incur on a DH plant. It is found that the market uncertainties in a 4 months simulated period increased Ringkøbing District Heatings costs by less than 1%. Several factors are however not included in this paper....

  11. Non-fragile robust optimal guaranteed cost control of uncertain 2-D discrete state-delayed systems

    Science.gov (United States)

    Tandon, Akshata; Dhawan, Amit

    2016-10-01

    This paper is concerned with the problem of non-fragile robust optimal guaranteed cost control for a class of uncertain two-dimensional (2-D) discrete state-delayed systems described by the general model with norm-bounded uncertainties. Our attention is focused on the design of non-fragile state feedback controllers such that the resulting closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible parameter uncertainties and controller gain variations. A sufficient condition for the existence of such controllers is established under the linear matrix inequality framework. Moreover, a convex optimisation problem is proposed to select a non-fragile robust optimal guaranteed cost controller stabilising the 2-D discrete state-delayed system as well as achieving the least guaranteed cost for the resulting closed-loop system. The proposed method is compared with the previously reported criterion. Finally, illustrative examples are given to show the potential of the proposed technique.

  12. Physical Protection System Upgrades - Optimizing for Performance and Cost

    International Nuclear Information System (INIS)

    Hicks, Mary Jane; Bouchard, Ann M.

    1999-01-01

    CPA--Cost and Performance Analysis--is an architecture that supports analysis of physical protection systems and upgrade options. ASSESS (Analytic System and Software for Evaluating Security Systems), a tool for evaluating performance of physical protection systems, currently forms the cornerstone for evaluating detection probabilities and delay times of the system. Cost and performance data are offered to the decision-maker at the systems level and to technologists at the path-element level. A new optimization engine has been attached to the CPA methodology to automate analyses of many combinations (portfolios) of technologies. That engine controls a new analysis sequencer that automatically modifies ASSESS PPS files (facility descriptions), automatically invokes ASSESS Outsider analysis and then saves results for post-processing. Users can constrain the search to an upper bound on total cost, to a lower bound on level of performance, or to include specific technologies or technology types. This process has been applied to a set of technology development proposals to identify those portfolios that provide the most improvement in physical security for the lowest cost to install, operate and maintain at a baseline facility

  13. Physical Protection System Upgrades - Optimizing for Performance and Cost

    Energy Technology Data Exchange (ETDEWEB)

    Bouchard, Ann M.; Hicks, Mary Jane

    1999-07-09

    CPA--Cost and Performance Analysis--is an architecture that supports analysis of physical protection systems and upgrade options. ASSESS (Analytic System and Software for Evaluating Security Systems), a tool for evaluating performance of physical protection systems, currently forms the cornerstone for evaluating detection probabilities and delay times of the system. Cost and performance data are offered to the decision-maker at the systems level and to technologists at the path-element level. A new optimization engine has been attached to the CPA methodology to automate analyses of many combinations (portfolios) of technologies. That engine controls a new analysis sequencer that automatically modifies ASSESS PPS files (facility descriptions), automatically invokes ASSESS Outsider analysis and then saves results for post-processing. Users can constrain the search to an upper bound on total cost, to a lower bound on level of performance, or to include specific technologies or technology types. This process has been applied to a set of technology development proposals to identify those portfolios that provide the most improvement in physical security for the lowest cost to install, operate and maintain at a baseline facility.

  14. Fuel Cell System for Transportation -- 2005 Cost Estimate

    Energy Technology Data Exchange (ETDEWEB)

    Wheeler, D.

