Including operational data in QMRA model: development and impact of model inputs.
Jaidi, Kenza; Barbeau, Benoit; Carrière, Annie; Desjardins, Raymond; Prévost, Michèle
2009-03-01
A Monte Carlo model, based on the Quantitative Microbial Risk Analysis approach (QMRA), has been developed to assess the relative risks of infection associated with the presence of Cryptosporidium and Giardia in drinking water. The impact of various approaches for modelling the initial parameters of the model on the final risk assessments is evaluated. The Monte Carlo simulations that we performed showed that the occurrence of parasites in raw water was best described by a mixed distribution: log-Normal for concentrations > detection limit (DL), and a uniform distribution for concentrations risks significantly. The mean annual risks for conventional treatment are: 1.97E-03 (removal credit adjusted by log parasite = log spores), 1.58E-05 (log parasite = 1.7 x log spores) or 9.33E-03 (regulatory credits based on the turbidity measurement in filtered water). Using full scale validated SCADA data, the simplified calculation of CT performed at the plant was shown to largely underestimate the risk relative to a more detailed CT calculation, which takes into consideration the downtime and system failure events identified at the plant (1.46E-03 vs. 3.93E-02 for the mean risk).
Directory of Open Access Journals (Sweden)
P.-L. Blelly
2005-02-01
Full Text Available The TRANSCAR ionospheric model was extended to account for the convection of the magnetic field lines in the auroral and polar ionosphere. A mixed Eulerian-Lagrangian 13-moment approach was used to describe the dynamics of an ionospheric plasma tube. In the present study, one focuses on large scale transports in the polar ionosphere. The model was used to simulate a 35-h period of EISCAT-UHF observations on 16-17 February 1993. The first day was magnetically quiet, and characterized by elevated electron concentrations: the diurnal F_{2} layer reached as much as 10^{12}m^{-3}, which is unusual for a winter and moderate solar activity (F_{10.7}=130 period. An intense geomagnetic event occurred on the second day, seen in the data as a strong intensification of the ionosphere convection velocities in the early afternoon (with the northward electric field reaching 150mVm^{-1} and corresponding frictional heating of the ions up to 2500K. The simulation used time-dependent AMIE outputs to infer flux-tube transports in the polar region, and to provide magnetospheric particle and energy inputs to the ionosphere. The overall very good agreement, obtained between the model and the observations, demonstrates the high ability of the extended TRANSCAR model for quantitative modelling of the high-latitude ionosphere; however, some differences are found which are attributed to the precipitation of electrons with very low energy. All these results are finally discussed in the frame of modelling the auroral ionosphere with space weather applications in mind.
Directory of Open Access Journals (Sweden)
P.-L. Blelly
2005-02-01
Full Text Available The TRANSCAR ionospheric model was extended to account for the convection of the magnetic field lines in the auroral and polar ionosphere. A mixed Eulerian-Lagrangian 13-moment approach was used to describe the dynamics of an ionospheric plasma tube. In the present study, one focuses on large scale transports in the polar ionosphere. The model was used to simulate a 35-h period of EISCAT-UHF observations on 16-17 February 1993. The first day was magnetically quiet, and characterized by elevated electron concentrations: the diurnal F2 layer reached as much as 1012m-3, which is unusual for a winter and moderate solar activity (F10.7=130 period. An intense geomagnetic event occurred on the second day, seen in the data as a strong intensification of the ionosphere convection velocities in the early afternoon (with the northward electric field reaching 150mVm-1 and corresponding frictional heating of the ions up to 2500K. The simulation used time-dependent AMIE outputs to infer flux-tube transports in the polar region, and to provide magnetospheric particle and energy inputs to the ionosphere. The overall very good agreement, obtained between the model and the observations, demonstrates the high ability of the extended TRANSCAR model for quantitative modelling of the high-latitude ionosphere; however, some differences are found which are attributed to the precipitation of electrons with very low energy. All these results are finally discussed in the frame of modelling the auroral ionosphere with space weather applications in mind.
Modeling and generating input processes
Energy Technology Data Exchange (ETDEWEB)
Johnson, M.E.
1987-01-01
This tutorial paper provides information relevant to the selection and generation of stochastic inputs to simulation studies. The primary area considered is multivariate but much of the philosophy at least is relevant to univariate inputs as well. 14 refs.
Input-output linearizing tracking control of induction machine with the included magnetic saturation
DEFF Research Database (Denmark)
Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd
2003-01-01
The tracking control design of an induction motor, based on input-output linearisation with magnetic saturation included is addressed. The magnetic saturation is represented by a nonlinear magnetising curve for the iron core and is used in the control, the observer of the state variables, and in ...
Remote sensing inputs to water demand modeling
Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.
1975-01-01
In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.
Robust input design for nonlinear dynamic modeling of AUV.
Nouri, Nowrouz Mohammad; Valadi, Mehrdad
2017-09-01
Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
A probabilistic graphical model based stochastic input model construction
International Nuclear Information System (INIS)
Wan, Jiang; Zabaras, Nicholas
2014-01-01
Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. A. Wasiolek
2003-01-01
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-09-24
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air
On Optimal Input Design and Model Selection for Communication Channels
Energy Technology Data Exchange (ETDEWEB)
Li, Yanyan [ORNL; Djouadi, Seddik M [ORNL; Olama, Mohammed M [ORNL
2013-01-01
In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.
Analytic uncertainty and sensitivity analysis of models with input correlations
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
ON MODELING METHODS OF REPRODUCTION OF FIXED ASSETS IN DYNAMIC INPUT - OUTPUT MODELS
Directory of Open Access Journals (Sweden)
Baranov A. O.
2014-12-01
Full Text Available The article presents a comparative study of methods for modeling reproduction of fixed assets in various types of dynamic input-output models, which have been developed at the Novosibirsk State University and at the Institute of Economics and Industrial Engineering of the Siberian Division of Russian Academy of Sciences. The study compares the technique of information providing for the investment blocks of the models. Considered in detail mathematical description of the block of fixed assets reproduction in the Dynamic Input - Output Model included in the KAMIN system and the optimization interregional input - output model. Analyzes the peculiarities of information support of investment and fixed assets blocks of the Dynamic Input - Output Model included in the KAMIN system and the optimization interregional input - output model. In conclusion of the article provides suggestions for joint use of the analyzed models for Russian economy development forecasting. Provided the use of the KAMIN system’s models for short-term and middle-term forecasting and the optimization interregional input - output model to develop long-term forecasts based on the spatial structure of the economy.
Variance-based sensitivity indices for models with dependent inputs
International Nuclear Information System (INIS)
Mara, Thierry A.; Tarantola, Stefano
2012-01-01
Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.
Soil-related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
A. J. Smith
2003-01-01
This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash
A stochastic model of input effectiveness during irregular gamma rhythms.
Dumont, Grégory; Northoff, Georg; Longtin, André
2016-02-01
Gamma-band synchronization has been linked to attention and communication between brain regions, yet the underlying dynamical mechanisms are still unclear. How does the timing and amplitude of inputs to cells that generate an endogenously noisy gamma rhythm affect the network activity and rhythm? How does such "communication through coherence" (CTC) survive in the face of rhythm and input variability? We present a stochastic modelling approach to this question that yields a very fast computation of the effectiveness of inputs to cells involved in gamma rhythms. Our work is partly motivated by recent optogenetic experiments (Cardin et al. Nature, 459(7247), 663-667 2009) that tested the gamma phase-dependence of network responses by first stabilizing the rhythm with periodic light pulses to the interneurons (I). Our computationally efficient model E-I network of stochastic two-state neurons exhibits finite-size fluctuations. Using the Hilbert transform and Kuramoto index, we study how the stochastic phase of its gamma rhythm is entrained by external pulses. We then compute how this rhythmic inhibition controls the effectiveness of external input onto pyramidal (E) cells, and how variability shapes the window of firing opportunity. For transferring the time variations of an external input to the E cells, we find a tradeoff between the phase selectivity and depth of rate modulation. We also show that the CTC is sensitive to the jitter in the arrival times of spikes to the E cells, and to the degree of I-cell entrainment. We further find that CTC can occur even if the underlying deterministic system does not oscillate; quasicycle-type rhythms induced by the finite-size noise retain the basic CTC properties. Finally a resonance analysis confirms the relative importance of the I cell pacing for rhythm generation. Analysis of whole network behaviour, including computations of synchrony, phase and shifts in excitatory-inhibitory balance, can be further sped up by orders of
A didactic Input-Output model for territorial ecology analyses
Garry Mcdonald
2010-01-01
This report describes a didactic input-output modelling framework created jointly be the team at REEDS, Universite de Versailles and Dr Garry McDonald, Director, Market Economics Ltd. There are three key outputs associated with this framework: (i) a suite of didactic input-output models developed in Microsoft Excel, (ii) a technical report (this report) which describes the framework and the suite of models1, and (iii) a two week intensive workshop dedicated to the training of REEDS researcher...
Stability Analysis of a Class of Second Order Sliding Mode Control Including Delay in Input
Directory of Open Access Journals (Sweden)
Pedro R. Acosta
2013-01-01
Full Text Available This paper deals with a class of second order sliding mode systems. Based on the derivative of the sliding surface, sufficient conditions are given for stability. However, the discontinuous control signal depend neither on the derivative of sliding surface nor on its estimate. Time delay in control input is also an important issue in sliding mode control for engineering applications. Therefore, also sufficient conditions are given for the time delay size on the discontinuous input signal, so that this class of second order sliding mode systems might have amplitude bounded oscillations. Moreover, amplitude of such oscillations may be estimated. Some numerical examples are given to validate the results. At the end, some conclusions are given on the possibilities of the results as well as their limitations.
Global sensitivity analysis of computer models with functional inputs
International Nuclear Information System (INIS)
Iooss, Bertrand; Ribatet, Mathieu
2009-01-01
Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.
Soil-Related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Smith, A. J.
2004-01-01
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This
Soil-Related Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
A. J. Smith
2004-09-09
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure
Computer supported estimation of input data for transportation models
Cenek, Petr; Tarábek, Peter; Kopf, Marija
2010-01-01
Control and management of transportation systems frequently rely on optimization or simulation methods based on a suitable model. Such a model uses optimization or simulation procedures and correct input data. The input data define transportation infrastructure and transportation flows. Data acquisition is a costly process and so an efficient approach is highly desirable. The infrastructure can be recognized from drawn maps using segmentation, thinning and vectorization. The accurate definiti...
Applications of flocking algorithms to input modeling for agent movement
Singham, Dashi; Therkildsen, Meredith; Schruben, Lee
2011-01-01
Refereed Conference Paper The article of record as published can be found at http://dx.doi.org/10.1109/WSC.2011.6147953 Simulation flocking has been introduced as a method for generating simulation input from multivariate dependent time series for sensitivity and risk analysis. It can be applied to data for which a parametric model is not readily available or imposes too many restrictions on the possible inputs. This method uses techniques from agent-based modeling to generate ...
Space market model space industry input-output model
Hodgin, Robert F.; Marchesini, Roberto
1987-01-01
The goal of the Space Market Model (SMM) is to develop an information resource for the space industry. The SMM is intended to contain information appropriate for decision making in the space industry. The objectives of the SMM are to: (1) assemble information related to the development of the space business; (2) construct an adequate description of the emerging space market; (3) disseminate the information on the space market to forecasts and planners in government agencies and private corporations; and (4) provide timely analyses and forecasts of critical elements of the space market. An Input-Output model of market activity is proposed which are capable of transforming raw data into useful information for decision makers and policy makers dealing with the space sector.
Lysimeter data as input to performance assessment models
International Nuclear Information System (INIS)
McConnell, J.W. Jr.
1998-01-01
The Field Lysimeter Investigations: Low-Level Waste Data Base Development Program is obtaining information on the performance of radioactive waste forms in a disposal environment. Waste forms fabricated using ion-exchange resins from EPICOR-117 prefilters employed in the cleanup of the Three Mile Island (TMI) Nuclear Power Station are being tested to develop a low-level waste data base and to obtain information on survivability of waste forms in a disposal environment. The program includes reviewing radionuclide releases from those waste forms in the first 7 years of sampling and examining the relationship between code input parameters and lysimeter data. Also, lysimeter data are applied to performance assessment source term models, and initial results from use of data in two models are presented
Bayesian tsunami fragility modeling considering input data uncertainty
De Risi, Raffaele; Goda, Katsu; Mori, Nobuhito; Yasuda, Tomohiro
2017-01-01
Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data ...
Environmental Transport Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Wasiolek, M. A.
2003-01-01
developed in this report, and the related FEPs, are listed in Table 1-1. The relationship between the parameters and FEPs was based on a comparison of the parameter definition and the FEP descriptions as presented in BSC (2003 [160699], Section 6.2). The parameter values developed in this report support the biosphere model and are reflected in the TSPA through the biosphere dose conversion factors (BDCFs). Biosphere modeling focuses on radionuclides screened for the TSPA-LA (BSC 2002 [160059]). The same list of radionuclides is used in this analysis (Section 6.1.4). The analysis considers two human exposure scenarios (groundwater and volcanic ash) and climate change (Section 6.1.5). This analysis combines and revises two previous reports, ''Transfer Coefficient Analysis'' (CRWMS MandO 2000 [152435]) and ''Environmental Transport Parameter Analysis'' (CRWMS MandO 2001 [152434]), because the new ERMYN biosphere model requires a redefined set of input parameters. The scope of this analysis includes providing a technical basis for the selection of radionuclide- and element-specific biosphere parameters (except for Kd) that are important for calculating BDCFs based on the available radionuclide inventory abstraction data. The environmental transport parameter values were developed specifically for use in the biosphere model and may not be appropriate for other applications
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-06-27
], Section 6.2). Parameter values developed in this report, and the related FEPs, are listed in Table 1-1. The relationship between the parameters and FEPs was based on a comparison of the parameter definition and the FEP descriptions as presented in BSC (2003 [160699], Section 6.2). The parameter values developed in this report support the biosphere model and are reflected in the TSPA through the biosphere dose conversion factors (BDCFs). Biosphere modeling focuses on radionuclides screened for the TSPA-LA (BSC 2002 [160059]). The same list of radionuclides is used in this analysis (Section 6.1.4). The analysis considers two human exposure scenarios (groundwater and volcanic ash) and climate change (Section 6.1.5). This analysis combines and revises two previous reports, ''Transfer Coefficient Analysis'' (CRWMS M&O 2000 [152435]) and ''Environmental Transport Parameter Analysis'' (CRWMS M&O 2001 [152434]), because the new ERMYN biosphere model requires a redefined set of input parameters. The scope of this analysis includes providing a technical basis for the selection of radionuclide- and element-specific biosphere parameters (except for Kd) that are important for calculating BDCFs based on the available radionuclide inventory abstraction data. The environmental transport parameter values were developed specifically for use in the biosphere model and may not be appropriate for other applications.
Assigning probability distributions to input parameters of performance assessment models
International Nuclear Information System (INIS)
Mishra, Srikanta
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available
Assigning probability distributions to input parameters of performance assessment models
Energy Technology Data Exchange (ETDEWEB)
Mishra, Srikanta [INTERA Inc., Austin, TX (United States)
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
Agricultural and Environmental Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rasmuson; K. Rautenstrauch
2004-01-01
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters
Quality assurance of weather data for agricultural system model input
It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rautenstrauch
2004-01-01
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rautenstrauch
2004-09-10
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Investigation of RADTRAN Stop Model input parameters for truck stops
International Nuclear Information System (INIS)
Griego, N.R.; Smith, J.D.; Neuhauser, K.S.
1996-01-01
RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops
Environmental Transport Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2004-01-01
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2004-09-10
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
Kaylie Rasmuson; Kurt Rautenstrauch
2003-06-20
This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.
DEFF Research Database (Denmark)
Róg, Tomasz; Orłowski, Adam; Llorente, Alicia
2016-01-01
In this Data in Brief article we provide a data package of GROMACS input files for atomistic molecular dynamics simulations of multicomponent, asymmetric lipid bilayers using the OPLS-AA force field. These data include 14 model bilayers composed of 8 different lipid molecules. The lipids present......, and cholesterol, while the extracellular leaflet is composed of SM, PC and cholesterol discussed in Van Meer et al. (2008) [2]. The provided data include lipids' topologies, equilibrated structures of asymmetric bilayers, all force field parameters, and input files with parameters describing simulation conditions...
Model reduction of nonlinear systems subject to input disturbances
Ndoye, Ibrahima
2017-07-10
The method of convex optimization is used as a tool for model reduction of a class of nonlinear systems in the presence of disturbances. It is shown that under some conditions the nonlinear disturbed system can be approximated by a reduced order nonlinear system with similar disturbance-output properties to the original plant. The proposed model reduction strategy preserves the nonlinearity and the input disturbance nature of the model. It guarantees a sufficiently small error between the outputs of the original and the reduced-order systems, and also maintains the properties of input-to-state stability. The matrices of the reduced order system are given in terms of a set of linear matrix inequalities (LMIs). The paper concludes with a demonstration of the proposed approach on model reduction of a nonlinear electronic circuit with additive disturbances.
Effects of input uncertainty on cross-scale crop modeling
Waha, Katharina; Huth, Neil; Carberry, Peter
2014-05-01
The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2006-01-01
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2006-06-05
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
Seepage Model for PA Including Drift Collapse
International Nuclear Information System (INIS)
Li, G.; Tsang, C.
2000-01-01
The purpose of this Analysis/Model Report (AMR) is to document the predictions and analysis performed using the Seepage Model for Performance Assessment (PA) and the Disturbed Drift Seepage Submodel for both the Topopah Spring middle nonlithophysal and lower lithophysal lithostratigraphic units at Yucca Mountain. These results will be used by PA to develop the probability distribution of water seepage into waste-emplacement drifts at Yucca Mountain, Nevada, as part of the evaluation of the long term performance of the potential repository. This AMR is in accordance with the ''Technical Work Plan for Unsaturated Zone (UZ) Flow and Transport Process Model Report'' (CRWMS M andO 2000 [153447]). This purpose is accomplished by performing numerical simulations with stochastic representations of hydrological properties, using the Seepage Model for PA, and evaluating the effects of an alternative drift geometry representing a partially collapsed drift using the Disturbed Drift Seepage Submodel. Seepage of water into waste-emplacement drifts is considered one of the principal factors having the greatest impact of long-term safety of the repository system (CRWMS M andO 2000 [153225], Table 4-1). This AMR supports the analysis and simulation that are used by PA to develop the probability distribution of water seepage into drift, and is therefore a model of primary (Level 1) importance (AP-3.15Q, ''Managing Technical Product Inputs''). The intended purpose of the Seepage Model for PA is to support: (1) PA; (2) Abstraction of Drift-Scale Seepage; and (3) Unsaturated Zone (UZ) Flow and Transport Process Model Report (PMR). Seepage into drifts is evaluated by applying numerical models with stochastic representations of hydrological properties and performing flow simulations with multiple realizations of the permeability field around the drift. The Seepage Model for PA uses the distribution of permeabilities derived from air injection testing in niches and in the cross drift to
Seepage Model for PA Including Dift Collapse
Energy Technology Data Exchange (ETDEWEB)
G. Li; C. Tsang
2000-12-20
The purpose of this Analysis/Model Report (AMR) is to document the predictions and analysis performed using the Seepage Model for Performance Assessment (PA) and the Disturbed Drift Seepage Submodel for both the Topopah Spring middle nonlithophysal and lower lithophysal lithostratigraphic units at Yucca Mountain. These results will be used by PA to develop the probability distribution of water seepage into waste-emplacement drifts at Yucca Mountain, Nevada, as part of the evaluation of the long term performance of the potential repository. This AMR is in accordance with the ''Technical Work Plan for Unsaturated Zone (UZ) Flow and Transport Process Model Report'' (CRWMS M&O 2000 [153447]). This purpose is accomplished by performing numerical simulations with stochastic representations of hydrological properties, using the Seepage Model for PA, and evaluating the effects of an alternative drift geometry representing a partially collapsed drift using the Disturbed Drift Seepage Submodel. Seepage of water into waste-emplacement drifts is considered one of the principal factors having the greatest impact of long-term safety of the repository system (CRWMS M&O 2000 [153225], Table 4-1). This AMR supports the analysis and simulation that are used by PA to develop the probability distribution of water seepage into drift, and is therefore a model of primary (Level 1) importance (AP-3.15Q, ''Managing Technical Product Inputs''). The intended purpose of the Seepage Model for PA is to support: (1) PA; (2) Abstraction of Drift-Scale Seepage; and (3) Unsaturated Zone (UZ) Flow and Transport Process Model Report (PMR). Seepage into drifts is evaluated by applying numerical models with stochastic representations of hydrological properties and performing flow simulations with multiple realizations of the permeability field around the drift. The Seepage Model for PA uses the distribution of permeabilities derived from air injection testing in
Input point distribution for regular stem form spline modeling
Directory of Open Access Journals (Sweden)
Karel Kuželka
2015-04-01
Full Text Available Aim of study: To optimize an interpolation method and distribution of measured diameters to represent regular stem form of coniferous trees using a set of discrete points. Area of study: Central-Bohemian highlands, Czech Republic; a region that represents average stand conditions of production forests of Norway spruce (Picea abies [L.] Karst. in central Europe Material and methods: The accuracy of stem curves modeled using natural cubic splines from a set of measured diameters was evaluated for 85 closely measured stems of Norway spruce using five statistical indicators and compared to the accuracy of three additional models based on different spline types selected for their ability to represent stem curves. The optimal positions to measure diameters were identified using an aggregate objective function approach. Main results: The optimal positions of the input points vary depending on the properties of each spline type. If the optimal input points for each spline are used, then all spline types are able to give reasonable results with higher numbers of input points. The commonly used natural cubic spline was outperformed by other spline types. The lowest errors occur by interpolating the points using the Catmull-Rom spline, which gives accurate and unbiased volume estimates, even with only five input points. Research highlights: The study contributes to more accurate representation of stem form and therefore more accurate estimation of stem volume using data obtained from terrestrial imagery or other close-range remote sensing methods.
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Applications of Flocking Algorithms to Input Modeling for Agent Movement
2011-12-01
2445 Singham, Therkildsen, and Schruben We apply the following flocking algorithm to this leading boid to generate followers, who will then be mapped...due to the paths crossing. 2447 Singham, Therkildsen, and Schruben Figure 2: Plot of the path of a boid generated by the Group 4 flocking algorithm ...on the possible inputs. This method uses techniques from agent-based modeling to generate a flock of boids that follow the data. In this paper, we
A one-model approach based on relaxed combinations of inputs for evaluating input congestion in DEA
Khodabakhshi, Mohammad
2009-08-01
This paper provides a one-model approach of input congestion based on input relaxation model developed in data envelopment analysis (e.g. [G.R. Jahanshahloo, M. Khodabakhshi, Suitable combination of inputs for improving outputs in DEA with determining input congestion -- Considering textile industry of China, Applied Mathematics and Computation (1) (2004) 263-273; G.R. Jahanshahloo, M. Khodabakhshi, Determining assurance interval for non-Archimedean ele improving outputs model in DEA, Applied Mathematics and Computation 151 (2) (2004) 501-506; M. Khodabakhshi, A super-efficiency model based on improved outputs in data envelopment analysis, Applied Mathematics and Computation 184 (2) (2007) 695-703; M. Khodabakhshi, M. Asgharian, An input relaxation measure of efficiency in stochastic data analysis, Applied Mathematical Modelling 33 (2009) 2010-2023]. This approach reduces solving three problems with the two-model approach introduced in the first of the above-mentioned reference to two problems which is certainly important from computational point of view. The model is applied to a set of data extracted from ISI database to estimate input congestion of 12 Canadian business schools.
Gutmann, E. D.
2016-12-01
Without good input data, almost any model will produce bad output; however, alpine environments are extremely difficult places to make measurements of those inputs. Perhaps the least well known input is precipitation, but almost as important are temperature, wind, humidity, and radiation. Recent advances in atmospheric modeling have improved the fidelity of the output such that model output is sometimes better than interpolated observations, particularly for precipitation; however these models come with a tremendous computational cost. We describe the Intermediate Complexity Atmospheric Research model (ICAR) as one path to a computationally efficient method to improve snow pack model inputs over complex terrain. ICAR provides estimates of all inputs at a small fraction of the computational cost of a traditional atmospheric model such as the Weather Research and Forecasting model (WRF). Importantly, ICAR is able to simulate feedbacks from the land surface that are critical for estimating the air temperature. In addition, we will explore future improvements to the local wind fields including the use of statistics derived from limited duration Large Eddy Simulation (LES) model runs. These wind fields play a critical role in determing the redistribution of snow, and the redistribution of snow changes the surface topography and thus the wind field. We show that a proper depiction of snowpack redistribution can have a large affect on streamflow timing, and an even larger effect on the climate change signal of that streamflow.
Remotely sensed soil moisture input to a hydrologic model
Engman, E. T.; Kustas, W. P.; Wang, J. R.
1989-01-01
The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.
Temporal rainfall estimation using input data reduction and model inversion
Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.
2016-12-01
Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a
Comprehensive Information Retrieval and Model Input Sequence (CIRMIS)
Energy Technology Data Exchange (ETDEWEB)
Friedrichs, D.R.
1977-04-01
The Comprehensive Information Retrieval and Model Input Sequence (CIRMIS) was developed to provide the research scientist with man--machine interactive capabilities in a real-time environment, and thereby produce results more quickly and efficiently. The CIRMIS system was originally developed to increase data storage and retrieval capabilities and ground-water model control for the Hanford site. The overall configuration, however, can be used in other areas. The CIRMIS system provides the user with three major functions: retrieval of well-based data, special application for manipulating surface data or background maps, and the manipulation and control of ground-water models. These programs comprise only a portion of the entire CIRMIS system. A complete description of the CIRMIS system is given in this report. 25 figures, 7 tables. (RWR)
SEEPAGE MODEL FOR PA INCLUDING DRIFT COLLAPSE
International Nuclear Information System (INIS)
C. Tsang
2004-01-01
The purpose of this report is to document the predictions and analyses performed using the seepage model for performance assessment (SMPA) for both the Topopah Spring middle nonlithophysal (Tptpmn) and lower lithophysal (Tptpll) lithostratigraphic units at Yucca Mountain, Nevada. Look-up tables of seepage flow rates into a drift (and their uncertainty) are generated by performing numerical simulations with the seepage model for many combinations of the three most important seepage-relevant parameters: the fracture permeability, the capillary-strength parameter 1/a, and the percolation flux. The percolation flux values chosen take into account flow focusing effects, which are evaluated based on a flow-focusing model. Moreover, multiple realizations of the underlying stochastic permeability field are conducted. Selected sensitivity studies are performed, including the effects of an alternative drift geometry representing a partially collapsed drift from an independent drift-degradation analysis (BSC 2004 [DIRS 166107]). The intended purpose of the seepage model is to provide results of drift-scale seepage rates under a series of parameters and scenarios in support of the Total System Performance Assessment for License Application (TSPA-LA). The SMPA is intended for the evaluation of drift-scale seepage rates under the full range of parameter values for three parameters found to be key (fracture permeability, the van Genuchten 1/a parameter, and percolation flux) and drift degradation shape scenarios in support of the TSPA-LA during the period of compliance for postclosure performance [Technical Work Plan for: Performance Assessment Unsaturated Zone (BSC 2002 [DIRS 160819], Section I-4-2-1)]. The flow-focusing model in the Topopah Spring welded (TSw) unit is intended to provide an estimate of flow focusing factors (FFFs) that (1) bridge the gap between the mountain-scale and drift-scale models, and (2) account for variability in local percolation flux due to
Olkiluoto surface hydrological modelling: Update 2012 including salt transport modelling
International Nuclear Information System (INIS)
Karvonen, T.
2013-11-01
Posiva Oy is responsible for implementing a final disposal program for spent nuclear fuel of its owners Teollisuuden Voima Oyj and Fortum Power and Heat Oy. The spent nuclear fuel is planned to be disposed at a depth of about 400-450 meters in the crystalline bedrock at the Olkiluoto site. Leakages located at or close to spent fuel repository may give rise to the upconing of deep highly saline groundwater and this is a concern with regard to the performance of the tunnel backfill material after the closure of the tunnels. Therefore a salt transport sub-model was added to the Olkiluoto surface hydrological model (SHYD). The other improvements include update of the particle tracking algorithm and possibility to estimate the influence of open drillholes in a case where overpressure in inflatable packers decreases causing a hydraulic short-circuit between hydrogeological zones HZ19 and HZ20 along the drillhole. Four new hydrogeological zones HZ056, HZ146, BFZ100 and HZ039 were added to the model. In addition, zones HZ20A and HZ20B intersect with each other in the new structure model, which influences salinity upconing caused by leakages in shafts. The aim of the modelling of long-term influence of ONKALO, shafts and repository tunnels provide computational results that can be used to suggest limits for allowed leakages. The model input data included all the existing leakages into ONKALO (35-38 l/min) and shafts in the present day conditions. The influence of shafts was computed using eight different values for total shaft leakage: 5, 11, 20, 30, 40, 50, 60 and 70 l/min. The selection of the leakage criteria for shafts was influenced by the fact that upconing of saline water increases TDS-values close to the repository areas although HZ20B does not intersect any deposition tunnels. The total limit for all leakages was suggested to be 120 l/min. The limit for HZ20 zones was proposed to be 40 l/min: about 5 l/min the present day leakages to access tunnel, 25 l/min from
Measurement of Laser Weld Temperatures for 3D Model Input
Energy Technology Data Exchange (ETDEWEB)
Dagel, Daryl [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grossetete, Grant [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maccallum, Danny O. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-10-01
Laser welding is a key joining process used extensively in the manufacture and assembly of critical components for several weapons systems. Sandia National Laboratories advances the understanding of the laser welding process through coupled experimentation and modeling. This report summarizes the experimental portion of the research program, which focused on measuring temperatures and thermal history of laser welds on steel plates. To increase confidence in measurement accuracy, researchers utilized multiple complementary techniques to acquire temperatures during laser welding. This data serves as input to and validation of 3D laser welding models aimed at predicting microstructure and the formation of defects and their impact on weld-joint reliability, a crucial step in rapid prototyping of weapons components.
The definition of input parameters for modelling of energetic subsystems
Directory of Open Access Journals (Sweden)
Ptacek M.
2013-06-01
Full Text Available This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
The definition of input parameters for modelling of energetic subsystems
Ptacek, M.
2013-06-01
This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
International Nuclear Information System (INIS)
Stripling, H.F.; McClarren, R.G.; Kuranz, C.C.; Grosskopf, M.J.; Rutter, E.; Torralva, B.R.
2011-01-01
We present a method for calibrating the uncertain inputs to a computer model using available experimental data. The goal of the procedure is to produce posterior distributions of the uncertain inputs such that when samples from the posteriors are used as inputs to future model runs, the model is more likely to replicate (or predict) the experimental response. The calibration is performed by sampling the space of the uncertain inputs, using the computer model (or, more likely, an emulator for the computer model) to assign weights to the samples, and applying the weights to produce the posterior distributions and generate predictions of new experiments within confidence bounds. The method is similar to the Markov chain Monte Carlo (MCMC) calibration methods with independent sampling with the exception that we generate samples beforehand and replace the candidate acceptance routine with a weighting scheme. We apply our method to the calibration of a Hyades 2D model of laser energy deposition in beryllium. We employ a Bayesian Multivariate Adaptive Regression Splines (BMARS) emulator as a surrogate for Hyades 2D. We treat a range of uncertainties in our system, including uncertainties in the experimental inputs, experimental measurement error, and systematic experimental timing errors. The results of the calibration are posterior distributions that both agree with intuition and improve the accuracy and decrease the uncertainty in experimental predictions. (author)
Phylogenetic mixtures and linear invariants for equal input models.
Casanellas, Marta; Steel, Mike
2017-04-01
The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).
Development of the MARS input model for Kori nuclear units 1 transient analyzer
International Nuclear Information System (INIS)
Hwang, M.; Kim, K. D.; Lee, S. W.; Lee, Y. J.; Lee, W. J.; Chung, B. D.; Jeong, J. J.
2004-11-01
KAERI has been developing the 'NSSS transient analyzer' based on best-estimate codes for Kori Nuclear Units 1 plants. The MARS and RETRAN codes have been used as the best-estimate codes for the NSSS transient analyzer. Among these codes, the MARS code is adopted for realistic analysis of small- and large-break loss-of-coolant accidents, of which break size is greater than 2 inch diameter. So it is necessary to develop the MARS input model for Kori Nuclear Units 1 plants. This report includes the input model (hydrodynamic component and heat structure models) requirements and the calculation note for the MARS input data generation for Kori Nuclear Units 1 plant analyzer (see the Appendix). In order to confirm the validity of the input data, we performed the calculations for a steady state at 100 % power operation condition and a double-ended cold leg break LOCA. The results of the steady-state calculation agree well with the design data. The results of the LOCA calculation seem to be reasonable and consistent with those of other best-estimate calculations. Therefore, the MARS input data can be used as a base input deck for the MARS transient analyzer for Kori Nuclear Units 1
Grand unified models including extra Z bosons
International Nuclear Information System (INIS)
Li Tiezhong
1989-01-01
The grand unified theories (GUT) of the simple Lie groups including extra Z bosons are discussed. Under authors's hypothesis there are only SU 5+m SO 6+4n and E 6 groups. The general discussion of SU 5+m is given, then the SU 6 and SU 7 are considered. In SU 6 the 15+6 * +6 * fermion representations are used, which are not same as others in fermion content, Yukawa coupling and broken scales. A conception of clans of particles, which are not families, is suggested. These clans consist of extra Z bosons and the corresponding fermions of the scale. The all of fermions in the clans are down quarks except for the standard model which consists of Z bosons and 15 fermions, therefore, the spectrum of the hadrons which are composed of these down quarks are different from hadrons at present
Metocean input data for drift models applications: Loustic study
International Nuclear Information System (INIS)
Michon, P.; Bossart, C.; Cabioc'h, M.
1995-01-01
Real-time monitoring and crisis management of oil slicks or floating structures displacement require a good knowledge of local winds, waves and currents used as input data for operational drift models. Fortunately, thanks to world-wide and all-weather coverage, satellite measurements have recently enabled the introduction of new methods for the remote sensing of the marine environment. Within a French joint industry project, a procedure has been developed using basically satellite measurements combined to metocean models in order to provide marine operators' drift models with reliable wind, wave and current analyses and short term forecasts. Particularly, a model now allows the calculation of the drift current, under the joint action of wind and sea-state, thus radically improving the classical laws. This global procedure either directly uses satellite wind and waves measurements (if available on the study area) or indirectly, as calibration of metocean models results which are brought to the oil slick or floating structure location. The operational use of this procedure is reported here with an example of floating structure drift offshore from the Brittany coasts
Input modeling with phase-type distributions and Markov models theory and applications
Buchholz, Peter; Felko, Iryna
2014-01-01
Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in the area. Due to progress made in recent years with respect to new algorithms to generate PH distributions and Markovian arrival processes from measured data, the models outlined are useful alternatives to other distributions or stochastic processes used for input modeling. Graduate students and researchers in applied probability, operations research and computer science along with practitioners using simulation or analytical models for performance analysis and capacity planning will find the unified notation and up-to-date results presented useful. Input modeling is the key step in model based system analysis to adequately describe the load of a system using stochastic models. The goal of input modeling is to find a stochastic model to describe a sequence of measurements from a real system...
International Nuclear Information System (INIS)
Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao
2017-01-01
Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction. (paper)
Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao
2017-03-01
Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction.
A Markovian model of evolving world input-output network.
Directory of Open Access Journals (Sweden)
Vahid Moosavi
Full Text Available The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.
A Markovian model of evolving world input-output network.
Moosavi, Vahid; Isacchini, Giulio
2017-01-01
The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.
Keesman, K.J.; Walter, E.
2014-01-01
The paper presents a methodology for an optimal input design for model discrimination. To allow analytical solutions, the method, using Pontryagin’s maximum principle, is developed for non-linear single-state systems that are affine in their joint input. The method is demonstrated on a fed-batch
An Integrated Biochemistry Laboratory, Including Molecular Modeling
Hall, Adele J. Wolfson Mona L.; Branham, Thomas R.
1996-11-01
) experience with methods of protein purification; (iii) incorporation of appropriate controls into experiments; (iv) use of basic statistics in data analysis; (v) writing papers and grant proposals in accepted scientific style; (vi) peer review; (vii) oral presentation of results and proposals; and (viii) introduction to molecular modeling. Figure 1 illustrates the modular nature of the lab curriculum. Elements from each of the exercises can be separated and treated as stand-alone exercises, or combined into short or long projects. We have been able to offer the opportunity to use sophisticated molecular modeling in the final module through funding from an NSF-ILI grant. However, many of the benefits of the research proposal can be achieved with other computer programs, or even by literature survey alone. Figure 1.Design of project-based biochemistry laboratory. Modules (projects, or portions of projects) are indicated as boxes. Each of these can be treated independently, or used as part of a larger project. Solid lines indicate some suggested paths from one module to the next. The skills and knowledge required for protein purification and design are developed in three units: (i) an introduction to critical assays needed to monitor degree of purification, including an evaluation of assay parameters; (ii) partial purification by ion-exchange techniques; and (iii) preparation of a grant proposal on protein design by mutagenesis. Brief descriptions of each of these units follow, with experimental details of each project at the end of this paper. Assays for Lysozyme Activity and Protein Concentration (4 weeks) The assays mastered during the first unit are a necessary tool for determining the purity of the enzyme during the second unit on purification by ion exchange. These assays allow an introduction to the concept of specific activity (units of enzyme activity per milligram of total protein) as a measure of purity. In this first sequence, students learn a turbidimetric assay
Regulation of Wnt signaling by nociceptive input in animal models
Directory of Open Access Journals (Sweden)
Shi Yuqiang
2012-06-01
Full Text Available Abstract Background Central sensitization-associated synaptic plasticity in the spinal cord dorsal horn (SCDH critically contributes to the development of chronic pain, but understanding of the underlying molecular pathways is still incomplete. Emerging evidence suggests that Wnt signaling plays a crucial role in regulation of synaptic plasticity. Little is known about the potential function of the Wnt signaling cascades in chronic pain development. Results Fluorescent immunostaining results indicate that β-catenin, an essential protein in the canonical Wnt signaling pathway, is expressed in the superficial layers of the mouse SCDH with enrichment at synapses in lamina II. In addition, Wnt3a, a prototypic Wnt ligand that activates the canonical pathway, is also enriched in the superficial layers. Immunoblotting analysis indicates that both Wnt3a a β-catenin are up-regulated in the SCDH of various mouse pain models created by hind-paw injection of capsaicin, intrathecal (i.t. injection of HIV-gp120 protein or spinal nerve ligation (SNL. Furthermore, Wnt5a, a prototypic Wnt ligand for non-canonical pathways, and its receptor Ror2 are also up-regulated in the SCDH of these models. Conclusion Our results suggest that Wnt signaling pathways are regulated by nociceptive input. The activation of Wnt signaling may regulate the expression of spinal central sensitization during the development of acute and chronic pain.
Development of an Input Model to MELCOR 1.8.5 for the Oskarshamn 3 BWR
Energy Technology Data Exchange (ETDEWEB)
Nilsson, Lars [Lentek, Nykoeping (Sweden)
2006-05-15
.8.6 code, but its models are incorporated in the COR package. Two demonstration runs with the NONBH version were carried out, a total loss of power case and a case simulating a large steam line LOCA. The results are briefly presented and discussed in the report. Complete lists of the input files can be found in the appendices. However, the appendices are not included in the report for disclosure reasons.
Enhanced battery model including temperature effects
Rosca, B.; Wilkins, S.
2013-01-01
Within electric and hybrid vehicles, batteries are used to provide/buffer the energy required for driving. However, battery performance varies throughout the temperature range specific to automotive applications, and as such, models that describe this behaviour are required. This paper presents a
Human upright posture control models based on multisensory inputs; in fast and slow dynamics.
Chiba, Ryosuke; Takakusaki, Kaoru; Ota, Jun; Yozu, Arito; Haga, Nobuhiko
2016-03-01
Posture control to maintain an upright stance is one of the most important and basic requirements in the daily life of humans. The sensory inputs involved in posture control include visual and vestibular inputs, as well as proprioceptive and tactile somatosensory inputs. These multisensory inputs are integrated to represent the body state (body schema); this is then utilized in the brain to generate the motion. Changes in the multisensory inputs result in postural alterations (fast dynamics), as well as long-term alterations in multisensory integration and posture control itself (slow dynamics). In this review, we discuss the fast and slow dynamics, with a focus on multisensory integration including an introduction of our study to investigate "internal force control" with multisensory integration-evoked posture alteration. We found that the study of the slow dynamics is lagging compared to that of fast dynamics, such that our understanding of long-term alterations is insufficient to reveal the underlying mechanisms and to propose suitable models. Additional studies investigating slow dynamics are required to expand our knowledge of this area, which would support the physical training and rehabilitation of elderly and impaired persons. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
The stability of input structures in a supply-driven input-output model: A regional analysis
Energy Technology Data Exchange (ETDEWEB)
Allison, T.