    2006-10-01

    Independent review report of the methodology used by TIAX to estimate the cost of producing PEM fuel cells using 2005 cell stack technology. The U.S. Department of Energy (DOE) Hydrogen, Fuel Cells and Infrastructure Technologies Program Manager asked the National Renewable Energy Laboratory (NREL) to commission an independent review of the 2005 TIAX cost analysis for fuel cell production. The NREL Systems Integrator is responsible for conducting independent reviews of progress toward meeting the DOE Hydrogen Program (the Program) technical targets. An important technical target of the Program is the proton exchange membrane (PEM) fuel cell cost in terms of dollars per kilowatt ($/kW). The Program's Multi-Year Program Research, Development, and Demonstration Plan established $125/kW as the 2005 technical target. Over the last several years, the Program has contracted with TIAX, LLC (TIAX) to produce estimates of the high volume cost of PEM fuel cell production for transportation use. Since no manufacturer is yet producing PEM fuel cells in the quantities needed for an initial hydrogen-based transportation economy, these estimates are necessary for DOE to gauge progress toward meeting its targets. For a PEM fuel cell system configuration developed by Argonne National Laboratory, TIAX estimated the total cost to be $108/kW, based on assumptions of 500,000 units per year produced with 2005 cell stack technology, vertical integration of cell stack manufacturing, and balance-of-plant (BOP) components purchased from a supplier network. Furthermore, TIAX conducted a Monte Carlo analysis by varying ten key parameters over a wide range of values and estimated with 98% certainty that the mean PEM fuel cell system cost would be below DOE's 2005 target of $125/kW. NREL commissioned DJW TECHNOLOGY, LLC to form an Independent Review Team (the Team) of industry fuel cell experts and to evaluate the cost estimation process and the results reported by TIAX. The results of

  15. The Cost and Benefit of Bulk Energy Storage in the Arizona Power Transmission System

    Science.gov (United States)

    Ruggiero, John

    This thesis addresses the issue of making an economic case for energy storage in power systems. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load; store energy when it is inexpensive and discharge energy when it is expensive; potentially defer transmission and generation expansion; and provide for generation reserve margins. As renewable energy resource penetration increases, the uncertainty and variability of wind and solar may be alleviated by bulk energy storage technologies. The quadratic programming function in MATLAB is used to simulate an economic dispatch that includes energy storage. A program is created that utilizes quadratic programming to analyze various cases using a 2010 summer peak load from the Arizona transmission system, part of the Western Electricity Coordinating Council (WECC). The MATLAB program is used first to test the Arizona test bed with a low level of energy storage to study how the storage power limit effects several optimization out-puts such as the system wide operating costs. Very high levels of energy storage are then added to see how high level energy storage affects peak shaving, load factor, and other system applications. Finally, various constraint relaxations are made to analyze why the applications tested eventually approach a constant value. This research illustrates the use of energy storage which helps minimize the system wide generator operating cost by "shaving" energy off of the peak demand.

  16. Robust Guaranteed Cost Observer Design for Singular Markovian Jump Time-Delay Systems with Generally Incomplete Transition Probability

    Directory of Open Access Journals (Sweden)

    Yanbo Li

    2014-01-01

    Full Text Available This paper is devoted to the investigation of the design of robust guaranteed cost observer for a class of linear singular Markovian jump time-delay systems with generally incomplete transition probability. In this singular model, each transition rate can be completely unknown or only its estimate value is known. Based on stability theory of stochastic differential equations and linear matrix inequality (LMI technique, we design an observer to ensure that, for all uncertainties, the resulting augmented system is regular, impulse free, and robust stochastically stable with the proposed guaranteed cost performance. Finally, a convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost filters for linear singular Markovian jump time-delay systems with generally incomplete transition probability.

  17. An Introduction to the NCHEMS Costing and Data Management System. Technical Report No. 55.

    Science.gov (United States)

    Haight, Mike; Martin, Ron

    The NCHEMS Costing and Data Management System is designed to assist institutions in the implementation of cost studies. There are at least two kinds of cost studies: historical cost studies which display cost-related data that reflect actual events over a specific prior time period, and predictive cost studies which forecast costs that will be…

  18. Prediction uncertainty assessment of a systems biology model requires a sample of the full probability distribution of its parameters

    NARCIS (Netherlands)

    Mourik, van S.; Braak, ter C.J.F.; Stigter, J.D.; Molenaar, J.

    2014-01-01

    Multi-parameter models in systems biology are typically ‘sloppy’: some parameters or combinations of parameters may be hard to estimate from data, whereas others are not. One might expect that parameter uncertainty automatically leads to uncertain predictions, but this is not the case. We illustrate

  19. A low cost PSD-based monocular motion capture system

    Science.gov (United States)

    Ryu, Young Kee; Oh, Choonsuk

    2007-10-01

    This paper describes a monocular PSD-based motion capture sensor to employ with commercial video game systems such as Microsoft's XBOX and Sony's Playstation II. The system is compact, low-cost, and only requires a one-time calibration at the factory. The system includes a PSD(Position Sensitive Detector) and active infrared (IR) LED markers that are placed on the object to be tracked. The PSD sensor is placed in the focal plane of a wide-angle lens. The micro-controller calculates the 3D position of the markers using only the measured intensity and the 2D position on the PSD. A series of experiments were performed to evaluate the performance of our prototype system. From the experimental results we see that the proposed system has the advantages of the compact size, the low cost, the easy installation, and the high frame rates to be suitable for high speed motion tracking in games.

  20. Assessing climate adaptation options and uncertainties for cereal systems in West Africa

    Science.gov (United States)

    Guan, K.; Sultan, B.; Biasutti, M.; Lobell, D. B.

    2015-12-01

    The already fragile agriculture production system in West Africa faces further challenges in meeting food security in the coming decades, primarily due to a fast increasing population and risks of climate change. Successful adaptation of agriculture should not only benefit in the current climate but should also reduce negative (or enhance positive) impacts for climate change. Assessment of various possible adaptation options and their uncertainties provides key information for prioritizing adaptation investments. Here, based on the several robust aspects of climate projections in this region (i.e. temperature increases and rainfall pattern shifts), we use two well-validated crop models (i.e. APSIM and SARRA-H) and an ensemble of downscaled climate forcing to assess five possible and realistic adaptation options (late sowing, intensification, thermal time increase, water harvesting and increased resilience to heat stress) in West Africa for the staple crop production of sorghum. We adopt a new assessment framework to account for both the impacts of adaptation options in current climate and their ability to reduce impacts of future climate change, and also consider changes in both mean yield and its variability. Our results reveal that most proposed "adaptation options" are not more beneficial in the future than in the current climate, i.e. not really reduce the climate change impacts. Increased temperature resilience during grain number formation period is the main adaptation that emerges. We also find that changing from the traditional to modern cultivar, and later sowing in West Sahel appear to be robust adaptations.

  1. A Metaheuristically Tuned Interval Type 2 Fuzzy System to Reduce Segmentation Uncertainty in Brain MRI Images.

    Science.gov (United States)

    Taghribi, Abolfazl; Sharifian, Saeed

    2017-09-19

    Precise segmentation of magnetic resonance image (MRI) seems challenging because of the complex structure of the brain, non-uniform field in images, and noise. As a result, decision-making is associated with uncertainty. Fuzzy based approaches have been developed to overcome this problem, though most of them use fuzzy type 1 method, and sometimes contain a pre-processing step. This paper "modified type 2 fuzzy system" (MT2FS) declares a state-of-the-art method to segment MRI images using interval fuzzy type-2. Furthermore, Genetic algorithm has been employed to specify the best values for mean and variance of upper and lower membership functions. This strategy will determine discrimination boundaries for different brain tissues to be less independent from the training set. Finally, the result of fuzzy rules is extracted by using Dempster-Shafer rule combination method. Simulation results demonstrate a satisfactory output on both simulated and real MRI images in comparison with previously conducted research works without the need for a pre-processing stage.

  2. Preliminary Tests of a New Low-Cost Photogrammetric System

    Science.gov (United States)

    Santise, M.; Thoeni, K.; Roncella, R.; Sloan, S. W.; Giacomini, A.

    2017-11-01

    This paper presents preliminary tests of a new low-cost photogrammetric system for 4D modelling of large scale areas for civil engineering applications. The system consists of five stand-alone units. Each of the units is composed of a Raspberry Pi 2 Model B (RPi2B) single board computer connected to a PiCamera Module V2 (8 MP) and is powered by a 10 W solar panel. The acquisition of the images is performed automatically using Python scripts and the OpenCV library. Images are recorded at different times during the day and automatically uploaded onto a FTP server from where they can be accessed for processing. Preliminary tests and outcomes of the system are discussed in detail. The focus is on the performance assessment of the low-cost sensor and the quality evaluation of the digital surface models generated by the low-cost photogrammetric systems in the field under real test conditions. Two different test cases were set up in order to calibrate the low-cost photogrammetric system and to assess its performance. First comparisons with a TLS model show a good agreement.