1994-06-01
Disruptions in the supply of strategic resources or other crucial factor inputs often present significant problems for planners and policymakers. The problem may be particularly significant at the regional level where higher levels of product specialization mean supply restrictions are more likely to affect leading regional industries. To maintain economic stability in the event of a supply restriction, regional planners may therefore need to evaluate the importance of market versus non-market systems for allocating the remaining supply of the disrupted resource to the region`s leading consuming industries. This paper reports on research that has attempted to show that large short term changes on the supply side do not lead to substantial changes in input coefficients and do not therefore mean the abandonment of the concept of the production function as has been suggested (Oosterhaven, 1988). The supply-driven model was tested for six sectors of the economy of Washington State and found to yield new input coefficients whose values were in most cases close approximations of their original values, even with substantial changes in supply. Average coefficient changes from a 50% output reduction in these six sectors were in the vast majority of cases (297 from a total of 315) less than +2.0% of their original values, excluding coefficient changes for the restricted input. Given these small changes, the most important issue for the validity of the supply-driven input-output model may therefore be the empirical question of the extent to which these coefficient changes are acceptable as being within the limits of approximation.
Energy Technology Data Exchange (ETDEWEB)
Woods, Jason D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Winkler, Jonathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2018-01-31
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to the interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.
Design, Fabrication, and Modeling of a Novel Dual-Axis Control Input PZT Gyroscope
Directory of Open Access Journals (Sweden)
Cheng-Yang Chang
2017-10-01
Full Text Available Conventional gyroscopes are equipped with a single-axis control input, limiting their performance. Although researchers have proposed control algorithms with dual-axis control inputs to improve gyroscope performance, most have verified the control algorithms through numerical simulations because they lacked practical devices with dual-axis control inputs. The aim of this study was to design a piezoelectric gyroscope equipped with a dual-axis control input so that researchers may experimentally verify those control algorithms in future. Designing a piezoelectric gyroscope with a dual-axis control input is more difficult than designing a conventional gyroscope because the control input must be effective over a broad frequency range to compensate for imperfections, and the multiple mode shapes in flexural deformations complicate the relation between flexural deformation and the proof mass position. This study solved these problems by using a lead zirconate titanate (PZT material, introducing additional electrodes for shielding, developing an optimal electrode pattern, and performing calibrations of undesired couplings. The results indicated that the fabricated device could be operated at 5.5±1 kHz to perform dual-axis actuations and position measurements. The calibration of the fabricated device was completed by system identifications of a new dynamic model including gyroscopic motions, electromechanical coupling, mechanical coupling, electrostatic coupling, and capacitive output impedance. Finally, without the assistance of control algorithms, the “open loop sensitivity” of the fabricated gyroscope was 1.82 μV/deg/s with a nonlinearity of 9.5% full-scale output. This sensitivity is comparable with those of other PZT gyroscopes with single-axis control inputs.
Design, Fabrication, and Modeling of a Novel Dual-Axis Control Input PZT Gyroscope.
Chang, Cheng-Yang; Chen, Tsung-Lin
2017-10-31
Conventional gyroscopes are equipped with a single-axis control input, limiting their performance. Although researchers have proposed control algorithms with dual-axis control inputs to improve gyroscope performance, most have verified the control algorithms through numerical simulations because they lacked practical devices with dual-axis control inputs. The aim of this study was to design a piezoelectric gyroscope equipped with a dual-axis control input so that researchers may experimentally verify those control algorithms in future. Designing a piezoelectric gyroscope with a dual-axis control input is more difficult than designing a conventional gyroscope because the control input must be effective over a broad frequency range to compensate for imperfections, and the multiple mode shapes in flexural deformations complicate the relation between flexural deformation and the proof mass position. This study solved these problems by using a lead zirconate titanate (PZT) material, introducing additional electrodes for shielding, developing an optimal electrode pattern, and performing calibrations of undesired couplings. The results indicated that the fabricated device could be operated at 5.5±1 kHz to perform dual-axis actuations and position measurements. The calibration of the fabricated device was completed by system identifications of a new dynamic model including gyroscopic motions, electromechanical coupling, mechanical coupling, electrostatic coupling, and capacitive output impedance. Finally, without the assistance of control algorithms, the "open loop sensitivity" of the fabricated gyroscope was 1.82 μV/deg/s with a nonlinearity of 9.5% full-scale output. This sensitivity is comparable with those of other PZT gyroscopes with single-axis control inputs.
Development of the MARS input model for Ulchin 1/2 transient analyzer
International Nuclear Information System (INIS)
Jeong, J. J.; Kim, K. D.; Lee, S. W.; Lee, Y. J.; Chung, B. D.; Hwang, M.
2003-03-01
KAERI has been developing the NSSS transient analyzer based on best-estimate codes for Ulchin 1/2 plants. The MARS and RETRAN code are used as the best-estimate codes for the NSSS transient analyzer. Among the two codes, the MARS code is to be used for realistic analysis of small- and large-break loss-of-coolant accidents, of which break size is greater than 2 inch diameter. This report includes the input model requirements and the calculation note for the Ulchin 1/2 MARS input data generation (see the Appendix). In order to confirm the validity of the input data, we performed the calculations for a steady state at 100 % power operation condition and a double-ended cold leg break LOCA. The results of the steady-state calculation agree well with the design data. The results of the LOCA calculation seem to be reasonable and consistent with those of other best-estimate calculations. Therefore, the MARS input data can be used as a base input deck for the MARS transient analyzer for Ulchin 1/2
Development of the MARS input model for Ulchin 3/4 transient analyzer
International Nuclear Information System (INIS)
Jeong, J. J.; Kim, K. D.; Lee, S. W.; Lee, Y. J.; Lee, W. J.; Chung, B. D.; Hwang, M. G.
2003-12-01
KAERI has been developing the NSSS transient analyzer based on best-estimate codes.The MARS and RETRAN code are adopted as the best-estimate codes for the NSSS transient analyzer. Among these two codes, the MARS code is to be used for realistic analysis of small- and large-break loss-of-coolant accidents, of which break size is greater than 2 inch diameter. This report includes the MARS input model requirements and the calculation note for the MARS input data generation (see the Appendix) for Ulchin 3/4 plant analyzer. In order to confirm the validity of the input data, we performed the calculations for a steady state at 100 % power operation condition and a double-ended cold leg break LOCA. The results of the steady-state calculation agree well with the design data. The results of the LOCA calculation seem to be reasonable and consistent with those of other best-estimate calculations. Therefore, the MARS input data can be used as a base input deck for the MARS transient analyzer for Ulchin 3/4
Including spatial data in nutrient balance modelling on dairy farms
van Leeuwen, Maricke; van Middelaar, Corina; Stoof, Cathelijne; Oenema, Jouke; Stoorvogel, Jetse; de Boer, Imke
2017-04-01
The Annual Nutrient Cycle Assessment (ANCA) calculates the nitrogen (N) and phosphorus (P) balance at a dairy farm, while taking into account the subsequent nutrient cycles of the herd, manure, soil and crop components. Since January 2016, Dutch dairy farmers are required to use ANCA in order to increase understanding of nutrient flows and to minimize nutrient losses to the environment. A nutrient balance calculates the difference between nutrient inputs and outputs. Nutrients enter the farm via purchased feed, fertilizers, deposition and fixation by legumes (nitrogen), and leave the farm via milk, livestock, manure, and roughages. A positive balance indicates to which extent N and/or P are lost to the environment via gaseous emissions (N), leaching, run-off and accumulation in soil. A negative balance indicates that N and/or P are depleted from soil. ANCA was designed to calculate average nutrient flows on farm level (for the herd, manure, soil and crop components). ANCA was not designed to perform calculations of nutrient flows at the field level, as it uses averaged nutrient inputs and outputs across all fields, and it does not include field specific soil characteristics. Land management decisions, however, such as the level of N and P application, are typically taken at the field level given the specific crop and soil characteristics. Therefore the information that ANCA provides is likely not sufficient to support farmers' decisions on land management to minimize nutrient losses to the environment. This is particularly a problem when land management and soils vary between fields. For an accurate estimate of nutrient flows in a given farming system that can be used to optimize land management, the spatial scale of nutrient inputs and outputs (and thus the effect of land management and soil variation) could be essential. Our aim was to determine the effect of the spatial scale of nutrient inputs and outputs on modelled nutrient flows and nutrient use efficiencies
CONSTRUCTION OF A DYNAMIC INPUT-OUTPUT MODEL WITH A HUMAN CAPITAL BLOCK
Directory of Open Access Journals (Sweden)
Baranov A. O.
2017-03-01
Full Text Available The accumulation of human capital is an important factor of economic growth. It seems to be useful to include «human capital» as a factor of a macroeconomic model, as it helps to take into account the quality differentiation of the workforce. Most of the models usually distinguish labor force by the levels of education, while some of the factors remain unaccounted. Among them are health status and culture development level, which influence productivity level as well as gross product reproduction. Inclusion of the human capital block to the interindustry model can help to make it more reliable for economic development forecasting. The article presents a mathematical description of the extended dynamic input-output model (DIOM with a human capital block. The extended DIOM is based on the Input-Output Model from The KAMIN system (the System of Integrated Analyses of Interindustrial Information developed at the Institute of Economics and Industrial Engineering of the Siberian Branch of the Academy of Sciences of the Russian Federation and at the Novosibirsk State University. The extended input-output model can be used to analyze and forecast development of Russian economy.
Róg, Tomasz; Orłowski, Adam; Llorente, Alicia; Skotland, Tore; Sylvänne, Tuulia; Kauhanen, Dimple; Ekroos, Kim; Sandvig, Kirsten; Vattulainen, Ilpo
2016-06-01
In this Data in Brief article we provide a data package of GROMACS input files for atomistic molecular dynamics simulations of multicomponent, asymmetric lipid bilayers using the OPLS-AA force field. These data include 14 model bilayers composed of 8 different lipid molecules. The lipids present in these models are: cholesterol (CHOL), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylethanolamine (POPE), 1-stearoyl-2-oleoyl-sn-glycero-3-phosphatidyl-ethanolamine (SOPE), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS), 1-stearoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (SOPS), N-palmitoyl-D-erythro-sphingosyl-phosphatidylcholine (SM16), and N-lignoceroyl-D-erythro-sphingosyl-phosphatidylcholine (SM24). The bilayers׳ compositions are based on lipidomic studies of PC-3 prostate cancer cells and exosomes discussed in Llorente et al. (2013) [1], showing an increase in the section of long-tail lipid species (SOPS, SOPE, and SM24) in the exosomes. Former knowledge about lipid asymmetry in cell membranes was accounted for in the models, meaning that the model of the inner leaflet is composed of a mixture of PC, PS, PE, and cholesterol, while the extracellular leaflet is composed of SM, PC and cholesterol discussed in Van Meer et al. (2008) [2]. The provided data include lipids׳ topologies, equilibrated structures of asymmetric bilayers, all force field parameters, and input files with parameters describing simulation conditions (md.mdp). The data is associated with the research article "Interdigitation of Long-Chain Sphingomyelin Induces Coupling of Membrane Leaflets in a Cholesterol Dependent Manner" (Róg et al., 2016) [3].
Input parameters and scenarios, including economic inputs
DEFF Research Database (Denmark)
Boklund, Anette; Hisham Beshara Halasa, Tariq
2012-01-01
stand still was initiated. Furthermore, infected herds were depopulated and a 3 km detection zone and a 10 km surveillance zone were implemented around all infected herds. Within the protections zones, all herds were simulated to be clinically surveyed twice, first within 7 days after implementing...... the zone, and second 21 days later. Sheep within the zone were simulated to be tested. Within the surveillance zone, all herds were simulated to be clinically surveyed within 7 days, and sheep within the zone were simulated to be tested within 7 days and again before lifting the zone. Herds, which had...... in ringzones of varying radii around infected herds. In alternative scenarios, we tested the effect of depopulating in zones of 500, 1000 and 1500 meters from infected herds. Depopulation was started on day 14 after detection of the first herd, or after detecting 10, 20, 30 or 50 infected herds. In some...
High Temperature Test Facility Preliminary RELAP5-3D Input Model Description
Energy Technology Data Exchange (ETDEWEB)
Bayless, Paul David [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-12-01
A RELAP5-3D input model is being developed for the High Temperature Test Facility at Oregon State University. The current model is described in detail. Further refinements will be made to the model as final as-built drawings are released and when system characterization data are available for benchmarking the input model.
GEN-IV Benchmarking of Triso Fuel Performance Models under accident conditions modeling input data
Energy Technology Data Exchange (ETDEWEB)
Collin, Blaise Paul [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2016-09-01
This document presents the benchmark plan for the calculation of particle fuel performance on safety testing experiments that are representative of operational accidental transients. The benchmark is dedicated to the modeling of fission product release under accident conditions by fuel performance codes from around the world, and the subsequent comparison to post-irradiation experiment (PIE) data from the modeled heating tests. The accident condition benchmark is divided into three parts: • The modeling of a simplified benchmark problem to assess potential numerical calculation issues at low fission product release. • The modeling of the AGR-1 and HFR-EU1bis safety testing experiments. • The comparison of the AGR-1 and HFR-EU1bis modeling results with PIE data. The simplified benchmark case, thereafter named NCC (Numerical Calculation Case), is derived from “Case 5” of the International Atomic Energy Agency (IAEA) Coordinated Research Program (CRP) on coated particle fuel technology [IAEA 2012]. It is included so participants can evaluate their codes at low fission product release. “Case 5” of the IAEA CRP-6 showed large code-to-code discrepancies in the release of fission products, which were attributed to “effects of the numerical calculation method rather than the physical model” [IAEA 2012]. The NCC is therefore intended to check if these numerical effects subsist. The first two steps imply the involvement of the benchmark participants with a modeling effort following the guidelines and recommendations provided by this document. The third step involves the collection of the modeling results by Idaho National Laboratory (INL) and the comparison of these results with the available PIE data. The objective of this document is to provide all necessary input data to model the benchmark cases, and to give some methodology guidelines and recommendations in order to make all results suitable for comparison with each other. The participants should read
Little Higgs model limits from LHC - Input for Snowmass 2013
International Nuclear Information System (INIS)
Reuter, Juergen; Tonini, Marco; Vries, Maikel de
2013-07-01
The status of the most prominent model implementations of the Little Higgs paradigm, the Littlest Higgs with and without discrete T parity as well as the Simplest Little Higgs are reviewed. For this, we are taking into account a fit to 21 electroweak precision observables from LEP, SLC, Tevatron together with the full 25 fb -1 of Higgs data reported from ATLAS and CMS at Moriond 2013. We also - focusing on the Littlest Higgs with T parity - include an outlook on corresponding direct searches at the 8 TeV LHC and their competitiveness with the EW and Higgs data regarding their exclusion potential. This contribution to the Snowmass procedure serves as a guideline which regions in parameter space of Little Higgs models are still compatible for the upcoming LHC runs and future experiments at the energy frontier. For this we propose two different benchmark scenarios for the Littlest Higgs with T parity, one with heavy mirror quarks, one with light ones.
Lakemond, Nicolette; Rosell, David T.
2011-01-01
There are many studies on supplier collaborations in NPD. However, there is not much written about what suppliers actually contribute to innovation. Based on a literature review focusing on 80 articles we develop a conceptual framework categorizing different supplier inputs to innovation. This model is formulated by characterizing supplier inputs related to the component level and architectural level, and inputs that are incremental or radical in nature. On a component level, supplier inputs ...
Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions
Jung, J. Y.; Niemann, J. D.; Greimann, B. P.
2016-12-01
Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.
Gaussian-input Gaussian mixture model for representing density maps and atomic models.
Kawabata, Takeshi
2018-03-06
A new Gaussian mixture model (GMM) has been developed for better representations of both atomic models and electron microscopy 3D density maps. The standard GMM algorithm employs an EM algorithm to determine the parameters. It accepted a set of 3D points with weights, corresponding to voxel or atomic centers. Although the standard algorithm worked reasonably well; however, it had three problems. First, it ignored the size (voxel width or atomic radius) of the input, and thus it could lead to a GMM with a smaller spread than the input. Second, the algorithm had a singularity problem, as it sometimes stopped the iterative procedure due to a Gaussian function with almost zero variance. Third, a map with a large number of voxels required a long computation time for conversion to a GMM. To solve these problems, we have introduced a Gaussian-input GMM algorithm, which considers the input atoms or voxels as a set of Gaussian functions. The standard EM algorithm of GMM was extended to optimize the new GMM. The new GMM has identical radius of gyration to the input, and does not suddenly stop due to the singularity problem. For fast computation, we have introduced a down-sampled Gaussian functions (DSG) by merging neighboring voxels into an anisotropic Gaussian function. It provides a GMM with thousands of Gaussian functions in a short computation time. We also have introduced a DSG-input GMM: the Gaussian-input GMM with the DSG as the input. This new algorithm is much faster than the standard algorithm. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
A New Ensemble of Perturbed-Input-Parameter Simulations by the Community Atmosphere Model
Energy Technology Data Exchange (ETDEWEB)
Covey, C; Brandon, S; Bremer, P T; Domyancis, D; Garaizar, X; Johannesson, G; Klein, R; Klein, S A; Lucas, D D; Tannahill, J; Zhang, Y
2011-10-27
Uncertainty quantification (UQ) is a fundamental challenge in the numerical simulation of Earth's weather and climate, and other complex systems. It entails much more than attaching defensible error bars to predictions: in particular it includes assessing low-probability but high-consequence events. To achieve these goals with models containing a large number of uncertain input parameters, structural uncertainties, etc., raw computational power is needed. An automated, self-adapting search of the possible model configurations is also useful. Our UQ initiative at the Lawrence Livermore National Laboratory has produced the most extensive set to date of simulations from the US Community Atmosphere Model. We are examining output from about 3,000 twelve-year climate simulations generated with a specialized UQ software framework, and assessing the model's accuracy as a function of 21 to 28 uncertain input parameter values. Most of the input parameters we vary are related to the boundary layer, clouds, and other sub-grid scale processes. Our simulations prescribe surface boundary conditions (sea surface temperatures and sea ice amounts) to match recent observations. Fully searching this 21+ dimensional space is impossible, but sensitivity and ranking algorithms can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination. Bayesian statistical constraints, employing a variety of climate observations as metrics, also seem promising. Observational constraints will be important in the next step of our project, which will compute sea surface temperatures and sea ice interactively, and will study climate change due to increasing atmospheric carbon dioxide.
Baumann-Stanzer, K.; Stenzel, S.
2009-04-01
Several air dispersion models are available for prediction and simulation of the hazard areas associated with accidental releases of toxic gases. The most model packages (commercial or free of charge) include a chemical database, an intuitive graphical user interface (GUI) and automated graphical output for effective presentation of results. The models are designed especially for analyzing different accidental toxic release scenarios ("worst-case scenarios"), preparing emergency response plans and optimal countermeasures as well as for real-time risk assessment and management. Uncertainties in the meteorological input together with incorrect estimates of the source play a critical role for the model results. The research project RETOMOD (reference scenarios calculations for toxic gas releases - model systems and their utility for the fire brigade) was conducted by the Central Institute for Meteorology and Geodynamics (ZAMG) in cooperation with the Vienna fire brigade, OMV Refining & Marketing GmbH and Synex Ries & Greßlehner GmbH. RETOMOD was funded by the KIRAS safety research program at the Austrian Ministry of Transport, Innovation and Technology (www.kiras.at). The main tasks of this project were 1. Sensitivity study and optimization of the meteorological input for modeling of the hazard areas (human exposure) during the accidental toxic releases. 2. Comparison of several model packages (based on reference scenarios) in order to estimate the utility for the fire brigades. This presentation gives a short introduction to the project and presents the results of task 1 (meteorological input). The results of task 2 are presented by Stenzel and Baumann-Stanzer in this session. For the aim of this project, the observation-based analysis and forecasting system INCA, developed in the Central Institute for Meteorology and Geodynamics (ZAMG) was used. INCA (Integrated Nowcasting through Comprehensive Analysis) data were calculated with 1 km horizontal resolution and
The MARINA model (Model to Assess River Inputs of Nutrients to seAs)
Strokal, Maryna; Kroeze, Carolien; Wang, Mengru; Bai, Zhaohai; Ma, Lin
2016-01-01
Chinese agriculture has been developing fast towards industrial food production systems that discharge nutrient-rich wastewater into rivers. As a result, nutrient export by rivers has been increasing, resulting in coastal water pollution. We developed a Model to Assess River Inputs of Nutrients
Stream Heat Budget Modeling of Groundwater Inputs: Model Development and Validation
Glose, A.; Lautz, L. K.
2012-12-01
Models of physical processes in fluvial systems are useful for improving understanding of hydrologic systems and for predicting future conditions. Process-based models of fluid flow and heat transport in fluvial systems can be used to quantify unknown spatial and temporal patterns of hydrologic fluxes, such as groundwater discharge, and to predict system response to future change. In this study, a stream heat budget model was developed and calibrated to observed stream water temperature data for Meadowbrook Creek in Syracuse, NY. The one-dimensional (longitudinal), transient stream temperature model is programmed in Matlab and solves the equations for heat and fluid transport using a Crank-Nicholson finite difference scheme. The model considers four meteorologically driven heat fluxes: shortwave solar radiation, longwave radiation, latent heat flux, and sensible heat flux. Streambed conduction is also considered. Input data for the model were collected from June 13-18, 2012 over a 500 m reach of Meadowbrook Creek, a first order urban stream that drains a retention pond in the city of Syracuse, NY. Stream temperature data were recorded every 20 m longitudinally in the stream at 5-minute intervals using iButtons (model DS1922L, accuracy of ±0.5°C, resolution of 0.0625°C). Meteorological data, including air temperature, solar radiation, relative humidity, and wind speed, were recorded at 5-minute intervals using an on-site weather station. Groundwater temperature was measured in wells adjacent to the stream. Stream dimensions, bed temperatures, and type of bed sediments were also collected. A constant rate tracer injection of Rhodamine WT was used to quantify groundwater inputs every 10 m independently to validate model results. Stream temperatures fluctuated diurnally by ~3-5 °C during the observation period with temperatures peaking around 2 pm and cooling overnight, reaching a minimum between 6 and 7 am. Spatially, the stream shows a cooling trend along the
Combining predictions from linear models when training and test inputs differ
T. van Ommen (Thijs); N.L. Zhang (Nevin); J. Tian (Jin)
2014-01-01
textabstractMethods for combining predictions from different models in a supervised learning setting must somehow estimate/predict the quality of a model's predictions at unknown future inputs. Many of these methods (often implicitly) make the assumption that the test inputs are identical to the
Myers, Jerry G.; Young, M.; Goodenow, Debra A.; Keenan, A.; Walton, M.; Boley, L.
2015-01-01
Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.
Motivation Monitoring and Assessment Extension for Input-Process-Outcome Game Model
Ghergulescu, Ioana; Muntean, Cristina Hava
2014-01-01
This article proposes a Motivation Assessment-oriented Input-Process-Outcome Game Model (MotIPO), which extends the Input-Process-Outcome game model with game-centred and player-centred motivation assessments performed right from the beginning of the game-play. A feasibility case-study involving 67 participants playing an educational game and…
The Modulated-Input Modulated-Output Model
National Research Council Canada - National Science Library
Moskowitz, Ira S; Kang, Myong H
1995-01-01
.... The data replication problem in database systems is our motivation. We introduce a new queueing theoretic model, the MIMO model, that incorporates burstiness in the sending side and busy periods in the receiving side...
Modeling and Control of a Dual-Input Isolated Full-Bridge Boost Converter
DEFF Research Database (Denmark)
Zhang, Zhe; Thomsen, Ole Cornelius; Andersen, Michael A. E.
2012-01-01
In this paper, a steady-state model, a large-signal (LS) model and an ac small-signal (SS) model for a recently proposed dual-input transformer-isolated boost converter are derived respectively by the switching flow-graph (SFG) nonlinear modeling technique. Based upon the converter’s model, the c....... The measured experimental results match the simulation results fairly well on both input source dynamic and step load transient responses....
The MARINA model (Model to Assess River Inputs of Nutrients to seAs)
Strokal, Maryna; Kroeze, Carolien; Wang, Mengru; Bai, Zhaohai; Ma, Lin
2016-01-01
Chinese agriculture has been developing fast towards industrial food production systems that discharge nutrient-rich wastewater into rivers. As a result, nutrient export by rivers has been increasing, resulting in coastal water pollution. We developed a Model to Assess River Inputs of Nutrients to seAs (MARINA) for China. The MARINA Nutrient Model quantifies river export of nutrients by source at the sub-basin scale as a function of human activities on land. MARINA is a downscaled version for...
Precipitation forecasts and their uncertainty as input into hydrological models
Directory of Open Access Journals (Sweden)
M. Kobold
2005-01-01
Full Text Available Torrential streams and fast runoff are characteristic of most Slovenian rivers and extensive damage is caused almost every year by rainstorms affecting different regions of Slovenia. Rainfall-runoff models which are tools for runoff calculation can be used for flood forecasting. In Slovenia, the lag time between rainfall and runoff is only a few hours and on-line data are used only for now-casting. Predicted precipitation is necessary in flood forecasting some days ahead. The ECMWF (European Centre for Medium-Range Weather Forecasts model gives general forecasts several days ahead while more detailed precipitation data with the ALADIN/SI model are available for two days ahead. Combining the weather forecasts with the information on catchment conditions and a hydrological forecasting model can give advance warning of potential flooding notwithstanding a certain degree of uncertainty in using precipitation forecasts based on meteorological models. Analysis of the sensitivity of the hydrological model to the rainfall error has shown that the deviation in runoff is much larger than the rainfall deviation. Therefore, verification of predicted precipitation for large precipitation events was performed with the ECMWF model. Measured precipitation data were interpolated on a regular grid and compared with the results from the ECMWF model. The deviation in predicted precipitation from interpolated measurements is shown with the model bias resulting from the inability of the model to predict the precipitation correctly and a bias for horizontal resolution of the model and natural variability of precipitation.
Characteristic length scale of input data in distributed models: implications for modeling grid size
Artan, G. A.; Neale, C. M. U.; Tarboton, D. G.
2000-01-01
The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m2 modeling grid size. A modeling grid size of about 10×10 m2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.
Artan, Guleid A.; Neale, C. M. U.; Tarboton, D. G.
2000-01-01
The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m2 modeling grid size. A modeling grid size of about 10×10 m2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.
Influence of input matrix representation on topic modelling performance
CSIR Research Space (South Africa)
De Waal, A
2010-11-01
Full Text Available Topic models explain a collection of documents with a small set of distributions over terms. These distributions over terms define the topics. Topic models ignore the structure of documents and use a bag-of-words approach which relies solely...
Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.
Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin
2015-02-01
To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.
"Updates to Model Algorithms & Inputs for the Biogenic ...
We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observations. This has resulted in improvements in model evaluations of modeled isoprene, NOx, and O3. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Using Crowd Sensed Data as Input to Congestion Model
DEFF Research Database (Denmark)
Lehmann, Anders; Gross, Allan
2016-01-01
Emission of airborne pollutants and climate gasses from the transport sector is a growing problem, both in indus- trialised and developing countries. Planning of urban transport system is essential to minimise the environmental, health and economic impact of congestion in the transport system...... traffic systems, in less than an hour. The model is implemented in an open source database system, for easy interface with GIS resources and crowd sensed transportation data........ To get accurate and timely information on traffic congestion, and by extension information on air pollution, near real time traffic models are needed. We present in this paper an implementation of the Restricted Stochastic User equilibrium model, that is capable to model congestions for very large Urban...
Directory of Open Access Journals (Sweden)
Robert B. Gramacy
2010-02-01
Full Text Available This document describes the new features in version 2.x of the tgp package for R, implementing treed Gaussian process (GP models. The topics covered include methods for dealing with categorical inputs and excluding inputs from the tree or GP part of the model; fully Bayesian sensitivity analysis for inputs/covariates; sequential optimization of black-box functions; and a new Monte Carlo method for inference in multi-modal posterior distributions that combines simulated tempering and importance sampling. These additions extend the functionality of tgp across all models in the hierarchy: from Bayesian linear models, to classification and regression trees (CART, to treed Gaussian processes with jumps to the limiting linear model. It is assumed that the reader is familiar with the baseline functionality of the package, outlined in the first vignette (Gramacy 2007.
Modelling groundwater discharge areas using only digital elevation models as input data
International Nuclear Information System (INIS)
Brydsten, Lars
2006-10-01
Advanced geohydrological models require data on topography, soil distribution in three dimensions, vegetation, land use, bedrock fracture zones. To model present geohydrological conditions, these factors can be gathered with different techniques. If a future geohydrological condition is modelled in an area with positive shore displacement (say 5,000 or 10,000 years), some of these factors can be difficult to measure. This could include the development of wetlands and the filling of lakes. If the goal of the model is to predict distribution of groundwater recharge and discharge areas in the landscape, the most important factor is topography. The question is how much can topography alone explain the distribution of geohydrological objects in the landscape. A simplified description of the distribution of geohydrological objects in the landscape is that groundwater recharge areas occur at local elevation curvatures and discharge occurs in lakes, brooks, and low situated slopes. Areas in-between these make up discharge areas during wet periods and recharge areas during dry periods. A model that could predict this pattern only using topography data needs to be able to predict high ridges and future lakes and brooks. This study uses GIS software with four different functions using digital elevation models as input data, geomorphometrical parameters to predict landscape ridges, basin fill for predicting lakes, flow accumulations for predicting future waterways, and topographical wetness indexes for dividing in-between areas based on degree of wetness. An area between the village of and Forsmarks' Nuclear Power Plant has been used to calibrate the model. The area is within the SKB 10-metre Elevation Model (DEM) and has a high-resolution orienteering map for wetlands. Wetlands are assumed to be groundwater discharge areas. Five hundred points were randomly distributed across the wetlands. These are potential discharge points. Model parameters were chosen with the
Modelling groundwater discharge areas using only digital elevation models as input data
Energy Technology Data Exchange (ETDEWEB)
Brydsten, Lars [Umeaa Univ. (Sweden). Dept. of Biology and Environmental Science
2006-10-15
Advanced geohydrological models require data on topography, soil distribution in three dimensions, vegetation, land use, bedrock fracture zones. To model present geohydrological conditions, these factors can be gathered with different techniques. If a future geohydrological condition is modelled in an area with positive shore displacement (say 5,000 or 10,000 years), some of these factors can be difficult to measure. This could include the development of wetlands and the filling of lakes. If the goal of the model is to predict distribution of groundwater recharge and discharge areas in the landscape, the most important factor is topography. The question is how much can topography alone explain the distribution of geohydrological objects in the landscape. A simplified description of the distribution of geohydrological objects in the landscape is that groundwater recharge areas occur at local elevation curvatures and discharge occurs in lakes, brooks, and low situated slopes. Areas in-between these make up discharge areas during wet periods and recharge areas during dry periods. A model that could predict this pattern only using topography data needs to be able to predict high ridges and future lakes and brooks. This study uses GIS software with four different functions using digital elevation models as input data, geomorphometrical parameters to predict landscape ridges, basin fill for predicting lakes, flow accumulations for predicting future waterways, and topographical wetness indexes for dividing in-between areas based on degree of wetness. An area between the village of and Forsmarks' Nuclear Power Plant has been used to calibrate the model. The area is within the SKB 10-metre Elevation Model (DEM) and has a high-resolution orienteering map for wetlands. Wetlands are assumed to be groundwater discharge areas. Five hundred points were randomly distributed across the wetlands. These are potential discharge points. Model parameters were chosen with the
Input-dependent wave attenuation in a critically-balanced model of cortex.
Directory of Open Access Journals (Sweden)
Xiao-Hu Yan
Full Text Available A number of studies have suggested that many properties of brain activity can be understood in terms of critical systems. However it is still not known how the long-range susceptibilities characteristic of criticality arise in the living brain from its local connectivity structures. Here we prove that a dynamically critically-poised model of cortex acquires an infinitely-long ranged susceptibility in the absence of input. When an input is presented, the susceptibility attenuates exponentially as a function of distance, with an increasing spatial attenuation constant (i.e., decreasing range the larger the input. This is in direct agreement with recent results that show that waves of local field potential activity evoked by single spikes in primary visual cortex of cat and macaque attenuate with a characteristic length that also increases with decreasing contrast of the visual stimulus. A susceptibility that changes spatial range with input strength can be thought to implement an input-dependent spatial integration: when the input is large, no additional evidence is needed in addition to the local input; when the input is weak, evidence needs to be integrated over a larger spatial domain to achieve a decision. Such input-strength-dependent strategies have been demonstrated in visual processing. Our results suggest that input-strength dependent spatial integration may be a natural feature of a critically-balanced cortical network.
Reissner-Mindlin plate model with uncertain input data
Czech Academy of Sciences Publication Activity Database
Hlaváček, Ivan; Chleboun, J.
2014-01-01
Roč. 17, Jun (2014), s. 71-88 ISSN 1468-1218 Institutional support: RVO:67985840 Keywords : Reissner-Mindlin model * orthotropic plate Subject RIV: BA - General Mathematics Impact factor: 2.519, year: 2014 http://www.sciencedirect.com/science/article/pii/S1468121813001077
Determining input values for a simple parametric model to estimate ...
African Journals Online (AJOL)
Estimating soil evaporation (Es) is an important part of modelling vineyard evapotranspiration for irrigation purposes. Furthermore, quantification of possible soil texture and trellis effects is essential. Daily Es from six topsoils packed into lysimeters was measured under grapevines on slanting and vertical trellises, ...
Land Building Models: Uncertainty in and Sensitivity to Input Parameters
2013-08-01
Vicksburg, MS: US Army Engineer Research and Development Center. An electronic copy of this CHETN is available from http://chl.erdc.usace.army.mil/chetn...Nourishment Module, Chapter 8. In Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) Model of Louisiana Coastal Area ( LCA ) Comprehensive
Sumit, M.; Takayama, S.; Linderman, J. J.
2016-01-01
Temporally modulated input mimics physiology. This chemical communication strategy filters the biochemical noise through entrainment and phase-locking. Under laboratory conditions, it also expands the observability space for downstream responses. A combined approach involving microfluidic pulsatile stimulation and mathematical modeling has led to deciphering of hidden/unknown temporal motifs in several mammalian signaling pathways and has provided mechanistic insights, including how these motifs combine to form distinct band-pass filters and govern fate regulation under dynamic microenvironment. This approach can be utilized to understand signaling circuit architectures and to gain mechanistic insights for several other signaling systems. Potential applications include synthetic biology and biotechnology, in developing pharmaceutical interventions, and in developing lab-on-chip models. PMID:27868126
Sumit, M; Takayama, S; Linderman, J J
2017-01-23
Temporally modulated input mimics physiology. This chemical communication strategy filters the biochemical noise through entrainment and phase-locking. Under laboratory conditions, it also expands the observability space for downstream responses. A combined approach involving microfluidic pulsatile stimulation and mathematical modeling has led to deciphering of hidden/unknown temporal motifs in several mammalian signaling pathways and has provided mechanistic insights, including how these motifs combine to form distinct band-pass filters and govern fate regulation under dynamic microenvironment. This approach can be utilized to understand signaling circuit architectures and to gain mechanistic insights for several other signaling systems. Potential applications include synthetic biology and biotechnology, in developing pharmaceutical interventions, and in developing lab-on-chip models.
Scientific and technical advisory committee review of the nutrient inputs to the watershed model
The following is a report by a STAC Review Team concerning the methods and documentation used by the Chesapeake Bay Partnership for evaluation of nutrient inputs to Phase 6 of the Chesapeake Bay Watershed Model. The “STAC Review of the Nutrient Inputs to the Watershed Model” (previously referred to...
Crop growth modelling and crop yield forecasting using satellite derived meteorological inputs
Wit, de A.J.W.; Diepen, van K.
2006-01-01
One of the key challenges for operational crop monitoring and yield forecasting using crop models is to find spatially representative meteorological input data. Currently, weather inputs are often interpolated from low density networks of weather stations or derived from output from coarse (0.5
Mechanistic interpretation of glass reaction: Input to kinetic model development
International Nuclear Information System (INIS)
Bates, J.K.; Ebert, W.L.; Bradley, J.P.; Bourcier, W.L.
1991-05-01
Actinide-doped SRL 165 type glass was reacted in J-13 groundwater at 90 degree C for times up to 278 days. The reaction was characterized by both solution and solid analyses. The glass was seen to react nonstoichiometrically with preferred leaching of alkali metals and boron. High resolution electron microscopy revealed the formation of a complex layer structure which became separated from the underlying glass as the reaction progressed. The formation of the layer and its effect on continued glass reaction are discussed with respect to the current model for glass reaction used in the EQ3/6 computer simulation. It is concluded that the layer formed after 278 days is not protective and may eventually become fractured and generate particulates that may be transported by liquid water. 5 refs., 5 figs. , 3 tabs
Miller, L. D.; Tom, C.; Nualchawee, K.
1977-01-01
A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.
Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City
Directory of Open Access Journals (Sweden)
Priska Arindya Purnama
2017-11-01
Full Text Available The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Yt sequence expected to be effected by an input series (Xt and other inputs in a group called a noise series (Nt. Multi input transfer function model obtained is (b1,s1,r1 (b2,s2,r2 (b3,s3,r3 (b4,s4,r4(pn,qn = (0,0,0 (23,0,0 (1,2,0 (0,0,0 ([5,8],2 and shows that air temperature on t-day affects rainfall on t-day, rainfall on t-day is influenced by air humidity in the previous 23 days, rainfall on t-day is affected by wind speed in the previous day , and rainfall on day t is affected by clouds on day t. The results of rainfall forecasting in Batu City with multi input transfer function model can be said to be accurate, because it produces relatively small RMSE value. The value of RMSE data forecasting training is 7.7921 while forecasting data testing is 4.2184. Multi-input transfer function model is suitable for rainfall in Batu City.
A Water-Withdrawal Input-Output Model of the Indian Economy.
Bogra, Shelly; Bakshi, Bhavik R; Mathur, Ritu
2016-02-02
Managing freshwater allocation for a highly populated and growing economy like India can benefit from knowledge about the effect of economic activities. This study transforms the 2003-2004 economic input-output (IO) table of India into a water withdrawal input-output model to quantify direct and indirect flows. This unique model is based on a comprehensive database compiled from diverse public sources, and estimates direct and indirect water withdrawal of all economic sectors. It distinguishes between green (rainfall), blue (surface and ground), and scarce groundwater. Results indicate that the total direct water withdrawal is nearly 3052 billion cubic meter (BCM) and 96% of this is used in agriculture sectors with the contribution of direct green water being about 1145 BCM, excluding forestry. Apart from 727 BCM direct blue water withdrawal for agricultural, other significant users include "Electricity" with 64 BCM, "Water supply" with 44 BCM and other industrial sectors with nearly 14 BCM. "Construction", "miscellaneous food products"; "Hotels and restaurants"; "Paper, paper products, and newsprint" are other significant indirect withdrawers. The net virtual water import is found to be insignificant compared to direct water used in agriculture nationally, while scarce ground water associated with crops is largely contributed by northern states.
Modeling of heat transfer into a heat pipe for a localized heat input zone
International Nuclear Information System (INIS)
Rosenfeld, J.H.
1987-01-01
A general model is presented for heat transfer into a heat pipe using a localized heat input. Conduction in the wall of the heat pipe and boiling in the interior structure are treated simultaneously. The model is derived from circumferential heat transfer in a cylindrical heat pipe evaporator and for radial heat transfer in a circular disk with boiling from the interior surface. A comparison is made with data for a localized heat input zone. Agreement between the theory and the model is good. This model can be used for design purposes if a boiling correlation is available. The model can be extended to provide improved predictions of heat pipe performance
Pritchard, David; Fowler, Hayley; Forsythe, Nathan; O'Donnell, Greg; Rutter, Nick; Bardossy, Andras
2017-04-01
Snow and glacier melt in the mountainous Upper Indus Basin (UIB) sustain water supplies, irrigation networks, hydropower production and ecosystems in extensive downstream lowlands. Understanding hydrological and cryospheric sensitivities to climatic variability and change in the basin is therefore critical for local, national and regional water resources management. Assessing these sensitivities using numerical modelling is challenging, due to limitations in the quality and quantity of input and evaluation data, as well as uncertainties in model structures and parameters. This study explores how these uncertainties in inputs and process parameterisations affect distributed simulations of ablation in the complex climatic setting of the UIB. The role of model forcing uncertainties is explored using combinations of local observations, remote sensing and reanalysis - including the high resolution High Asia Refined Analysis - to generate multiple realisations of spatiotemporal model input fields. Forcing a range of model structures with these input fields then provides an indication of how different ablation parameterisations respond to uncertainties and perturbations in climatic drivers. Model structures considered include simple, empirical representations of melt processes through to physically based, full energy balance models with multi-physics options for simulating snowpack evolution (including an adapted version of FSM). Analysing model input and structural uncertainties in this way provides insights for methodological choices in climate sensitivity assessments of data-sparse, high mountain catchments. Such assessments are key for supporting water resource management in these catchments, particularly given the potential complications of enhanced warming through elevation effects or, in the case of the UIB, limited understanding of how and why local climate change signals differ from broader patterns.
INPUT DATA OF BURNING WOOD FOR CFD MODELLING USING SMALL-SCALE EXPERIMENTS
Directory of Open Access Journals (Sweden)
Petr Hejtmánek
2017-12-01
Full Text Available The paper presents an option how to acquire simplified input data for modelling of burning wood in CFD programmes. The option lies in combination of data from small- and molecular-scale experiments in order to describe the material as a one-reaction material property. Such virtual material would spread fire, develop the fire according to surrounding environment and it could be extinguished without using complex reaction molecular description. Series of experiments including elemental analysis, thermogravimetric analysis and difference thermal analysis, and combustion analysis were performed. Then the FDS model of burning pine wood in a cone calorimeter was built. In the model where those values were used. The model was validated to HRR (Heat Release Rate from the real cone calorimeter experiment. The results show that for the purpose of CFD modelling the effective heat of combustion, which is one of the basic material property for fire modelling affecting the total intensity of burning, should be used. Using the net heat of combustion in the model leads to higher values of HRR in comparison to the real experiment data. Considering all the results shown in this paper, it was shown that it is possible to simulate burning of wood using the extrapolated data obtained in small-size experiments.