  3. PRELIMINARY TESTS OF A NEW LOW-COST PHOTOGRAMMETRIC SYSTEM

    Directory of Open Access Journals (Sweden)

    M. Santise

    2017-11-01

    Full Text Available This paper presents preliminary tests of a new low-cost photogrammetric system for 4D modelling of large scale areas for civil engineering applications. The system consists of five stand-alone units. Each of the units is composed of a Raspberry Pi 2 Model B (RPi2B single board computer connected to a PiCamera Module V2 (8 MP and is powered by a 10 W solar panel. The acquisition of the images is performed automatically using Python scripts and the OpenCV library. Images are recorded at different times during the day and automatically uploaded onto a FTP server from where they can be accessed for processing. Preliminary tests and outcomes of the system are discussed in detail. The focus is on the performance assessment of the low-cost sensor and the quality evaluation of the digital surface models generated by the low-cost photogrammetric systems in the field under real test conditions. Two different test cases were set up in order to calibrate the low-cost photogrammetric system and to assess its performance. First comparisons with a TLS model show a good agreement.

  4. ATTITUDE CONTROL SYSTEM DESIGN FOR A RIGID-FLEXIBLE SATELLITE USING THE H-INFINITY METHOD WITH PARAMETRIC UNCERTAINTY

    OpenAIRE

    Souza, Alain Giacobini de; Souza, Luiz Carlos Gadelha de

    2017-01-01

    This paper presents the Attitude Control System (ACS) design for a rigid-flexible satellite with two vibrations mode, using the H infinity method considering the parametric uncertainty over the mass matrix. Usually the mathematic model obtained from the linearization and/or reduction of the rigid flexible model loses information about the flexible dynamical behavior and introduces some uncertainty. As a result, the ACS performance can be degraded when controlling large angle maneuvers. One wa...

  5. Battery energy storage systems life cycle costs case studies

    Energy Technology Data Exchange (ETDEWEB)

    Swaminathan, S.; Miller, N.F.; Sen, R.K. [SENTECH, Inc., Bethesda, MD (United States)

    1998-08-01

    This report presents a comparison of life cycle costs between battery energy storage systems and alternative mature technologies that could serve the same utility-scale applications. Two of the battery energy storage systems presented in this report are located on the supply side, providing spinning reserve and system stability benefits. These systems are compared with the alternative technologies of oil-fired combustion turbines and diesel generators. The other two battery energy storage systems are located on the demand side for use in power quality applications. These are compared with available uninterruptible power supply technologies.

  6. A possibilistic model to determine the cost of environmental quality in mid/short term planning of an electricity distribution system

    International Nuclear Information System (INIS)

    Schweickardt, Gustavo Alejandro; Gimenez Alvarez, Juan Manuel

    2012-01-01

    This work presents a Possibilistic Optimization Model to determine the Dynamic Environmental Quality Cost, applied on an Electricity Distribution System and measured as Network System Visual Impact. The Mid/Short Term Planning is the Regulatory Control Period. A multicriteria optimization approach is proposed, and for each criterion, non-stochastic uncertainties are recognized and represented by mean the introduction of Fuzzy Sets. In this way, a possibility in the occurrence of criteria variables values is established. In addition, as consequence of uncertainties of criteria preference ranking, a Model to obtain criteria Priority Vector is introduced. The Environmental Quality Cost determination is based in the relationship between the Investment Cost and an Impact Index of Network System Environmental Quality, proposed in this work. Finally, a simulation on a real system and the most important conclusions are presented.

  7. A Fractionated Spacecraft System Assessment Tool Based on Lifecycle Simulation Under Uncertainty

    NARCIS (Netherlands)

    Yao, W.; Chen, X.; Zhao, Y.; Van Tooren, M.J.L.

    2012-01-01

    To comprehensively assess fractionated spacecraft, an assessment tool is developed based on lifecycle simulation under uncertainty driven by modular evolutionary stochastic models. First, fractionated spacecraft nomenclature and architecture are clarified, and assessment criteria are analyzed. The

  8. Data Quality Assessment of the Uncertainty Analysis Applied to the Greenhouse Gas Emissions of a Dairy Cow System

    Directory of Open Access Journals (Sweden)

    Chun-Youl Baek

    2017-09-01

    Full Text Available The results of an uncertainty analysis are achieved by the statistical information (standard error, type of probability distributions, and range of minimum and maximum of the selected input parameters. However, there are limitations in identifying sufficient data samples for the selected input parameters for statistical information in the field of life cycle assessment (LCA. Therefore, there is a strong need for a consistent screening procedure to identify the input parameters for use in uncertainty analysis in the area of LCA. The conventional procedure for identifying input parameters for the uncertainty analysis method includes assessing the data quality using the pedigree method and the contribution analysis of the LCA results. This paper proposes a simplified procedure for ameliorating the existing data quality assessment method, which can lead to an efficient uncertainly analysis of LCA results. The proposed method has two salient features: (i a simplified procedure based on contribution analysis followed by a data quality assessment for selecting the input parameters for the uncertainty analysis; and (ii a quantitative data quality assessment method is proposed, based on the pedigree method, that adopts the analytic hierarchy process (AHP method and quality function deployment (QFD. The effects of the uncertainty of the selected input parameters on the LCA results were assessed using the Monte Carlo simulation method. A case study of greenhouse gas (GHG emissions from a dairy cow system was used to demonstrate the applicability of the proposed procedure.

  9. Data uncertainty impact in radiotoxicity evaluation connected to EFR and IRF systems

    International Nuclear Information System (INIS)

    Palmiotti, G.; Salvatores, M.

    1993-01-01

    Time-dependent sensitivity techniques, which have been used in the past for standard reactor applications, have been adapted to calculate the impact of data uncertainties in radiotoxicity evaluations. The methodology has been applied to different strategies of radioactive waste management connected with the EFR and IFR reactor fuel cycles. Results are provided in terms of sensitivity coefficients to basic data (cross sections and decay constants), and uncertainties on global radiotoxicity at different times of storing after discharge

  10. COST BENEFIT ANALYSIS OF A DG INTEGRATED SYSTEM: CASE STUDY

    Directory of Open Access Journals (Sweden)

    Ch. V. S. S. SAILAJA

    2017-09-01

    Full Text Available Distributed Generation is capable of meeting the load of the consumers partially or completely. Depending on the type of DG involved it can be operated in interconnected mode and islanded mode. The availability of numerous alternatives present for the DG technologies and large initial investments necessitates a detailed cost benefit analysis for the implementation of DG technologies. In this work an attempt has been made to study the costs involved in implementing the DG technologies. A practical system having two kinds of distributed generation i.e., Diesel Generator and solar photovoltaic system for its back up purpose is considered. A detailed cost analysis of the two DG technologies is carried out.

  11. A Layered Decision Model for Cost-Effective System Security

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Huaqiang; Alves-Foss, James; Soule, Terry; Pforsich, Hugh; Zhang, Du; Frincke, Deborah A.

    2008-10-01

    System security involves decisions in at least three areas: identification of well-defined security policies, selection of cost-effective defence strategies, and implementation of real-time defence tactics. Although choices made in each of these areas affect the others, existing decision models typically handle these three decision areas in isolation. There is no comprehensive tool that can integrate them to provide a single efficient model for safeguarding a network. In addition, there is no clear way to determine which particular combinations of defence decisions result in cost-effective solutions. To address these problems, this paper introduces a Layered Decision Model (LDM) for use in deciding how to address defence decisions based on their cost-effectiveness. To validate the LDM and illustrate how it is used, we used simulation to test model rationality and applied the LDM to the design of system security for an e-commercial business case.

  12. An Analysis of Aviation Maintenance Operations and Supporting Costs, and Cost Capturing Systems

    Science.gov (United States)

    2012-12-04

    Cost Accounting NAE Naval Aviation Enterprise NALCOMIS Naval Aviation Logistics Command Management Information System NALDA Naval Aviation Logistics...the Secretary of Defense SAF/FM Secretary of the Air Force, Financial Management SUF Suffix TEC Type Equipment Code TD Technical Directive TOC...directives ( TDs ) are implemented when trends occur and/or safe-for-flight concerns are raised. Most TDs are inspection based, but some require the

  13. System cost model user's manual, version 1.2

    International Nuclear Information System (INIS)

    Shropshire, D.