Dynamic hysteresis modeling including skin effect using diffusion equation model
Energy Technology Data Exchange (ETDEWEB)
Hamada, Souad, E-mail: souadhamada@yahoo.fr [LSP-IE: Research Laboratory, Electrical Engineering Department, University of Batna, 05000 Batna (Algeria); Louai, Fatima Zohra, E-mail: fz_louai@yahoo.com [LSP-IE: Research Laboratory, Electrical Engineering Department, University of Batna, 05000 Batna (Algeria); Nait-Said, Nasreddine, E-mail: n_naitsaid@yahoo.com [LSP-IE: Research Laboratory, Electrical Engineering Department, University of Batna, 05000 Batna (Algeria); Benabou, Abdelkader, E-mail: Abdelkader.Benabou@univ-lille1.fr [L2EP, Université de Lille1, 59655 Villeneuve d’Ascq (France)
2016-07-15
An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.
Input-output model for MACCS nuclear accident impacts estimation¹
Energy Technology Data Exchange (ETDEWEB)
Outkin, Alexander V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bixler, Nathan E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vargas, Vanessa N [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-01-27
Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.
Allocatable Fixed Inputs and Two-Stage Aggregation Models of Multioutput Production Decisions
Barry T. Coyle
1993-01-01
Allocation decisions for a fixed input such as land are incorporated into a two-stage aggregation model of multioutput production decisions. The resulting two-stage model is more realistic and is as tractable for empirical research as the standard model.
Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input
Peter Martey Addo
2014-01-01
This study defines a multivariate Self--Exciting Threshold Autoregressive with eXogenous input (MSETARX) models and present an estimation procedure for the parameters. The conditions for stationarity of the nonlinear MSETARX models is provided. In particular, the efficiency of an adaptive parameter estimation algorithm and LSE (least squares estimate) algorithm for this class of models is then provided via simulations.
Stochastic modelling of two-phase flows including phase change
International Nuclear Information System (INIS)
Hurisse, O.; Minier, J.P.
2011-01-01
Stochastic modelling has already been developed and applied for single-phase flows and incompressible two-phase flows. In this article, we propose an extension of this modelling approach to two-phase flows including phase change (e.g. for steam-water flows). Two aspects are emphasised: a stochastic model accounting for phase transition and a modelling constraint which arises from volume conservation. To illustrate the whole approach, some remarks are eventually proposed for two-fluid models. (authors)
Reconstruction of neuronal input through modeling single-neuron dynamics and computations
International Nuclear Information System (INIS)
Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok
2016-01-01
Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.
Reconstruction of neuronal input through modeling single-neuron dynamics and computations
Energy Technology Data Exchange (ETDEWEB)
Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin, E-mail: dengbin@tju.edu.cn; Chan, Wai-lok [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2016-06-15
Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.
Loss of GABAergic inputs in APP/PS1 mouse model of Alzheimer's disease
Directory of Open Access Journals (Sweden)
Tutu Oyelami
2014-04-01
Full Text Available Alzheimer's disease (AD is characterized by symptoms which include seizures, sleep disruption, loss of memory as well as anxiety in patients. Of particular importance is the possibility of preventing the progressive loss of neuronal projections in the disease. Transgenic mice overexpressing EOFAD mutant PS1 (L166P and mutant APP (APP KM670/671NL Swedish (APP/PS1 develop a very early and robust Amyloid pathology and display synaptic plasticity impairments and cognitive dysfunction. Here we investigated GABAergic neurotransmission, using multi-electrode array (MEA technology and pharmacological manipulation to quantify the effect of GABA Blockers on field excitatory postsynaptic potentials (fEPSP, and immunostaining of GABAergic neurons. Using MEA technology we confirm impaired LTP induction by high frequency stimulation in APPPS1 hippocampal CA1 region that was associated with reduced alteration of the pair pulse ratio after LTP induction. Synaptic dysfunction was also observed under manipulation of external Calcium concentration and input-output curve. Electrophysiological recordings from brain slice of CA1 hippocampus area, in the presence of GABAergic receptors blockers cocktails further demonstrated significant reduction in the GABAergic inputs in APP/PS1 mice. Moreover, immunostaining of GAD65 a specific marker for GABAergic neurons revealed reduction of the GABAergic inputs in CA1 area of the hippocampus. These results might be linked to increased seizure sensitivity, premature death and cognitive dysfunction in this animal model of AD. Further in depth analysis of GABAergic dysfunction in APP/PS1 mice is required and may open new perspectives for AD therapy by restoring GABAergic function.
Akhtar, M.; Ahmad, N.; Booij, Martijn J.
2009-01-01
The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and
Backstepping control for a 3DOF model helicopter with input and output constraints
Directory of Open Access Journals (Sweden)
Rong Mei
2016-02-01
Full Text Available In this article, a backstepping control scheme is developed for the motion control of a Three degrees of freedom (3DOF model helicopter with unknown external disturbance, modelling uncertainties and input and output constraints. In the developed robust control scheme, augmented state observers are applied to estimate the unknown states, unknown external disturbance and modelling uncertainties. Auxiliary systems are designed to deal with input saturation. A barrier Lyapunov function is employed to handle the output saturation. The stability of closed-loop system is proved by the Lyapunov method. Simulation results show that the designed control scheme is effective at dealing with the motion control of a 3DOF model helicopter in the presence of unknown external disturbance and modelling uncertainties, and input and output saturation.
ASR in a Human Word Recognition Model: Generating Phonemic Input for Shortlist
Scharenborg, O.E.; Boves, L.W.J.; Veth, J.M. de
2002-01-01
The current version of the psycholinguistic model of human word recognition Shortlist suffers from two unrealistic constraints. First, the input of Shortlist must consist of a single string of phoneme symbols. Second, the current version of the search in Shortlist makes it difficult to deal with insertions and deletions in the input phoneme string. This research attempts to fully automatically derive a phoneme string from the acoustic signal that is as close as possible to the number of phone...
Modeling Electric Double-Layers Including Chemical Reaction Effects
DEFF Research Database (Denmark)
Paz-Garcia, Juan Manuel; Johannesson, Björn; Ottosen, Lisbeth M.
2014-01-01
A physicochemical and numerical model for the transient formation of an electric double-layer between an electrolyte and a chemically-active flat surface is presented, based on a finite elements integration of the nonlinear Nernst-Planck-Poisson model including chemical reactions. The model works...
Sensitivity Analysis of Input Parameters for a Dynamic Food Chain Model DYNACON
International Nuclear Information System (INIS)
Hwang, Won Tae; Lee, Geun Chang; Han, Moon Hee; Cho, Gyu Seong
2000-01-01
The sensitivity analysis of input parameters for a dynamic food chain model DYNACON was conducted as a function of deposition data for the long-lived radionuclides ( 137 Cs, 90 Sr). Also, the influence of input parameters for the short and long-terms contamination of selected foodstuffs (cereals, leafy vegetables, milk) was investigated. The input parameters were sampled using the LHS technique, and their sensitivity indices represented as PRCC. The sensitivity index was strongly dependent on contamination period as well as deposition data. In case of deposition during the growing stages of plants, the input parameters associated with contamination by foliar absorption were relatively important in long-term contamination as well as short-term contamination. They were also important in short-term contamination in case of deposition during the non-growing stages. In long-term contamination, the influence of input parameters associated with foliar absorption decreased, while the influence of input parameters associated with root uptake increased. These phenomena were more remarkable in case of the deposition of non-growing stages than growing stages, and in case of 90 Sr deposition than 137 Cs deposition. In case of deposition during growing stages of pasture, the input parameters associated with the characteristics of cattle such as feed-milk transfer factor and daily intake rate of cattle were relatively important in contamination of milk
The interspike interval of a cable model neuron with white noise input.
Tuckwell, H C; Wan, F Y; Wong, Y S
1984-01-01
The firing time of a cable model neuron in response to white noise current injection is investigated with various methods. The Fourier decomposition of the depolarization leads to partial differential equations for the moments of the firing time. These are solved by perturbation and numerical methods, and the results obtained are in excellent agreement with those obtained by Monte Carlo simulation. The convergence of the random Fourier series is found to be very slow for small times so that when the firing time is small it is more efficient to simulate the solution of the stochastic cable equation directly using the two different representations of the Green's function, one which converges rapidly for small times and the other which converges rapidly for large times. The shape of the interspike interval density is found to depend strongly on input position. The various shapes obtained for different input positions resemble those for real neurons. The coefficient of variation of the interspike interval decreases monotonically as the distance between the input and trigger zone increases. A diffusion approximation for a nerve cell receiving Poisson input is considered and input/output frequency relations obtained for different input sites. The cases of multiple trigger zones and multiple input sites are briefly discussed.
Input data requirements for performance modelling and monitoring of photovoltaic plants
DEFF Research Database (Denmark)
Gavriluta, Anamaria Florina; Spataru, Sergiu; Sera, Dezso
2018-01-01
This work investigates the input data requirements in the context of performance modeling of thin-film photovoltaic (PV) systems. The analysis focuses on the PVWatts performance model, well suited for on-line performance monitoring of PV strings, due to its low number of parameters and high...... accuracy. The work aims to identify the minimum amount of input data required for parameterizing an accurate model of the PV plant. The analysis was carried out for both amorphous silicon (a-Si) and cadmium telluride (CdTe), using crystalline silicon (c-Si) as a base for comparison. In the studied cases...
Tuo, Ye; Duan, Zheng; Disse, Markus; Chiogna, Gabriele
2016-12-15
Precipitation is often the most important input data in hydrological models when simulating streamflow. The Soil and Water Assessment Tool (SWAT), a widely used hydrological model, only makes use of data from one precipitation gauge station that is nearest to the centroid of each subbasin, which is eventually corrected using the elevation band method. This leads in general to inaccurate representation of subbasin precipitation input data, particularly in catchments with complex topography. To investigate the impact of different precipitation inputs on the SWAT model simulations in Alpine catchments, 13years (1998-2010) of daily precipitation data from four datasets including OP (Observed precipitation), IDW (Inverse Distance Weighting data), CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and TRMM (Tropical Rainfall Measuring Mission) has been considered. Both model performances (comparing simulated and measured streamflow data at the catchment outlet) as well as parameter and prediction uncertainties have been quantified. For all three subbasins, the use of elevation bands is fundamental to match the water budget. Streamflow predictions obtained using IDW inputs are better than those obtained using the other datasets in terms of both model performance and prediction uncertainty. Models using the CHIRPS product as input provide satisfactory streamflow estimation, suggesting that this satellite product can be applied to this data-scarce Alpine region. Comparing the performance of SWAT models using different precipitation datasets is therefore important in data-scarce regions. This study has shown that, precipitation is the main source of uncertainty, and different precipitation datasets in SWAT models lead to different best estimate ranges for the calibrated parameters. This has important implications for the interpretation of the simulated hydrological processes. Copyright Â© 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model
Chen, Quanrun; Dietzenbacher, Erik; Los, Bart; Yang, Cuihong
2016-01-01
In this study, we propose a new semi-closed input-output model, which reconciles input-output analysis with modern consumption theories. It can simulate changes in household consumption behavior when exogenous stimulus policies lead to higher disposable income levels. It is useful for quantifying
Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models
Koks, E.E.; Carrera, L.; Jonkeren, O.; Aerts, J.C.J.H.; Husby, T.G.; Thissen, M.; Standardi, G.; Mysiak, J.
2016-01-01
A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input-output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of
Improving the Performance of Water Demand Forecasting Models by Using Weather Input
Bakker, M.; Van Duist, H.; Van Schagen, K.; Vreeburg, J.; Rietveld, L.
2014-01-01
Literature shows that water demand forecasting models which use water demand as single input, are capable of generating a fairly accurate forecast. However, at changing weather conditions the forecasting errors are quite large. In this paper three different forecasting models are studied: an
Logistics flows and enterprise input-output models: aggregate and disaggregate analysis
Albino, V.; Yazan, Devrim; Messeni Petruzzelli, A.; Okogbaa, O.G.
2011-01-01
In the present paper, we propose the use of enterprise input-output (EIO) models to describe and analyse the logistics flows considering spatial issues and related environmental effects associated with production and transportation processes. In particular, transportation is modelled as a specific
Including investment risk in large-scale power market models
DEFF Research Database (Denmark)
Lemming, Jørgen Kjærgaard; Meibom, P.
2003-01-01
can be included in large-scale partial equilibrium models of the power market. The analyses are divided into a part about risk measures appropriate for power market investors and a more technical part about the combination of a risk-adjustment model and a partial-equilibrium model. To illustrate...... the analyses quantitatively, a framework based on an iterative interaction between the equilibrium model and a separate risk-adjustment module was constructed. To illustrate the features of the proposed modelling approach we examined how uncertainty in demand and variable costs affects the optimal choice...
Schattan, Paul; Bellinger, Johannes; Förster, Kristian; Schöber, Johannes; Huttenlau, Matthias; Kirnbauer, Robert; Achleitner, Stefan
2017-04-01
Modelling water resources in snow-dominated mountainous catchments is challenging due to both, short concentration times and a highly variable contribution of snow melt in space and time from complex terrain. A number of model setups exist ranging from physically based models to conceptional models which do not attempt to represent the natural processes in a physically meaningful way. Within the flood forecasting system for the Tyrolean Inn River two serially linked hydrological models with differing process representation are used. Non- glacierized catchments are modelled by a semi-distributed, water balance model (HQsim) based on the HRU-approach. A fully-distributed energy and mass balance model (SES), purpose-built for snow- and icemelt, is used for highly glacierized headwater catchments. Previous work revealed uncertainties and limitations within the models' structures regarding (i) the representation of snow processes in HQsim, (ii) the runoff routing of SES, and (iii) the spatial resolution of the meteorological input data in both models. To overcome these limitations, a "strengths driven" model coupling is applied. Instead of linking the models serially, a vertical one-way coupling of models has been implemented. The fully-distributed snow modelling of SES is combined with the semi-distributed HQsim structure, allowing to benefit from soil and runoff routing schemes in HQsim. A monte-carlo based modelling experiment was set up to evaluate the resulting differences in the runoff prediction due to the improved model coupling and a refined spatial resolution of the meteorological forcing. The experiment design follows a gradient of spatial discretisation of hydrological processes and meteorological forcing data with a total of six different model setups for the alpine headwater basin of the Fagge River in the Tyrolean Alps. In general, all setups show a good performance for this particular basin. It is therefore planned to include other basins with differing
Design of vaccination and fumigation on Host-Vector Model by input-output linearization method
Nugraha, Edwin Setiawan; Naiborhu, Janson; Nuraini, Nuning
2017-03-01
Here, we analyze the Host-Vector Model and proposed design of vaccination and fumigation to control infectious population by using feedback control especially input-output liniearization method. Host population is divided into three compartments: susceptible, infectious and recovery. Whereas the vector population is divided into two compartment such as susceptible and infectious. In this system, vaccination and fumigation treat as input factors and infectious population as output result. The objective of design is to stabilize of the output asymptotically tend to zero. We also present the examples to illustrate the design model.
Recurrent network models for perfect temporal integration of fluctuating correlated inputs.
Directory of Open Access Journals (Sweden)
Hiroshi Okamoto
2009-06-01
Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.
Progressive IRP Models for Power Resources Including EPP
Directory of Open Access Journals (Sweden)
Yiping Zhu
2017-01-01
Full Text Available In the view of optimizing regional power supply and demand, the paper makes effective planning scheduling of supply and demand side resources including energy efficiency power plant (EPP, to achieve the target of benefit, cost, and environmental constraints. In order to highlight the characteristics of different supply and demand resources in economic, environmental, and carbon constraints, three planning models with progressive constraints are constructed. Results of three models by the same example show that the best solutions to different models are different. The planning model including EPP has obvious advantages considering pollutant and carbon emission constraints, which confirms the advantages of low cost and emissions of EPP. The construction of progressive IRP models for power resources considering EPP has a certain reference value for guiding the planning and layout of EPP within other power resources and achieving cost and environmental objectives.
Keller Alevtina; Vinogradova Tatyana
2017-01-01
The article considers the issue of allocation of depreciation costs in the dynamic inputoutput model of an industrial enterprise. Accounting the depreciation costs in such a model improves the policy of fixed assets management. It is particularly relevant to develop the algorithm for the allocation of depreciation costs in the construction of dynamic input-output model of an industrial enterprise, since such enterprises have a significant amount of fixed assets. Implementation of terms of the...
Modeling heart rate variability including the effect of sleep stages
Soliński, Mateusz; Gierałtowski, Jan; Żebrowski, Jan
2016-02-01
We propose a model for heart rate variability (HRV) of a healthy individual during sleep with the assumption that the heart rate variability is predominantly a random process. Autonomic nervous system activity has different properties during different sleep stages, and this affects many physiological systems including the cardiovascular system. Different properties of HRV can be observed during each particular sleep stage. We believe that taking into account the sleep architecture is crucial for modeling the human nighttime HRV. The stochastic model of HRV introduced by Kantelhardt et al. was used as the initial starting point. We studied the statistical properties of sleep in healthy adults, analyzing 30 polysomnographic recordings, which provided realistic information about sleep architecture. Next, we generated synthetic hypnograms and included them in the modeling of nighttime RR interval series. The results of standard HRV linear analysis and of nonlinear analysis (Shannon entropy, Poincaré plots, and multiscale multifractal analysis) show that—in comparison with real data—the HRV signals obtained from our model have very similar properties, in particular including the multifractal characteristics at different time scales. The model described in this paper is discussed in the context of normal sleep. However, its construction is such that it should allow to model heart rate variability in sleep disorders. This possibility is briefly discussed.
Input-Output model for waste management plan for Nigeria | Njoku ...
African Journals Online (AJOL)
An Input-Output Model for Waste Management Plan has been developed for Nigeria based on Leontief concept and life cycle analysis. Waste was considered as source of pollution, loss of resources, and emission of green house gasses from bio-chemical treatment and decomposition, with negative impact on the ...
Land cover models to predict non-point nutrient inputs for selected ...
African Journals Online (AJOL)
WQSAM is a practical water quality model for use in guiding southern African water quality management. However, the estimation of non-point nutrient inputs within WQSAM is uncertain, as it is achieved through a combination of calibration and expert knowledge. Non-point source loads can be correlated to particular land ...
Comparison of plasma input and reference tissue models for analysing [(11)C]flumazenil studies
Klumpers, Ursula M. H.; Veltman, Dick J.; Boellaard, Ronald; Comans, Emile F.; Zuketto, Cassandra; Yaqub, Maqsood; Mourik, Jurgen E. M.; Lubberink, Mark; Hoogendijk, Witte J. G.; Lammertsma, Adriaan A.
2008-01-01
A single-tissue compartment model with plasma input is the established method for analysing [(11)C]flumazenil ([(11)C]FMZ) studies. However, arterial cannulation and measurement of metabolites are time-consuming. Therefore, a reference tissue approach is appealing, but this approach has not been
The economic impact of multifunctional agriculture in The Netherlands: A regional input-output model
Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.
2012-01-01
Multifunctional agriculture is a broad concept lacking a precise and uniform definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model is constructed for multifunctional
The economic impact of multifunctional agriculture in Dutch regions: An input-output model
Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.
2013-01-01
Multifunctional agriculture is a broad concept lacking a precise definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model was constructed for multifunctional agriculture
Linear and quadratic models of point process systems: contributions of patterned input to output.
Lindsay, K A; Rosenberg, J R
2012-08-01
In the 1880's Volterra characterised a nonlinear system using a functional series connecting continuous input and continuous output. Norbert Wiener, in the 1940's, circumvented problems associated with the application of Volterra series to physical problems by deriving from it a new series of terms that are mutually uncorrelated with respect to Gaussian processes. Subsequently, Brillinger, in the 1970's, introduced a point-process analogue of Volterra's series connecting point-process inputs to the instantaneous rate of point-process output. We derive here a new series from this analogue in which its terms are mutually uncorrelated with respect to Poisson processes. This new series expresses how patterned input in a spike train, represented by third-order cross-cumulants, is converted into the instantaneous rate of an output point-process. Given experimental records of suitable duration, the contribution of arbitrary patterned input to an output process can, in principle, be determined. Solutions for linear and quadratic point-process models with one and two inputs and a single output are investigated. Our theoretical results are applied to isolated muscle spindle data in which the spike trains from the primary and secondary endings from the same muscle spindle are recorded in response to stimulation of one and then two static fusimotor axons in the absence and presence of a random length change imposed on the parent muscle. For a fixed mean rate of input spikes, the analysis of the experimental data makes explicit which patterns of two input spikes contribute to an output spike. Copyright © 2012 Elsevier Ltd. All rights reserved.
Fentzke, J. T.; Janches, D.; Sparks, J. J.
2009-05-01
In this work, we use a semi-empirical model of the micrometeor input function (MIF) together with meteor head-echo observations obtained with two high power and large aperture (HPLA) radars, the 430 MHz Arecibo Observatory (AO) radar in Puerto Rico (18°N, 67°W) and the 450 MHz Poker flat incoherent scatter radar (PFISR) in Alaska (65°N, 147°W), to study the seasonal and geographical dependence of the meteoric flux in the upper atmosphere. The model, recently developed by Janches et al. [2006a. Modeling the global micrometeor input function in the upper atmosphere observed by high power and large aperture radars. Journal of Geophysical Research 111] and Fentzke and Janches [2008. A semi-empirical model of the contribution from sporadic meteoroid sources on the meteor input function observed at arecibo. Journal of Geophysical Research (Space Physics) 113 (A03304)], includes an initial mass flux that is provided by the six known meteor sources (i.e. orbital families of dust) as well as detailed modeling of meteoroid atmospheric entry and ablation physics. In addition, we use a simple ionization model to treat radar sensitivity issues by defining minimum electron volume density production thresholds required in the meteor head-echo plasma for detection. This simplified approach works well because we use observations from two radars with similar frequencies, but different sensitivities and locations. This methodology allows us to explore the initial input of particles and how it manifests in different parts of the MLT as observed by these instruments without the need to invoke more sophisticated plasma models, which are under current development. The comparisons between model predictions and radar observations show excellent agreement between diurnal, seasonal, and latitudinal variability of the detected meteor rate and radial velocity distributions, allowing us to understand how individual meteoroid populations contribute to the overall flux at a particular
A hydrodynamic model for granular material flows including segregation effects
Directory of Open Access Journals (Sweden)
Gilberg Dominik
2017-01-01
Full Text Available The simulation of granular flows including segregation effects in large industrial processes using particle methods is accurate, but very time-consuming. To overcome the long computation times a macroscopic model is a natural choice. Therefore, we couple a mixture theory based segregation model to a hydrodynamic model of Navier-Stokes-type, describing the flow behavior of the granular material. The granular flow model is a hybrid model derived from kinetic theory and a soil mechanical approach to cover the regime of fast dilute flow, as well as slow dense flow, where the density of the granular material is close to the maximum packing density. Originally, the segregation model has been formulated by Thornton and Gray for idealized avalanches. It is modified and adapted to be in the preferred form for the coupling. In the final coupled model the segregation process depends on the local state of the granular system. On the other hand, the granular system changes as differently mixed regions of the granular material differ i.e. in the packing density. For the modeling process the focus lies on dry granular material flows of two particle types differing only in size but can be easily extended to arbitrary granular mixtures of different particle size and density. To solve the coupled system a finite volume approach is used. To test the model the rotational mixing of small and large particles in a tumbler is simulated.
A hydrodynamic model for granular material flows including segregation effects
Gilberg, Dominik; Klar, Axel; Steiner, Konrad
2017-06-01
The simulation of granular flows including segregation effects in large industrial processes using particle methods is accurate, but very time-consuming. To overcome the long computation times a macroscopic model is a natural choice. Therefore, we couple a mixture theory based segregation model to a hydrodynamic model of Navier-Stokes-type, describing the flow behavior of the granular material. The granular flow model is a hybrid model derived from kinetic theory and a soil mechanical approach to cover the regime of fast dilute flow, as well as slow dense flow, where the density of the granular material is close to the maximum packing density. Originally, the segregation model has been formulated by Thornton and Gray for idealized avalanches. It is modified and adapted to be in the preferred form for the coupling. In the final coupled model the segregation process depends on the local state of the granular system. On the other hand, the granular system changes as differently mixed regions of the granular material differ i.e. in the packing density. For the modeling process the focus lies on dry granular material flows of two particle types differing only in size but can be easily extended to arbitrary granular mixtures of different particle size and density. To solve the coupled system a finite volume approach is used. To test the model the rotational mixing of small and large particles in a tumbler is simulated.
Responses of two nonlinear microbial models to warming and increased carbon input
Wang, Y. P.; Jiang, J.; Chen-Charpentier, B.; Agusto, F. B.; Hastings, A.; Hoffman, F.; Rasmussen, M.; Smith, M. J.; Todd-Brown, K.; Wang, Y.; Xu, X.; Luo, Y. Q.
2016-02-01
A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. A thorough analysis of their key differences is needed to inform future model developments. Here we compare two nonlinear microbial models of soil carbon decomposition: one based on reverse Michaelis-Menten kinetics (model A) and the other on regular Michaelis-Menten kinetics (model B). Using analytic approximations and numerical solutions, we find that the oscillatory responses of carbon pools to a small perturbation in their initial pool sizes dampen faster in model A than in model B. Soil warming always decreases carbon storage in model A, but in model B it predominantly decreases carbon storage in cool regions and increases carbon storage in warm regions. For both models, the CO2 efflux from soil carbon decomposition reaches a maximum value some time after increased carbon input (as in priming experiments). This maximum CO2 efflux (Fmax) decreases with an increase in soil temperature in both models. However, the sensitivity of Fmax to the increased amount of carbon input increases with soil temperature in model A but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to discern which model is more realistic when compared to results from field or laboratory experiments. These insights will contribute to an improved understanding of the significance of soil microbial processes in soil carbon responses to future climate change.
Decreased Hering-Breuer input-output entrainment in a mouse model of Rett syndrome
Directory of Open Access Journals (Sweden)
Rishi R Dhingra
2013-04-01
Full Text Available Rett syndrome, a severe X-linked neurodevelopmental disorder caused by mutations in the gene encoding methyl-CpG-binding protein 2 (Mecp2, is associated with a highly irregular respiratory pattern including severe upper-airway dysfunction. Recent work suggests that hyperexcitability of the Hering-Breuer reflex (HBR pathway contributes to respiratory dysrhythmia in Mecp2 mutant mice. To assess how enhanced HBR input impacts respiratory entrainment by sensory afferents in closed-loop in vivo-like conditions, we investigated the input (vagal stimulus trains – output (phrenic bursting entrainment via the HBR in wild-type and Mecp2-deficient mice. Using the in situ perfused brainstem preparation, which maintains an intact pontomedullary axis capable of generating an in vivo-like respiratory rhythm in the absence of the HBR, we mimicked the HBR feedback input by stimulating the vagus nerve (at threshold current, 0.5 ms pulse duration, 75 Hz pulse frequency, 100 ms train duration at an inter-burst frequency matching that of the intrinsic oscillation of the inspiratory motor output of each preparation. Using this approach, we observed significant input-output entrainment in wild-type mice as measured by the maximum of the cross-correlation function, the peak of the instantaneous relative phase distribution, and the mutual information of the instantaneous phases. This entrainment was associated with a reduction in inspiratory duration during feedback stimulation. In contrast, the strength of input-output entrainment was significantly weaker in Mecp2-/+ mice. However, Mecp2-/+ mice also had a reduced inspiratory duration during stimulation, indicating that reflex behavior in the HBR pathway was intact. Together, these observations suggest that the respiratory network compensates for enhanced sensitivity of HBR inputs by reducing HBR input-output entrainment.
Simple suggestions for including vertical physics in oil spill models
International Nuclear Information System (INIS)
D'Asaro, Eric; University of Washington, Seatle, WA
2001-01-01
Current models of oil spills include no vertical physics. They neglect the effect of vertical water motions on the transport and concentration of floating oil. Some simple ways to introduce vertical physics are suggested here. The major suggestion is to routinely measure the density stratification of the upper ocean during oil spills in order to develop a database on the effect of stratification. (Author)
ANALYSIS OF THE BANDUNG CHANGES EXCELLENT POTENTIAL THROUGH INPUT-OUTPUT MODEL USING INDEX LE MASNE
Directory of Open Access Journals (Sweden)
Teti Sofia Yanti
2017-03-01
Full Text Available Input-Output Table is arranged to present an overview of the interrelationships and interdependence between units of activity (sector production in the whole economy. Therefore the input-output models are complete and comprehensive analytical tool. The usefulness of input-output tables is an analysis of the economic structure of the national/regional level which covers the structure of production and value-added (GDP of each sector. For the purposes of planning and evaluation of the outcomes of development that is comprehensive both national and smaller scale (district/city, a model for regional development planning approach can use the model input-output analysis. Analysis of Bandung Economic Structure did use Le Masne index, by comparing the coefficients of the technology in 2003 and 2008, of which nearly 50% change. The trade sector has grown very conspicuous than other areas, followed by the services of road transport and air transport services, the development priorities and investment Bandung should be directed to these areas, this is due to these areas can be thrust and be power attraction for the growth of other areas. The areas that experienced the highest decrease was Industrial Chemicals and Goods from Chemistry, followed by Oil and Refinery Industry Textile Industry Except For Garment.
DEFF Research Database (Denmark)
Rasmussen, Bjarne D.; Jakobsen, Arne
1999-01-01
Mathematical models of refrigeration systems are often based on a coupling of component models forming a “closed loop” type of system model. In these models the coupling structure of the component models represents the actual flow path of refrigerant in the system. Very often numerical...... variables with narrow definition intervals for the exchange of information between the cycle model and the component models.The advantages of the cycle-oriented method are illustrated by an example showing the refrigeration cycle similarities between two very different refrigeration systems....... instabilities prevent the practical use of such a system model for more than one input/output combination and for other magnitudes of refrigerating capacities.A higher numerical robustness of system models can be achieved by making a model for the refrigeration cycle the core of the system model and by using...
Liu, Bing; Xu, Ling; Kang, Baolin
2013-01-01
By using pollution model and impulsive delay differential equation, we formulate a pest control model with stage structure for natural enemy in a polluted environment by introducing a constant periodic pollutant input and killing pest at different fixed moments and investigate the dynamics of such a system. We assume only that the natural enemies are affected by pollution, and we choose the method to kill the pest without harming natural enemies. Sufficient conditions for global attractivity ...
Filtering Based Recursive Least Squares Algorithm for Multi-Input Multioutput Hammerstein Models
Wang, Ziyun; Wang, Yan; Ji, Zhicheng
2014-01-01
This paper considers the parameter estimation problem for Hammerstein multi-input multioutput finite impulse response (FIR-MA) systems. Filtered by the noise transfer function, the FIR-MA model is transformed into a controlled autoregressive model. The key-term variable separation principle is used to derive a data filtering based recursive least squares algorithm. The numerical examples confirm that the proposed algorithm can estimate parameters more accurately and has a higher computational...
Input parameters for LEAP and analysis of the Model 22C data base
Energy Technology Data Exchange (ETDEWEB)
Stewart, L.; Goldstein, M.
1981-05-01
The input data for the Long-Term Energy Analysis Program (LEAP) employed by EIA for projections of long-term energy supply and demand in the US were studied and additional documentation provided. Particular emphasis has been placed on the LEAP Model 22C input data base, which was used in obtaining the output projections which appear in the 1978 Annual Report to Congress. Definitions, units, associated model parameters, and translation equations are given in detail. Many parameters were set to null values in Model 22C so as to turn off certain complexities in LEAP; these parameters are listed in Appendix B along with parameters having constant values across all activities. The values of the parameters for each activity are tabulated along with the source upon which each parameter is based - and appropriate comments provided, where available. The structure of the data base is briefly outlined and an attempt made to categorize the parameters according to the methods employed for estimating the numerical values. Due to incomplete documentation and/or lack of specific parameter definitions, few of the input values could be traced and uniquely interpreted using the information provided in the primary and secondary sources. Input parameter choices were noted which led to output projections which are somewhat suspect. Other data problems encountered are summarized. Some of the input data were corrected and a revised base case was constructed. The output projections for this revised case are compared with the Model 22C output for the year 2020, for the Transportation Sector. LEAP could be a very useful tool, especially so in the study of emerging technologies over long-time frames.
Holcomb, Paul S; Hoffpauir, Brian K; Hoyson, Mitchell C; Jackson, Dakota R; Deerinck, Thomas J; Marrs, Glenn S; Dehoff, Marlin; Wu, Jonathan; Ellisman, Mark H; Spirou, George A
2013-08-07
Hallmark features of neural circuit development include early exuberant innervation followed by competition and pruning to mature innervation topography. Several neural systems, including the neuromuscular junction and climbing fiber innervation of Purkinje cells, are models to study neural development in part because they establish a recognizable endpoint of monoinnervation of their targets and because the presynaptic terminals are large and easily monitored. We demonstrate here that calyx of Held (CH) innervation of its target, which forms a key element of auditory brainstem binaural circuitry, exhibits all of these characteristics. To investigate CH development, we made the first application of serial block-face scanning electron microscopy to neural development with fine temporal resolution and thereby accomplished the first time series for 3D ultrastructural analysis of neural circuit formation. This approach revealed a growth spurt of added apposed surface area (ASA)>200 μm2/d centered on a single age at postnatal day 3 in mice and an initial rapid phase of growth and competition that resolved to monoinnervation in two-thirds of cells within 3 d. This rapid growth occurred in parallel with an increase in action potential threshold, which may mediate selection of the strongest input as the winning competitor. ASAs of competing inputs were segregated on the cell body surface. These data suggest mechanisms to select "winning" inputs by regional reinforcement of postsynaptic membrane to mediate size and strength of competing synaptic inputs.
Energy Technology Data Exchange (ETDEWEB)
2017-02-01
The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.
Application of a Linear Input/Output Model to Tankless Water Heaters
Energy Technology Data Exchange (ETDEWEB)
Butcher T.; Schoenbauer, B.
2011-12-31
In this study, the applicability of a linear input/output model to gas-fired, tankless water heaters has been evaluated. This simple model assumes that the relationship between input and output, averaged over both active draw and idle periods, is linear. This approach is being applied to boilers in other studies and offers the potential to make a small number of simple measurements to obtain the model parameters. These parameters can then be used to predict performance under complex load patterns. Both condensing and non-condensing water heaters have been tested under a very wide range of load conditions. It is shown that this approach can be used to reproduce performance metrics, such as the energy factor, and can be used to evaluate the impacts of alternative draw patterns and conditions.
DEFF Research Database (Denmark)
Bigoni, Daniele; Engsig-Karup, Allan Peter; Eskilsson, Claes
2016-01-01
A major challenge in next-generation industrial applications is to improve numerical analysis by quantifying uncertainties in predictions. In this work we present a formulation of a fully nonlinear and dispersive potential flow water wave model with random inputs for the probabilistic description...... of the evolution of waves. The model is analyzed using random sampling techniques and nonintrusive methods based on generalized polynomial chaos (PC). These methods allow us to accurately and efficiently estimate the probability distribution of the solution and require only the computation of the solution...... at different points in the parameter space, allowing for the reuse of existing simulation software. The choice of the applied methods is driven by the number of uncertain input parameters and by the fact that finding the solution of the considered model is computationally intensive. We revisit experimental...
Walterscheid, R. L.; Brinkman, D. G.; Clemmons, J. H.; Hecht, J. H.; Lessard, M.; Fritz, B.; Hysell, D. L.; Clausen, L. B. N.; Moen, J.; Oksavik, K.; Yeoman, T. K.
2017-12-01
The Earth's magnetospheric cusp provides direct access of energetic particles to the thermosphere. These particles produce ionization and kinetic (particle) heating of the atmosphere. The increased ionization coupled with enhanced electric fields in the cusp produces increased Joule heating and ion drag forcing. These energy inputs cause large wind and temperature changes in the cusp region. The Rocket Experiment for Neutral Upwelling -2 (RENU-2) launched from Andoya, Norway at 0745UT on 13 December 2015 into the ionosphere-thermosphere beneath the magnetic cusp. It made measurements of the energy inputs (e.g., precipitating particles, electric fields) and the thermospheric response to these energy inputs (e.g., neutral density and temperature, neutral winds). Complementary ground based measurements were made. In this study, we use a high resolution two-dimensional time-dependent non hydrostatic nonlinear dynamical model driven by rocket and ground based measurements of the energy inputs to simulate the thermospheric response during the RENU-2 flight. Model simulations will be compared to the corresponding measurements of the thermosphere to see what they reveal about thermospheric structure and the nature of magnetosphere-ionosphere-thermosphere coupling in the cusp. Acknowledgements: This material is based upon work supported by the National Aeronautics and Space Administration under Grants: NNX16AH46G and NNX13AJ93G. This research was also supported by The Aerospace Corporation's Technical Investment program
Input vs. Output Taxation—A DSGE Approach to Modelling Resource Decoupling
Directory of Open Access Journals (Sweden)
Marek Antosiewicz
2016-04-01
Full Text Available Environmental taxes constitute a crucial instrument aimed at reducing resource use through lower production losses, resource-leaner products, and more resource-efficient production processes. In this paper we focus on material use and apply a multi-sector dynamic stochastic general equilibrium (DSGE model to study two types of taxation: tax on material inputs used by industry, energy, construction, and transport sectors, and tax on output of these sectors. We allow for endogenous adoption of resource-saving technologies. We calibrate the model for the EU27 area using an IO matrix. We consider taxation introduced from 2021 and simulate its impact until 2050. We compare the taxes along their ability to induce reduction in material use and raise revenue. We also consider the effect of spending this revenue on reduction of labour taxation. We find that input and output taxation create contrasting incentives and have opposite effects on resource efficiency. The material input tax induces investment in efficiency-improving technology which, in the long term, results in GDP and employment by 15%–20% higher than in the case of a comparable output tax. We also find that using revenues to reduce taxes on labour has stronger beneficial effects for the input tax.
MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering
Directory of Open Access Journals (Sweden)
M. Proksch
2015-08-01
Full Text Available The Microwave Emission Model of Layered Snowpacks (MEMLS was originally developed for microwave emissions of snowpacks in the frequency range 5–100 GHz. It is based on six-flux theory to describe radiative transfer in snow including absorption, multiple volume scattering, radiation trapping due to internal reflection and a combination of coherent and incoherent superposition of reflections between horizontal layer interfaces. Here we introduce MEMLS3&a, an extension of MEMLS, which includes a backscatter model for active microwave remote sensing of snow. The reflectivity is decomposed into diffuse and specular components. Slight undulations of the snow surface are taken into account. The treatment of like- and cross-polarization is accomplished by an empirical splitting parameter q. MEMLS3&a (as well as MEMLS is set up in a way that snow input parameters can be derived by objective measurement methods which avoid fitting procedures of the scattering efficiency of snow, required by several other models. For the validation of the model we have used a combination of active and passive measurements from the NoSREx (Nordic Snow Radar Experiment campaign in Sodankylä, Finland. We find a reasonable agreement between the measurements and simulations, subject to uncertainties in hitherto unmeasured input parameters of the backscatter model. The model is written in Matlab and the code is publicly available for download through the following website: http://www.iapmw.unibe.ch/research/projects/snowtools/memls.html.
Ecological input-output modeling for embodied resources and emissions in Chinese economy 2005
Chen, Z. M.; Chen, G. Q.; Zhou, J. B.; Jiang, M. M.; Chen, B.
2010-07-01
For the embodiment of natural resources and environmental emissions in Chinese economy 2005, a biophysical balance modeling is carried out based on an extension of the economic input-output table into an ecological one integrating the economy with its various environmental driving forces. Included resource flows into the primary resource sectors and environmental emission flows from the primary emission sectors belong to seven categories as energy resources in terms of fossil fuels, hydropower and nuclear energy, biomass, and other sources; freshwater resources; greenhouse gas emissions in terms of CO2, CH4, and N2O; industrial wastes in terms of waste water, waste gas, and waste solid; exergy in terms of fossil fuel resources, biological resources, mineral resources, and environmental resources; solar emergy and cosmic emergy in terms of climate resources, soil, fossil fuels, and minerals. The resulted database for embodiment intensity and sectoral embodiment of natural resources and environmental emissions is of essential implications in context of systems ecology and ecological economics in general and of global climate change in particular.
A non-linear dimension reduction methodology for generating data-driven stochastic input models
Ganapathysubramanian, Baskar; Zabaras, Nicholas
2008-06-01
Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low
A non-linear dimension reduction methodology for generating data-driven stochastic input models
International Nuclear Information System (INIS)
Ganapathysubramanian, Baskar; Zabaras, Nicholas
2008-01-01
Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R n . An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R d (d<< n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology
Integrate-and-fire models with an almost periodic input function
Kasprzak, Piotr; Nawrocki, Adam; Signerska-Rynkowska, Justyna
2018-02-01
We investigate leaky integrate-and-fire models (LIF models for short) driven by Stepanov and μ-almost periodic functions. Special attention is paid to the properties of the firing map and its displacement, which give information about the spiking behavior of the considered system. We provide conditions under which such maps are well-defined and are uniformly continuous. We show that the LIF models with Stepanov almost periodic inputs have uniformly almost periodic displacements. We also show that in the case of μ-almost periodic drives it may happen that the displacement map is uniformly continuous, but is not μ-almost periodic (and thus cannot be Stepanov or uniformly almost periodic). By allowing discontinuous inputs, we extend some previous results, showing, for example, that the firing rate for the LIF models with Stepanov almost periodic input exists and is unique. This is a starting point for the investigation of the dynamics of almost-periodically driven integrate-and-fire systems.
Caridakis, G; Karpouzis, K; Drosopoulos, A; Kollias, S
2012-12-01
Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost. Copyright © 2012 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Koichi Kobayashi
2013-01-01
Full Text Available We propose computational techniques for model predictive control of large-scale systems with both continuous-valued control inputs and discrete-valued control inputs, which are a class of hybrid systems. In the proposed method, we introduce the notion of virtual control inputs, which are obtained by relaxing discrete-valued control inputs to continuous variables. In online computation, first, we find continuous-valued control inputs and virtual control inputs minimizing a cost function. Next, using the obtained virtual control inputs, only discrete-valued control inputs at the current time are computed in each subsystem. In addition, we also discuss the effect of quantization errors. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method enables us to reduce and decentralize the computation load.
Exclusive queueing model including the choice of service windows
Tanaka, Masahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro
2018-01-01
In a queueing system involving multiple service windows, choice behavior is a significant concern. This paper incorporates the choice of service windows into a queueing model with a floor represented by discrete cells. We contrived a logit-based choice algorithm for agents considering the numbers of agents and the distances to all service windows. Simulations were conducted with various parameters of agent choice preference for these two elements and for different floor configurations, including the floor length and the number of service windows. We investigated the model from the viewpoint of transit times and entrance block rates. The influences of the parameters on these factors were surveyed in detail and we determined that there are optimum floor lengths that minimize the transit times. In addition, we observed that the transit times were determined almost entirely by the entrance block rates. The results of the presented model are relevant to understanding queueing systems including the choice of service windows and can be employed to optimize facility design and floor management.
Input vs. Output Taxation—A DSGE Approach to Modelling Resource Decoupling
Marek Antosiewicz; Piotr Lewandowski; Jan Witajewski-Baltvilks
2016-01-01
Environmental taxes constitute a crucial instrument aimed at reducing resource use through lower production losses, resource-leaner products, and more resource-efficient production processes. In this paper we focus on material use and apply a multi-sector dynamic stochastic general equilibrium (DSGE) model to study two types of taxation: tax on material inputs used by industry, energy, construction, and transport sectors, and tax on output of these sectors. We allow for endogenous adoption of...
Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling
Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood
2005-01-01
The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.
International Nuclear Information System (INIS)
Serfontein, Dawid E.; Mulder, Eben J.; Reitsma, Frederik
2014-01-01
A computer code was developed for the semi-automatic translation of input models for the VSOP-A diffusion neutronics simulation code to the format of the newer VSOP 99/05 code. In this paper, this algorithm is presented as a generic method for producing codes for the automatic translation of input models from the format of one code version to another, or even to that of a completely different code. Normally, such translations are done manually. However, input model files, such as for the VSOP codes, often are very large and may consist of many thousands of numeric entries that make no particular sense to the human eye. Therefore the task, of for instance nuclear regulators, to verify the accuracy of such translated files can be very difficult and cumbersome. This may cause translation errors not to be picked up, which may have disastrous consequences later on when a reactor with such a faulty design is built. Therefore a generic algorithm for producing such automatic translation codes may ease the translation and verification process to a great extent. It will also remove human error from the process, which may significantly enhance the accuracy and reliability of the process. The developed algorithm also automatically creates a verification log file which permanently record the names and values of each variable used, as well as the list of meanings of all the possible values. This should greatly facilitate reactor licensing applications
Responses of two nonlinear microbial models to warming or increased carbon input
Wang, Y. P.; Jiang, J.; Chen-Charpentier, B.; Agusto, F. B.; Hastings, A.; Hoffman, F.; Rasmussen, M.; Smith, M. J.; Todd-Brown, K.; Wang, Y.; Xu, X.; Luo, Y. Q.
2015-09-01
A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. Therefore a thorough analysis of their key differences will be very useful for the future development of these models. Here we compare two nonlinear microbial models of soil carbon decomposition: one is based on reverse Michaelis-Menten kinetics (model A) and the other on regular Michaelis-Menten kinetics (model B). Using a combination of analytic solutions and numerical simulations, we find that the oscillatory responses of carbon pools model A to a small perturbation in the initial pool sizes have a higher frequency and damps faster than model B. In response to soil warming, soil carbon always decreases in model A; but likely decreases in cool regions and increases in warm regions in model B. Maximum CO2 efflux from soil carbon decomposition (Fmax) after an increased carbon addition decreases with an increase in soil temperature in both models, and the sensitivity of Fmax to the amount of carbon input increases with soil temperature in model A; but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to differentiate which model is more realistic with field or laboratory experiments. This will lead to a better understanding of the significance of soil microbial processes in the responses of soil carbon to future climate change at regional or global scales.
Directory of Open Access Journals (Sweden)
Keller Alevtina
2017-01-01
Full Text Available The article considers the issue of allocation of depreciation costs in the dynamic inputoutput model of an industrial enterprise. Accounting the depreciation costs in such a model improves the policy of fixed assets management. It is particularly relevant to develop the algorithm for the allocation of depreciation costs in the construction of dynamic input-output model of an industrial enterprise, since such enterprises have a significant amount of fixed assets. Implementation of terms of the adequacy of such an algorithm itself allows: evaluating the appropriateness of investments in fixed assets, studying the final financial results of an industrial enterprise, depending on management decisions in the depreciation policy. It is necessary to note that the model in question for the enterprise is always degenerate. It is caused by the presence of zero rows in the matrix of capital expenditures by lines of structural elements unable to generate fixed assets (part of the service units, households, corporate consumers. The paper presents the algorithm for the allocation of depreciation costs for the model. This algorithm was developed by the authors and served as the basis for further development of the flowchart for subsequent implementation with use of software. The construction of such algorithm and its use for dynamic input-output models of industrial enterprises is actualized by international acceptance of the effectiveness of the use of input-output models for national and regional economic systems. This is what allows us to consider that the solutions discussed in the article are of interest to economists of various industrial enterprises.
A time-resolved model of the mesospheric Na layer: constraints on the meteor input function
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J. M. C. Plane
2004-01-01
Full Text Available A time-resolved model of the Na layer in the mesosphere/lower thermosphere region is described, where the continuity equations for the major sodium species Na, Na+ and NaHCO3 are solved explicity, and the other short-lived species are treated in steady-state. It is shown that the diurnal variation of the Na layer can only be modelled satisfactorily if sodium species are permanently removed below about 85 km, both through the dimerization of NaHCO3 and the uptake of sodium species on meteoric smoke particles that are assumed to have formed from the recondensation of vaporized meteoroids. When the sensitivity of the Na layer to the meteoroid input function is considered, an inconsistent picture emerges. The ratio of the column abundance of Na+ to Na is shown to increase strongly with the average meteoroid velocity, because the Na is injected at higher altitudes. Comparison with a limited set of Na+ measurements indicates that the average meteoroid velocity is probably less than about 25 km s-1, in agreement with velocity estimates from conventional meteor radars, and considerably slower than recent observations made by wide aperture incoherent scatter radars. The Na column abundance is shown to be very sensitive to the meteoroid mass input rate, and to the rate of vertical transport by eddy diffusion. Although the magnitude of the eddy diffusion coefficient in the 80–90 km region is uncertain, there is a consensus between recent models using parameterisations of gravity wave momentum deposition that the average value is less than 3×105 cm2 s-1. This requires that the global meteoric mass input rate is less than about 20 td-1, which is closest to estimates from incoherent scatter radar observations. Finally, the diurnal variation in the meteoroid input rate only slight perturbs the Na layer, because the residence time of Na in the layer is several days, and diurnal effects are effectively averaged out.
Filtering Based Recursive Least Squares Algorithm for Multi-Input Multioutput Hammerstein Models
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Ziyun Wang
2014-01-01
Full Text Available This paper considers the parameter estimation problem for Hammerstein multi-input multioutput finite impulse response (FIR-MA systems. Filtered by the noise transfer function, the FIR-MA model is transformed into a controlled autoregressive model. The key-term variable separation principle is used to derive a data filtering based recursive least squares algorithm. The numerical examples confirm that the proposed algorithm can estimate parameters more accurately and has a higher computational efficiency compared with the recursive least squares algorithm.
Unitary input DEA model to identify beef cattle production systems typologies
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Eliane Gonçalves Gomes
2012-08-01
Full Text Available The cow-calf beef production sector in Brazil has a wide variety of operating systems. This suggests the identification and the characterization of homogeneous regions of production, with consequent implementation of actions to achieve its sustainability. In this paper we attempted to measure the performance of 21 livestock modal production systems, in their cow-calf phase. We measured the performance of these systems, considering husbandry and production variables. The proposed approach is based on data envelopment analysis (DEA. We used unitary input DEA model, with apparent input orientation, together with the efficiency measurements generated by the inverted DEA frontier. We identified five modal production systems typologies, using the isoefficiency layers approach. The results showed that the knowledge and the processes management are the most important factors for improving the efficiency of beef cattle production systems.
Yan, Z.; Wilkinson, S. K.; Stitt, E. H.; Marigo, M.
2015-09-01
Selection or calibration of particle property input parameters is one of the key problematic aspects for the implementation of the discrete element method (DEM). In the current study, a parametric multi-level sensitivity method is employed to understand the impact of the DEM input particle properties on the bulk responses for a given simple system: discharge of particles from a flat bottom cylindrical container onto a plate. In this case study, particle properties, such as Young's modulus, friction parameters and coefficient of restitution were systematically changed in order to assess their effect on material repose angles and particle flow rate (FR). It was shown that inter-particle static friction plays a primary role in determining both final angle of repose and FR, followed by the role of inter-particle rolling friction coefficient. The particle restitution coefficient and Young's modulus were found to have insignificant impacts and were strongly cross correlated. The proposed approach provides a systematic method that can be used to show the importance of specific DEM input parameters for a given system and then potentially facilitates their selection or calibration. It is concluded that shortening the process for input parameters selection and calibration can help in the implementation of DEM.
DEFF Research Database (Denmark)
Vafamand, Navid; Asemani, Mohammad Hassan; Khayatiyan, Alireza
2018-01-01
criterion, new robust controller design conditions in terms of linear matrix inequalities are derived. Three practical case studies, electric power steering system, a helicopter model and servo-mechanical system, are presented to demonstrate the importance of such class of nonlinear systems comprising......This paper proposes a novel robust controller design for a class of nonlinear systems including hard nonlinearity functions. The proposed approach is based on Takagi-Sugeno (TS) fuzzy modeling, nonquadratic Lyapunov function, and nonparallel distributed compensation scheme. In this paper, a novel...... TS modeling of the nonlinear dynamics with signum functions is proposed. This model can exactly represent the original nonlinear system with hard nonlinearity while the discontinuous signum functions are not approximated. Based on the bounded-input-bounded-output stability scheme and L₁ performance...
The sensitivity of ecosystem service models to choices of input data and spatial resolution
Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge
2018-01-01
Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.
DEFF Research Database (Denmark)
Harnefors, Lennart; Finger, Raphael; Wang, Xiongfei
2017-01-01
The interconnection stability of a gridconnected voltage-source converter (VSC) can be assessed via the dissipative properties of its input admittance. In this paper, the modeling of the current control loop is revisited with the aim to improve the accuracy of the input-admittance model above the...
Directory of Open Access Journals (Sweden)
Peter A Appleby
Full Text Available Recently, we presented a study of adult neurogenesis in a simplified hippocampal memory model. The network was required to encode and decode memory patterns despite changing input statistics. We showed that additive neurogenesis was a more effective adaptation strategy compared to neuronal turnover and conventional synaptic plasticity as it allowed the network to respond to changes in the input statistics while preserving representations of earlier environments. Here we extend our model to include realistic, spatially driven input firing patterns in the form of grid cells in the entorhinal cortex. We compare network performance across a sequence of spatial environments using three distinct adaptation strategies: conventional synaptic plasticity, where the network is of fixed size but the connectivity is plastic; neuronal turnover, where the network is of fixed size but units in the network may die and be replaced; and additive neurogenesis, where the network starts out with fewer initial units but grows over time. We confirm that additive neurogenesis is a superior adaptation strategy when using realistic, spatially structured input patterns. We then show that a more biologically plausible neurogenesis rule that incorporates cell death and enhanced plasticity of new granule cells has an overall performance significantly better than any one of the three individual strategies operating alone. This adaptation rule can be tailored to maximise performance of the network when operating as either a short- or long-term memory store. We also examine the time course of adult neurogenesis over the lifetime of an animal raised under different hypothetical rearing conditions. These growth profiles have several distinct features that form a theoretical prediction that could be tested experimentally. Finally, we show that place cells can emerge and refine in a realistic manner in our model as a direct result of the sparsification performed by the dentate gyrus
Directory of Open Access Journals (Sweden)
Domozhirov D. A.
2017-06-01
Full Text Available The article demonstrates the possibilities of spatial analysis provided by the Agent-Based Multiregional Input - Output Model (ABMIOM of the Russian economy. The basic hypothesis of the ABMIOM is that agents’ decisions at the microeconomic level lead to spatial changes at the macro level. Confirmation of this hypothesis requires experimental calculations with changes in various parameters that influence agents’ decisions (such as prices, taxes, tariffs, etc.. Analyzing the results of these calculations requires moving from microeconomic data to the macro level. The paper proposes a method for the structural analysis of the model simulation results using input-output tables. The method involves statistical aggregation of calculation results, construction of regional, national and interregional input-output tables and structural analysis of the obtained tables including calculation of regional Leontief multipliers. The method proposed is used to study the influence of the level of transport costs on the geographical structure of trade flows. The results of the experiments confirmed that with the increase of transportation costs economic agents prefer to interact with nearest agents, which leads to a decreased interregional commodity exchange and to economic «insulation» of the regions.
Strokal, Maryna; Kroeze, Carolien; Wang, Mengru; Bai, Zhaohai; Ma, Lin
2016-08-15
Chinese agriculture has been developing fast towards industrial food production systems that discharge nutrient-rich wastewater into rivers. As a result, nutrient export by rivers has been increasing, resulting in coastal water pollution. We developed a Model to Assess River Inputs of Nutrients to seAs (MARINA) for China. The MARINA Nutrient Model quantifies river export of nutrients by source at the sub-basin scale as a function of human activities on land. MARINA is a downscaled version for China of the Global NEWS-2 (Nutrient Export from WaterSheds) model with an improved approach for nutrient losses from animal production and population. We use the model to quantify dissolved inorganic and organic nitrogen (N) and phosphorus (P) export by six large rivers draining into the Bohai Gulf (Yellow, Hai, Liao), Yellow Sea (Yangtze, Huai) and South China Sea (Pearl) in 1970, 2000 and 2050. We addressed uncertainties in the MARINA Nutrient model. Between 1970 and 2000 river export of dissolved N and P increased by a factor of 2-8 depending on sea and nutrient form. Thus, the risk for coastal eutrophication increased. Direct losses of manure to rivers contribute to 60-78% of nutrient inputs to the Bohai Gulf and 20-74% of nutrient inputs to the other seas in 2000. Sewage is an important source of dissolved inorganic P, and synthetic fertilizers of dissolved inorganic N. Over half of the nutrients exported by the Yangtze and Pearl rivers originated from human activities in downstream and middlestream sub-basins. The Yellow River exported up to 70% of dissolved inorganic N and P from downstream sub-basins and of dissolved organic N and P from middlestream sub-basins. Rivers draining into the Bohai Gulf are drier, and thus transport fewer nutrients. For the future we calculate further increases in river export of nutrients. The MARINA Nutrient model quantifies the main sources of coastal water pollution for sub-basins. This information can contribute to formulation of
International Nuclear Information System (INIS)
Meyer, Carsten; Peligrad, Dragos-Nicolae; Weibrecht, Martin
2007-01-01
Cardiac 82 rubidium dynamic PET studies allow quantifying absolute myocardial perfusion by using tracer kinetic modeling. Here, the accurate measurement of the input function, i.e. the tracer concentration in blood plasma, is a major challenge. This measurement is deteriorated by inappropriate temporal sampling, spillover, etc. Such effects may influence the measured input peak value and the measured blood pool clearance. The aim of our study is to evaluate the effect of input function distortions on the myocardial perfusion as estimated by the model. To this end, we simulate noise-free myocardium time activity curves (TACs) with a two-compartment kinetic model. The input function to the model is a generic analytical function. Distortions of this function have been introduced by varying its parameters. Using the distorted input function, the compartment model has been fitted to the simulated myocardium TAC. This analysis has been performed for various sets of model parameters covering a physiologically relevant range. The evaluation shows that ±10% error in the input peak value can easily lead to ±10-25% error in the model parameter K 1 , which relates to myocardial perfusion. Variations in the input function tail are generally less relevant. We conclude that an accurate estimation especially of the plasma input peak is crucial for a reliable kinetic analysis and blood flow estimation
Influence of the spatial extent and resolution of input data on soil carbon models in Florida, USA
Vasques, Gustavo M.; Grunwald, S.; Myers, D. Brenton
2012-12-01
Understanding the causes of spatial variation of soil carbon (C) has important implications for regional and global C dynamics studies. Soil C predictive models can identify sources of C variation, but may be influenced by scale parameters, including the spatial extent and resolution of input data. Our objective was to investigate the influence of these scale parameters on soil C spatial predictive models in Florida, USA. We used data from three nested spatial extents (Florida, 150,000 km2; Santa Fe River watershed, 3,585 km2; and University of Florida Beef Cattle Station, 5.58 km2) to derive stepwise linear models of soil C as a function of 24 environmental properties. Models were derived within the three extents and for seven resolutions (30-1920 m) of input environmental data in Florida and in the watershed, then cross-evaluated among extents and resolutions, respectively. The quality of soil C models increased with an increase in the spatial extent (R2 from 0.10 in the cattle station to 0.61 in Florida) and with a decrease in the resolution of input data (R2 from 0.33 at 1920-m resolution to 0.61 at 30-m resolution in Florida). Soil and hydrologic variables were the most important across the seven resolutions both in Florida and in the watershed. The spatial extent and resolution of environmental covariates modulate soil C variation and soil-landscape correlations influencing soil C predictive models. Our results provide scale boundaries to observe environmental data and assess soil C spatial patterns, supporting C sequestration, budgeting and monitoring programs.
Directory of Open Access Journals (Sweden)
Christian Vögeli
2016-12-01
Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.
PERMODELAN INDEKS HARGA KONSUMEN INDONESIA DENGAN MENGGUNAKAN MODEL INTERVENSI MULTI INPUT
Novianti, Putri Wikie
2017-01-24
There are some events which are expected effecting CPI’s fluctuation, i.e. financial crisis 1997/1998, fuel price risings, base year changing’s, independence of Timor-Timur (October 1999), and Tsunami disaster in Aceh (December 2004). During re-search period, there were eight fuel price risings and four base year changing’s. The objective of this research is to obtain multi input intervention model which can des-cribe magnitude and duration of each event effected to CPI. Most of intervention re-searches that have been done are only contain of an intervention with single input, ei-ther step or pulse function. Multi input intervention was used in Indonesia CPI case because there are some events which are expected effecting CPI. Based on the result, those events were affecting CPI. Additionally, other events, such as Ied on January 1999, events on April 2002, July 2003, December 2005, and September 2008, were affecting CPI too. In general, those events gave positive effect to CPI, except events on April 2002 and July 2003 which gave negative effects.
Input-Output Modeling for Urban Energy Consumption in Beijing: Dynamics and Comparison
Zhang, Lixiao; Hu, Qiuhong; Zhang, Fan
2014-01-01
Input-output analysis has been proven to be a powerful instrument for estimating embodied (direct plus indirect) energy usage through economic sectors. Using 9 economic input-output tables of years 1987, 1990, 1992, 1995, 1997, 2000, 2002, 2005, and 2007, this paper analyzes energy flows for the entire city of Beijing and its 30 economic sectors, respectively. Results show that the embodied energy consumption of Beijing increased from 38.85 million tonnes of coal equivalent (Mtce) to 206.2 Mtce over the past twenty years of rapid urbanization; the share of indirect energy consumption in total energy consumption increased from 48% to 76%, suggesting the transition of Beijing from a production-based and manufacturing-dominated economy to a consumption-based and service-dominated economy. Real estate development has shown to be a major driving factor of the growth in indirect energy consumption. The boom and bust of construction activities have been strongly correlated with the increase and decrease of system-side indirect energy consumption. Traditional heavy industries remain the most energy-intensive sectors in the economy. However, the transportation and service sectors have contributed most to the rapid increase in overall energy consumption. The analyses in this paper demonstrate that a system-wide approach such as that based on input-output model can be a useful tool for robust energy policy making. PMID:24595199
Input data for mathematical modeling and numerical simulation of switched reluctance machines
Directory of Open Access Journals (Sweden)
Ali Asghar Memon
2017-10-01
Full Text Available The modeling and simulation of Switched Reluctance (SR machine and drives is challenging for its dual pole salient structure and magnetic saturation. This paper presents the input data in form of experimentally obtained magnetization characteristics. This data was used for computer simulation based model of SR machine, “Selecting Best Interpolation Technique for Simulation Modeling of Switched Reluctance Machine” [1], “Modeling of Static Characteristics of Switched Reluctance Motor” [2]. This data is primary source of other data tables of co energy and static torque which are also among the required data essential for the simulation and can be derived from this data. The procedure and experimental setup for collection of the data is presented in detail.
Input data for mathematical modeling and numerical simulation of switched reluctance machines.
Memon, Ali Asghar; Shaikh, Muhammad Mujtaba
2017-10-01
The modeling and simulation of Switched Reluctance (SR) machine and drives is challenging for its dual pole salient structure and magnetic saturation. This paper presents the input data in form of experimentally obtained magnetization characteristics. This data was used for computer simulation based model of SR machine, "Selecting Best Interpolation Technique for Simulation Modeling of Switched Reluctance Machine" [1], "Modeling of Static Characteristics of Switched Reluctance Motor" [2]. This data is primary source of other data tables of co energy and static torque which are also among the required data essential for the simulation and can be derived from this data. The procedure and experimental setup for collection of the data is presented in detail.
Modelling Effects on Grid Cells of Sensory Input During Self-motion
2016-04-20
Olton et al. 1979, 1986; Morris et al. 1982), and hence their accurate updating on the basis of sensory features appears to be essential to memory -guided...J Physiol 000.0 (2016) pp 1–14 1 Th e Jo u rn al o f Ph ys io lo g y N eu ro sc ie nc e SYMPOS IUM REV IEW Modelling effects on grid cells of sensory ...input during self-motion Florian Raudies, James R. Hinman and Michael E. Hasselmo Center for Systems Neuroscience, Centre for Memory and Brain
Input-constrained model predictive control via the alternating direction method of multipliers
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Frison, Gianluca; Andersen, Martin S.
2014-01-01
is quadratic in the dimensions of the controlled system, and linear in the length of the prediction horizon. Simulations show that the approach proposed in this paper is more than an order of magnitude faster than several state-of-the-art quadratic programming algorithms, and that the difference in computation......This paper presents an algorithm, based on the alternating direction method of multipliers, for the convex optimal control problem arising in input-constrained model predictive control. We develop an efficient implementation of the algorithm for the extended linear quadratic control problem (LQCP...
Using Whole-House Field Tests to Empirically Derive Moisture Buffering Model Inputs
Energy Technology Data Exchange (ETDEWEB)
Woods, J.; Winkler, J.; Christensen, D.; Hancock, E.
2014-08-01
Building energy simulations can be used to predict a building's interior conditions, along with the energy use associated with keeping these conditions comfortable. These models simulate the loads on the building (e.g., internal gains, envelope heat transfer), determine the operation of the space conditioning equipment, and then calculate the building's temperature and humidity throughout the year. The indoor temperature and humidity are affected not only by the loads and the space conditioning equipment, but also by the capacitance of the building materials, which buffer changes in temperature and humidity. This research developed an empirical method to extract whole-house model inputs for use with a more accurate moisture capacitance model (the effective moisture penetration depth model). The experimental approach was to subject the materials in the house to a square-wave relative humidity profile, measure all of the moisture transfer terms (e.g., infiltration, air conditioner condensate) and calculate the only unmeasured term: the moisture absorption into the materials. After validating the method with laboratory measurements, we performed the tests in a field house. A least-squares fit of an analytical solution to the measured moisture absorption curves was used to determine the three independent model parameters representing the moisture buffering potential of this house and its furnishings. Follow on tests with realistic latent and sensible loads showed good agreement with the derived parameters, especially compared to the commonly-used effective capacitance approach. These results show that the EMPD model, once the inputs are known, is an accurate moisture buffering model.
Loncich, Kristen Teczar
Bat echolocation strategies and neural processing of acoustic information, with a focus on cluttered environments, is investigated in this study. How a bat processes the dense field of echoes received while navigating and foraging in the dark is not well understood. While several models have been developed to describe the mechanisms behind bat echolocation, most are based in mathematics rather than biology, and focus on either peripheral or neural processing---not exploring how these two levels of processing are vitally connected. Current echolocation models also do not use habitat specific acoustic input, or account for field observations of echolocation strategies. Here, a new approach to echolocation modeling is described capturing the full picture of echolocation from signal generation to a neural picture of the acoustic scene. A biologically inspired echolocation model is developed using field research measurements of the interpulse interval timing used by a frequency modulating (FM) bat in the wild, with a whole method approach to modeling echolocation including habitat specific acoustic inputs, a biologically accurate peripheral model of sound processing by the outer, middle, and inner ear, and finally a neural model incorporating established auditory pathways and neuron types with echolocation adaptations. Field recordings analyzed underscore bat sonar design differences observed in the laboratory and wild, and suggest a correlation between interpulse interval groupings and increased clutter. The scenario model provides habitat and behavior specific echoes and is a useful tool for both modeling and behavioral studies, and the peripheral and neural model show that spike-time information and echolocation specific neuron types can produce target localization in the midbrain.
Visual Predictive Check in Models with Time-Varying Input Function.
Largajolli, Anna; Bertoldo, Alessandra; Campioni, Marco; Cobelli, Claudio
2015-11-01
The nonlinear mixed effects models are commonly used modeling techniques in the pharmaceutical research as they enable the characterization of the individual profiles together with the population to which the individuals belong. To ensure a correct use of them is fundamental to provide powerful diagnostic tools that are able to evaluate the predictive performance of the models. The visual predictive check (VPC) is a commonly used tool that helps the user to check by visual inspection if the model is able to reproduce the variability and the main trend of the observed data. However, the simulation from the model is not always trivial, for example, when using models with time-varying input function (IF). In this class of models, there is a potential mismatch between each set of simulated parameters and the associated individual IF which can cause an incorrect profile simulation. We introduce a refinement of the VPC by taking in consideration a correlation term (the Mahalanobis or normalized Euclidean distance) that helps the association of the correct IF with the individual set of simulated parameters. We investigate and compare its performance with the standard VPC in models of the glucose and insulin system applied on real and simulated data and in a simulated pharmacokinetic/pharmacodynamic (PK/PD) example. The newly proposed VPC performance appears to be better with respect to the standard VPC especially for the models with big variability in the IF where the probability of simulating incorrect profiles is higher.
Yang, Jian-Feng; Zhao, Zhen-Hua; Zhang, Yu; Zhao, Li; Yang, Li-Ming; Zhang, Min-Ming; Wang, Bo-Yin; Wang, Ting; Lu, Bao-Chun
2016-04-07
To investigate the feasibility of a dual-input two-compartment tracer kinetic model for evaluating tumorous microvascular properties in advanced hepatocellular carcinoma (HCC). From January 2014 to April 2015, we prospectively measured and analyzed pharmacokinetic parameters [transfer constant (Ktrans), plasma flow (Fp), permeability surface area product (PS), efflux rate constant (kep), extravascular extracellular space volume ratio (ve), blood plasma volume ratio (vp), and hepatic perfusion index (HPI)] using dual-input two-compartment tracer kinetic models [a dual-input extended Tofts model and a dual-input 2-compartment exchange model (2CXM)] in 28 consecutive HCC patients. A well-known consensus that HCC is a hypervascular tumor supplied by the hepatic artery and the portal vein was used as a reference standard. A paired Student's t-test and a nonparametric paired Wilcoxon rank sum test were used to compare the equivalent pharmacokinetic parameters derived from the two models, and Pearson correlation analysis was also applied to observe the correlations among all equivalent parameters. The tumor size and pharmacokinetic parameters were tested by Pearson correlation analysis, while correlations among stage, tumor size and all pharmacokinetic parameters were assessed by Spearman correlation analysis. The Fp value was greater than the PS value (FP = 1.07 mL/mL per minute, PS = 0.19 mL/mL per minute) in the dual-input 2CXM; HPI was 0.66 and 0.63 in the dual-input extended Tofts model and the dual-input 2CXM, respectively. There were no significant differences in the kep, vp, or HPI between the dual-input extended Tofts model and the dual-input 2CXM (P = 0.524, 0.569, and 0.622, respectively). All equivalent pharmacokinetic parameters, except for ve, were correlated in the two dual-input two-compartment pharmacokinetic models; both Fp and PS in the dual-input 2CXM were correlated with Ktrans derived from the dual-input extended Tofts model (P = 0.002, r = 0.566; P
A switchable light-input, light-output system modelled and constructed in yeast
Directory of Open Access Journals (Sweden)
Kozma-Bognar Laszlo
2009-09-01
Full Text Available Abstract Background Advances in synthetic biology will require spatio-temporal regulation of biological processes in heterologous host cells. We develop a light-switchable, two-hybrid interaction in yeast, based upon the Arabidopsis proteins PHYTOCHROME A and FAR-RED ELONGATED HYPOCOTYL 1-LIKE. Light input to this regulatory module allows dynamic control of a light-emitting LUCIFERASE reporter gene, which we detect by real-time imaging of yeast colonies on solid media. Results The reversible activation of the phytochrome by red light, and its inactivation by far-red light, is retained. We use this quantitative readout to construct a mathematical model that matches the system's behaviour and predicts the molecular targets for future manipulation. Conclusion Our model, methods and materials together constitute a novel system for a eukaryotic host with the potential to convert a dynamic pattern of light input into a predictable gene expression response. This system could be applied for the regulation of genetic networks - both known and synthetic.
Single-Phase Bundle Flows Including Macroscopic Turbulence Model
Energy Technology Data Exchange (ETDEWEB)
Lee, Seung Jun; Yoon, Han Young [KAERI, Daejeon (Korea, Republic of); Yoon, Seok Jong; Cho, Hyoung Kyu [Seoul National University, Seoul (Korea, Republic of)
2016-05-15
To deal with various thermal hydraulic phenomena due to rapid change of fluid properties when an accident happens, securing mechanistic approaches as much as possible may reduce the uncertainty arising from improper applications of the experimental models. In this study, the turbulence mixing model, which is well defined in the subchannel analysis code such as VIPRE, COBRA, and MATRA by experiments, is replaced by a macroscopic k-e turbulence model, which represents the aspect of mathematical derivation. The performance of CUPID with macroscopic turbulence model is validated against several bundle experiments: CNEN 4x4 and PNL 7x7 rod bundle tests. In this study, the macroscopic k-e model has been validated for the application to subchannel analysis. It has been implemented in the CUPID code and validated against CNEN 4x4 and PNL 7x7 rod bundle tests. The results showed that the macroscopic k-e turbulence model can estimate the experiments properly.
On Input Vector Representation for the SVR model of Reactor Core Loading Pattern Critical Parameters
International Nuclear Information System (INIS)
Trontl, K.; Pevec, D.; Smuc, T.
2008-01-01
Determination and optimization of reactor core loading pattern is an important factor in nuclear power plant operation. The goal is to minimize the amount of enriched uranium (fresh fuel) and burnable absorbers placed in the core, while maintaining nuclear power plant operational and safety characteristics. The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. Recently, we proposed a new method for fast loading pattern evaluation based on general robust regression model relying on the state of the art research in the field of machine learning. We employed Support Vector Regression (SVR) technique. SVR is a supervised learning method in which model parameters are automatically determined by solving a quadratic optimization problem. The preliminary tests revealed a good potential of the SVR method application for fast and accurate reactor core loading pattern evaluation. However, some aspects of model development are still unresolved. The main objective of the work reported in this paper was to conduct additional tests and analyses required for full clarification of the SVR applicability for loading pattern evaluation. We focused our attention on the parameters defining input vector, primarily its structure and complexity, and parameters defining kernel functions. All the tests were conducted on the NPP Krsko reactor core, using MCRAC code for the calculation of reactor core loading pattern critical parameters. The tested input vector structures did not influence the accuracy of the models suggesting that the initially tested input vector, consisted of the number of IFBAs and the k-inf at the beginning of the cycle, is adequate. The influence of kernel function specific parameters (σ for RBF kernel
Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke
2017-04-01
Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.
Targeting the right input data to improve crop modeling at global level
Adam, M.; Robertson, R.; Gbegbelegbe, S.; Jones, J. W.; Boote, K. J.; Asseng, S.
2012-12-01
Designed for location-specific simulations, the use of crop models at a global level raises important questions. Crop models are originally premised on small unit areas where environmental conditions and management practices are considered homogeneous. Specific information describing soils, climate, management, and crop characteristics are used in the calibration process. However, when scaling up for global application, we rely on information derived from geographical information systems and weather generators. To run crop models at broad, we use a modeling platform that assumes a uniformly generated grid cell as a unit area. Specific weather, specific soil and specific management practices for each crop are represented for each of the cell grids. Studies on the impacts of the uncertainties of weather information and climate change on crop yield at a global level have been carried out (Osborne et al, 2007, Nelson et al., 2010, van Bussel et al, 2011). Detailed information on soils and management practices at global level are very scarce but recognized to be of critical importance (Reidsma et al., 2009). Few attempts to assess the impact of their uncertainties on cropping systems performances can be found. The objectives of this study are (i) to determine sensitivities of a crop model to soil and management practices, inputs most relevant to low input rainfed cropping systems, and (ii) to define hotspots of sensitivity according to the input data. We ran DSSAT v4.5 globally (CERES-CROPSIM) to simulate wheat yields at 45arc-minute resolution. Cultivar parameters were calibrated and validated for different mega-environments (results not shown). The model was run for nitrogen-limited production systems. This setting was chosen as the most representative to simulate actual yield (especially for low-input rainfed agricultural systems) and assumes crop growth to be free of any pest and diseases damages. We conducted a sensitivity analysis on contrasting management
Global atmospheric model for mercury including oxidation by bromine atoms
Directory of Open Access Journals (Sweden)
C. D. Holmes
2010-12-01
Full Text Available Global models of atmospheric mercury generally assume that gas-phase OH and ozone are the main oxidants converting Hg^{0} to Hg^{II} and thus driving mercury deposition to ecosystems. However, thermodynamic considerations argue against the importance of these reactions. We demonstrate here the viability of atomic bromine (Br as an alternative Hg^{0} oxidant. We conduct a global 3-D simulation with the GEOS-Chem model assuming gas-phase Br to be the sole Hg^{0} oxidant (Hg + Br model and compare to the previous version of the model with OH and ozone as the sole oxidants (Hg + OH/O_{3} model. We specify global 3-D Br concentration fields based on our best understanding of tropospheric and stratospheric Br chemistry. In both the Hg + Br and Hg + OH/O_{3} models, we add an aqueous photochemical reduction of Hg^{II} in cloud to impose a tropospheric lifetime for mercury of 6.5 months against deposition, as needed to reconcile observed total gaseous mercury (TGM concentrations with current estimates of anthropogenic emissions. This added reduction would not be necessary in the Hg + Br model if we adjusted the Br oxidation kinetics downward within their range of uncertainty. We find that the Hg + Br and Hg + OH/O_{3} models are equally capable of reproducing the spatial distribution of TGM and its seasonal cycle at northern mid-latitudes. The Hg + Br model shows a steeper decline of TGM concentrations from the tropics to southern mid-latitudes. Only the Hg + Br model can reproduce the springtime depletion and summer rebound of TGM observed at polar sites; the snowpack component of GEOS-Chem suggests that 40% of Hg^{II} deposited to snow in the Arctic is transferred to the ocean and land reservoirs, amounting to a net deposition flux to the Arctic of 60 Mg a^{−1}. Summertime events of depleted Hg^{0} at Antarctic sites due to subsidence are much better simulated by
Thematic report: Macroeconomic models including specifically social and environmental aspects
Kratena, Kurt
2015-01-01
WWWforEurope Deliverable No. 8, 30 pages A significant reduction of the global environmental consequences of European consumption and production activities are the main objective of the policy simulations carried out in this paper. For this purpose three different modelling approaches have been chosen. Two macroeconomic models following the philosophy of consistent stock-flow accounting for the main institutional sectors (households, firms, banks, central bank and government) are used for...
An Approach for Generating Precipitation Input for Worst-Case Flood Modelling
Felder, Guido; Weingartner, Rolf
2015-04-01
There is a lack of suitable methods for creating precipitation scenarios that can be used to realistically estimate peak discharges with very low probabilities. On the one hand, existing methods are methodically questionable when it comes to physical system boundaries. On the other hand, the spatio-temporal representativeness of precipitation patterns as system input is limited. In response, this study proposes a method of deriving representative spatio-temporal precipitation patterns and presents a step towards making methodically correct estimations of infrequent floods by using a worst-case approach. A Monte-Carlo rainfall-runoff model allows for the testing of a wide range of different spatio-temporal distributions of an extreme precipitation event and therefore for the generation of a hydrograph for each of these distributions. Out of these numerous hydrographs and their corresponding peak discharges, the worst-case catchment reactions on the system input can be derived. The spatio-temporal distributions leading to the highest peak discharges are identified and can eventually be used for further investigations.
National Research Council Canada - National Science Library
Matthew, William
2001-01-01
This report describes processes we have implemented to use global pyranometer-based estimates of mean radiant temperature as the common solar load input for the Scenario model, the USARIEM heat strain...
Marmarelis, Vasilis Z; Zanos, Theodoros P; Berger, Theodore W
2009-08-01
This paper presents a new modeling approach for neural systems with point-process (spike) inputs and outputs that utilizes Boolean operators (i.e. modulo 2 multiplication and addition that correspond to the logical AND and OR operations respectively, as well as the AND_NOT logical operation representing inhibitory effects). The form of the employed mathematical models is akin to a "Boolean-Volterra" model that contains the product terms of all relevant input lags in a hierarchical order, where terms of order higher than first represent nonlinear interactions among the various lagged values of each input point-process or among lagged values of various inputs (if multiple inputs exist) as they reflect on the output. The coefficients of this Boolean-Volterra model are also binary variables that indicate the presence or absence of the respective term in each specific model/system. Simulations are used to explore the properties of such models and the feasibility of their accurate estimation from short data-records in the presence of noise (i.e. spurious spikes). The results demonstrate the feasibility of obtaining reliable estimates of such models, with excitatory and inhibitory terms, in the presence of considerable noise (spurious spikes) in the outputs and/or the inputs in a computationally efficient manner. A pilot application of this approach to an actual neural system is presented in the companion paper (Part II).
Reconstruction of rocks petrophysical properties as input data for reservoir modeling
Cantucci, B.; Montegrossi, G.; Lucci, F.; Quattrocchi, F.
2016-11-01
The worldwide increasing energy demand triggered studies focused on defining the underground energy potential even in areas previously discharged or neglected. Nowadays, geological gas storage (CO2 and/or CH4) and geothermal energy are considered strategic for low-carbon energy development. A widespread and safe application of these technologies needs an accurate characterization of the underground, in terms of geology, hydrogeology, geochemistry, and geomechanics. However, during prefeasibility study-stage, the limited number of available direct measurements of reservoirs, and the high costs of reopening closed deep wells must be taken into account. The aim of this work is to overcome these limits, proposing a new methodology to reconstruct vertical profiles, from surface to reservoir base, of: (i) thermal capacity, (ii) thermal conductivity, (iii) porosity, and (iv) permeability, through integration of well-log information, petrographic observations on inland outcropping samples, and flow and heat transport modeling. As case study to test our procedure we selected a deep structure, located in the medium Tyrrhenian Sea (Italy). Obtained results are consistent with measured data, confirming the validity of the proposed model. Notwithstanding intrinsic limitations due to manual calibration of the model with measured data, this methodology represents an useful tool for reservoir and geochemical modelers that need to define petrophysical input data for underground modeling before the well reopening.
Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models
International Nuclear Information System (INIS)
Lamboni, Matieyendou; Monod, Herve; Makowski, David
2011-01-01
Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006 ) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.