    1995-06-01

    The System Cost Model (SCM) was developed by Lockheed Martin Idaho Technologies in Idaho Falls, Idaho and MK-Environmental Services in San Francisco, California to support the Baseline Environmental Management Report sensitivity analysis for the U.S. Department of Energy (DOE). The SCM serves the needs of the entire DOE complex for treatment, storage, and disposal (TSD) of mixed low-level, low-level, and transuranic waste. The model can be used to evaluate total complex costs based on various configuration options or to evaluate site-specific options. The site-specific cost estimates are based on generic assumptions such as waste loads and densities, treatment processing schemes, existing facilities capacities and functions, storage and disposal requirements, schedules, and cost factors. The SCM allows customization of the data for detailed site-specific estimates. There are approximately forty TSD module designs that have been further customized to account for design differences for nonalpha, alpha, remote-handled, and transuranic wastes. The SCM generates cost profiles based on the model default parameters or customized user-defined input and also generates costs for transporting waste from generators to TSD sites

  14. Marginal cost calculation of energy production in hydro thermoelectric systems considering the transmission system

    International Nuclear Information System (INIS)

    Pereira, M.V.F.; Gorenstin, B.G.; Alvarenga Filho, S.

    1989-01-01

    The alternatives for calculation of energy marginal cost in hydroelectric systems, considering the transmission one, was analysed, including fundamental concepts; generation/transmission systems, represented by linear power flow model; production marginal costs in hydrothermal systems and computation aspects. (C.G.C.). 11 refs, 5 figs

  15. Low cost sensors- applications for Intelligent Transport Systems

    OpenAIRE

    Olivares, Gustavo

    2017-01-01

    A New Zealand perspective on the current status and potential of low-cost sensors within an intelligent transport systems.Part of the joint CASANZ TSIG and NZ Transport and Environment Knowledge Hub - Emissions Group workshop at NIWA Auckland. 2017-12-12.

  16. A cost-effective Geographic Information Systems for Transportation ...

    African Journals Online (AJOL)

    A cost-effective Geographic Information Systems for Transportation (GIS-T) application for traffic congestion analyses in the Developing World. ... The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader). If you would like ...

  17. Smartfactory, a modular, low cost productivity monitoring system

    CSIR Research Space (South Africa)

    Bosscha, PA

    2010-07-01

    Full Text Available As a technology colony, South Africa has often had to rely on imported technologies to assist in the monitoring of production floor statistics. This results in high costs in both procurement and support of such systems. Whilst this is the accepted...

  18. Uncertainty analysis of daily potable water demand on the performance evaluation of rainwater harvesting systems in residential buildings.

    Science.gov (United States)

    Silva, Arthur Santos; Ghisi, Enedir

    2016-09-15

    The objective of this paper is to perform a sensitivity analysis of design variables and an uncertainty analysis of daily potable water demand to evaluate the performance of rainwater harvesting systems in residential buildings. Eight cities in Brazil with different rainfall patterns were analysed. A numeric experiment was performed by means of computer simulation of rainwater harvesting. A sensitivity analysis was performed using variance-based indices for identifying the most important design parameters for rainwater harvesting systems when assessing the potential for potable water savings and underground tank capacity sizing. The uncertainty analysis was performed for different scenarios of potable water demand with stochastic variations in a normal distribution with different coefficients of variation throughout the simulated period. The results have shown that different design variables, such as potable water demand, number of occupants, rainwater demand, and roof area are important for obtaining the ideal underground tank capacity and estimating the potential for potable water savings. The stochastic variations on the potable water demand caused amplitudes of up to 4.8% on the potential for potable water savings and 9.4% on the ideal underground tank capacity. Average amplitudes were quite low for all cities. However, some combinations of parameters resulted in large amplitude of uncertainty and difference from uniform distribution for tank capacities and potential for potable water savings. Stochastic potable water demand generated low uncertainties in the performance evaluation of rainwater harvesting systems; therefore, uniform distribution could be used in computer simulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Hybrid energy system cost analysis: San Nicolas Island, California

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, T.L.; McKenna, E.

    1996-07-01

    This report analyzes the local wind resource and evaluates the costs and benefits of supplementing the current diesel-powered energy system on San Nicolas Island, California (SNI), with wind turbines. In Section 2.0 the SNI site, naval operations, and current energy system are described, as are the data collection and analysis procedures. Section 3.0 summarizes the wind resource data and analyses that were presented in NREL/TP 442-20231. Sections 4.0 and 5.0 present the conceptual design and cost analysis of a hybrid wind and diesel energy system on SNI, with conclusions following in Section 6. Appendix A presents summary pages of the hybrid system spreadsheet model, and Appendix B contains input and output files for the HYBRID2 program.