Comparison of several climate indices as inputs in modelling of the Baltic Sea runoff
Energy Technology Data Exchange (ETDEWEB)
Hanninen, J.; Vuorinen, I. [Turku Univ. (Finland). Archipelaco Research Inst.], e-mail: jari.hanninen@utu.fi
2012-11-01
Using Transfer function (TF) models, we have earlier presented a chain of events between changes in the North Atlantic Oscillation (NAO) and their oceanographical and ecological consequences in the Baltic Sea. Here we tested whether other climate indices as inputs would improve TF models, and our understanding of the Baltic Sea ecosystem. Besides NAO, the predictors were the Arctic Oscillation (AO), sea-level air pressures at Iceland (SLP), and wind speeds at Hoburg (Gotland). All indices produced good TF models when the total riverine runoff to the Baltic Sea was used as a modelling basis. AO was not applicable in all study areas, showing a delay of about half a year between climate and runoff events, connected with freezing and melting time of ice and snow in the northern catchment area of the Baltic Sea. NAO appeared to be most useful modelling tool as its area of applicability was the widest of the tested indices, and the time lag between climate and runoff events was the shortest. SLP and Hoburg wind speeds showed largely same results as NAO, but with smaller areal applicability. Thus AO and NAO were both mostly contributing to the general understanding of climate control of runoff events in the Baltic Sea ecosystem. (orig.)
Directory of Open Access Journals (Sweden)
Simone Fiori
2007-07-01
Full Text Available Bivariate statistical modeling from incomplete data is a useful statistical tool that allows to discover the model underlying two data sets when the data in the two sets do not correspond in size nor in ordering. Such situation may occur when the sizes of the two data sets do not match (i.e., there are Ã‚Â“holesÃ‚Â” in the data or when the data sets have been acquired independently. Also, statistical modeling is useful when the amount of available data is enough to show relevant statistical features of the phenomenon underlying the data. We propose to tackle the problem of statistical modeling via a neural (nonlinear system that is able to match its input-output statistic to the statistic of the available data sets. A key point of the new implementation proposed here is that it is based on look-up-table (LUT neural systems, which guarantee a computationally advantageous way of implementing neural systems. A number of numerical experiments, performed on both synthetic and real-world data sets, illustrate the features of the proposed modeling procedure.
Identifying Clusters with Mixture Models that Include Radial Velocity Observations
Czarnatowicz, Alexis; Ybarra, Jason E.
2018-01-01
The study of stellar clusters plays an integral role in the study of star formation. We present a cluster mixture model that considers radial velocity data in addition to spatial data. Maximum likelihood estimation through the Expectation-Maximization (EM) algorithm is used for parameter estimation. Our mixture model analysis can be used to distinguish adjacent or overlapping clusters, and estimate properties for each cluster.Work supported by awards from the Virginia Foundation for Independent Colleges (VFIC) Undergraduate Science Research Fellowship and The Research Experience @Bridgewater (TREB).
Unsteady panel method for complex configurations including wake modeling
CSIR Research Space (South Africa)
Van Zyl, Lourens H
2008-01-01
Full Text Available The calculation of unsteady air loads is an essential step in any aeroelastic analysis. The subsonic doublet lattice method (DLM) is used extensively for this purpose due to its simplicity and reliability. The body models available with the popular...
DEFF Research Database (Denmark)
2014-01-01
The present invention proposes methods, devices and computer program products. To this extent, there is defined a set X including N distinct parameter values x_i for at least one input parameter x, N being an integer greater than or equal to 1, first measured the physical quantity Pm1 for each...... based on the Vandermonde matrix and the first measured physical quantity according to the equation W=(VMT*VM)-1*VMT*Pm1. The model is iteratively refined so as to obtained a desired emulation precision.; The model can later be used to emulate the physical quantity based on input parameters or logs taken...
van der Zijden, A M; Groen, B E; Tanck, E; Nienhuis, B; Verdonschot, N; Weerdesteyn, V
2017-03-21
Many research groups have studied fall impact mechanics to understand how fall severity can be reduced to prevent hip fractures. Yet, direct impact force measurements with force plates are restricted to a very limited repertoire of experimental falls. The purpose of this study was to develop a generic model for estimating hip impact forces (i.e. fall severity) in in vivo sideways falls without the use of force plates. Twelve experienced judokas performed sideways Martial Arts (MA) and Block ('natural') falls on a force plate, both with and without a mat on top. Data were analyzed to determine the hip impact force and to derive 11 selected (subject-specific and kinematic) variables. Falls from kneeling height were used to perform a stepwise regression procedure to assess the effects of these input variables and build the model. The final model includes four input variables, involving one subject-specific measure and three kinematic variables: maximum upper body deceleration, body mass, shoulder angle at the instant of 'maximum impact' and maximum hip deceleration. The results showed that estimated and measured hip impact forces were linearly related (explained variances ranging from 46 to 63%). Hip impact forces of MA falls onto the mat from a standing position (3650±916N) estimated by the final model were comparable with measured values (3698±689N), even though these data were not used for training the model. In conclusion, a generic linear regression model was developed that enables the assessment of fall severity through kinematic measures of sideways falls, without using force plates. Copyright © 2017 Elsevier Ltd. All rights reserved.
Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David
2011-01-01
This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations
Directory of Open Access Journals (Sweden)
Faa Jeng Lin
2016-11-01
Full Text Available This paper outlines the modeling and controller design of a novel two-stage photovoltaic (PV micro inverter (MI that eliminates the need for an electrolytic capacitor (E-cap and input current sensor. The proposed MI uses an active-clamped current-fed push-pull DC-DC converter, cascaded with a full-bridge inverter. Three strategies are proposed to cope with the inherent limitations of a two-stage PV MI: (i high-speed DC bus voltage regulation using an integrator to deal with the 2nd harmonic voltage ripples found in single-phase systems; (ii inclusion of a small film capacitor in the DC bus to achieve ripple-free PV voltage; (iii improved incremental conductance (INC maximum power point tracking (MPPT without the need for current sensing by the PV module. Simulation and experimental results demonstrate the efficacy of the proposed system.
International Nuclear Information System (INIS)
1978-07-01
A static model in the form of a regional input-output model was constructed for Eddy and Lea Counties, New Mexico. Besides the WIPP project, the model was also used for several other projects to determine the economic impact of proposed new facilities and developments. Both private and public sectors are covered. Sub-sectors for WIPP below-ground construction, above-ground construction, and operation and transport are included
A thermal lens model including the Soret effect
International Nuclear Information System (INIS)
Cabrera, Humberto; Sira, Eloy; Rahn, Kareem; Garcia-Sucre, Maximo
2009-01-01
In this letter we generalize the thermal lens model to account for the Soret effect in binary liquid mixtures. This formalism permits the precise determination of the Soret coefficient in a steady-state situation. The theory is experimentally verified using the measured values in the ethanol/water mixtures. The time evolution of the Soret signal has been used to derive mass-diffusion times from which mass-diffusion coefficients were calculated. (Author)
Including lateral interactions into microkinetic models of catalytic reactions
DEFF Research Database (Denmark)
Hellman, Anders; Honkala, Johanna Karoliina
2007-01-01
In many catalytic reactions lateral interactions between adsorbates are believed to have a strong influence on the reaction rates. We apply a microkinetic model to explore the effect of lateral interactions and how to efficiently take them into account in a simple catalytic reaction. Three differ...... different approximations are investigated: site, mean-field, and quasichemical approximations. The obtained results are compared to accurate Monte Carlo numbers. In the end, we apply the approximations to a real catalytic reaction, namely, ammonia synthesis....
A stochastic model of gene expression including splicing events
Penim, Flávia Alexandra Mendes
2014-01-01
Tese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2014 Proteins carry out the great majority of the catalytic and structural work within an organism. The RNA templates used in their synthesis determines their identity, and this is dictated by which genes are transcribed. Therefore, gene expression is the fundamental determinant of an organism’s nature. The main objective of this thesis was to develop a stochastic computational model a...
Xu, R.; Tian, H.; Pan, S.; Yang, J.; Lu, C.; Zhang, B.
2016-12-01
Human activities have caused significant perturbations of the nitrogen (N) cycle, resulting in about 21% increase of atmospheric N2O concentration since the pre-industrial era. This large increase is mainly caused by intensive agricultural activities including the application of nitrogen fertilizer and the expansion of leguminous crops. Substantial efforts have been made to quantify the global and regional N2O emission from agricultural soils in the last several decades using a wide variety of approaches, such as ground-based observation, atmospheric inversion, and process-based model. However, large uncertainties exist in those estimates as well as methods themselves. In this study, we used a coupled biogeochemical model (DLEM) to estimate magnitude, spatial, and temporal patterns of N2O emissions from global croplands in the past five decades (1961-2012). To estimate uncertainties associated with input data and model parameters, we have implemented a number of simulation experiments with DLEM, accounting for key parameter values that affect calculation of N2O fluxes (i.e., maximum nitrification and denitrification rates, N fixation rate, and the adsorption coefficient for soil ammonium and nitrate), different sets of input data including climate, land management practices (i.e., nitrogen fertilizer types, application rates and timings, with/without irrigation), N deposition, and land use and land cover change. This work provides a robust estimate of global N2O emissions from agricultural soils as well as identifies key gaps and limitations in the existing model and data that need to be investigated in the future.
Modelling and control of a microgrid including photovoltaic and wind generation
Hussain, Mohammed Touseef
Extensive increase of distributed generation (DG) penetration and the existence of multiple DG units at distribution level have introduced the notion of micro-grid. This thesis develops a detailed non-linear and small-signal dynamic model of a microgrid that includes PV, wind and conventional small scale generation along with their power electronics interfaces and the filters. The models developed evaluate the amount of generation mix from various DGs for satisfactory steady state operation of the microgrid. In order to understand the interaction of the DGs on microgrid system initially two simpler configurations were considered. The first one consists of microalternator, PV and their electronics, and the second system consists of microalternator and wind system each connected to the power system grid. Nonlinear and linear state space model of each microgrid are developed. Small signal analysis showed that the large participation of PV/wind can drive the microgrid to the brink of unstable region without adequate control. Non-linear simulations are carried out to verify the results obtained through small-signal analysis. The role of the extent of generation mix of a composite microgrid consisting of wind, PV and conventional generation was investigated next. The findings of the smaller systems were verified through nonlinear and small signal modeling. A central supervisory capacitor energy storage controller interfaced through a STATCOM was proposed to monitor and enhance the microgrid operation. The potential of various control inputs to provide additional damping to the system has been evaluated through decomposition techniques. The signals identified to have damping contents were employed to design the supervisory control system. The controller gains were tuned through an optimal pole placement technique. Simulation studies demonstrate that the STATCOM voltage phase angle and PV inverter phase angle were the best inputs for enhanced stability boundaries.
Directory of Open Access Journals (Sweden)
Mansoureh Ashghali-Farahani
2018-01-01
Full Text Available Background: Weakness of curriculum development in nursing education results in lack of professional skills in graduates. This study was done on master's students in nursing to evaluate challenges of neonatal intensive care nursing curriculum based on context, input, process, and product (CIPP evaluation model. Materials and Methods: This study was conducted with qualitative approach, which was completed according to the CIPP evaluation model. The study was conducted from May 2014 to April 2015. The research community included neonatal intensive care nursing master's students, the graduates, faculty members, neonatologists, nurses working in neonatal intensive care unit (NICU, and mothers of infants who were hospitalized in such wards. Purposeful sampling was applied. Results: The data analysis showed that there were two main categories: “inappropriate infrastructure” and “unknown duties,” which influenced the context formation of NICU master's curriculum. The input was formed by five categories, including “biomedical approach,” “incomprehensive curriculum,” “lack of professional NICU nursing mentors,” “inappropriate admission process of NICU students,” and “lack of NICU skill labs.” Three categories were extracted in the process, including “more emphasize on theoretical education,” “the overlap of credits with each other and the inconsistency among the mentors,” and “ineffective assessment.” Finally, five categories were extracted in the product, including “preferring routine work instead of professional job,” “tendency to leave the job,” “clinical incompetency of graduates,” “the conflict between graduates and nursing staff expectations,” and “dissatisfaction of graduates.” Conclusions: Some changes are needed in NICU master's curriculum by considering the nursing experts' comments and evaluating the consequences of such program by them.
Parton recombination model including resonance production. RL-78-040
International Nuclear Information System (INIS)
Roberts, R.G.; Hwa, R.C.; Matsuda, S.
1978-05-01
Possible effects of resonance production on the meson inclusive distribution in the fragmentation region are investigated in the framework of the parton recombination model. From a detailed study of the data on vector-meson production, a reliable ratio of the vector-to-pseudoscalar rates is determined. Then the influence of the decay of the vector mesons on the pseudoscalar spectrum is examined, and the effect found to be no more than 25% for x > 0.5. The normalization of the non-strange antiquark distributions are still higher than those in a quiescent proton. The agreement between the calculated results and data remain very good. 36 references
Extending PSA models including ageing and asset management - 15291
International Nuclear Information System (INIS)
Martorell, S.; Marton, I.; Carlos, S.; Sanchez, A.I.
2015-01-01
This paper proposes a new approach to Ageing Probabilistic Safety Assessment (APSA) modelling, which is intended to be used to support risk-informed decisions on the effectiveness of maintenance management programs and technical specification requirements of critical equipment of Nuclear Power Plants (NPP) within the framework of the Risk Informed Decision Making according to R.G. 1.174 principles. This approach focuses on the incorporation of not only equipment ageing but also effectiveness of maintenance and efficiency of surveillance testing explicitly into APSA models and data. This methodology is applied to a motor-operated valve of the auxiliary feed water system (AFWS) of a PWR. This simple example of application focuses on a critical safety-related equipment of a NPP in order to evaluate the risk impact of considering different approaches to APSA and the combined effect of equipment ageing and maintenance and testing alternatives along NPP design life. The risk impact of several alternatives in maintenance strategy is discussed
Energy Technology Data Exchange (ETDEWEB)
Carey, D.C.
1999-12-09
TURTLE is a computer program useful for determining many characteristics of a particle beam once an initial design has been achieved, Charged particle beams are usually designed by adjusting various beam line parameters to obtain desired values of certain elements of a transfer or beam matrix. Such beam line parameters may describe certain magnetic fields and their gradients, lengths and shapes of magnets, spacings between magnetic elements, or the initial beam accepted into the system. For such purposes one typically employs a matrix multiplication and fitting program such as TRANSPORT. TURTLE is designed to be used after TRANSPORT. For convenience of the user, the input formats of the two programs have been made compatible. The use of TURTLE should be restricted to beams with small phase space. The lumped element approximation, described below, precludes the inclusion of the effect of conventional local geometric aberrations (due to large phase space) or fourth and higher order. A reading of the discussion below will indicate clearly the exact uses and limitations of the approach taken in TURTLE.
International Nuclear Information System (INIS)
Carey, D.C.
1999-01-01
TURTLE is a computer program useful for determining many characteristics of a particle beam once an initial design has been achieved, Charged particle beams are usually designed by adjusting various beam line parameters to obtain desired values of certain elements of a transfer or beam matrix. Such beam line parameters may describe certain magnetic fields and their gradients, lengths and shapes of magnets, spacings between magnetic elements, or the initial beam accepted into the system. For such purposes one typically employs a matrix multiplication and fitting program such as TRANSPORT. TURTLE is designed to be used after TRANSPORT. For convenience of the user, the input formats of the two programs have been made compatible. The use of TURTLE should be restricted to beams with small phase space. The lumped element approximation, described below, precludes the inclusion of the effect of conventional local geometric aberrations (due to large phase space) or fourth and higher order. A reading of the discussion below will indicate clearly the exact uses and limitations of the approach taken in TURTLE
Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty
Directory of Open Access Journals (Sweden)
K. Steffens
2014-02-01
Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.
Realistic modeling of seismic input for megacities and large urban areas
International Nuclear Information System (INIS)
Panza, Giuliano F.; Alvarez, Leonardo; Aoudia, Abdelkrim
2002-06-01
The project addressed the problem of pre-disaster orientation: hazard prediction, risk assessment, and hazard mapping, in connection with seismic activity and man-induced vibrations. The definition of realistic seismic input has been obtained from the computation of a wide set of time histories and spectral information, corresponding to possible seismotectonic scenarios for different source and structural models. The innovative modeling technique, that constitutes the common tool to the entire project, takes into account source, propagation and local site effects. This is done using first principles of physics about wave generation and propagation in complex media, and does not require to resort to convolutive approaches, that have been proven to be quite unreliable, mainly when dealing with complex geological structures, the most interesting from the practical point of view. In fact, several techniques that have been proposed to empirically estimate the site effects using observations convolved with theoretically computed signals corresponding to simplified models, supply reliable information about the site response to non-interfering seismic phases. They are not adequate in most of the real cases, when the seismic sequel is formed by several interfering waves. The availability of realistic numerical simulations enables us to reliably estimate the amplification effects even in complex geological structures, exploiting the available geotechnical, lithological, geophysical parameters, topography of the medium, tectonic, historical, palaeoseismological data, and seismotectonic models. The realistic modeling of the ground motion is a very important base of knowledge for the preparation of groundshaking scenarios that represent a valid and economic tool for the seismic microzonation. This knowledge can be very fruitfully used by civil engineers in the design of new seismo-resistant constructions and in the reinforcement of the existing built environment, and, therefore
Predicting musically induced emotions from physiological inputs: Linear and neural network models
Directory of Open Access Journals (Sweden)
Frank A. Russo
2013-08-01
Full Text Available Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of 'felt' emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants – heart rate, respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a nonlinear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The nonlinear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the nonlinear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.
Murata, Atsuo; Fukunaga, Daichi
2018-04-01
This study attempted to investigate the effects of the target shape and the movement direction on the pointing time using an eye-gaze input system and extend Fitts' model so that these factors are incorporated into the model and the predictive power of Fitts' model is enhanced. The target shape, the target size, the movement distance, and the direction of target presentation were set as within-subject experimental variables. The target shape included: a circle, and rectangles with an aspect ratio of 1:1, 1:2, 1:3, and 1:4. The movement direction included eight directions: upper, lower, left, right, upper left, upper right, lower left, and lower right. On the basis of the data for identifying the effects of the target shape and the movement direction on the pointing time, an attempt was made to develop a generalized and extended Fitts' model that took into account the movement direction and the target shape. As a result, the generalized and extended model was found to fit better to the experimental data, and be more effective for predicting the pointing time for a variety of human-computer interaction (HCI) task using an eye-gaze input system. Copyright © 2017. Published by Elsevier Ltd.
I. M. Yassin; M. F. Abdul Khalid; S. H. Herman; I. Pasya; N. Ab Wahab; Z. Awang
2017-01-01
The prediction of stocks in the stock market is important in investment as it would help the investor to time buy and sell transactions to maximize profits. In this paper, a Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) model was used to predict the prices of the Apple Inc. weekly stock prices over a time horizon of 1995 to 2013. The NARX model belongs is a system identification model that constructs a mathematical model from the dynamic input/outpu...
"Updates to Model Algorithms & Inputs for the Biogenic Emissions Inventory System (BEIS) Model"
We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observatio...
Modelling Implicit Communication in Multi-Agent Systems with Hybrid Input/Output Automata
Directory of Open Access Journals (Sweden)
Marta Capiluppi
2012-10-01
Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. To this end we decided to specialize some variables of the HIOAs whose values are functions both of time and space. We call them world variables. Basically they are treated similarly to the other variables of HIOAs, but they have the function of representing the interaction of each automaton with the surrounding environment, hence they can be output, input or internal variables. Since these special variables have the role of simulating implicit communication, their dynamics are specified both in time and space, because they model the perturbations induced by the agent to the environment, and the perturbations of the environment as perceived by the agent. Parallel composition of world variables is slightly different from parallel composition of the other variables, since their signals are summed. The theory is illustrated through a simple example of agents systems.
Effects of model input data uncertainty in simulating water resources of a transnational catchment
Camargos, Carla; Breuer, Lutz
2016-04-01
Landscape consists of different ecosystem components and how these components affect water quantity and quality need to be understood. We start from the assumption that water resources are generated in landscapes and that rural land use (particular agriculture) has a strong impact on water resources that are used downstream for domestic and industrial supply. Partly located in the north of Luxembourg and partly in the southeast of Belgium, the Haute-Sûre catchment is about 943 km2. As part of the catchment, the Haute-Sûre Lake is an important source of drinking water for Luxembourg population, satisfying 30% of the city's demand. The objective of this study is investigate impact of spatial input data uncertainty on water resources simulations for the Haute-Sûre catchment. We apply the SWAT model for the period 2006 to 2012 and use a variety of digital information on soils, elevation and land uses with various spatial resolutions. Several objective functions are being evaluated and we consider resulting parameter uncertainty to quantify an important part of the global uncertainty in model simulations.
El Haimar, Amine; Santos, Joost R
2014-03-01
Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input-output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as-planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health-care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics. © 2013 Society for Risk Analysis.
Modeling imbalanced economic recovery following a natural disaster using input-output analysis.
Li, Jun; Crawford-Brown, Douglas; Syddall, Mark; Guan, Dabo
2013-10-01
Input-output analysis is frequently used in studies of large-scale weather-related (e.g., Hurricanes and flooding) disruption of a regional economy. The economy after a sudden catastrophe shows a multitude of imbalances with respect to demand and production and may take months or years to recover. However, there is no consensus about how the economy recovers. This article presents a theoretical route map for imbalanced economic recovery called dynamic inequalities. Subsequently, it is applied to a hypothetical postdisaster economic scenario of flooding in London around the year 2020 to assess the influence of future shocks to a regional economy and suggest adaptation measures. Economic projections are produced by a macro econometric model and used as baseline conditions. The results suggest that London's economy would recover over approximately 70 months by applying a proportional rationing scheme under the assumption of initial 50% labor loss (with full recovery in six months), 40% initial loss to service sectors, and 10-30% initial loss to other sectors. The results also suggest that imbalance will be the norm during the postdisaster period of economic recovery even though balance may occur temporarily. Model sensitivity analysis suggests that a proportional rationing scheme may be an effective strategy to apply during postdisaster economic reconstruction, and that policies in transportation recovery and in health care are essential for effective postdisaster economic recovery. © 2013 Society for Risk Analysis.
Ning, Jia; Schubert, Tilman; Johnson, Kevin M; Roldán-Alzate, Alejandro; Chen, Huijun; Yuan, Chun; Reeder, Scott B
2018-06-01
To propose a simple method to correct vascular input function (VIF) due to inflow effects and to test whether the proposed method can provide more accurate VIFs for improved pharmacokinetic modeling. A spoiled gradient echo sequence-based inflow quantification and contrast agent concentration correction method was proposed. Simulations were conducted to illustrate improvement in the accuracy of VIF estimation and pharmacokinetic fitting. Animal studies with dynamic contrast-enhanced MR scans were conducted before, 1 week after, and 2 weeks after portal vein embolization (PVE) was performed in the left portal circulation of pigs. The proposed method was applied to correct the VIFs for model fitting. Pharmacokinetic parameters fitted using corrected and uncorrected VIFs were compared between different lobes and visits. Simulation results demonstrated that the proposed method can improve accuracy of VIF estimation and pharmacokinetic fitting. In animal study results, pharmacokinetic fitting using corrected VIFs demonstrated changes in perfusion consistent with changes expected after PVE, whereas the perfusion estimates derived by uncorrected VIFs showed no significant changes. The proposed correction method improves accuracy of VIFs and therefore provides more precise pharmacokinetic fitting. This method may be promising in improving the reliability of perfusion quantification. Magn Reson Med 79:3093-3102, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Three-scale input-output modeling for urban economy: Carbon emission by Beijing 2007
Chen, G. Q.; Guo, Shan; Shao, Ling; Li, J. S.; Chen, Zhan-Ming
2013-09-01
For urban economies, an ecological endowment embodiment analysis has to be supported by endowment intensities at both the international and domestic scales to reflect the international and domestic imports of increasing importance. A three-scale input-output modeling for an urban economy to give nine categories of embodiment fluxes is presented in this paper by a case study on the carbon dioxide emissions by the Beijing economy in 2007, based on the carbon intensities for the average world and national economies. The total direct emissions are estimated at 1.03E+08 t, in which 91.61% is energy-related emissions. By the modeling, emissions embodied in fixed capital formation amount to 7.20E+07 t, emissions embodied in household consumption are 1.58 times those in government consumption, and emissions in gross capital formation are 14.93% more than those in gross consumption. As a net exporter of carbon emissions, Beijing exports 5.21E+08 t carbon embodied in foreign imported commodities and 1.06E+08 t in domestic imported commodities, while emissions embodied in foreign and domestic imported commodities are 3.34E+07 and 1.75E+08 t respectively. The algorithm presented in this study is applicable to the embodiment analysis of other environmental resources for regional economies characteristic of multi-scales.
Three-Verb Clusters in Interference Frisian: A Stochastic Model over Sequential Syntactic Input.
Hoekstra, Eric; Versloot, Arjen
2016-03-01
Abstract Interference Frisian (IF) is a variety of Frisian, spoken by mostly younger speakers, which is heavily influenced by Dutch. IF exhibits all six logically possible word orders in a cluster of three verbs. This phenomenon has been researched by Koeneman and Postma (2006), who argue for a parameter theory, which leaves frequency differences between various orders unexplained. Rejecting Koeneman and Postma's parameter theory, but accepting their conclusion that Dutch (and Frisian) data are input for the grammar of IF, we will argue that the word order preferences of speakers of IF are determined by frequency and similarity. More specifically, three-verb clusters in IF are sensitive to: their linear left-to-right similarity to two-verb clusters and three-verb clusters in Frisian and in Dutch; the (estimated) frequency of two- and three-verb clusters in Frisian and Dutch. The model will be shown to work best if Dutch and Frisian, and two- and three-verb clusters, have equal impact factors. If different impact factors are taken, the model's predictions do not change substantially, testifying to its robustness. This analysis is in line with recent ideas that the sequential nature of human speech is more important to syntactic processes than commonly assumed, and that less burden need be put on the hierarchical dimension of syntactic structure.
Realistic modelling of the seismic input: Site effects and parametric studies
International Nuclear Information System (INIS)
Romanelli, F.; Vaccari, F.; Panza, G.F.
2002-11-01
We illustrate the work done in the framework of a large international cooperation, showing the very recent numerical experiments carried out within the framework of the EC project 'Advanced methods for assessing the seismic vulnerability of existing motorway bridges' (VAB) to assess the importance of non-synchronous seismic excitation of long structures. The definition of the seismic input at the Warth bridge site, i.e. the determination of the seismic ground motion due to an earthquake with a given magnitude and epicentral distance from the site, has been done following a theoretical approach. In order to perform an accurate and realistic estimate of site effects and of differential motion it is necessary to make a parametric study that takes into account the complex combination of the source and propagation parameters, in realistic geological structures. The computation of a wide set of time histories and spectral information, corresponding to possible seismotectonic scenarios for different sources and structural models, allows us the construction of damage scenarios that are out of the reach of stochastic models, at a very low cost/benefit ratio. (author)
A generalized model for optimal transport of images including dissipation and density modulation
Maas, Jan
2015-11-01
© EDP Sciences, SMAI 2015. In this paper the optimal transport and the metamorphosis perspectives are combined. For a pair of given input images geodesic paths in the space of images are defined as minimizers of a resulting path energy. To this end, the underlying Riemannian metric measures the rate of transport cost and the rate of viscous dissipation. Furthermore, the model is capable to deal with strongly varying image contrast and explicitly allows for sources and sinks in the transport equations which are incorporated in the metric related to the metamorphosis approach by Trouvé and Younes. In the non-viscous case with source term existence of geodesic paths is proven in the space of measures. The proposed model is explored on the range from merely optimal transport to strongly dissipative dynamics. For this model a robust and effective variational time discretization of geodesic paths is proposed. This requires to minimize a discrete path energy consisting of a sum of consecutive image matching functionals. These functionals are defined on corresponding pairs of intensity functions and on associated pairwise matching deformations. Existence of time discrete geodesics is demonstrated. Furthermore, a finite element implementation is proposed and applied to instructive test cases and to real images. In the non-viscous case this is compared to the algorithm proposed by Benamou and Brenier including a discretization of the source term. Finally, the model is generalized to define discrete weighted barycentres with applications to textures and objects.
Energy Technology Data Exchange (ETDEWEB)
Achatz, M. [Bundesamt fuer Strahlenschutz, Berlin (Germany); Urso, L. [Bundesamt fuer Strahlenschutz, Oberschleissheim (Germany)
2016-07-01
87 % of mineral phosphate fertilizers are produced of sedimentary rock phosphate, which generally contains heavy metals, like uranium. The solution and migration behavior of uranium is apart from its redox ratio, determined by its pH conditions as well as its ligand quality and quantity. A further important role in sorption is played by soil components like clay minerals, pedogenic oxides and soil organic matter. To provide a preferably detailed speciation model of U in soil several physical and chemical components have to be included to be able to state distribution coefficients (k{sub D}) and sorption processes. The model of Hormann and Fischer served as the basis of modelling uranium mobility in soil by using the program PhreeqC. The usage of real soil and soil water measurements may contribute to identify factors and processes influencing the mobility of uranium under preferably realistic conditions. Additionally, the assessment of further predictions towards uranium migration in soil can be made based on a modelling with PhreeqC. The modelling of uranium inputs and its fate in soil can help to elucidate the human caused occurrence or geogenic origin of uranium in soil.
Karandish, Fatemeh; Šimůnek, Jiří
2016-12-01
Soil water content (SWC) is a key factor in optimizing the usage of water resources in agriculture since it provides information to make an accurate estimation of crop water demand. Methods for predicting SWC that have simple data requirements are needed to achieve an optimal irrigation schedule, especially for various water-saving irrigation strategies that are required to resolve both food and water security issues under conditions of water shortages. Thus, a two-year field investigation was carried out to provide a dataset to compare the effectiveness of HYDRUS-2D, a physically-based numerical model, with various machine-learning models, including Multiple Linear Regressions (MLR), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Support Vector Machines (SVM), for simulating time series of SWC data under water stress conditions. SWC was monitored using TDRs during the maize growing seasons of 2010 and 2011. Eight combinations of six, simple, independent parameters, including pan evaporation and average air temperature as atmospheric parameters, cumulative growth degree days (cGDD) and crop coefficient (Kc) as crop factors, and water deficit (WD) and irrigation depth (In) as crop stress factors, were adopted for the estimation of SWCs in the machine-learning models. Having Root Mean Square Errors (RMSE) in the range of 0.54-2.07 mm, HYDRUS-2D ranked first for the SWC estimation, while the ANFIS and SVM models with input datasets of cGDD, Kc, WD and In ranked next with RMSEs ranging from 1.27 to 1.9 mm and mean bias errors of -0.07 to 0.27 mm, respectively. However, the MLR models did not perform well for SWC forecasting, mainly due to non-linear changes of SWCs under the irrigation process. The results demonstrated that despite requiring only simple input data, the ANFIS and SVM models could be favorably used for SWC predictions under water stress conditions, especially when there is a lack of data. However, process-based numerical models are undoubtedly a
Directory of Open Access Journals (Sweden)
S. C. van Pelt
2009-12-01
Full Text Available Studies have demonstrated that precipitation on Northern Hemisphere mid-latitudes has increased in the last decades and that it is likely that this trend will continue. This will have an influence on discharge of the river Meuse. The use of bias correction methods is important when the effect of precipitation change on river discharge is studied. The objective of this paper is to investigate the effect of using two different bias correction methods on output from a Regional Climate Model (RCM simulation. In this study a Regional Atmospheric Climate Model (RACMO2 run is used, forced by ECHAM5/MPIOM under the condition of the SRES-A1B emission scenario, with a 25 km horizontal resolution. The RACMO2 runs contain a systematic precipitation bias on which two bias correction methods are applied. The first method corrects for the wet day fraction and wet day average (WD bias correction and the second method corrects for the mean and coefficient of variance (MV bias correction. The WD bias correction initially corrects well for the average, but it appears that too many successive precipitation days were removed with this correction. The second method performed less well on average bias correction, but the temporal precipitation pattern was better. Subsequently, the discharge was calculated by using RACMO2 output as forcing to the HBV-96 hydrological model. A large difference was found between the simulated discharge of the uncorrected RACMO2 run, the WD bias corrected run and the MV bias corrected run. These results show the importance of an appropriate bias correction.
Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M
2017-10-01
Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal
DEFF Research Database (Denmark)
Keel, S G; Leifeld, Jens; Mayer, Julius
2017-01-01
referred to as soil carbon inputs (C). The soil C inputs from plants are derived from measured agricultural yields using allometric equations. Here we compared the results of five previously published equations. Our goal was to test whether the choice of method is critical for modelling soil C and if so...... with the model C-TOOL showed that calculated SOC stocks were affected strongly by the choice of the allometric equation. With four equations, a decrease in SOC stocks was simulated, whereas with one equation there was no change. This considerable uncertainty in modelled soil C is attributable solely...... to the allometric equation used to estimate the soil C input. We identify the evaluation and selection of allometric equations and associated coefficients as critical steps when setting up a model-based soil C inventory for agricultural systems....
Milzow, C.; Kgotlhang, L.; Kinzelbach, W.; Bauer-Gottwein, P.
2006-12-01
medium-term. The Delta's size and limited accessibility make direct data acquisition on the ground difficult. Remote sensing methods are the most promising source of acquiring spatially distributed data for both, model input and calibration. Besides ground data, METEOSAT and NOAA data are used for precipitation and evapotranspiration inputs respectively. The topography is taken from a study from Gumbricht et al. (2004) where the SRTM shuttle mission data is refined using remotely sensed vegetation indexes. The aquifer thickness was determined with an aeromagnetic survey. For calibration, the simulated flooding patterns are compared to patterns derived from satellite imagery: recent ENVISAT ASAR and older NOAA AVHRR scenes. The final objective is to better understand the hydrological and hydraulic aspects of this complex ecosystem and eventually predict the consequences of human interventions. It will provide a tool for decision makers involved to assess the impact of possible upstream dams and water abstraction scenarios.
International Nuclear Information System (INIS)
Penner, J.E.; Haselman, L.C. Jr.
1985-04-01
Smoke from fires produced in the aftermath of a major nuclear exchange has been predicted to cause large decreases in land surface temperatures. The extent of the decrease and even the sign of the temperature change depend on the optical characteristics of the smoke and how it is distributed with altitude. The height distribution of smoke over a fire is determined by the amount of buoyant energy produced by the fire and the amount of energy released by the latent heat of condensation of water vapor. The optical properties of the smoke depend on the size distribution of smoke particles which changes due to coagulation within the lofted plume. We present calculations demonstrating these processes and estimate their importance for the smoke source term input for climate models. For high initial smoke densities and for absorbing smoke ( m = 1.75 - 0.3i), coagulation of smoke particles within the smoke plume is predicted to first increase, then decrease, the size-integrated extinction cross section. However, at the smoke densities predicted in our model (assuming a 3% emission rate for smoke) and for our assumed initial size distribution, the attachment rates for brownian and turbulent collision processes are not fast enough to alter the smoke size distribution enough to significantly change the integrated extinction cross section. Early-time coagulation is, however, fast enough to allow further coagulation, on longer time scales, to act to decrease the extinction cross section. On these longer time scales appropriate to climate models, coagulation can decrease the extinction cross section by almost a factor of two before the smoke becomes well mixed around the globe. This process has been neglected in past climate effect evaluations, but could have a significant effect, since the extinction cross section enters as an exponential factor in calculating the light attenuation due to smoke. 10 refs., 20 figs
Jones, Belinda; Hopkins, Genevieve; Wherry, Sally-Anne; Lueck, Christian J; Das, Chandi P; Dugdale, Paul
2016-01-01
A nurse-led Parkinson's service was introduced at Canberra Hospital and Health Services in 2012 with the primary objective of improving the care and self-management of people with a diagnosis of Parkinson's disease (PD) and related movement disorders. Other objectives of the Service included improving the quality of life of patients with PD and reducing their caregiver burden, improving the knowledge and understanding of PD among healthcare professionals, and reducing unnecessary hospital admissions. This article evaluates the first 2 years of this Service. The Context, Input, Process, and Product Evaluation Model was used to evaluate the Parkinson's and Movement Disorder Service. The context evaluation was conducted through discussions with stakeholders, review of PD guidelines and care pathways, and assessment of service gaps. Input: The input evaluation was carried out by reviewing the resources and strategies used in the development of the Service. The process evaluation was undertaken by reviewing the areas of the implementation that went well and identifying issues and ongoing gaps in service provision. Product: Finally, product evaluation was undertaken by conducting stakeholder interviews and surveying patients in order to assess their knowledge and perception of value, and the patient experience of the Service. Admission data before and after implementation of the Parkinson's and Movement Disorder Service were also compared for any notable trends. Several gaps in service provision for patients with PD in the Australian Capital Territory were identified, prompting the development of a PD Service to address some of them. Input: Funding for a Parkinson's disease nurse specialist was made available, and existing resources were used to develop clinics, education sessions, and outreach services. Clinics and education sessions were implemented successfully, with positive feedback from patients and healthcare professionals. However, outreach services were limited
Kalicka, Renata; Pietrenko-Dabrowska, Anna
2007-03-01
In the paper MRI measurements are used for assessment of brain tissue perfusion and other features and functions of the brain (cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). Perfusion is an important indicator of tissue viability and functioning as in pathological tissue blood flow, vascular and tissue structure are altered with respect to normal tissue. MRI enables diagnosing diseases at an early stage of their course. The parametric and non-parametric approaches to the identification of MRI models are presented and compared. The non-parametric modeling adopts gamma variate functions. The parametric three-compartmental catenary model, based on the general kinetic model, is also proposed. The parameters of the models are estimated on the basis of experimental data. The goodness of fit of the gamma variate and the three-compartmental models to the data and the accuracy of the parameter estimates are compared. Kalman filtering, smoothing the measurements, was adopted to improve the estimate accuracy of the parametric model. Parametric modeling gives a better fit and better parameter estimates than non-parametric and allows an insight into the functioning of the system. To improve the accuracy optimal experiment design related to the input signal was performed.
Kuik, Friderike; Lauer, Axel; Churkina, Galina; Denier van der Gon, Hugo A. C.; Fenner, Daniel; Mar, Kathleen A.; Butler, Tim M.
2016-12-01
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols
Hanasaki, N.; Kanae, S.; Oki, T.; Masuda, K.; Motoya, K.; Shirakawa, N.; Shen, Y.; Tanaka, K.
2008-07-01
To assess global water availability and use at a subannual timescale, an integrated global water resources model was developed consisting of six modules: land surface hydrology, river routing, crop growth, reservoir operation, environmental flow requirement estimation, and anthropogenic water withdrawal. The model simulates both natural and anthropogenic water flow globally (excluding Antarctica) on a daily basis at a spatial resolution of 1°×1° (longitude and latitude). This first part of the two-feature report describes the six modules and the input meteorological forcing. The input meteorological forcing was provided by the second Global Soil Wetness Project (GSWP2), an international land surface modeling project. Several reported shortcomings of the forcing component were improved. The land surface hydrology module was developed based on a bucket type model that simulates energy and water balance on land surfaces. The crop growth module is a relatively simple model based on concepts of heat unit theory, potential biomass, and a harvest index. In the reservoir operation module, 452 major reservoirs with >1 km3 each of storage capacity store and release water according to their own rules of operation. Operating rules were determined for each reservoir by an algorithm that used currently available global data such as reservoir storage capacity, intended purposes, simulated inflow, and water demand in the lower reaches. The environmental flow requirement module was newly developed based on case studies from around the world. Simulated runoff was compared and validated with observation-based global runoff data sets and observed streamflow records at 32 major river gauging stations around the world. Mean annual runoff agreed well with earlier studies at global and continental scales, and in individual basins, the mean bias was less than ±20% in 14 of the 32 river basins and less than ±50% in 24 basins. The error in the peak was less than ±1 mo in 19 of the 27
The Use of an Eight-Step Instructional Model to Train School Staff in Partner-Augmented Input
Senner, Jill E.; Baud, Matthew R.
2017-01-01
An eight-step instruction model was used to train a self-contained classroom teacher, speech-language pathologist, and two instructional assistants in partner-augmented input, a modeling strategy for teaching augmentative and alternative communication use. With the exception of a 2-hr training session, instruction primarily was conducted during…
Usefulness of non-linear input-output models for economic impact analyses in tourism and recreation
Klijs, J.; Peerlings, J.H.M.; Heijman, W.J.M.
2015-01-01
In tourism and recreation management it is still common practice to apply traditional input–output (IO) economic impact models, despite their well-known limitations. In this study the authors analyse the usefulness of applying a non-linear input–output (NLIO) model, in which price-induced input
Thorndahl, Søren; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer
2016-12-01
Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events - especially in the future climate - it is valuable to be able to simulate these events numerically, both historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper, radar data observations with different spatial and temporal resolution, radar nowcasts of 0-2 h leadtime, and numerical weather models with leadtimes up to 24 h are used as inputs to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on the small town of Lystrup in Denmark, which was flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps in real-time with high resolution radar rainfall data, but rather limited forecast performance in predicting floods with leadtimes more than half an hour.
Energy Technology Data Exchange (ETDEWEB)
NONE
2006-09-15
The Laxemar subarea is the focus for the complete site investigations in the Simpevarp area. The south and southwestern parts of the subarea (the so-called 'focused area') have been designated for focused studies during the remainder of the site investigations. This area, some 5.3 square kilometres in size, is characterised on the surface by an arc shaped body of quartz monzodiorite gently dipping to the north, flanked in the north and south by Aevroe granite. The current report documents work conducted during stage 2.1 of the site-descriptive modelling of the Laxemar subarea. The primary objective of the work performed is to provide feedback to the site investigations at Laxemar to ensure that adequate and timely data and information are obtained during the remaining investigation stage. The work has been conducted in cooperation with the site investigation team at Laxemar and representatives from safety assessment and repository engineering. The principal aim of this joint effort has been to safeguard that adequate data are collected that resolve the remaining issues/uncertainties which are of importance for repository layout and long-term safety. The proposed additional works presented in this report should be regarded as recommended additions and/or modifications in relation to the CSI programme published early 2006. The overall conclusion of the discipline-wise review of critical issues is that the CSI programme overall satisfies the demands to resolve the remaining uncertainties. This is interpreted to be partly a result of the close interaction between the site modelling team, site investigation team and the repository engineering teams, which has been in operation since early 2005. In summary, the performed interpretations and modelling have overall confirmed the version 1.2 results. The exception being Hydrogeology where the new Laxemar 2.1 borehole data suggest more favourable conditions in the south and west parts of the focused area compared
International Nuclear Information System (INIS)
2006-09-01
The Laxemar subarea is the focus for the complete site investigations in the Simpevarp area. The south and southwestern parts of the subarea (the so-called 'focused area') have been designated for focused studies during the remainder of the site investigations. This area, some 5.3 square kilometres in size, is characterised on the surface by an arc shaped body of quartz monzodiorite gently dipping to the north, flanked in the north and south by Aevroe granite. The current report documents work conducted during stage 2.1 of the site-descriptive modelling of the Laxemar subarea. The primary objective of the work performed is to provide feedback to the site investigations at Laxemar to ensure that adequate and timely data and information are obtained during the remaining investigation stage. The work has been conducted in cooperation with the site investigation team at Laxemar and representatives from safety assessment and repository engineering. The principal aim of this joint effort has been to safeguard that adequate data are collected that resolve the remaining issues/uncertainties which are of importance for repository layout and long-term safety. The proposed additional works presented in this report should be regarded as recommended additions and/or modifications in relation to the CSI programme published early 2006. The overall conclusion of the discipline-wise review of critical issues is that the CSI programme overall satisfies the demands to resolve the remaining uncertainties. This is interpreted to be partly a result of the close interaction between the site modelling team, site investigation team and the repository engineering teams, which has been in operation since early 2005. In summary, the performed interpretations and modelling have overall confirmed the version 1.2 results. The exception being Hydrogeology where the new Laxemar 2.1 borehole data suggest more favourable conditions in the south and west parts of the focused area compared with the
Modeling DPOAE input/output function compression: comparisons with hearing thresholds.
Bhagat, Shaum P
2014-09-01
Basilar membrane input/output (I/O) functions in mammalian animal models are characterized by linear and compressed segments when measured near the location corresponding to the characteristic frequency. A method of studying basilar membrane compression indirectly in humans involves measuring distortion-product otoacoustic emission (DPOAE) I/O functions. Previous research has linked compression estimates from behavioral growth-of-masking functions to hearing thresholds. The aim of this study was to compare compression estimates from DPOAE I/O functions and hearing thresholds at 1 and 2 kHz. A prospective correlational research design was performed. The relationship between DPOAE I/O function compression estimates and hearing thresholds was evaluated with Pearson product-moment correlations. Normal-hearing adults (n = 16) aged 22-42 yr were recruited. DPOAE I/O functions (L₂ = 45-70 dB SPL) and two-interval forced-choice hearing thresholds were measured in normal-hearing adults. A three-segment linear regression model applied to DPOAE I/O functions supplied estimates of compression thresholds, defined as breakpoints between linear and compressed segments and the slopes of the compressed segments. Pearson product-moment correlations between DPOAE compression estimates and hearing thresholds were evaluated. A high correlation between DPOAE compression thresholds and hearing thresholds was observed at 2 kHz, but not at 1 kHz. Compression slopes also correlated highly with hearing thresholds only at 2 kHz. The derivation of cochlear compression estimates from DPOAE I/O functions provides a means to characterize basilar membrane mechanics in humans and elucidates the role of compression in tone detection in the 1-2 kHz frequency range. American Academy of Audiology.
Arsad, Roslah; Nasir Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi
2017-09-01
Stock evaluation has always been an interesting problem for investors. In this paper, a comparison regarding the efficiency stocks of listed companies in Bursa Malaysia were made through the application of estimation method of Data Envelopment Analysis (DEA). One of the interesting research subjects in DEA is the selection of appropriate input and output parameter. In this study, DEA was used to measure efficiency of stocks of listed companies in Bursa Malaysia in terms of the financial ratio to evaluate performance of stocks. Based on previous studies and Fuzzy Delphi Method (FDM), the most important financial ratio was selected. The results indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share, price to earnings and debt to equity were the most important ratios. Using expert information, all the parameter were clarified as inputs and outputs. The main objectives were to identify most critical financial ratio, clarify them based on expert information and compute the relative efficiency scores of stocks as well as rank them in the construction industry and material completely. The methods of analysis using Alirezaee and Afsharian’s model were employed in this study, where the originality of Charnes, Cooper and Rhodes (CCR) with the assumption of Constant Return to Scale (CSR) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by the Balance Index. The interested data was made for year 2015 and the population of the research includes accepted companies in stock markets in the construction industry and material (63 companies). According to the ranking, the proposed model can rank completely for 63 companies using selected financial ratio.
Holtrop, Kendal; Chaviano, Casey L; Scott, Jenna C; McNeil Smith, Shardé
2015-11-01
Homeless families in transitional housing face a number of distinct challenges, yet there is little research seeking to guide prevention and intervention work with homeless parents. Informed by the tenets of community-based participatory research, the purpose of this study was to identify relevant components to include in a parenting intervention for this population. Data were gathered from 40 homeless parents through semistructured individual interviews and were analyzed using qualitative content analysis. The resulting 15 categories suggest several topics, approach considerations, and activities that can inform parenting intervention work with homeless families in transitional housing. Study findings are discussed within the context of intervention fidelity versus adaptation, and implications for practice, research, and policy are suggested. This study provides important insights for informing parenting intervention adaptation and implementation efforts with homeless families in transitional housing. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Modeling spray drift and runoff-related inputs of pesticides to receiving water.
Zhang, Xuyang; Luo, Yuzhou; Goh, Kean S
2018-03-01
Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) modeling framework will be useful for assessing the relative exposure from pesticides related to spray drift and runoff in receiving waters and the design of management practices for mitigating pesticide
Prasad, Kanchan; Gorai, Amit Kumar; Goyal, Pramila
2016-03-01
This study aims to develop adaptive neuro-fuzzy inference system (ANFIS) for forecasting of daily air pollution concentrations of five air pollutants [sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particular matters (PM10)] in the atmosphere of a Megacity (Howrah). Air pollution in the city (Howrah) is rising in parallel with the economics and thus observing, forecasting and controlling the air pollution becomes increasingly important due to the health impact. ANFIS serve as a basis for constructing a set of fuzzy IF-THEN rules, with appropriate membership functions to generate the stipulated input-output pairs. The ANFIS model predictor considers the value of meteorological factors (pressure, temperature, relative humidity, dew point, visibility, wind speed, and precipitation) and previous day's pollutant concentration in different combinations as the inputs to predict the 1-day advance and same day air pollution concentration. The concentration value of five air pollutants and seven meteorological parameters of the Howrah city during the period 2009 to 2011 were used for development of the ANFIS model. Collinearity tests were conducted to eliminate the redundant input variables. A forward selection (FS) method is used for selecting the different subsets of input variables. Application of collinearity tests and FS techniques reduces the numbers of input variables and subsets which helps in reducing the computational cost and time. The performances of the models were evaluated on the basis of four statistical indices (coefficient of determination, normalized mean square error, index of agreement, and fractional bias).
Loss and thermal model for power semiconductors including device rating information
DEFF Research Database (Denmark)
Ma, Ke; Bahman, Amir Sajjad; Beczkowski, Szymon
2014-01-01
pre-defined by experience with poor design flexibility. Consequently a more complete loss and thermal model is proposed in this paper, which takes into account not only the electrical loading but also the device rating as input variables. The quantified correlation between the power loss, thermal...
Vrugt, J.A.; Braak, ter C.J.F.; Clark, M.P.; Hyman, J.M.; Robinson, B.A.
2008-01-01
There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled
Automated detection of arterial input function in DSC perfusion MRI in a stroke rat model
Energy Technology Data Exchange (ETDEWEB)
Yeh, M-Y; Liu, H-L [Graduate Institute of Medical Physics and Imaging Science, Chang Gung University, Taoyuan, Taiwan (China); Lee, T-H; Yang, S-T; Kuo, H-H [Stroke Section, Department of Neurology, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan (China); Chyi, T-K [Molecular Imaging Center Chang Gung Memorial Hospital, Taoyuan, Taiwan (China)], E-mail: hlaliu@mail.cgu.edu.tw
2009-05-15
Quantitative cerebral blood flow (CBF) estimation requires deconvolution of the tissue concentration time curves with an arterial input function (AIF). However, image-based determination of AIF in rodent is challenged due to limited spatial resolution. We evaluated the feasibility of quantitative analysis using automated AIF detection and compared the results with commonly applied semi-quantitative analysis. Permanent occlusion of bilateral or unilateral common carotid artery was used to induce cerebral ischemia in rats. The image using dynamic susceptibility contrast method was performed on a 3-T magnetic resonance scanner with a spin-echo echo-planar-image sequence (TR/TE = 700/80 ms, FOV = 41 mm, matrix = 64, 3 slices, SW = 2 mm), starting from 7 s prior to contrast injection (1.2 ml/kg) at four different time points. For quantitative analysis, CBF was calculated by the AIF which was obtained from 10 voxels with greatest contrast enhancement after deconvolution. For semi-quantitative analysis, relative CBF was estimated by the integral divided by the first moment of the relaxivity time curves. We observed if the AIFs obtained in the three different ROIs (whole brain, hemisphere without lesion and hemisphere with lesion) were similar, the CBF ratios (lesion/normal) between quantitative and semi-quantitative analyses might have a similar trend at different operative time points. If the AIFs were different, the CBF ratios might be different. We concluded that using local maximum one can define proper AIF without knowing the anatomical location of arteries in a stroke rat model.
Rogge, Nicky; De Jaeger, Simon
2012-10-01
This paper proposed an adjusted "shared-input" version of the popular efficiency measurement technique Data Envelopment Analysis (DEA) that enables evaluating municipality waste collection and processing performances in settings in which one input (waste costs) is shared among treatment efforts of multiple municipal solid waste fractions. The main advantage of this version of DEA is that it not only provides an estimate of the municipalities overall cost efficiency but also estimates of the municipalities' cost efficiency in the treatment of the different fractions of municipal solid waste (MSW). To illustrate the practical usefulness of the shared input DEA-model, we apply the model to data on 293 municipalities in Flanders, Belgium, for the year 2008. Copyright © 2012 Elsevier Ltd. All rights reserved.
Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M
2007-01-01
Stochastic resonance (SR) has been shown to enhance the signal to noise ratio or detection of signals in neurons. It is not yet clear how this effect of SR on the signal to noise ratio affects signal processing in neural networks. In this paper, we investigate the effects of the location of background noise input on information transmission in a hippocampal CA1 neuron model. In the computer simulation, random sub-threshold spike trains (signal) generated by a filtered homogeneous Poisson process were presented repeatedly to the middle point of the main apical branch, while the homogeneous Poisson shot noise (background noise) was applied to a location of the dendrite in the hippocampal CA1 model consisting of the soma with a sodium, a calcium, and five potassium channels. The location of the background noise input was varied along the dendrites to investigate the effects of background noise input location on information transmission. The computer simulation results show that the information rate reached a maximum value for an optimal amplitude of the background noise amplitude. It is also shown that this optimal amplitude of the background noise is independent of the distance between the soma and the noise input location. The results also show that the location of the background noise input does not significantly affect the maximum values of the information rates generated by stochastic resonance.
Berger, Theodore W.; Song, Dong; Chan, Rosa H. M.; Marmarelis, Vasilis Z.
2010-01-01
The successful development of neural prostheses requires an understanding of the neurobiological bases of cognitive processes, i.e., how the collective activity of populations of neurons results in a higher level process not predictable based on knowledge of the individual neurons and/or synapses alone. We have been studying and applying novel methods for representing nonlinear transformations of multiple spike train inputs (multiple time series of pulse train inputs) produced by synaptic and field interactions among multiple subclasses of neurons arrayed in multiple layers of incompletely connected units. We have been applying our methods to study of the hippocampus, a cortical brain structure that has been demonstrated, in humans and in animals, to perform the cognitive function of encoding new long-term (declarative) memories. Without their hippocampi, animals and humans retain a short-term memory (memory lasting approximately 1 min), and long-term memory for information learned prior to loss of hippocampal function. Results of more than 20 years of studies have demonstrated that both individual hippocampal neurons, and populations of hippocampal cells, e.g., the neurons comprising one of the three principal subsystems of the hippocampus, induce strong, higher order, nonlinear transformations of hippocampal inputs into hippocampal outputs. For one synaptic input or for a population of synchronously active synaptic inputs, such a transformation is represented by a sequence of action potential inputs being changed into a different sequence of action potential outputs. In other words, an incoming temporal pattern is transformed into a different, outgoing temporal pattern. For multiple, asynchronous synaptic inputs, such a transformation is represented by a spatiotemporal pattern of action potential inputs being changed into a different spatiotemporal pattern of action potential outputs. Our primary thesis is that the encoding of short-term memories into new, long
Kavgaoglu, Derya; Alci, Bülent
2016-01-01
The goal of this research which was carried out in reputable dedicated call centres within the Turkish telecommunication sector aims is to evaluate competence-based curriculums designed by means of internal funding through Stufflebeam's context, input, process, product (CIPP) model. In the research, a general scanning pattern in the scope of…
Mairani, A.; Magro, G.; Tessonnier, T.; Böhlen, T. T.; Molinelli, S.; Ferrari, A.; Parodi, K.; Debus, J.; Haberer, T.
2017-06-01
Models able to predict relative biological effectiveness (RBE) values are necessary for an accurate determination of the biological effect with proton and 4He ion beams. This is particularly important when including RBE calculations in treatment planning studies comparing biologically optimized proton and 4He ion beam plans. In this work, we have tailored the predictions of the modified microdosimetric kinetic model (MKM), which is clinically applied for carbon ion beam therapy in Japan, to reproduce RBE with proton and 4He ion beams. We have tuned the input parameters of the MKM, i.e. the domain and nucleus radii, reproducing an experimental database of initial RBE data for proton and He ion beams. The modified MKM, with the best fit parameters obtained, has been used to reproduce in vitro cell survival data in clinically-relevant scenarios. A satisfactory agreement has been found for the studied cell lines, A549 and RENCA, with the mean absolute survival variation between the data and predictions within 2% and 5% for proton and 4He ion beams, respectively. Moreover, a sensitivity study has been performed varying the domain and nucleus radii and the quadratic parameter of the photon response curve. The promising agreement found in this work for the studied clinical-like scenarios supports the usage of the modified MKM for treatment planning studies in proton and 4He ion beam therapy.
Enhancement of regional wet deposition estimates based on modeled precipitation inputs
James A. Lynch; Jeffery W. Grimm; Edward S. Corbett
1996-01-01
Application of a variety of two-dimensional interpolation algorithms to precipitation chemistry data gathered at scattered monitoring sites for the purpose of estimating precipitation- born ionic inputs for specific points or regions have failed to produce accurate estimates. The accuracy of these estimates is particularly poor in areas of high topographic relief....
Directory of Open Access Journals (Sweden)
Hatice Sancar Tokmak
2013-07-01
Full Text Available This study aimed to evaluate and redesign an online master’s degree program consisting of 12 courses from the informatics field using a context, input, process, product (CIPP evaluation model. Research conducted during the redesign of the online program followed a mixed methodology in which data was collected through a CIPP survey, focus-group interview, and open-ended questionnaire. An initial CIPP survey sent to students, which had a response rate of approximately 60%, indicated that the Fuzzy Logic course did not fully meet the needs of students. Based on these findings, the program managers decided to improve this course, and a focus group was organized with the students of the Fuzzy Logic course in order to obtain more information to help in redesigning the course. Accordingly, the course was redesigned to include more examples and visuals, including videos; student-instructor interaction was increased through face-to-face meetings; and extra meetings were arranged before exams so that additional examples could be presented for problem-solving to satisfy students about assessment procedures. Lastly, the modifications to the Fuzzy Logic course were implemented, and the students in the course were sent an open-ended form asking them what they thought about the modifications. The results indicated that most students were pleased with the new version of the course.
Directory of Open Access Journals (Sweden)
Jelena Jovanović
2010-03-01
Full Text Available The research is oriented on improvement of environmental management system (EMS using BSC (Balanced Scorecard model that presents strategic model of measurem ents and improvement of organisational performance. The research will present approach of objectives and environmental management me trics involvement (proposed by literature review in conventional BSC in "Ad Barska plovi dba" organisation. Further we will test creation of ECO-BSC model based on business activities of non-profit organisations in order to improve envir onmental management system in parallel with other systems of management. Using this approach we may obtain 4 models of BSC that includ es elements of environmen tal management system for AD "Barska plovidba". Taking into acc ount that implementation and evaluation need long period of time in AD "Barska plovidba", the final choice will be based on 14598 (Information technology - Software product evaluation and ISO 9126 (Software engineering - Product quality using AHP method. Those standards are usually used for evaluation of quality software product and computer programs that serve in organisation as support and factors for development. So, AHP model will be bas ed on evolution criteria based on suggestion of ISO 9126 standards and types of evaluation from two evaluation teams. Members of team & will be experts in BSC and environmental management system that are not em ployed in AD "Barska Plovidba" organisation. The members of team 2 will be managers of AD "Barska Plovidba" organisation (including manage rs from environmental department. Merging results based on previously cr eated two AHP models, one can obtain the most appropriate BSC that includes elements of environmental management system. The chosen model will present at the same time suggestion for approach choice including ecological metrics in conventional BSC model for firm that has at least one ECO strategic orientation.
The input and output management of solid waste using DEA models: A case study at Jengka, Pahang
Mohamed, Siti Rosiah; Ghazali, Nur Fadzrina Mohd; Mohd, Ainun Hafizah
2017-08-01
Data Envelopment Analysis (DEA) as a tool for obtaining performance indices has been used extensively in several of organizations sector. The ways to improve the efficiency of Decision Making Units (DMUs) is impractical because some of inputs and outputs are uncontrollable and in certain situation its produce weak efficiency which often reflect the impact for operating environment. Based on the data from Alam Flora Sdn. Bhd Jengka, the researcher wants to determine the efficiency of solid waste management (SWM) in town Jengka Pahang using CCRI and CCRO model of DEA and duality formulation with vector average input and output. Three input variables (length collection in meter, frequency time per week in hour and number of garbage truck) and 2 outputs variables (frequency collection and the total solid waste collection in kilogram) are analyzed. As a conclusion, it shows only three roads from 23 roads are efficient that achieve efficiency score 1. Meanwhile, 20 other roads are in an inefficient management.
Comparison of squashing and self-consistent input-output models of quantum feedback
Peřinová, V.; Lukš, A.; Křepelka, J.
2018-03-01
The paper (Yanagisawa and Hope, 2010) opens with two ways of analysis of a measurement-based quantum feedback. The scheme of the feedback includes, along with the homodyne detector, a modulator and a beamsplitter, which does not enable one to extract the nonclassical field. In the present scheme, the beamsplitter is replaced by the quantum noise evader, which makes it possible to extract the nonclassical field. We re-approach the comparison of two models related to the same scheme. The first one admits that in the feedback loop between the photon annihilation and creation operators, unusual commutation relations hold. As a consequence, in the feedback loop, squashing of the light occurs. In the second one, the description arrives at the feedback loop via unitary transformations. But it is obvious that the unitary transformation which describes the modulator changes even the annihilation operator of the mode which passes by the modulator which is not natural. The first model could be called "squashing model" and the second one could be named "self-consistent model". Although the predictions of the two models differ only a little and both the ways of analysis have their advantages, they have also their drawbacks and further investigation is possible.
Directory of Open Access Journals (Sweden)
Daniela Molinari
2017-09-01
Full Text Available IN-depth SYnthetic Model for Flood Damage Estimation (INSYDE is a model for the estimation of flood damage to residential buildings at the micro-scale. This study investigates the sensitivity of INSYDE to the accuracy of input data. Starting from the knowledge of input parameters at the scale of individual buildings for a case study, the level of detail of input data is progressively downgraded until the condition in which a representative value is defined for all inputs at the census block scale. The analysis reveals that two conditions are required to limit the errors in damage estimation: the representativeness of representatives values with respect to micro-scale values and the local knowledge of the footprint area of the buildings, being the latter the main extensive variable adopted by INSYDE. Such a result allows for extending the usability of the model at the meso-scale, also in different countries, depending on the availability of aggregated building data.
Higgs, R J; Chase, L E; Ross, D A; Van Amburgh, M E
2015-09-01
The Cornell Net Carbohydrate and Protein System (CNCPS) is a nutritional model that evaluates the environmental and nutritional resources available in an animal production system and enables the formulation of diets that closely match the predicted animal requirements. The model includes a library of approximately 800 different ingredients that provide the platform for describing the chemical composition of the diet to be formulated. Each feed in the feed library was evaluated against data from 2 commercial laboratories and updated when required to enable more precise predictions of dietary energy and protein supply. A multistep approach was developed to predict uncertain values using linear regression, matrix regression, and optimization. The approach provided an efficient and repeatable way of evaluating and refining the composition of a large number of different feeds against commercially generated data similar to that used by CNCPS users on a daily basis. The protein A fraction in the CNCPS, formerly classified as nonprotein nitrogen, was reclassified to ammonia for ease and availability of analysis and to provide a better prediction of the contribution of metabolizable protein from free AA and small peptides. Amino acid profiles were updated using contemporary data sets and now represent the profile of AA in the whole feed rather than the insoluble residue. Model sensitivity to variation in feed library inputs was investigated using Monte Carlo simulation. Results showed the prediction of metabolizable energy was most sensitive to variation in feed chemistry and fractionation, whereas predictions of metabolizable protein were most sensitive to variation in digestion rates. Regular laboratory analysis of samples taken on-farm remains the recommended approach to characterizing the chemical components of feeds in a ration. However, updates to the CNCPS feed library provide a database of ingredients that are consistent with current feed chemistry information and
International Nuclear Information System (INIS)
Liu, Xiuli; Moreno, Blanca; García, Ana Salomé
2016-01-01
A combined forecast of Grey forecasting method and neural network back propagation model, which is called Grey Neural Network and Input-Output Combined Forecasting Model (GNF-IO model), is proposed. A real case of energy consumption forecast is used to validate the effectiveness of the proposed model. The GNF-IO model predicts coal, crude oil, natural gas, renewable and nuclear primary energy consumption volumes by Spain's 36 sub-sectors from 2010 to 2015 according to three different GDP growth scenarios (optimistic, baseline and pessimistic). Model test shows that the proposed model has higher simulation and forecasting accuracy on energy consumption than Grey models separately and other combination methods. The forecasts indicate that the primary energies as coal, crude oil and natural gas will represent on average the 83.6% percent of the total of primary energy consumption, raising concerns about security of supply and energy cost and adding risk for some industrial production processes. Thus, Spanish industry must speed up its transition to an energy-efficiency economy, achieving a cost reduction and increase in the level of self-supply. - Highlights: • Forecasting System Using Grey Models combined with Input-Output Models is proposed. • Primary energy consumption in Spain is used to validate the model. • The grey-based combined model has good forecasting performance. • Natural gas will represent the majority of the total of primary energy consumption. • Concerns about security of supply, energy cost and industry competitiveness are raised.
SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations
Baes, M.; Camps, P.
2015-09-01
The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.
Realistic modeling of seismic input for megacities and large urban areas
Panza, G. F.; Unesco/Iugs/Igcp Project 414 Team
2003-04-01
The project addressed the problem of pre-disaster orientation: hazard prediction, risk assessment, and hazard mapping, in connection with seismic activity and man-induced vibrations. The definition of realistic seismic input has been obtained from the computation of a wide set of time histories and spectral information, corresponding to possible seismotectonic scenarios for different source and structural models. The innovative modeling technique, that constitutes the common tool to the entire project, takes into account source, propagation and local site effects. This is done using first principles of physics about wave generation and propagation in complex media, and does not require to resort to convolutive approaches, that have been proven to be quite unreliable, mainly when dealing with complex geological structures, the most interesting from the practical point of view. In fact, several techniques that have been proposed to empirically estimate the site effects using observations convolved with theoretically computed signals corresponding to simplified models, supply reliable information about the site response to non-interfering seismic phases. They are not adequate in most of the real cases, when the seismic sequel is formed by several interfering waves. The availability of realistic numerical simulations enables us to reliably estimate the amplification effects even in complex geological structures, exploiting the available geotechnical, lithological, geophysical parameters, topography of the medium, tectonic, historical, palaeoseismological data, and seismotectonic models. The realistic modeling of the ground motion is a very important base of knowledge for the preparation of groundshaking scenarios that represent a valid and economic tool for the seismic microzonation. This knowledge can be very fruitfully used by civil engineers in the design of new seismo-resistant constructions and in the reinforcement of the existing built environment, and, therefore
International Nuclear Information System (INIS)
Suzuki, K.; Sato, H.
1975-01-01
The power and the cross power spectrum analysis by which the vibration characteristic of structures, such as natural frequency, mode of vibration and damping ratio, can be identified would be effective for the confirmation of the characteristics after the construction is completed by using the response for small earthquakes or the micro-tremor under the operating condition. This method of analysis previously utilized only from the view point of systems with single input so far, is extensively applied for the analysis of a medium scale model of a piping system subjected to two seismic inputs. The piping system attached to a three storied concrete structure model which is constructed on a shaking table was excited due to earthquake motions. The inputs to the piping system were recorded at the second floor and the ceiling of the third floor where the system was attached to. The output, the response of the piping system, was instrumented at a middle point on the system. As a result, the multi-dimensional power spectrum analysis is effective for a more reliable identification of the vibration characteristics of the multi-input structure system
Hanasaki, N.; Kanae, S.; Oki, T.; Masuda, K.; Motoya, K.; Shen, Y.; Tanaka, K.
2007-10-01
An integrated global water resources model was developed consisting of six modules: land surface hydrology, river routing, crop growth, reservoir operation, environmental flow requirement estimation, and anthropogenic water withdrawal. It simulates both natural and anthropogenic water flow globally (excluding Antarctica) on a daily basis at a spatial resolution of 1°×1° (longitude and latitude). The simulation period is 10 years, from 1986 to 1995. This first part of the two-feature report describes the input meteorological forcing and natural hydrological cycle modules of the integrated model, namely the land surface hydrology module and the river routing module. The input meteorological forcing was provided by the second Global Soil Wetness Project (GSWP2), an international land surface modeling project. Several reported shortcomings of the forcing component were improved. The land surface hydrology module was developed based on a bucket type model that simulates energy and water balance on land surfaces. Simulated runoff was compared and validated with observation-based global runoff data sets and observed streamflow records at 32 major river gauging stations around the world. Mean annual runoff agreed well with earlier studies at global, continental, and continental zonal mean scales, indicating the validity of the input meteorological data and land surface hydrology module. In individual basins, the mean bias was less than ±20% in 14 of the 32 river basins and less than ±50% in 24 of the basins. The performance was similar to the best available precedent studies with closure of energy and water. The timing of the peak in streamflow and the shape of monthly hydrographs were well simulated in most of the river basins when large lakes or reservoirs did not affect them. The results indicate that the input meteorological forcing component and the land surface hydrology module provide a framework with which to assess global water resources, with the potential
DEFF Research Database (Denmark)
Beier, C.; Moldan, F.; Wright, R.F.
2003-01-01
to 3 large-scale "clean rain" experiments, the so-called roof experiments at Risdalsheia, Norway; Gardsjon, Sweden, and Klosterhede, Denmark. Implementation of the Gothenburg protocol will initiate recovery of the soils at all 3 sites by rebuilding base saturation. The rate of recovery is small...... and base saturation increases less than 5% over the next 30 years. A climate-induced increase in storm severity will increase the sea-salt input to the ecosystems. This will provide additional base cations to the soils and more than double the rate of the recovery, but also lead to strong acid pulses...... following high sea-salt inputs as the deposited base cations exchange with the acidity stored in the soil. Future recovery of soils and runoff at acidified catchments will thus depend on the amount and rate of reduction of acid deposition, and in the case of systems near the coast, the frequency...
Directory of Open Access Journals (Sweden)
S.N.M.P. Simamora
2014-10-01
Full Text Available Efficiency condition occurs when the value of the used outputs compared to the resource total that has been used almost close to the value 1 (absolute environment. An instrument to achieve efficiency if the power output level has decreased significantly in the life of the instrument used, if it compared to the previous condition, when the instrument is not equipped with additional systems (or proposed model improvement. Even more effective if the inputs model that are used in unison to achieve a homogeneous output. On this research has been designed and implemented the automatic control system for models of single input-dual-output, wherein the sampling instruments used are lamp and fan. Source voltage used is AC (alternate-current and tested using quantitative research methods and instrumentation (with measuring instruments are observed. The results obtained demonstrate the efficiency of the instrument experienced a significant current model of single-input-dual-output applied separately instrument trials such as lamp and fan when it compared to the condition or state before. And the result show that the design has been built, can also run well.
Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo
2012-07-01
To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.
Eidenshink, J. C.; Schmer, F. A.
1979-01-01
The Lake Herman watershed in southeastern South Dakota has been selected as one of seven water resources systems in the United States for involvement in the National Model Implementation Program (MIP). MIP is a pilot program initiated to illustrate the effectiveness of existing water resources quality improvement programs. The Remote Sensing Institute (RSI) at South Dakota State University has produced a computerized geographic information system for the Lake Herman watershed. All components necessary for the monitoring and evaluation process were included in the data base. The computerized data were used to produce thematic maps and tabular data for the land cover and soil classes within the watershed. These data are being utilized operationally by SCS resource personnel for planning and management purposes.
Dynamics of a Birth-Pulse Single-Species Model with Restricted Toxin Input and Pulse Harvesting
Directory of Open Access Journals (Sweden)
Yi Ma
2010-01-01
Full Text Available We consider a birth-pulses single-species model with restricted toxin input and pulse harvesting in a polluted environment. Pollution accumulates as a slowly decaying stock and is assumed to affect the growth of the renewable resource population. Firstly, by using the discrete dynamical system determined by the stroboscopic map, we obtain an exact 1-period solution of system whose birth function is Ricker function or Beverton-Holt function and obtain the threshold conditions for their stability. Furthermore, we show that the timing of harvesting has a strong impact on the maximum annual sustainable yield. The best timing of harvesting is immediately after the birth pulses. Finally, we investigate the effect of the amount of toxin input on the stable resource population size. We find that when the birth rate is comparatively lower, the population size is decreasing with the increase of toxin input; that when the birth rate is high, the population size may begin to rise and then drop with the increase of toxin input.
Hall, Alix E; Bryant, Jamie; Sanson-Fisher, Rob W; Fradgley, Elizabeth A; Proietto, Anthony M; Roos, Ian
2018-03-07
To ensure the provision of patient-centred health care, it is essential that consumers are actively involved in the process of determining and implementing health-care quality improvements. However, common strategies used to involve consumers in quality improvements, such as consumer membership on committees and collection of patient feedback via surveys, are ineffective and have a number of limitations, including: limited representativeness; tokenism; a lack of reliable and valid patient feedback data; infrequent assessment of patient feedback; delays in acquiring feedback; and how collected feedback is used to drive health-care improvements. We propose a new active model of consumer engagement that aims to overcome these limitations. This model involves the following: (i) the development of a new measure of consumer perceptions; (ii) low cost and frequent electronic data collection of patient views of quality improvements; (iii) efficient feedback to the health-care decision makers; and (iv) active involvement of consumers that fosters power to influence health system changes. © 2018 The Authors Health Expectations published by John Wiley & Sons Ltd.
Gasification of biomass in a fixed bed downdraft gasifier--a realistic model including tar.
Barman, Niladri Sekhar; Ghosh, Sudip; De, Sudipta
2012-03-01
This study presents a model for fixed bed downdraft biomass gasifiers considering tar also as one of the gasification products. A representative tar composition along with its mole fractions, as available in the literature was used as an input parameter within the model. The study used an equilibrium approach for the applicable gasification reactions and also considered possible deviations from equilibrium to further upgrade the equilibrium model to validate a range of reported experimental results. Heat balance was applied to predict the gasification temperature and the predicted values were compared with reported results in literature. A comparative study was made with some reference models available in the literature and also with experimental results reported in the literature. Finally a predicted variation of performance of the gasifier by this validated model for different air-fuel ratio and moisture content was also discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.
Legleiter, C. J.; McDonald, R.; Kyriakidis, P. C.; Nelson, J. M.
2009-12-01
Numerical models of flow and sediment transport increasingly are used to inform studies of aquatic habitat and river morphodynamics. Accurate topographic information is required to parameterize such models, but this fundamental input is typically subject to considerable uncertainty, which can propagate through a model to produce uncertain predictions of flow hydraulics. In this study, we examined the effects of uncertain topographic input on the output from FaSTMECH, a two-dimensional, finite difference flow model implemented on a regular, channel-centered grid; the model was applied to a simple, restored gravel-bed river. We adopted a spatially explicit stochastic simulation approach because elevation differences (i.e., perturbations) at one node of the computational grid influenced model predictions at nearby nodes, due to the strong coupling between proximal locations dictated by the governing equations of fluid flow. Geostatistical techniques provided an appropriate framework for examining the impacts of topographic uncertainty by generating many, equally likely realizations, each consistent with a statistical model summarizing the variability and spatial structure of channel morphology. By applying the model to each realization in turn, a distribution of model outputs was generated for each grid node. One set of realizations, conditioned to the available survey data and progressively thinned versions thereof, was used to quantify the effects of sampling strategy on topographic uncertainty and hence the uncertainty of model predictions. This analysis indicated that as the spacing between surveyed cross-sections increased, the reach-averaged ensemble standard deviation of water surface elevation, depth, velocity, and boundary shear stress increased as well, for both baseflow conditions and for a discharge of ~75% bankfull. A second set of realizations was generated by retaining randomly selected subsets of the original survey data and used to investigate the
Oral, Elif; Gélis, Céline; Bonilla, Luis Fabián; Delavaud, Elise
2017-12-01
Numerical modelling of seismic wave propagation, considering soil nonlinearity, has become a major topic in seismic hazard studies when strong shaking is involved under particular soil conditions. Indeed, when strong ground motion propagates in saturated soils, pore pressure is another important parameter to take into account when successive phases of contractive and dilatant soil behaviour are expected. Here, we model 1-D seismic wave propagation in linear and nonlinear media using the spectral element numerical method. The study uses a three-component (3C) nonlinear rheology and includes pore-pressure excess. The 1-D-3C model is used to study the 1987 Superstition Hills earthquake (ML 6.6), which was recorded at the Wildlife Refuge Liquefaction Array, USA. The data of this event present strong soil nonlinearity involving pore-pressure effects. The ground motion is numerically modelled for different assumptions on soil rheology and input motion (1C versus 3C), using the recorded borehole signals as input motion. The computed acceleration-time histories show low-frequency amplification and strong high-frequency damping due to the development of pore pressure in one of the soil layers. Furthermore, the soil is found to be more nonlinear and more dilatant under triaxial loading compared to the classical 1C analysis, and significant differences in surface displacements are observed between the 1C and 3C approaches. This study contributes to identify and understand the dominant phenomena occurring in superficial layers, depending on local soil properties and input motions, conditions relevant for site-specific studies.
A Diffusion Approximation and Numerical Methods for Adaptive Neuron Models with Stochastic Inputs.
Rosenbaum, Robert
2016-01-01
Characterizing the spiking statistics of neurons receiving noisy synaptic input is a central problem in computational neuroscience. Monte Carlo approaches to this problem are computationally expensive and often fail to provide mechanistic insight. Thus, the field has seen the development of mathematical and numerical approaches, often relying on a Fokker-Planck formalism. These approaches force a compromise between biological realism, accuracy and computational efficiency. In this article we develop an extension of existing diffusion approximations to more accurately approximate the response of neurons with adaptation currents and noisy synaptic currents. The implementation refines existing numerical schemes for solving the associated Fokker-Planck equations to improve computationally efficiency and accuracy. Computer code implementing the developed algorithms is made available to the public.
Nonlinear neural network for hemodynamic model state and input estimation using fMRI data
Karam, Ayman M.
2014-11-01
Originally inspired by biological neural networks, artificial neural networks (ANNs) are powerful mathematical tools that can solve complex nonlinear problems such as filtering, classification, prediction and more. This paper demonstrates the first successful implementation of ANN, specifically nonlinear autoregressive with exogenous input (NARX) networks, to estimate the hemodynamic states and neural activity from simulated and measured real blood oxygenation level dependent (BOLD) signals. Blocked and event-related BOLD data are used to test the algorithm on real experiments. The proposed method is accurate and robust even in the presence of signal noise and it does not depend on sampling interval. Moreover, the structure of the NARX networks is optimized to yield the best estimate with minimal network architecture. The results of the estimated neural activity are also discussed in terms of their potential use.
Realistic modelling of the seismic input Site effects and parametric studies
Romanelli, F; Vaccari, F
2002-01-01
We illustrate the work done in the framework of a large international cooperation, showing the very recent numerical experiments carried out within the framework of the EC project 'Advanced methods for assessing the seismic vulnerability of existing motorway bridges' (VAB) to assess the importance of non-synchronous seismic excitation of long structures. The definition of the seismic input at the Warth bridge site, i.e. the determination of the seismic ground motion due to an earthquake with a given magnitude and epicentral distance from the site, has been done following a theoretical approach. In order to perform an accurate and realistic estimate of site effects and of differential motion it is necessary to make a parametric study that takes into account the complex combination of the source and propagation parameters, in realistic geological structures. The computation of a wide set of time histories and spectral information, corresponding to possible seismotectonic scenarios for different sources and stru...
The sensitivity of ecosystem service models to choices of input data and spatial resolution
Kenneth J. Bagstad; Erika Cohen; Zachary H. Ancona; Steven. G. McNulty; Ge Sun
2018-01-01
Although ecosystem service (ES) modeling has progressed rapidly in the last 10â15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address...
Modeling moisture content of fine dead wildland fuels: Input to the BEHAVE fire prediction system
Richard C. Rothermel; Ralph A. Wilson; Glen A. Morris; Stephen S. Sackett
1986-01-01
Describes a model for predicting moisture content of fine fuels for use with the BEHAVE fire behavior and fuel modeling system. The model is intended to meet the need for more accurate predictions of fine fuel moisture, particularly in northern conifer stands and on days following rain. The model is based on the Canadian Fine Fuel Moisture Code (FFMC), modified to...
Embodied water analysis for Hebei Province, China by input-output modelling
Liu, Siyuan; Han, Mengyao; Wu, Xudong; Wu, Xiaofang; Li, Zhi; Xia, Xiaohua; Ji, Xi
2018-03-01
With the accelerating coordinated development of the Beijing-Tianjin-Hebei region, regional economic integration is recognized as a national strategy. As water scarcity places Hebei Province in a dilemma, it is of critical importance for Hebei Province to balance water resources as well as make full use of its unique advantages in the transition to sustainable development. To our knowledge, related embodied water accounting analysis has been conducted for Beijing and Tianjin, while similar works with the focus on Hebei are not found. In this paper, using the most complete and recent statistics available for Hebei Province, the embodied water use in Hebei Province is analyzed in detail. Based on input-output analysis, it presents a complete set of systems accounting framework for water resources. In addition, a database of embodied water intensity is proposed which is applicable to both intermediate inputs and final demand. The result suggests that the total amount of embodied water in final demand is 10.62 billion m3, of which the water embodied in urban household consumption accounts for more than half. As a net embodied water importer, the water embodied in the commodity trade in Hebei Province is 17.20 billion m3. The outcome of this work implies that it is particularly urgent to adjust industrial structure and trade policies for water conservation, to upgrade technology and to improve water utilization. As a result, to relieve water shortages in Hebei Province, it is of crucial importance to regulate the balance of water use within the province, thus balancing water distribution in the various industrial sectors.
Köhler, Annette; Hellweg, Stefanie; Recan, Ercan; Hungerbühler, Konrad
2007-08-01
Industrial wastewater-treatment systems need to ensure a high level of protection for the environment as a whole. Life-cycle assessment (LCA) comprehensively evaluates the environmental impacts of complex treatment systems, taking into account impacts from auxiliaries and energy consumption as well as emissions. However, the application of LCA is limited by a scarcity of wastewater-specific life-cycle inventory (LCI) data. This study presents a modular gate-to-gate inventory model for industrial wastewater purification in the chemical and related sectors. It enables the calculation of inventory parameters as a function of the wastewater composition and the technologies applied. Forthis purpose, data on energy and auxiliaries' consumption, wastewater composition, and process parameters was collected from chemical industry. On this basis, causal relationships between wastewater input, emissions, and technical inputs were identified. These causal relationships were translated into a generic inventory model. Generic and site-specific data ranges for LCI parameters are provided for the following processes: mechanical-biological treatment, high-pressure wet-air oxidation, nanofiltration, and extraction. The input- and technology-dependent process inventories help to bridge data gaps where primary data are not available. Thus, they substantially help to perform an environmental assessment of industrial wastewater purification in the chemical and associated industries, which may be used, for instance, for technology choices.
International Nuclear Information System (INIS)
Vomvoris, S.; Andrews, R.W.; Lanyon, G.W.; Voborny, O.; Wilson, W.