  20. Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

    Science.gov (United States)

    Qi, Di

    Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

  1. Space Transportation Systems Life Cycle Cost Assessment and Control

    Science.gov (United States)

    Robinson, John W.; Rhodes, Russell E.; Zapata, Edgar; Levack, Daniel J. H.; Donahue, Benjaamin B.; Knuth, William

    2008-01-01

    Civil and military applications of space transportation have been pursued for just over 50 years and there has been, and still is, a need for safe, dependable, affordable, and sustainable space transportation systems. Fully expendable and partially reusable space transportation systems have been developed and put in operation that have not adequately achieved this need. Access to space is technically achievable, but presently very expensive and will remain so until there is a breakthrough in the way we do business. Since 1991 the national Space Propulsion Synergy Team (SPST) has reviewed and assessed the lessons learned from the major U.S. space programs of the past decades focusing on what has been learned from the assessment and control of Life Cycle Cost (LCC) from these systems. This paper presents the results of a selected number of studies and analyses that have been conducted by the SPST addressing the need, as well as the solutions, for improvement in LCC. The major emphasis of the SPST processes is on developing the space transportation system requirements first (up front). These requirements must include both the usual system flight performance requirements and also the system functional requirements, including the infrastructure on Earth's surface, in-space and on the Moon and Mars surfaces to determine LCC. This paper describes the development of specific innovative engineering and management approaches and processes. This includes a focus on flight hardware maturity for reliability, ground operations approaches, and business processes between contractor and government organizations. A major change in program/project cost control is being proposed by the SPST to achieve a sustainable space transportation system LCC - controlling cost as a program metric in addition to the existing practice of controlling performance and weight. Without a firm requirement and methodically structured cost control, it is unlikely that an affordable and sustainable space

  2. Photometric Uncertainties

    Science.gov (United States)

    Zou, Xiao-Duan; Li, Jian-Yang; Clark, Beth Ellen; Golish, Dathon

    2018-01-01

    The OSIRIS-REx spacecraft, launched in September, 2016, will study the asteroid Bennu and return a sample from its surface to Earth in 2023. Bennu is a near-Earth carbonaceous asteroid which will provide insight into the formation and evolution of the solar system. OSIRIS-REx will first approach Bennu in August 2018 and will study the asteroid for approximately two years before sampling. OSIRIS-REx will develop its photometric model (including Lommel-Seelinger, ROLO, McEwen, Minnaert and Akimov) of Bennu with OCAM and OVIRS during the Detailed Survey mission phase. The model developed during this phase will be used to photometrically correct the OCAM and OVIRS data.Here we present the analysis of the error for the photometric corrections. Based on our testing data sets, we find:1. The model uncertainties is only correct when we use the covariance matrix to calculate, because the parameters are highly correlated.2. No evidence of domination of any parameter in each model.3. And both model error and the data error contribute to the final correction error comparably.4. We tested the uncertainty module on fake and real data sets, and find that model performance depends on the data coverage and data quality. These tests gave us a better understanding of how different model behave in different case.5. L-S model is more reliable than others. Maybe because the simulated data are based on L-S model. However, the test on real data (SPDIF) does show slight advantage of L-S, too. ROLO is not reliable to use when calculating bond albedo. The uncertainty of McEwen model is big in most cases. Akimov performs unphysical on SOPIE 1 data.6. Better use L-S as our default choice, this conclusion is based mainly on our test on SOPIE data and IPDIF.

  3. SURE: a system of computer codes for performing sensitivity/uncertainty analyses with the RELAP code. [PWR

    Energy Technology Data Exchange (ETDEWEB)

    Bjerke, M.A.

    1983-02-01

    A package of computer codes has been developed to perform a nonlinear uncertainty analysis on transient thermal-hydraulic systems which are modeled with the RELAP computer code. Using an uncertainty around the analyses of experiments in the PWR-BDHT Separate Effects Program at Oak Ridge National Laboratory. The use of FORTRAN programs running interactively on the PDP-10 computer has made the system very easy to use and provided great flexibility in the choice of processing paths. Several experiments simulating a loss-of-coolant accident in a nuclear reactor have been successfully analyzed. It has been shown that the system can be automated easily to further simplify its use and that the conversion of the entire system to a base code other than RELAP is possible.