1996-04-01
Switzerland is one of many nations with nuclear power that is seeking to identify rock types and locations that would be suitable for the underground disposal of nuclear waste. A common challenge among these programs is to provide engineering designers and safety analysts with a reasonably representative hydrogeological input dataset that synthesizes the relevant information from direct field observations as well as inferences and model results derived from those observations. Needed are estimates of the volumetric flux through a volume of rock and the distribution of that flux into discrete pathways between the repository zones and the biosphere. These fluxes are not directly measurable but must be derived based on understandings of the range of plausible hydrogeologic conditions expected at the location investigated. The methodology described in this report utilizes conceptual and numerical models at various scales to derive the input dataset. The methodology incorporates an innovative approach, called the geometric approach, in which field observations and their associated uncertainty, together with a conceptual representation of those features that most significantly affect the groundwater flow regime, were rigorously applied to generate alternative possible realizations of hydrogeologic features in the geosphere. In this approach, the ranges in the output values directly reflect uncertainties in the input values. As a demonstration, the methodology is applied to the derivation of the hydrogeological dataset for the crystalline basement of Northern Switzerland. (author) figs., tabs., refs
International Nuclear Information System (INIS)
Haenni, H.P.; Smith, A.L.
1986-01-01
The sources of the uncertainties are generally accepted as modeling deficiencies, lack of completeness in the analysis and the input data deficiencies. The role of judgement in selecting input data for establishing safety goals will be discussed. As an example, a safety goal for unacceptable radioactivity release will be considered. Two analysts are discussing the introduction of an emergency service water system, applying a different way of engineering judgement. Using PRA combined with safety goals as a decision-making tool it could have an important influence on the design and the costs of the plant. The suitability of the methodology has to be generally accepted before it will be established as a regulatory requirement. (orig.)
1987-09-14
inputs. Tesauro (1986) has criticized the SB model on the grounds that it is only applicable in situations where inputs are represented locally...Barto, A.G. A temporal-difference model of classical conditioning. , Technical Report TR87-509.2, GTE Labs, Waltham, Mass. (1987). Tesauro , G. Simple
Langseth, Brian J.; Jones, Michael L.; Riley, Stephen C.
2014-01-01
Ecopath with Ecosim (EwE) is a widely used modeling tool in fishery research and management. Ecopath requires a mass-balanced snapshot of a food web at a particular point in time, which Ecosim then uses to simulate changes in biomass over time. Initial inputs to Ecopath, including estimates for biomasses, production to biomass ratios, consumption to biomass ratios, and diets, rarely produce mass balance, and thus ad hoc changes to inputs are required to balance the model. There has been little previous research of whether ad hoc changes to achieve mass balance affect Ecosim simulations. We constructed an EwE model for the offshore community of Lake Huron, and balanced the model using four contrasting but realistic methods. The four balancing methods were based on two contrasting approaches; in the first approach, production of unbalanced groups was increased by increasing either biomass or the production to biomass ratio, while in the second approach, consumption of predators on unbalanced groups was decreased by decreasing either biomass or the consumption to biomass ratio. We compared six simulation scenarios based on three alternative assumptions about the extent to which mortality rates of prey can change in response to changes in predator biomass (i.e., vulnerabilities) under perturbations to either fishing mortality or environmental production. Changes in simulated biomass values over time were used in a principal components analysis to assess the comparative effect of balancing method, vulnerabilities, and perturbation types. Vulnerabilities explained the most variation in biomass, followed by the type of perturbation. Choice of balancing method explained little of the overall variation in biomass. Under scenarios where changes in predator biomass caused large changes in mortality rates of prey (i.e., high vulnerabilities), variation in biomass was greater than when changes in predator biomass caused only small changes in mortality rates of prey (i.e., low
Adaptive Fault-Tolerant Control for Flight Systems with Input Saturation and Model Mismatch
Directory of Open Access Journals (Sweden)
Man Wang
2013-01-01
the original reference model may not be appropriate. Under this circumstance, an adaptive reference model which can also provide satisfactory performance is designed. Simulations of a flight control example are given to illustrate the effectiveness of the proposed scheme.
Effect of Manure vs. Fertilizer Inputs on Productivity of Forage Crop Models
Directory of Open Access Journals (Sweden)
Pasquale Martiniello
2011-06-01
Full Text Available Manure produced by livestock activity is a dangerous product capable of causing serious environmental pollution. Agronomic management practices on the use of manure may transform the target from a waste to a resource product. Experiments performed on comparison of manure with standard chemical fertilizers (CF were studied under a double cropping per year regime (alfalfa, model I; Italian ryegrass-corn, model II; barley-seed sorghum, model III; and horse-bean-silage sorghum, model IV. The total amount of manure applied in the annual forage crops of the model II, III and IV was 158, 140 and 80 m3 ha−1, respectively. The manure applied to soil by broadcast and injection procedure provides an amount of nitrogen equal to that supplied by CF. The effect of manure applications on animal feeding production and biochemical soil characteristics was related to the models. The weather condition and manures and CF showed small interaction among treatments. The number of MFU ha−1 of biomass crop gross product produced in autumn and spring sowing models under manure applications was 11,769, 20,525, 11,342, 21,397 in models I through IV, respectively. The reduction of MFU ha−1 under CF ranges from 10.7% to 13.2% those of the manure models. The effect of manure on organic carbon and total nitrogen of topsoil, compared to model I, stressed the parameters as CF whose amount was higher in models II and III than model IV. In term of percentage the organic carbon and total nitrogen of model I and treatment with manure was reduced by about 18.5 and 21.9% in model II and model III and 8.8 and 6.3% in model IV, respectively. Manure management may substitute CF without reducing gross production and sustainability of cropping systems, thus allowing the opportunity to recycle the waste product for animal forage feeding.
'Fingerprints' of four crop models as affected by soil input data aggregation
DEFF Research Database (Denmark)
Angulo, Carlos; Gaiser, Thomas; Rötter, Reimund P
2014-01-01
. In this study we used four crop models (SIMPLACE, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically...
Directory of Open Access Journals (Sweden)
S. E. Pryse
2009-03-01
Full Text Available Electric potential patterns obtained by the SuperDARN radar network are used as input to the Coupled Thermosphere-Ionosphere-Plasmasphere model, in an attempt to improve the modelling of the spatial distribution of the ionospheric plasma at high latitudes. Two case studies are considered, one under conditions of stable IMF Bz negative and the other under stable IMF Bz positive. The modelled plasma distributions are compared with sets of well-established tomographic reconstructions, which have been interpreted previously in multi-instrument studies. For IMF Bz negative both the model and observations show a tongue-of-ionisation on the nightside, with good agreement between the electron density and location of the tongue. Under Bz positive, the SuperDARN input allows the model to reproduce a spatial plasma distribution akin to that observed. In this case plasma, unable to penetrate the polar cap boundary into the polar cap, is drawn by the convective flow in a tongue-of-ionisation around the periphery of the polar cap.
Directory of Open Access Journals (Sweden)
S. E. Pryse
2009-03-01
Full Text Available Electric potential patterns obtained by the SuperDARN radar network are used as input to the Coupled Thermosphere-Ionosphere-Plasmasphere model, in an attempt to improve the modelling of the spatial distribution of the ionospheric plasma at high latitudes. Two case studies are considered, one under conditions of stable IMF B_{z} negative and the other under stable IMF B_{z} positive. The modelled plasma distributions are compared with sets of well-established tomographic reconstructions, which have been interpreted previously in multi-instrument studies. For IMF B_{z} negative both the model and observations show a tongue-of-ionisation on the nightside, with good agreement between the electron density and location of the tongue. Under B_{z} positive, the SuperDARN input allows the model to reproduce a spatial plasma distribution akin to that observed. In this case plasma, unable to penetrate the polar cap boundary into the polar cap, is drawn by the convective flow in a tongue-of-ionisation around the periphery of the polar cap.
Modeling of the impact of Rhone River nutrient inputs on the dynamics of planktonic diversity
Alekseenko, Elena; Baklouti, Melika; Garreau, Pierre; Guyennon, Arnaud; Carlotti, François
2014-05-01
Recent studies devoted to the Mediterranean Sea highlight that a large number of uncertainties still exist particularly as regards the variations of elemental stoichiometry of all compartments of pelagic ecosystems (The MerMex Group, 2011, Pujo-Pay et al., 2011, Malatonne-Rizotti and the Pan-Med Group, 2012). Moreover, during the last two decades, it was observed that the inorganic ratio N:P ratio in among all the Mediterranean rivers, including the Rhone River, has dramatically increased, thus strengthening the P-limitation in the Mediterranean waters (Ludwig et al, 2009, The MerMex group, 2011) and increasing the anomaly in the ratio N:P of the Gulf of Lions and all the western part of NW Mediterranean. At which time scales such a change will impact the biogeochemical stocks and fluxes of the Gulf of Lion and of the whole NW Mediterranean sea still remains unknown. In the same way, it is still uncertain how this increase in the N:P ratio will modify the composition of the trophic web, and potentially lead to regime shifts by favouring for example one of the classical food chains of the sea considered in Parsons & Lalli (2002). To address this question, the Eco3M-MED biogeochemical model (Baklouti et al., 2006a,b, Alekseenko et al., 2014) representing the first trophic levels from bacteria to mesozooplankton, coupled with the hydrodynamical model MARS3D (Lazure&Dumas, 2008) is used. This model has already been partially validated (Alekseenko et al., 2014) and the fact that it describes each biogenic compartment in terms of its abundance (for organisms), and carbon, phosphorus, nitrogen and chlorophyll (for autotrophs) implies that all the information on the intracellular status of organisms and on the element(s) that limit(s) their growth will be available. The N:P ratios in water, organisms and in the exported material will also be analyzed. In practice, the work will first consist in running different scenarios starting from similar initial early winter
Directory of Open Access Journals (Sweden)
Rajib Kar
2010-09-01
Full Text Available This work presents an accurate and efficient model to compute the delay and slew metric of on-chip interconnect of high speed CMOS circuits foe ramp input. Our metric assumption is based on the Burr’s Distribution function. The Burr’s distribution is used to characterize the normalized homogeneous portion of the step response. We used the PERI (Probability distribution function Extension for Ramp Inputs technique that extends delay metrics and slew metric for step inputs to the more general and realistic non-step inputs. The accuracy of our models is justified with the results compared with that of SPICE simulations.
Directory of Open Access Journals (Sweden)
Muayad Al-Qaisy
2015-02-01
Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.
Better temperature predictions in geothermal modelling by improved quality of input parameters
DEFF Research Database (Denmark)
Fuchs, Sven; Bording, Thue Sylvester; Balling, N.
2015-01-01
Thermal modelling is used to examine the subsurface temperature field and geothermal conditions at various scales (e.g. sedimentary basins, deep crust) and in the framework of different problem settings (e.g. scientific or industrial use). In such models, knowledge of rock thermal properties...
Czech Academy of Sciences Publication Activity Database
Kainen, P.C.; Kůrková, Věra; Sanguineti, M.
2012-01-01
Roč. 58, č. 2 (2012), s. 1203-1214 ISSN 0018-9448 R&D Projects: GA MŠk(CZ) ME10023; GA ČR GA201/08/1744; GA ČR GAP202/11/1368 Grant - others:CNR-AV ČR(CZ-IT) Project 2010–2012 Complexity of Neural-Network and Kernel Computational Models Institutional research plan: CEZ:AV0Z10300504 Keywords : dictionary -based computational models * high-dimensional approximation and optimization * model complexity * polynomial upper bounds Subject RIV: IN - Informatics, Computer Science Impact factor: 2.621, year: 2012
Directory of Open Access Journals (Sweden)
GERMÁN LOBOS
2015-12-01
Full Text Available ABSTRACT The traditional method of net present value (NPV to analyze the economic profitability of an investment (based on a deterministic approach does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L. production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in
Development of a General Form CO_{2} and Brine Flux Input Model
Energy Technology Data Exchange (ETDEWEB)
Mansoor, K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sun, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Carroll, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-08-01
The National Risk Assessment Partnership (NRAP) project is developing a science-based toolset for the quantitative analysis of the potential risks associated with changes in groundwater chemistry from CO_{2} injection. In order to address uncertainty probabilistically, NRAP is developing efficient, reduced-order models (ROMs) as part of its approach. These ROMs are built from detailed, physics-based process models to provide confidence in the predictions over a range of conditions. The ROMs are designed to reproduce accurately the predictions from the computationally intensive process models at a fraction of the computational time, thereby allowing the utilization of Monte Carlo methods to probe variability in key parameters. This report presents the procedures used to develop a generalized model for CO_{2} and brine leakage fluxes based on the output of a numerical wellbore simulation. The resulting generalized parameters and ranges reported here will be used for the development of third-generation groundwater ROMs.
Bobrowski, Maria; Schickhoff, Udo
2017-04-01
Betula utilis is a major constituent of alpine treeline ecotones in the western and central Himalayan region. The objective of this study is to provide first time analysis of the potential distribution of Betula utilis in the subalpine and alpine belts of the Himalayan region using species distribution modelling. Using Generalized Linear Models (GLM) we aim at examining climatic factors controlling the species distribution under current climate conditions. Furthermore we evaluate the prediction ability of climate data derived from different statistical methods. GLMs were created using least correlated bioclimatic variables derived from two different climate models: 1) interpolated climate data (i.e. Worldclim, Hijmans et al., 2005) and 2) quasi-mechanistical statistical downscaling (i.e. Chelsa; Karger et al., 2016). Model accuracy was evaluated by the ability to predict the potential species distribution range. We found that models based on variables of Chelsa climate data had higher predictive power, whereas models using Worldclim climate data consistently overpredicted the potential suitable habitat for Betula utilis. Although climatic variables of Worldclim are widely used in modelling species distribution, our results suggest to treat them with caution when remote regions like the Himalayan mountains are in focus. Unmindful usage of climatic variables for species distribution models potentially cause misleading projections and may lead to wrong implications and recommendations for nature conservation. References: Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N., Linder, H.P. & Kessler, M. (2016) Climatologies at high resolution for the earth land surface areas. arXiv:1607.00217 [physics].
Weaver, Robert J.; Taeb, Peyman; Lazarus, Steven; Splitt, Michael; Holman, Bryan P.; Colvin, Jeffrey
2016-12-01
In this study, a four member ensemble of meteorological forcing is generated using the Weather Research and Forecasting (WRF) model in order to simulate a frontal passage event that impacted the Indian River Lagoon (IRL) during March 2015. The WRF model is run to provide high and low, spatial (0.005° and 0.1°) and temporal (30 min and 6 h) input wind and pressure fields. The four member ensemble is used to force the Advanced Circulation model (ADCIRC) coupled with Simulating Waves Nearshore (SWAN) and compute the hydrodynamic and wave response. Results indicate that increasing the spatial resolution of the meteorological forcing has a greater impact on the results than increasing the temporal resolution in coastal systems like the IRL where the length scales are smaller than the resolution of the operational meteorological model being used to generate the forecast. Changes in predicted water elevations are due in part to the upwind and downwind behavior of the input wind forcing. The significant wave height is more sensitive to the meteorological forcing, exhibited by greater ensemble spread throughout the simulation. It is important that the land mask, seen by the meteorological model, is representative of the geography of the coastal estuary as resolved by the hydrodynamic model. As long as the temporal resolution of the wind field captures the bulk characteristics of the frontal passage, computational resources should be focused so as to ensure that the meteorological model resolves the spatial complexities, such as the land-water interface, that drive the land use responsible for dynamic downscaling of the winds.
International Nuclear Information System (INIS)
Ukidwe, Nandan U.; Bakshi, Bhavik R.
2007-01-01
This paper develops a thermodynamic input-output (TIO) model of the 1997 United States economy that accounts for the flow of cumulative exergy in the 488-sector benchmark economic input-output model in two different ways. Industrial cumulative exergy consumption (ICEC) captures the exergy of all natural resources consumed directly and indirectly by each economic sector, while ecological cumulative exergy consumption (ECEC) also accounts for the exergy consumed in ecological systems for producing each natural resource. Information about exergy consumed in nature is obtained from the thermodynamics of biogeochemical cycles. As used in this work, ECEC is analogous to the concept of emergy, but does not rely on any of its controversial claims. The TIO model can also account for emissions from each sector and their impact and the role of labor. The use of consistent exergetic units permits the combination of various streams to define aggregate metrics that may provide insight into aspects related to the impact of economic sectors on the environment. Accounting for the contribution of natural capital by ECEC has been claimed to permit better representation of the quality of ecosystem goods and services than ICEC. The results of this work are expected to permit evaluation of these claims. If validated, this work is expected to lay the foundation for thermodynamic life cycle assessment, particularly of emerging technologies and with limited information
A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews
Zhang, Liujie; Zhou, Yanquan; Duan, Xiuyu; Chen, Ruiqi
2018-03-01
Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.
The Lag Model, a Turbulence Model for Wall Bounded Flows Including Separation
Olsen, Michael E.; Coakley, Thomas J.; Kwak, Dochan (Technical Monitor)
2001-01-01
A new class of turbulence model is described for wall bounded, high Reynolds number flows. A specific turbulence model is demonstrated, with results for favorable and adverse pressure gradient flowfields. Separation predictions are as good or better than either Spalart Almaras or SST models, do not require specification of wall distance, and have similar or reduced computational effort compared with these models.
Modeling microstructure of incudostapedial joint and the effect on cochlear input
Gan, Rong Z.; Wang, Xuelin
2015-12-01
The incudostapedial joint (ISJ) connects the incus to stapes in human ear and plays an important role for sound transmission from the tympanic membrane (TM) to cochlea. ISJ is a synovial joint composed of articular cartilage on the lenticular process and stapes head with the synovial fluid between them. However, there is no study on how the synovial ISJ affects the middle ear and cochlear functions. Recently, we have developed a 3-dimensinal finite element (FE) model of synovial ISJ and connected the model to our comprehensive FE model of the human ear. The motions of TM, stapes footplate, and basilar membrane and the pressures in scala vestibule and scala tympani were derived over frequencies and compared with experimental measurements. Results show that the synovial ISJ affects sound transmission into cochlea and the frequency-dependent viscoelastic behavior of ISJ provides protection for cochlea from high intensity sound.
Investigations of the sensitivity of a coronal mass ejection model (ENLIL) to solar input parameters
DEFF Research Database (Denmark)
Falkenberg, Thea Vilstrup; Vršnak, B.; Taktakishvili, A.
2010-01-01
Understanding space weather is not only important for satellite operations and human exploration of the solar system but also to phenomena here on Earth that may potentially disturb and disrupt electrical signals. Some of the most violent space weather effects are caused by coronal mass ejections...... investigate the parameter space of the ENLILv2.5b model using the CME event of 25 July 2004. ENLIL is a time‐dependent 3‐D MHD model that can simulate the propagation of cone‐shaped interplanetary coronal mass ejections (ICMEs) through the solar system. Excepting the cone parameters (radius, position...
GALEV evolutionary synthesis models – I. Code, input physics and web
Kotulla, R.; Fritze, U.; Weilbacher, P.; Anders, P.
2009-01-01
GALEV (GALaxy EVolution) evolutionary synthesis models describe the evolution of stellar populations in general, of star clusters as well as of galaxies, both in terms of resolved stellar populations and of integrated light properties over cosmological time-scales of ≥13 Gyr from the onset of star
Modeling chronic diseases: the diabetes module. Justification of (new) input data
Baan CA; Bos G; Jacobs-van der Bruggen MAM; Baan CA; Bos G; Jacobs-van der Bruggen MAM; PZO
2005-01-01
The RIVM chronic disease model (CDM) is an instrument designed to estimate the effects of changes in the prevalence of risk factors for chronic diseases on disease burden and mortality. To enable the computation of the effects of various diabetes prevention scenarios, the CDM has been updated and
Multiscale Deterministic Wave Modeling with Wind Input and Wave Breaking Dissipation
2009-01-01
Kudryavtsev , V. N., Makin, V. K. & Meirink, J. F. 2001 “Simplified model of the air flow above the waves,” Boundary-Layer Meteorol. 100, 63-90. 5 Li...Figure 6. Comparison of pressure profiles with exponential decays: solid line, the Kudryavtsev et al. (2001) profile estimated by Donelan et al
Packaging tomorrow : modelling the material input for European packaging in the 21st century
Hekkert, M.P.; Joosten, L.A.J.; Worrell, E.
2006-01-01
This report is a result of the MATTER project (MATerials Technology for CO2 Emission Reduction). The project focuses on CO2 emission reductions that are related to the Western European materials system. The total impact of the reduction options for different scenario's will be modeled in MARKAL
Input Harmonic Analysis on the Slim DC-Link Drive Using Harmonic State Space Model
DEFF Research Database (Denmark)
Yang, Feng; Kwon, Jun Bum; Wang, Xiongfei
2017-01-01
variation according to the switching instant, the harmonics at the steady-state condition, as well as the coupling between the multiple harmonic impedances. By using this model, the impaction on the harmonics performance by the film capacitor and the grid inductance is derived. Simulation and experimental...
Model-based extraction of input and organ functions in dynamic scintigraphic imaging
Czech Academy of Sciences Publication Activity Database
Tichý, Ondřej; Šmídl, Václav; Šámal, M.
2016-01-01
Roč. 4, 3-4 (2016), s. 135-145 ISSN 2168-1171 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : blind source separation * convolution * dynamic medical imaging * compartment modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/AS/tichy-0428540.pdf
Evapotranspiration and Precipitation inputs for SWAT model using remotely sensed observations
The ability of numerical models, such as the Soil and Water Assessment Tool (or SWAT), to accurately represent the partition of the water budget and describe sediment loads and other pollutant conditions related to water quality strongly depends on how well spatiotemporal variability in precipitatio...
BioModels: expanding horizons to include more modelling approaches and formats.
Glont, Mihai; Nguyen, Tung V N; Graesslin, Martin; Hälke, Robert; Ali, Raza; Schramm, Jochen; Wimalaratne, Sarala M; Kothamachu, Varun B; Rodriguez, Nicolas; Swat, Maciej J; Eils, Jurgen; Eils, Roland; Laibe, Camille; Malik-Sheriff, Rahuman S; Chelliah, Vijayalakshmi; Le Novère, Nicolas; Hermjakob, Henning
2018-01-04
BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels. This new system allows submitting and sharing of a wide range of models with improved support for formats other than SBML. It also offers a version-control backed environment in which authors and curators can work collaboratively to curate models. This article summarises the features available in the current system and discusses the potential benefit they offer to the users over the previous system. In summary, the new portal broadens the scope of models accepted in BioModels and supports collaborative model curation which is crucial for model reproducibility and sharing. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Berg, Matthew; Hartley, Brian; Richters, Oliver
2015-01-01
By synthesizing stock-flow consistent models, input-output models, and aspects of ecological macroeconomics, a method is developed to simultaneously model monetary flows through the financial system, flows of produced goods and services through the real economy, and flows of physical materials through the natural environment. This paper highlights the linkages between the physical environment and the economic system by emphasizing the role of the energy industry. A conceptual model is developed in general form with an arbitrary number of sectors, while emphasizing connections with the agent-based, econophysics, and complexity economics literature. First, we use the model to challenge claims that 0% interest rates are a necessary condition for a stationary economy and conduct a stability analysis within the parameter space of interest rates and consumption parameters of an economy in stock-flow equilibrium. Second, we analyze the role of energy price shocks in contributing to recessions, incorporating several propagation and amplification mechanisms. Third, implied heat emissions from energy conversion and the effect of anthropogenic heat flux on climate change are considered in light of a minimal single-layer atmosphere climate model, although the model is only implicitly, not explicitly, linked to the economic model.
Future-year ozone prediction for the United States using updated models and inputs.
Collet, Susan; Kidokoro, Toru; Karamchandani, Prakash; Shah, Tejas; Jung, Jaegun
2017-08-01
The relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies. The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.
Gradient System Modelling of Matrix Converters with Input and Output Filters
Jeltsema, Dimitri; Scherpen, Jacquelien M.A.; Klaassens, J. Ben
2003-01-01
Due to its complexity, the dynamics of matrix converters are usually neglected in controller design. However, increasing demands on reduced harmonic generation and higher bandwidths makes it necessary to study large-signal dynamics. A unified methodology that considers matrix converters, including
Predicted fuel consumption in the Burnup model: sensitivity to four user inputs
D. C. Lutes
2013-01-01
Fuelbeds consist of a number of combustible components that are consumed during a fire, including duff, litter, vegetation (herbs, shrub, foliage, and branches) and down dead woody material (DWM). Combustion of DWM during a fire has a well-documented role in determining fire effects and fire behavior impacts such as emissions (Sandberg and others 2002), vegetative...
Zêzere, José Luis; Pereira, Susana; Melo, Raquel; Oliveira, Sérgio; Garcia, Ricardo
2017-04-01
There are multiple sources of uncertainty within statistically-based landslide susceptibility assessment that needs to be accounted and monitored. In this work we evaluate and discuss differences observed on landslide susceptibility maps resulting from the selection of the terrain mapping unit and the selection of the feature type to represent landslides (polygon vs point). The work is performed in the Silveira Basin (18.2 square kilometres) located north of Lisbon, Portugal, using a unique database of geo-environmental landslide predisposing factors and an inventory of 81 shallow translational slides. The Logistic Regression is the statistical method selected to combine the predictive factors with the dependent variable. Four landslide susceptibility models were computed using the complete landslide inventory and considering the total landslide area over four different terrain mapping units: Slope Terrain Units (STU), Geo-Hydrological Terrain Units (GHTU), Census Terrain Units (CTU) and Grid Cell Terrain Units (GCTU). Four additional landslide susceptibility models were made over the same four terrain mapping units using a landslide training group (50% of the inventory randomly selected). These models were independently validated with the other 50% of the landslide inventory (landslide test group). Lastly, two additional landslide susceptibility models were computed over GCTU, one using the landslide training group represented as point features corresponding to the centroid of landslide, and other using the centroid of landslide rupture zone. In total, 10 landslide susceptibility maps were constructed and classified in 10 classes of equal number of terrain units to allow comparison. The evaluation of the prediction skills of susceptibility models was made using ROC metrics and Success and Prediction rate curves. Lastly, the landslide susceptibility maps computed over GCTU were compared using the Kappa statistics. With this work we conclude that large differences
Output from Statistical Predictive Models as Input to eLearning Dashboards
Directory of Open Access Journals (Sweden)
Marlene A. Smith
2015-06-01
Full Text Available We describe how statistical predictive models might play an expanded role in educational analytics by giving students automated, real-time information about what their current performance means for eventual success in eLearning environments. We discuss how an online messaging system might tailor information to individual students using predictive analytics. The proposed system would be data-driven and quantitative; e.g., a message might furnish the probability that a student will successfully complete the certificate requirements of a massive open online course. Repeated messages would prod underperforming students and alert instructors to those in need of intervention. Administrators responsible for accreditation or outcomes assessment would have ready documentation of learning outcomes and actions taken to address unsatisfactory student performance. The article’s brief introduction to statistical predictive models sets the stage for a description of the messaging system. Resources and methods needed to develop and implement the system are discussed.
Czech Academy of Sciences Publication Activity Database
Angulo, C.; Rotter, R.; Trnka, Miroslav; Pirttioja, N. K.; Gaiser, T.; Hlavinka, Petr; Ewert, F.
2013-01-01
Roč. 49, AUG 2013 (2013), s. 104-114 ISSN 1161-0301 R&D Projects: GA MŠk(CZ) EE2.3.20.0248; GA MŠk(CZ) EE2.4.31.0056 Institutional support: RVO:67179843 Keywords : Crop model * Weather data resolution * Aggregation * Yield distribution Subject RIV: EH - Ecology, Behaviour Impact factor: 2.918, year: 2013
Fingerprints of four crop models as affected by soil input data aggregation
Czech Academy of Sciences Publication Activity Database
Angulo, C.; Gaiser, T.; Rötter, R. P.; Børgesen, C. D.; Hlavinka, Petr; Trnka, Miroslav; Ewert, F.
2014-01-01
Roč. 61, NOV 2014 (2014), s. 35-48 ISSN 1161-0301 R&D Projects: GA MŠk(CZ) EE2.3.20.0248; GA MŠk(CZ) EE2.4.31.0056; GA MZe QJ1310123 Institutional support: RVO:67179843 Keywords : crop model * soil data * spatial resolution * yield distribution * aggregation Subject RIV: EH - Ecology, Behaviour Impact factor: 2.704, year: 2014
Errors in estimation of the input signal for integrate-and-fire neuronal models
Czech Academy of Sciences Publication Activity Database
Bibbona, E.; Lánský, Petr; Sacerdote, L.; Sirovich, R.
2008-01-01
Roč. 78, č. 1 (2008), s. 1-10 ISSN 1539-3755 R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) 1ET400110401 Grant - others:EC(XE) MIUR PRIN 2005 Institutional research plan: CEZ:AV0Z50110509 Keywords : parameter estimation * stochastic neuronal model Subject RIV: BO - Biophysics Impact factor: 2.508, year: 2008 http://link.aps.org/abstract/PRE/v78/e011918
Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.
2009-12-01
The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.
Inputs and spatial distribution patterns of Cr in Jiaozhou Bay
Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming
2018-03-01
Cr pollution in marine bays has been one of the critical environmental issues, and understanding the input and spatial distribution patterns is essential to pollution control. In according to the source strengths of the major pollution sources, the input patterns of pollutants to marine bay include slight, moderate and heavy, and the spatial distribution are corresponding to three block models respectively. This paper analyzed input patterns and distributions of Cr in Jiaozhou Bay, eastern China based on investigation on Cr in surface waters during 1979-1983. Results showed that the input strengths of Cr in Jiaozhou Bay could be classified as moderate input and slight input, and the input strengths were 32.32-112.30 μg L-1 and 4.17-19.76 μg L-1, respectively. The input patterns of Cr included two patterns of moderate input and slight input, and the horizontal distributions could be defined by means of Block Model 2 and Block Model 3, respectively. In case of moderate input pattern via overland runoff, Cr contents were decreasing from the estuaries to the bay mouth, and the distribution pattern was parallel. In case of moderate input pattern via marine current, Cr contents were decreasing from the bay mouth to the bay, and the distribution pattern was parallel to circular. The Block Models were able to reveal the transferring process of various pollutants, and were helpful to understand the distributions of pollutants in marine bay.
A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System
Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.
2017-10-01
A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.
Optimization modeling of U.S. renewable electricity deployment using local input variables
Bernstein, Adam
For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter
Energy Technology Data Exchange (ETDEWEB)
Zdunek, A.; Soederberg, M. (Aeronautical Research Inst. of Sweden, Bromma (Sweden))
1989-01-01
The input card deck for the finite element program GARFEM version 3.2 is described in this manual. The program includes, but is not limited to, capabilities to handle the following problems: * Linear bar and beam element structures, * Geometrically non-linear problems (bar and beam), both static and transient dynamic analysis, * Transient response dynamics from a catalog of time varying external forcing function types or input function tables, * Eigenvalue solution (modes and frequencies), * Multi point constraints (MPC) for the modelling of mechanisms and e.g. rigid links. The MPC definition is used only in the geometrically linearized sense, * Beams with disjunct shear axis and neutral axis, * Beams with rigid offset. An interface exist that connects GARFEM with the program GAROS. GAROS is a program for aeroelastic analysis of rotating structures. Since this interface was developed GARFEM now serves as a preprocessor program in place of NASTRAN which was formerly used. Documentation of the methods applied in GARFEM exists but is so far limited to the capacities in existence before the GAROS interface was developed.
International Nuclear Information System (INIS)
Borgwaldt, H.; Baumann, W.; Willerding, G.
1991-05-01
FLUTAN is a highly vectorized computer code for 3-D fluiddynamic and thermal-hydraulic analyses in cartesian and cylinder coordinates. It is related to the family of COMMIX codes originally developed at Argonne National Laboratory, USA. To a large extent, FLUTAN relies on basic concepts and structures imported from COMMIX-1B and COMMIX-2 which were made available to KfK in the frame of cooperation contracts in the fast reactor safety field. While on the one hand not all features of the original COMMIX versions have been implemented in FLUTAN, the code on the other hand includes some essential innovative options like CRESOR solution algorithm, general 3-dimensional rebalacing scheme for solving the pressure equation, and LECUSSO-QUICK-FRAM techniques suitable for reducing 'numerical diffusion' in both the enthalphy and momentum equations. This report provides users with detailed input instructions, presents formulations of the various model options, and explains by means of comprehensive sample input, how to use the code. (orig.) [de
MODEL AND METHOD FOR SYNTHESIS OF PROJECT MANAGEMENT METHODOLOGY WITH FUZZY INPUT DATA
Directory of Open Access Journals (Sweden)
Igor V. KONONENKO
2016-02-01
Full Text Available Literature analysis concerning the selection or creation a project management methodology is performed. Creating a "complete" methodology is proposed which can be applied to managing projects with any complexity, various degrees of responsibility for results and different predictability of the requirements. For the formation of a "complete" methodology, it is proposed to take the PMBOK standard as the basis, which would be supplemented by processes of the most demanding plan driven and flexible Agile Methodologies. For each knowledge area of the PMBOK standard, The following groups of processes should be provided: initiation, planning, execution, reporting, and forecasting, controlling, analysis, decision making and closing. The method for generating a methodology for the specific project is presented. The multiple criteria mathematical model and method aredeveloped for the synthesis of methodology when initial data about the project and its environment are fuzzy.
Effect of delayed response in growth on the dynamics of a chemostat model with impulsive input
International Nuclear Information System (INIS)
Jiao Jianjun; Yang Xiaosong; Chen Lansun; Cai Shaohong
2009-01-01
In this paper, a chemostat model with delayed response in growth and impulsive perturbations on the substrate is considered. Using the discrete dynamical system determined by the stroboscopic map, we obtain a microorganism-extinction periodic solution, further, the globally attractive condition of the microorganism-extinction periodic solution is obtained. By the use of the theory on delay functional and impulsive differential equation, we also obtain the permanent condition of the investigated system. Our results indicate that the discrete time delay has influence to the dynamics behaviors of the investigated system, and provide tactical basis for the experimenters to control the outcome of the chemostat. Furthermore, numerical analysis is inserted to illuminate the dynamics of the system affected by the discrete time delay.
Saramago, Pedro; Manca, Andrea; Sutton, Alex J
2012-01-01
The evidence base informing economic evaluation models is rarely derived from a single source. Researchers are typically expected to identify and combine available data to inform the estimation of model parameters for a particular decision problem. The absence of clear guidelines on what data can be used and how to effectively synthesize this evidence base under different scenarios inevitably leads to different approaches being used by different modelers. The aim of this article is to produce a taxonomy that can help modelers identify the most appropriate methods to use when synthesizing the available data for a given model parameter. This article developed a taxonomy based on possible scenarios faced by the analyst when dealing with the available evidence. While mainly focusing on clinical effectiveness parameters, this article also discusses strategies relevant to other key input parameters in any economic model (i.e., disease natural history, resource use/costs, and preferences). The taxonomy categorizes the evidence base for health economic modeling according to whether 1) single or multiple data sources are available, 2) individual or aggregate data are available (or both), or 3) individual or multiple decision model parameters are to be estimated from the data. References to examples of the key methodological developments for each entry in the taxonomy together with citations to where such methods have been used in practice are provided throughout. The use of the taxonomy developed in this article hopes to improve the quality of the synthesis of evidence informing decision models by bringing to the attention of health economics modelers recent methodological developments in this field. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Ghatrehsamani, Shirin; Ebrahimi, Rahim; Kazi, Salim Newaz; Badarudin Badry, Ahmad; Sadeghinezhad, Emad
2016-01-01
The aim of this study was to determine the amount of input–output energy used in peach production and to develop an optimal model of production in Chaharmahal va Bakhtiari province, Iran. Data were collected from 100 producers by administering a questionnaire in face-to-face interviews. Farms were selected based on random sampling method. Results revealed that the total energy of production is 47,951.52 MJ/ha and the highest share of energy consumption belongs to chemical fertilizers (35.37%). Consumption of direct energy was 47.4% while indirect energy was 52.6%. Also, Total energy consumption was divided into two groups; renewable and non-renewable (19.2% and 80.8% respectively). Energy use efficiency, Energy productivity, Specific energy and Net energy were calculated as 0.433, 0.228 (kg/MJ), 4.38 (MJ/kg) and −27,161.722 (MJ/ha), respectively. According to the negative sign for Net energy, if special strategy is used, energy dismiss will decrease and negative effect of some parameters could be omitted. In the present case the amount is indicating decimate of production energy. In addition, energy efficiency was not high enough. Some of the input energies were applied to machinery, chemical fertilizer, water irrigation and electricity which had significant effect on increasing production and MPP (marginal physical productivity) was determined for variables. This parameter was positive for energy groups namely; machinery, diesel fuel, chemical fertilizer, water irrigation and electricity while it was negative for other kind of energy such as chemical pesticides and human labor. Finally, there is a need to pursue a new policy to force producers to undertake energy-efficient practices to establish sustainable production systems without disrupting the natural resources. In addition, extension activities are needed to improve the efficiency of energy consumption and to sustain the natural resources. - Highlights: • Replacing non-renewable energy with renewable
Madej, M.A.; Sutherland, D.G.; Lisle, T.E.; Pryor, B.
2009-01-01
At the reach scale, a channel adjusts to sediment supply and flow through mutual interactions among channel form, bed particle size, and flow dynamics that govern river bed mobility. Sediment can impair the beneficial uses of a river, but the timescales for studying recovery following high sediment loading in the field setting make flume experiments appealing. We use a flume experiment, coupled with field measurements in a gravel-bed river, to explore sediment transport, storage, and mobility relations under various sediment supply conditions. Our flume experiment modeled adjustments of channel morphology, slope, and armoring in a gravel-bed channel. Under moderate sediment increases, channel bed elevation increased and sediment output increased, but channel planform remained similar to pre-feed conditions. During the following degradational cycle, most of the excess sediment was evacuated from the flume and the bed became armored. Under high sediment feed, channel bed elevation increased, the bed became smoother, mid-channel bars and bedload sheets formed, and water surface slope increased. Concurrently, output increased and became more poorly sorted. During the last degradational cycle, the channel became armored and channel incision ceased before all excess sediment was removed. Selective transport of finer material was evident throughout the aggradational cycles and became more pronounced during degradational cycles as the bed became armored. Our flume results of changes in bed elevation, sediment storage, channel morphology, and bed texture parallel those from field surveys of Redwood Creek, northern California, which has exhibited channel bed degradation for 30??years following a large aggradation event in the 1970s. The flume experiment suggested that channel recovery in terms of reestablishing a specific morphology may not occur, but the channel may return to a state of balancing sediment supply and transport capacity.
Piquado, Tepring; Cousins, Katheryn A Q; Wingfield, Arthur; Miller, Paul
2010-12-13
Poor hearing acuity reduces memory for spoken words, even when the words are presented with enough clarity for correct recognition. An "effortful hypothesis" suggests that the perceptual effort needed for recognition draws from resources that would otherwise be available for encoding the word in memory. To assess this hypothesis, we conducted a behavioral task requiring immediate free recall of word-lists, some of which contained an acoustically masked word that was just above perceptual threshold. Results show that masking a word reduces the recall of that word and words prior to it, as well as weakening the linking associations between the masked and prior words. In contrast, recall probabilities of words following the masked word are not affected. To account for this effect we conducted computational simulations testing two classes of models: Associative Linking Models and Short-Term Memory Buffer Models. Only a model that integrated both contextual linking and buffer components matched all of the effects of masking observed in our behavioral data. In this Linking-Buffer Model, the masked word disrupts a short-term memory buffer, causing associative links of words in the buffer to be weakened, affecting memory for the masked word and the word prior to it, while allowing links of words following the masked word to be spared. We suggest that these data account for the so-called "effortful hypothesis", where distorted input has a detrimental impact on prior information stored in short-term memory. Copyright © 2010 Elsevier B.V. All rights reserved.
Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model
Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.
2015-11-01
In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.
Bilinearity in spatiotemporal integration of synaptic inputs.
Directory of Open Access Journals (Sweden)
Songting Li
2014-12-01
Full Text Available Neurons process information via integration of synaptic inputs from dendrites. Many experimental results demonstrate dendritic integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization analytically. Based on asymptotic analysis of a two-compartment passive cable model, given a pair of time-dependent synaptic conductance inputs, we derive a bilinear spatiotemporal dendritic integration rule. The summed somatic potential can be well approximated by the linear summation of the two postsynaptic potentials elicited separately, plus a third additional bilinear term proportional to their product with a proportionality coefficient [Formula: see text]. The rule is valid for a pair of synaptic inputs of all types, including excitation-inhibition, excitation-excitation, and inhibition-inhibition. In addition, the rule is valid during the whole dendritic integration process for a pair of synaptic inputs with arbitrary input time differences and input locations. The coefficient [Formula: see text] is demonstrated to be nearly independent of the input strengths but is dependent on input times and input locations. This rule is then verified through simulation of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. The rule is further generalized to describe the spatiotemporal dendritic integration of multiple excitatory and inhibitory synaptic inputs. The integration of multiple inputs can be decomposed into the sum of all possible pairwise integration, where each paired integration obeys the bilinear rule. This decomposition leads to a graph representation of dendritic integration, which can be viewed as functionally sparse.
Mathematical Model of Thyristor Inverter Including a Series-parallel Resonant Circuit
Directory of Open Access Journals (Sweden)
Miroslaw Luft
2008-01-01
Full Text Available The article presents a mathematical model of thyristor inverter including a series-parallel resonant circuit with theaid of state variable method. Maple procedures are used to compute current and voltage waveforms in the inverter.