  4. Relevant Costs for Decision in an Effective Controlling System

    Directory of Open Access Journals (Sweden)

    Mihaela TULVINSCHI

    2010-05-01

    Full Text Available Controlling is considered a leading concept in the sense of coordination, planning, control and automation, in order to produce the synthesis necessary in decision making. The purpose of article is to highlight the link between a dynamic accounting system and an effective controlling system. The research method used is based on the idea that the cost analysis in an efficient controlling system involves obtaining accounting information from within the entity which management then uses in decision making. In conclusion, we emphasize that an effective controlling system must provide managers the tools to meet their informational needs.

  5. Solar Water Heating with Low-Cost Plastic Systems

    Energy Technology Data Exchange (ETDEWEB)

    None

    2012-01-01

    Federal buildings consumed over 392,000 billion Btu of site delivered energy for buildings during FY 2007 at a total cost of $6.5 billion. Earlier data indicate that about 10% of this is used to heat water.[2] Targeting energy consumption in Federal buildings, the Energy Independence and Security Act of 2007 (EISA) requires new Federal buildings and major renovations to meet 30% of their hot water demand with solar energy, provided it is cost-effective over the life of the system. In October 2009, President Obama expanded the energy reduction and performance requirements of EISA and its subsequent regulations with his Executive Order 13514.

  6. Centralized contracting an imperative for reducing health system costs.

    Science.gov (United States)

    Baskel, Christopher

    2014-03-01

    As a health system expands, there is a concomitant need for its leaders to take steps to ensure that redundancies in purchasing processes do not drive up costs to unsustainable levels. Spectrum Health in Grand Rapids, Mich., tackled this challenge by instituting a revenue-driven, patient-care-focused value analysis process that centralized contracting processes in several areas of nonsalary expense. Spectrum went on to uncover opportunities for cutting costs in its decentralized, non-purchase order expenses, saving 24 percent in the first of four arenas.

  7. A Risk-Based Interval Two-Stage Programming Model for Agricultural System Management under Uncertainty

    Directory of Open Access Journals (Sweden)

    Ye Xu

    2016-01-01

    Full Text Available Nonpoint source (NPS pollution caused by agricultural activities is main reason that water quality in watershed becomes worse, even leading to deterioration. Moreover, pollution control is accompanied with revenue’s fall for agricultural system. How to design and generate a cost-effective and environmentally friendly agricultural production pattern is a critical issue for local managers. In this study, a risk-based interval two-stage programming model (RBITSP was developed. Compared to general ITSP model, significant contribution made by RBITSP model was that it emphasized importance of financial risk under various probabilistic levels, rather than only being concentrated on expected economic benefit, where risk is expressed as the probability of not meeting target profit under each individual scenario realization. This way effectively avoided solutions’ inaccuracy caused by traditional expected objective function and generated a variety of solutions through adjusting weight coefficients, which reflected trade-off between system economy and reliability. A case study of agricultural production management with the Tai Lake watershed was used to demonstrate superiority of proposed model. Obtained results could be a base for designing land-structure adjustment patterns and farmland retirement schemes and realizing balance of system benefit, system-failure risk, and water-body protection.

  8. A new process sensitivity index to identify important system processes under process model and parametric uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Dai, Heng [Pacific Northwest National Laboratory, Richland Washington USA; Ye, Ming [Department of Scientific Computing, Florida State University, Tallahassee Florida USA; Walker, Anthony P. [Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Chen, Xingyuan [Pacific Northwest National Laboratory, Richland Washington USA

    2017-04-01

    Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averaging methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.

  9. Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

    Science.gov (United States)

    Perdigão, R. A. P.

    2017-12-01

    Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

  10. Uncertainty analysis guide

    International Nuclear Information System (INIS)

    Andres, T.H.

    2002-05-01

    This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

  11. 100 years of California’s water rights system: patterns, trends and uncertainty

    Science.gov (United States)

    Grantham, Theodore E.; Viers, Joshua H.

    2014-08-01

    For 100 years, California’s State Water Resources Control Board and its predecessors have been responsible for allocating available water supplies to beneficial uses, but inaccurate and incomplete accounting of water rights has made the state ill-equipped to satisfy growing societal demands for water supply reliability and healthy ecosystems. Here, we present the first comprehensive eval