Mathematical model of thyristor inverter including a series-parallel resonant circuit
Luft, M.; Szychta, E.
2008-01-01
The article presents a mathematical model of thyristor inverter including a series-parallel resonant circuit with the aid of state variable method. Maple procedures are used to compute current and voltage waveforms in the inverter.
Mathematical Model of Thyristor Inverter Including a Series-parallel Resonant Circuit
Miroslaw Luft; Elzbieta Szychta
2008-01-01
The article presents a mathematical model of thyristor inverter including a series-parallel resonant circuit with theaid of state variable method. Maple procedures are used to compute current and voltage waveforms in the inverter.
National Research Council Canada - National Science Library
Boettner, Daisie
2001-01-01
.... This study develops models for a stand-alone Proton Exchange Membrane (PEM) fuel cell stack, a direct-hydrogen fuel cell system including auxiliaries, and a methanol reforming fuel cell system for integration into a vehicle performance simulator...
Energy Technology Data Exchange (ETDEWEB)
Whitehead, Camilla Dunham; Melody, Moya; Lutz, James
2009-05-29
Lawrence Berkeley National Laboratory (LBNL) is developing a computer model and spreadsheet tool for the United States Environmental Protection Agency (EPA) to help estimate the water savings attributable to their WaterSense program. WaterSense has developed a labeling program for three types of plumbing fixtures commonly used in commercial and institutional settings: flushometer valve toilets, urinals, and pre-rinse spray valves. This National Water Savings-Commercial/Institutional (NWS-CI) model is patterned after the National Water Savings-Residential model, which was completed in 2008. Calculating the quantity of water and money saved through the WaterSense labeling program requires three primary inputs: (1) the quantity of a given product in use; (2) the frequency with which units of the product are replaced or are installed in new construction; and (3) the number of times or the duration the product is used in various settings. To obtain the information required for developing the NWS-CI model, LBNL reviewed various resources pertaining to the three WaterSense-labeled commercial/institutional products. The data gathered ranged from the number of commercial buildings in the United States to numbers of employees in various sectors of the economy and plumbing codes for commercial buildings. This document summarizes information obtained about the three products' attributes, quantities, and use in commercial and institutional settings that is needed to estimate how much water EPA's WaterSense program saves.
Modeling of the Direct Current Generator Including the Magnetic Saturation and Temperature Effects
Directory of Open Access Journals (Sweden)
Alfonso J. Mercado-Samur
2013-11-01
Full Text Available In this paper the inclusion of temperature effect on the field resistance on the direct current generator model DC1A, which is valid to stability studies is proposed. First, the linear generator model is presented, after the effect of magnetic saturation and the change in the resistance value due to temperature produced by the field current are included. The comparison of experimental results and model simulations to validate the model is used. A direct current generator model which is a better representation of the generator is obtained. Visual comparison between simulations and experimental results shows the success of the proposed model, because it presents the lowest error of the compared models. The accuracy of the proposed model is observed via Modified Normalized Sum of Squared Errors index equal to 3.8979%.
Atmosphere-soil-vegetation model including CO2 exchange processes: SOLVEG2
International Nuclear Information System (INIS)
Nagai, Haruyasu
2004-11-01
A new atmosphere-soil-vegetation model named SOLVEG2 (SOLVEG version 2) was developed to study the heat, water, and CO 2 exchanges between the atmosphere and land-surface. The model consists of one-dimensional multilayer sub-models for the atmosphere, soil, and vegetation. It also includes sophisticated processes for solar and long-wave radiation transmission in vegetation canopy and CO 2 exchanges among the atmosphere, soil, and vegetation. Although the model usually simulates only vertical variation of variables in the surface-layer atmosphere, soil, and vegetation canopy by using meteorological data as top boundary conditions, it can be used by coupling with a three-dimensional atmosphere model. In this paper, details of SOLVEG2, which includes the function of coupling with atmosphere model MM5, are described. (author)
van Lith, PF; Betlem, BHL; Roffel, B
2003-01-01
This paper presents the development of a simple model which describes the product quality and production over time of an experimental batch distillation column, including start-up. The model structure is based on a simple physical framework, which is augmented with fuzzy logic. This provides a way
Enhanced UWB Radio Channel Model for Short-Range Communication Scenarios Including User Dynamics
DEFF Research Database (Denmark)
Kovacs, Istvan Zsolt; Nguyen, Tuan Hung; Eggers, Patrick Claus F.
2005-01-01
channel model represents an enhancement of the existing IEEE 802.15.3a/4a PAN channel model, where antenna and user-proximity effects are not included. Our investigations showed that significant variations of the received wideband power and time-delay signal clustering are possible due the human body...
DEFF Research Database (Denmark)
Andersen, Morten; Vinther, Frank; Ottesen, Johnny T.
2013-01-01
This paper presents a mathematical model of the HPA axis. The HPA axis consists of the hypothalamus, the pituitary and the adrenal glands in which the three hormones CRH, ACTH and cortisol interact through receptor dynamics. Furthermore, it has been suggested that receptors in the hippocampus have...... an influence on the axis.A model is presented with three coupled, non-linear differential equations, with the hormones CRH, ACTH and cortisol as variables. The model includes the known features of the HPA axis, and includes the effects from the hippocampus through its impact on CRH in the hypothalamus...
DEFF Research Database (Denmark)
Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo
2015-01-01
-year model outputs uncertainty. More precisely, this study contributes to the existing literature on the topic by investigating the effects on model outputs uncertainty deriving from the use of (i) different probability distributions in the sampling process, (ii) different assignment algorithms, and (iii...... of coefficient of variation, resulting from stochastic user equilibrium and user equilibrium is, respectively, of 0.425 and 0.468. Finally, network congestion does not show a high effect on model output uncertainty at the network level. However, the final uncertainty of links with higher volume/capacity ratio......If not properly quantified, the uncertainty inherent to transport models makes analyses based on their output highly unreliable. This study investigated uncertainty in four-stage transport models by analysing a Danish case-study: the Næstved model. The model describes the demand of transport...
Šiljić, Aleksandra; Antanasijević, Davor; Perić-Grujić, Aleksandra; Ristić, Mirjana; Pocajt, Viktor
2015-03-01
Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to report annual BOD values to Eurostat; however, BOD data at the national level is only available for 28 of 35 listed European countries for the period prior to 2008, among which 46% of data is missing. This paper describes the development of an artificial neural network model for the forecasting of annual BOD values at the national level, using widely available sustainability and economical/industrial parameters as inputs. The initial general regression neural network (GRNN) model was trained, validated and tested utilizing 20 inputs. The number of inputs was reduced to 15 using the Monte Carlo simulation technique as the input selection method. The best results were achieved with the GRNN model utilizing 25% less inputs than the initial model and a comparison with a multiple linear regression model trained and tested using the same input variables using multiple statistical performance indicators confirmed the advantage of the GRNN model. Sensitivity analysis has shown that inputs with the greatest effect on the GRNN model were (in descending order) precipitation, rural population with access to improved water sources, treatment capacity of wastewater treatment plants (urban) and treatment of municipal waste, with the last two having an equal effect. Finally, it was concluded that the developed GRNN model can be useful as a tool to support the decision-making process on sustainable development at a regional, national and international level.
Modification of TOUGH2 to Include the Dusty Gas Model for Gas Diffusion; TOPICAL
International Nuclear Information System (INIS)
WEBB, STEPHEN W.
2001-01-01
The GEO-SEQ Project is investigating methods for geological sequestration of CO(sub 2). This project, which is directed by LBNL and includes a number of other industrial, university, and national laboratory partners, is evaluating computer simulation methods including TOUGH2 for this problem. The TOUGH2 code, which is a widely used code for flow and transport in porous and fractured media, includes simplified methods for gas diffusion based on a direct application of Fick's law. As shown by Webb (1998) and others, the Dusty Gas Model (DGM) is better than Fick's Law for modeling gas-phase diffusion in porous media. In order to improve gas-phase diffusion modeling for the GEO-SEQ Project, the EOS7R module in the TOUGH2 code has been modified to include the Dusty Gas Model as documented in this report. In addition, the liquid diffusion model has been changed from a mass-based formulation to a mole-based model. Modifications for separate and coupled diffusion in the gas and liquid phases have also been completed. The results from the DGM are compared to the Fick's law behavior for TCE and PCE diffusion across a capillary fringe. The differences are small due to the relatively high permeability (k= 10(sup -11) m(sup 2)) of the problem and the small mole fraction of the gases. Additional comparisons for lower permeabilities and higher mole fractions may be useful
Román, Roberto; Bilbao, Julia; de Miguel, Argimiro; Pérez-Burgos, Ana
2014-05-01
The radiative transfer models can be used to obtain solar radiative quantities in the Earth surface as the erythemal ultraviolet (UVER) irradiance, which is the spectral irradiance weighted with the erythemal (sunburn) action spectrum, and the total shortwave irradiance (SW; 305-2,8000 nm). Aerosol and atmospheric properties are necessary as inputs in the model in order to calculate the UVER and SW irradiances under cloudless conditions, however the uncertainty in these inputs causes another uncertainty in the simulations. The objective of this work is to quantify the uncertainty in UVER and SW simulations generated by the aerosol optical depth (AOD) uncertainty. The data from different satellite retrievals were downloaded at nine Spanish places located in the Iberian Peninsula: Total ozone column from different databases, spectral surface albedo and water vapour column from MODIS instrument, AOD at 443 nm and Angström Exponent (between 443 nm and 670 nm) from MISR instrument onboard Terra satellite, single scattering albedo from OMI instrument onboard Aura satellite. The obtained AOD at 443 nm data from MISR were compared with AERONET measurements in six Spanish sites finding an uncertainty in the AOD from MISR of 0.074. In this work the radiative transfer model UVSPEC/Libradtran (1.7 version) was used to obtain the SW and UVER irradiance under cloudless conditions for each month and for different solar zenith angles (SZA) in the nine mentioned locations. The inputs used for these simulations were monthly climatology tables obtained with the available data in each location. Once obtained the UVER and SW simulations, they were repeated twice but changing the AOD monthly values by the same AOD plus/minus its uncertainty. The maximum difference between the irradiance run with AOD and the irradiance run with AOD plus/minus its uncertainty was calculated for each month, SZA, and location. This difference was considered as the uncertainty on the model caused by the AOD
Numerical Acoustic Models Including Viscous and Thermal losses: Review of Existing and New Methods
DEFF Research Database (Denmark)
Andersen, Peter Risby; Cutanda Henriquez, Vicente; Aage, Niels
2017-01-01
This work presents an updated overview of numerical methods including acoustic viscous and thermal losses. Numerical modelling of viscothermal losses has gradually become more important due to the general trend of making acoustic devices smaller. Not including viscothermal acoustic losses...... in such numerical computations will therefore lead to inaccurate or even wrong results. Both, Finite Element Method (FEM) and Boundary Element Method (BEM), formulations are available that incorporate these loss mechanisms. Including viscothermal losses in FEM computations can be computationally very demanding, due...... and BEM method including viscothermal dissipation are compared and investigated....
International Nuclear Information System (INIS)
Obe, Emeka S.; Binder, A.
2011-01-01
A detailed model in direct-phase variables of a synchronous reluctance motor operating at mains voltage and frequency is presented. The model includes the stator and rotor slot openings, the actual winding layout and the reluctance rotor geometry. Hence, all mmf and permeance harmonics are taken into account. It is seen that non-negligible harmonics introduced by slots are present in the inductances computed by the winding function procedure. These harmonics are usually ignored in d-q models. The machine performance is simulated in the stator reference frame to depict the difference between this new direct-phase model including all harmonics and the conventional rotor reference frame d-q model. Saturation is included by using a polynomial fitting the variation of d-axis inductance with stator current obtained by finite-element software FEMAG DC (registered) . The detailed phase-variable model can yield torque pulsations comparable to those obtained from finite elements while the d-q model cannot.
Azzopardi, George; Petkov, Nicolai
Simple cells in primary visual cortex are believed to extract local contour information from a visual scene. The 2D Gabor function (GF) model has gained particular popularity as a computational model of a simple cell. However, it short-cuts the LGN, it cannot reproduce a number of properties of real
Directory of Open Access Journals (Sweden)
Narges Neyazi
2016-06-01
Full Text Available Purpose: Objective of this research is to find out weaknesses of undergraduate programs in terms of personnel and financial, organizational management and facilities in view of faculty and library staff, and determining factors that may facilitate program quality–improvement. Methods: This is a descriptive analytical survey research and from purpose aspect is an application evaluation study that undergraduate groups of selected faculties (Public Health, Nursing and Midwifery, Allied Medical Sciences and Rehabilitation at Tehran University of Medical Sciences (TUMS have been surveyed using context input process product model in 2014. Statistical population were consist of three subgroups including department head (n=10, faculty members (n=61, and library staff (n=10 with total population of 81 people. Data collected through three researcher-made questionnaires which were based on Likert scale. The data were then analyzed using descriptive and inferential statistics. Results: Results showed desirable and relatively desirable situation for factors in context, input, process, and product fields except for factors of administration and financial; and research and educational spaces and equipment which were in undesirable situation. Conclusion: Based on results, researcher highlighted weaknesses in the undergraduate programs of TUMS in terms of research and educational spaces and facilities, educational curriculum, administration and financial; and recommended some steps in terms of financial, organizational management and communication with graduates in order to improve the quality of this system.
Sanz-Requena, Roberto; Prats-Montalbán, José Manuel; Martí-Bonmatí, Luis; Alberich-Bayarri, Ángel; García-Martí, Gracián; Pérez, Rosario; Ferrer, Alberto
2015-08-01
To introduce a segmentation method to calculate an automatic arterial input function (AIF) based on principal component analysis (PCA) of dynamic contrast enhanced MR (DCE-MR) imaging and compare it with individual manually selected and population-averaged AIFs using calculated pharmacokinetic parameters. The study included 65 individuals with prostate examinations (27 tumors and 38 controls). Manual AIFs were individually extracted and also averaged to obtain a population AIF. Automatic AIFs were individually obtained by applying PCA to volumetric DCE-MR imaging data and finding the highest correlation of the PCs with a reference AIF. Variability was assessed using coefficients of variation and repeated measures tests. The different AIFs were used as inputs to the pharmacokinetic model and correlation coefficients, Bland-Altman plots and analysis of variance tests were obtained to compare the results. Automatic PCA-based AIFs were successfully extracted in all cases. The manual and PCA-based AIFs showed good correlation (r between pharmacokinetic parameters ranging from 0.74 to 0.95), with differences below the manual individual variability (RMSCV up to 27.3%). The population-averaged AIF showed larger differences (r from 0.30 to 0.61). The automatic PCA-based approach minimizes the variability associated to obtaining individual volume-based AIFs in DCE-MR studies of the prostate. © 2014 Wiley Periodicals, Inc.
Modeling of Temperature-Dependent Noise in Silicon Nanowire FETs including Self-Heating Effects
Anandan, P.; Malathi, N.; Mohankumar, N.
2014-01-01
Silicon nanowires are leading the CMOS era towards the downsizing limit and its nature will be effectively suppress the short channel effects. Accurate modeling of thermal noise in nanowires is crucial for RF applications of nano-CMOS emerging technologies. In this work, a perfect temperature-dependent model for silicon nanowires including the self-heating effects has been derived and its effects on device parameters have been observed. The power spectral density as a function of thermal resi...
Dipole model analysis of highest precision HERA data, including very low Q2's
International Nuclear Information System (INIS)
Luszczak, A.; Kowalski, H.
2016-12-01
We analyse, within a dipole model, the final, inclusive HERA DIS cross section data in the low χ region, using fully correlated errors. We show, that these highest precision data are very well described within the dipole model framework starting from Q 2 values of 3.5 GeV 2 to the highest values of Q 2 =250 GeV 2 . To analyze the saturation effects we evaluated the data including also the very low 0.35including this region show a preference of the saturation ansatz.
The No-Core Gamow Shell Model: Including the continuum in the NCSM
Barrett, B R; Michel, N; Płoszajczak, M
2015-01-01
We are witnessing an era of intense experimental efforts that will provide information about the properties of nuclei far from the line of stability, regarding resonant and scattering states as well as (weakly) bound states. This talk describes our formalism for including these necessary ingredients into the No-Core Shell Model by using the Gamow Shell Model approach. Applications of this new approach, known as the No-Core Gamow Shell Model, both to benchmark cases as well as to unstable nuclei will be given.
Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures.
Klenk, Jochen; Becker, Clemens; Palumbo, Pierpaolo; Schwickert, Lars; Rapp, Kilan; Helbostad, Jorunn L; Todd, Chris; Lord, Stephen R; Kerse, Ngaire
2017-11-01
Falls are a major cause of injury and disability in older people, leading to serious health and social consequences including fractures, poor quality of life, loss of independence, and institutionalization. To design and provide adequate prevention measures, accurate understanding and identification of person's individual fall risk is important. However, to date, the performance of fall risk models is weak compared with models estimating, for example, cardiovascular risk. This deficiency may result from 2 factors. First, current models consider risk factors to be stable for each person and not change over time, an assumption that does not reflect real-life experience. Second, current models do not consider the interplay of individual exposure including type of activity (eg, walking, undertaking transfers) and environmental risks (eg, lighting, floor conditions) in which activity is performed. Therefore, we posit a dynamic fall risk model consisting of intrinsic risk factors that vary over time and exposure (activity in context). eHealth sensor technology (eg, smartphones) begins to enable the continuous measurement of both the above factors. We illustrate our model with examples of real-world falls from the FARSEEING database. This dynamic framework for fall risk adds important aspects that may improve understanding of fall mechanisms, fall risk models, and the development of fall prevention interventions. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.
Modeling of cylindrical surrounding gate MOSFETs including the fringing field effects
International Nuclear Information System (INIS)
Gupta, Santosh K.; Baishya, Srimanta
2013-01-01
A physically based analytical model for surface potential and threshold voltage including the fringing gate capacitances in cylindrical surround gate (CSG) MOSFETs has been developed. Based on this a subthreshold drain current model has also been derived. This model first computes the charge induced in the drain/source region due to the fringing capacitances and considers an effective charge distribution in the cylindrically extended source/drain region for the development of a simple and compact model. The fringing gate capacitances taken into account are outer fringe capacitance, inner fringe capacitance, overlap capacitance, and sidewall capacitance. The model has been verified with the data extracted from 3D TCAD simulations of CSG MOSFETs and was found to be working satisfactorily. (semiconductor devices)
International Nuclear Information System (INIS)
Chen, Y W; Zhang, L F; Huang, J P
2007-01-01
By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property
Including Effects of Water Stress on Dead Organic Matter Decay to a Forest Carbon Model
Kim, H.; Lee, J.; Han, S. H.; Kim, S.; Son, Y.
2017-12-01
Decay of dead organic matter is a key process of carbon (C) cycling in forest ecosystems. The change in decay rate depends on temperature sensitivity and moisture conditions. The Forest Biomass and Dead organic matter Carbon (FBDC) model includes a decay sub-model considering temperature sensitivity, yet does not consider moisture conditions as drivers of the decay rate change. This study aimed to improve the FBDC model by including a water stress function to the decay sub-model. Also, soil C sequestration under climate change with the FBDC model including the water stress function was simulated. The water stress functions were determined with data from decomposition study on Quercus variabilis forests and Pinus densiflora forests of Korea, and adjustment parameters of the functions were determined for both species. The water stress functions were based on the ratio of precipitation to potential evapotranspiration. Including the water stress function increased the explained variances of the decay rate by 19% for the Q. variabilis forests and 7% for the P. densiflora forests, respectively. The increase of the explained variances resulted from large difference in temperature range and precipitation range across the decomposition study plots. During the period of experiment, the mean annual temperature range was less than 3°C, while the annual precipitation ranged from 720mm to 1466mm. Application of the water stress functions to the FBDC model constrained increasing trend of temperature sensitivity under climate change, and thus increased the model-estimated soil C sequestration (Mg C ha-1) by 6.6 for the Q. variabilis forests and by 3.1 for the P. densiflora forests, respectively. The addition of water stress functions increased reliability of the decay rate estimation and could contribute to reducing the bias in estimating soil C sequestration under varying moisture condition. Acknowledgement: This study was supported by Korea Forest Service (2017044B10-1719-BB01)
International Nuclear Information System (INIS)
French McCay, Deborah; Reich, Danielle; Rowe, Jill; Schroeder, Melanie; Graham, Eileen
2011-01-01
This paper simulates the consequences of oil spills using a planning model known as the Offshore Environmental Cost Model (OECM). This study aims at creating various predictive models for possible oil spill scenarios in marine waters. A crucial part of this investigation was the SIMAP model. It analyzes the distance and the direction covered by the spill under certain test conditions, generating a regression equation that simulates the impact of the spill. Tests were run in two different regions; the Mid-Atlantic region and the Chukchi Sea. Results showed that the higher wind speeds and higher water temperature of the Mid-Atlantic region had greater impact on wildlife and the water column respectively. However, short-line impact was higher in the Chukchi area due to the multi-directional wind. It was also shown that, because of their higher diffusivity in water, lighter crude oils had more impact than heavier oils. It was suggested that this model could ultimately be applied to other oil spill scenarios happening under similar conditions.
A catchment-scale groundwater model including sewer pipe leakage in an urban system
Peche, Aaron; Fuchs, Lothar; Spönemann, Peter; Graf, Thomas; Neuweiler, Insa
2016-04-01
Keywords: pipe leakage, urban hydrogeology, catchment scale, OpenGeoSys, HYSTEM-EXTRAN Wastewater leakage from subsurface sewer pipe defects leads to contamination of the surrounding soil and groundwater (Ellis, 2002; Wolf et al., 2004). Leakage rates at pipe defects have to be known in order to quantify contaminant input. Due to inaccessibility of subsurface pipe defects, direct (in-situ) measurements of leakage rates are tedious and associated with a high degree of uncertainty (Wolf, 2006). Proposed catchment-scale models simplify leakage rates by neglecting unsaturated zone flow or by reducing spatial dimensions (Karpf & Krebs, 2013, Boukhemacha et al., 2015). In the present study, we present a physically based 3-dimensional numerical model incorporating flow in the pipe network, in the saturated zone and in the unsaturated zone to quantify leakage rates on the catchment scale. The model consists of the pipe network flow model HYSTEM-EXTAN (itwh, 2002), which is coupled to the subsurface flow model OpenGeoSys (Kolditz et al., 2012). We also present the newly developed coupling scheme between the two flow models. Leakage functions specific to a pipe defect are derived from simulations of pipe leakage using spatially refined grids around pipe defects. In order to minimize computational effort, these leakage functions are built into the presented numerical model using unrefined grids around pipe defects. The resulting coupled model is capable of efficiently simulating spatially distributed pipe leakage coupled with subsurficial water flow in a 3-dimensional environment. References: Boukhemacha, M. A., Gogu, C. R., Serpescu, I., Gaitanaru, D., & Bica, I. (2015). A hydrogeological conceptual approach to study urban groundwater flow in Bucharest city, Romania. Hydrogeology Journal, 23(3), 437-450. doi:10.1007/s10040-014-1220-3. Ellis, J. B., & Revitt, D. M. (2002). Sewer losses and interactions with groundwater quality. Water Science and Technology, 45(3), 195
Directory of Open Access Journals (Sweden)
Yuqiao Gu
Full Text Available In the antennal lobe of the noctuid moth Agrotis ipsilon, most pheromone-sensitive projection neurons (PNs exhibit a triphasic firing pattern of excitation (E1-inhibition (I-excitation (E2 in response to a pulse of the sex pheromone. To understand the mechanisms underlying this stereotypical discharge, we developed a biophysical model of a PN receiving inputs from olfactory receptor neurons (ORNs via nicotinic cholinergic synapses. The ORN is modeled as an inhomogeneous Poisson process whose firing rate is a function of time and is fitted to extracellular data recorded in response to pheromone stimulations at various concentrations and durations. The PN model is based on the Hodgkin-Huxley formalism with realistic ionic currents whose parameters were derived from previous studies. Simulations revealed that the inhibitory phase I can be produced by a SK current (Ca2+-gated small conductance K+ current and that the excitatory phase E2 can result from the long-lasting response of the ORNs. Parameter analysis further revealed that the ending time of E1 depends on some parameters of SK, Ca2+, nACh and Na+ currents; I duration mainly depends on the time constant of intracellular Ca2+ dynamics, conductance of Ca2+ currents and some parameters of nACh currents; The mean firing frequency of E1 and E2 depends differentially on the interaction of various currents. Thus it is likely that the interplay between PN intrinsic currents and feedforward synaptic currents are sufficient to generate the triphasic firing patterns observed in the noctuid moth A. ipsilon.
Bermudez, A.; Rivas, D.
2015-12-01
Phytoplankton bloom dynamics depends on the interactions of favorable physical, chemical, and biotic conditions, particularly on the available nutrients that enhance phytoplankton growth, like nitrogen. Costal and estuarine environments are heavily influenced by exogenous sources of nitrogen; the anthropogenic inputs include urban and rural wastewater coming from agricultural activities (i.e., fertilizers and animal waste). In response, new production is often enhanced, leading eutrophication and phytoplankton blooms, including harmful taxa. These events have become more frequent, and with it the interest to evaluate their effects on marine ecosystems and the impact on human health. In the Gulf of California the harmful algal blooms (HABs) had affected aquaculture, fisheries, and even tourism, thereby it is important to generate information about biological and physical factors that can influence their appearance. A numerical model is a tool that may bring key information about the origin and distribution of phytoplankton blooms. Herein the analysis is based on a three-dimensional, hydrodynamical numerical model, coupled to a Nitrogen-Phytoplankton-Zooplankton-Detritus (NPZD) model. Several numerical simulations using different forcing and scenarios are carried out in order to evaluate the processes that influence the phytoplankton growth. These numerical results are compared to available observations. Thus, the main environmental factors triggering the generation of HABs can be identified.
Including an ocean carbon cycle model into iLOVECLIM (v1.0)
Bouttes, N.; Roche, D.M.V.A.P.; Mariotti, V.; Bopp, L.
2015-01-01
The atmospheric carbon dioxide concentration plays a crucial role in the radiative balance and as such has a strong influence on the evolution of climate. Because of the numerous interactions between climate and the carbon cycle, it is necessary to include a model of the carbon cycle within a
Directory of Open Access Journals (Sweden)
Guijun Li
2016-09-01
Full Text Available An explanation and quantification of the water-energy-food nexus (WEF-Nexus is important to advance our understanding of regional resource management, which is presently in its infant stage. Evaluation of the current states, interconnections, and trends of WEF-Nexus, in cities, has largely been ignored due to quantification hurdles and the lack of available data. Based on the interaction of WEF-Nexus with population system, economic system, and environmental system, this paper builds the input output index system at the city level. Using the input output index system, we evaluate the WEF-Nexus input-output efficiency with the data envelopment analysis (DEA model. We regard the decision making unit as a “black box”, to explore the states and trends of WEF-Nexus. In the empirical study based on data from China, we compare the input-output efficiency of WEF-Nexus in 30 provinces across China, from 2005 to 2014, to better understand their statues and trends of the input-output efficiency holistically. Together with the Malmquist index, factors leading to regional differences in the fluctuation of input-output efficiency are explored. Finally, we conclude that the DEA model indicates the regional consumption of WEF resources in the horizontal dimension and the trends in vertical dimension, together with the Malmquist index, to explain the variations for proposing specific implications.
International Nuclear Information System (INIS)
Jensen, B.S.
1982-01-01
It is probably obvious to all, that establishing the scientific basis of geological waste disposal by going deeper and deeper in detail, may fill out the working hours of hundreds of scientists for hundreds of years. Such an endeavor is, however, impossible to attain, and we are forced to define some criteria telling us and others when knowledge and insight is sufficient. In thepresent case of geological disposal one need to be able to predict migration behavior of a series of radionuclides under diverse conditions to ascertain that unacceptable transfer to the biosphere never occurs. We have already collected a huge amount of data concerning migration phenomena, some very useful, oter less so, but we still need investigatoins departing from the simple ideal concepts, which most often have provided modellers with input data to their calculations. I therefore advocate that basic research is pursued to the point where it is possible to put limits on the effect of the lesser known factors on the migration behavior of radionuclides. When such limits have been established, it will be possible to make calculations on the worst cases, which may also occur. Although I personally believe, that these extra investigations will prove additional safety in geological disposal, this fact will convince nobody, only experimental facts will do
International Nuclear Information System (INIS)
Coolen, F.P.A.
1997-01-01
This paper is intended to make researchers in reliability theory aware of a recently introduced Bayesian model with imprecise prior distributions for statistical inference on failure data, that can also be considered as a robust Bayesian model. The model consists of a multinomial distribution with Dirichlet priors, making the approach basically nonparametric. New results for the model are presented, related to right-censored observations, where estimation based on this model is closely related to the product-limit estimator, which is an important statistical method to deal with reliability or survival data including right-censored observations. As for the product-limit estimator, the model considered in this paper aims at not using any information other than that provided by observed data, but our model fits into the robust Bayesian context which has the advantage that all inferences can be based on probabilities or expectations, or bounds for probabilities or expectations. The model uses a finite partition of the time-axis, and as such it is also related to life-tables
Diehl, S; Zambrano, J; Carlsson, B
2016-01-01
A reduced model of a completely stirred-tank bioreactor coupled to a settling tank with recycle is analyzed in its steady states. In the reactor, the concentrations of one dominant particulate biomass and one soluble substrate component are modelled. While the biomass decay rate is assumed to be constant, growth kinetics can depend on both substrate and biomass concentrations, and optionally model substrate inhibition. Compressive and hindered settling phenomena are included using the Bürger-Diehl settler model, which consists of a partial differential equation. Steady-state solutions of this partial differential equation are obtained from an ordinary differential equation, making steady-state analysis of the entire plant difficult. A key result showing that the ordinary differential equation can be replaced with an approximate algebraic equation simplifies model analysis. This algebraic equation takes the location of the sludge-blanket during normal operation into account, allowing for the limiting flux capacity caused by compressive settling to easily be included in the steady-state mass balance equations for the entire plant system. This novel approach grants the possibility of more realistic solutions than other previously published reduced models, comprised of yet simpler settler assumptions. The steady-state concentrations, solids residence time, and the wastage flow ratio are functions of the recycle ratio. Solutions are shown for various growth kinetics; with different values of biomass decay rate, influent volumetric flow, and substrate concentration. Copyright © 2015 Elsevier Ltd. All rights reserved.
Fully automated calculation of image-derived input function in simultaneous PET/MRI in a sheep model
Energy Technology Data Exchange (ETDEWEB)
Jochimsen, Thies H.; Zeisig, Vilia [Department of Nuclear Medicine, Leipzig University Hospital, Liebigstr. 18, Leipzig (Germany); Schulz, Jessica [Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig, D-04103 (Germany); Werner, Peter; Patt, Marianne; Patt, Jörg [Department of Nuclear Medicine, Leipzig University Hospital, Liebigstr. 18, Leipzig (Germany); Dreyer, Antje Y. [Fraunhofer Institute of Cell Therapy and Immunology, Perlickstr. 1, Leipzig, D-04103 (Germany); Translational Centre for Regenerative Medicine, University Leipzig, Philipp-Rosenthal-Str. 55, Leipzig, D-04103 (Germany); Boltze, Johannes [Fraunhofer Institute of Cell Therapy and Immunology, Perlickstr. 1, Leipzig, D-04103 (Germany); Translational Centre for Regenerative Medicine, University Leipzig, Philipp-Rosenthal-Str. 55, Leipzig, D-04103 (Germany); Fraunhofer Research Institution of Marine Biotechnology and Institute for Medical and Marine Biotechnology, University of Lübeck, Lübeck (Germany); Barthel, Henryk; Sabri, Osama; Sattler, Bernhard [Department of Nuclear Medicine, Leipzig University Hospital, Liebigstr. 18, Leipzig (Germany)
2016-02-13
Obtaining the arterial input function (AIF) from image data in dynamic positron emission tomography (PET) examinations is a non-invasive alternative to arterial blood sampling. In simultaneous PET/magnetic resonance imaging (PET/MRI), high-resolution MRI angiographies can be used to define major arteries for correction of partial-volume effects (PVE) and point spread function (PSF) response in the PET data. The present study describes a fully automated method to obtain the image-derived input function (IDIF) in PET/MRI. Results are compared to those obtained by arterial blood sampling. To segment the trunk of the major arteries in the neck, a high-resolution time-of-flight MRI angiography was postprocessed by a vessel-enhancement filter based on the inertia tensor. Together with the measured PSF of the PET subsystem, the arterial mask was used for geometrical deconvolution, yielding the time-resolved activity concentration averaged over a major artery. The method was compared to manual arterial blood sampling at the hind leg of 21 sheep (animal stroke model) during measurement of blood flow with O15-water. Absolute quantification of activity concentration was compared after bolus passage during steady state, i.e., between 2.5- and 5-min post injection. Cerebral blood flow (CBF) values from blood sampling and IDIF were also compared. The cross-calibration factor obtained by comparing activity concentrations in blood samples and IDIF during steady state is 0.98 ± 0.10. In all examinations, the IDIF provided a much earlier and sharper bolus peak than in the time course of activity concentration obtained by arterial blood sampling. CBF using the IDIF was 22 % higher than CBF obtained by using the AIF yielded by blood sampling. The small deviation between arterial blood sampling and IDIF during steady state indicates that correction of PVE and PSF is possible with the method presented. The differences in bolus dynamics and, hence, CBF values can be explained by the
International Nuclear Information System (INIS)
Santos, P.J.; Martins, A.G.; Pires, A.J.
2007-01-01
The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)
Energy Technology Data Exchange (ETDEWEB)
Santos, P.J. [LabSEI-ESTSetubal-Department of Electrical Engineering at Escola Superior de Tecnologia, Polytechnic Institute of Setubal Rua Vale de Chaves Estefanilha, 2910-761 Setubal (Portugal); Martins, A.G. [Department of Electrical Engineering, FCTUC/INESC, Polo 2 University of Coimbra, Pinhal de Marrocos, 3030 Coimbra (Portugal); Pires, A.J. [LabSEI-ESTSetubal-Department of Electrical Engineering at Escola Superior de Tecnologia, Polytechnic Institute of Setubal Rua Vale de, Chaves Estefanilha, 2910-761 Setubal (Portugal)
2007-05-15
The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)
A roller chain drive model including contact with guide-bars
DEFF Research Database (Denmark)
Pedersen, Sine Leergaard; Hansen, John Michael; Ambrósio, J. A. C.
2004-01-01
as continuous force. The model of the roller-chain drive now proposed departs from an earlier model where two contact/impact methods are proposed to describe the contact between the rollers of the chain and the teeth of the sprockets. These different formulations are based on unilateral constraints....... In the continuous force method the roller-sprocket contact, is represented by forces applied on each seated roller and in the respective sprocket teeth. These forces are functions of the pseudo penetrations between roller and sprocket, impacting velocities and a restitution coefficient. In the continuous force......A model of a roller chain drive is developed and applied to the simulation and analysis of roller chain drives of large marine diesel engines. The model includes the impact with guide-bars that are the motion delimiter components on the chain strands between the sprockets. The main components...
Prospects for genetically modified non-human primate models, including the common marmoset.
Sasaki, Erika
2015-04-01
Genetically modified mice have contributed much to studies in the life sciences. In some research fields, however, mouse models are insufficient for analyzing the molecular mechanisms of pathology or as disease models. Often, genetically modified non-human primate (NHP) models are desired, as they are more similar to human physiology, morphology, and anatomy. Recent progress in studies of the reproductive biology in NHPs has enabled the introduction of exogenous genes into NHP genomes or the alteration of endogenous NHP genes. This review summarizes recent progress in the production of genetically modified NHPs, including the common marmoset, and future perspectives for realizing genetically modified NHP models for use in life sciences research. Copyright © 2015 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.
D'Ambrosio, Michele; Tofani, Veronica; Rossi, Guglielmo; Salvatici, Teresa; Tacconi Stefanelli, Carlo; Rosi, Ascanio; Benedetta Masi, Elena; Pazzi, Veronica; Vannocci, Pietro; Catani, Filippo; Casagli, Nicola
2017-04-01
The Aosta Valley region is located in North-West Alpine mountain chain. The geomorphology of the region is characterized by steep slopes, high climatic and altitude (ranging from 400 m a.s.l of Dora Baltea's river floodplain to 4810 m a.s.l. of Mont Blanc) variability. In the study area (zone B), located in Eastern part of Aosta Valley, heavy rainfall of about 800-900 mm per year is the main landslides trigger. These features lead to a high hydrogeological risk in all territory, as mass movements interest the 70% of the municipality areas (mainly shallow rapid landslides and rock falls). An in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslides formation was conducted, with the aim to improve the reliability of deterministic model, named HIRESS (HIgh REsolution Stability Simulator). In particular, two campaigns of on site measurements and laboratory experiments were performed. The data obtained have been studied in order to assess the relationships existing among the different parameters and the bedrock lithology. The analyzed soils in 12 survey points are mainly composed of sand and gravel, with highly variable contents of silt. The range of effective internal friction angle (from 25.6° to 34.3°) and effective cohesion (from 0 kPa to 9.3 kPa) measured and the median ks (10E-6 m/s) value are consistent with the average grain sizes (gravelly sand). The data collected contributes to generate input map of parameters for HIRESS (static data). More static data are: volume weight, residual water content, porosity and grain size index. In order to improve the original formulation of the model, the contribution of the root cohesion has been also taken into account based on the vegetation map and literature values. HIRESS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and in large areas using parallel computational techniques. The software
Sherwood, John; Clabeaux, Raeanne; Carbajales-Dale, Michael
2017-10-01
We developed a physically-based environmental account of US food production systems and integrated these data into the environmental-input-output life cycle assessment (EIO-LCA) model. The extended model was used to characterize the food, energy, and water (FEW) intensities of every US economic sector. The model was then applied to every Bureau of Economic Analysis metropolitan statistical area (MSA) to determine their FEW usages. The extended EIO-LCA model can determine the water resource use (kGal), energy resource use (TJ), and food resource use in units of mass (kg) or energy content (kcal) of any economic activity within the United States. We analyzed every economic sector to determine its FEW intensities per dollar of economic output. This data was applied to each of the 382 MSAs to determine their total and per dollar of GDP FEW usages by allocating MSA economic production to the corresponding FEW intensities of US economic sectors. Additionally, a longitudinal study was performed for the Los Angeles-Long Beach-Anaheim, CA, metropolitan statistical area to examine trends from this singular MSA and compare it to the overall results. Results show a strong correlation between GDP and energy use, and between food and water use across MSAs. There is also a correlation between GDP and greenhouse gas emissions. The longitudinal study indicates that these correlations can shift alongside a shifting industrial composition. Comparing MSAs on a per GDP basis reveals that central and southern California tend to be more resource intensive than many other parts of the country, while much of Florida has abnormally low resource requirements. Results of this study enable a more complete understanding of food, energy, and water as key ingredients to a functioning economy. With the addition of the food data to the EIO-LCA framework, researchers will be able to better study the food-energy-water nexus and gain insight into how these three vital resources are interconnected
Improving weather predictability by including land-surface model parameter uncertainty
Orth, Rene; Dutra, Emanuel; Pappenberger, Florian
2016-04-01
The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by
Global Reference Atmospheric Models, Including Thermospheres, for Mars, Venus and Earth
Justh, Hilary L.; Justus, C. G.; Keller, Vernon W.
2006-01-01
This document is the viewgraph slides of the presentation. Marshall Space Flight Center's Natural Environments Branch has developed Global Reference Atmospheric Models (GRAMs) for Mars, Venus, Earth, and other solar system destinations. Mars-GRAM has been widely used for engineering applications including systems design, performance analysis, and operations planning for aerobraking, entry descent and landing, and aerocapture. Preliminary results are presented, comparing Mars-GRAM with measurements from Mars Reconnaissance Orbiter (MRO) during its aerobraking in Mars thermosphere. Venus-GRAM is based on the Committee on Space Research (COSPAR) Venus International Reference Atmosphere (VIRA), and is suitable for similar engineering applications in the thermosphere or other altitude regions of the atmosphere of Venus. Until recently, the thermosphere in Earth-GRAM has been represented by the Marshall Engineering Thermosphere (MET) model. Earth-GRAM has recently been revised. In addition to including an updated version of MET, it now includes an option to use the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar Extended Model (NRLMSISE-00) as an alternate thermospheric model. Some characteristics and results from Venus-GRAM and Earth-GRAM thermospheres are also presented.
A numerical model including PID control of a multizone crystal growth furnace
Panzarella, Charles H.; Kassemi, Mohammad
1992-01-01
This paper presents a 2D axisymmetric combined conduction and radiation model of a multizone crystal growth furnace. The model is based on a programmable multizone furnace (PMZF) designed and built at NASA Lewis Research Center for growing high quality semiconductor crystals. A novel feature of this model is a control algorithm which automatically adjusts the power in any number of independently controlled heaters to establish the desired crystal temperatures in the furnace model. The control algorithm eliminates the need for numerous trial and error runs previously required to obtain the same results. The finite element code, FIDAP, used to develop the furnace model, was modified to directly incorporate the control algorithm. This algorithm, which presently uses PID control, and the associated heat transfer model are briefly discussed. Together, they have been used to predict the heater power distributions for a variety of furnace configurations and desired temperature profiles. Examples are included to demonstrate the effectiveness of the PID controlled model in establishing isothermal, Bridgman, and other complicated temperature profies in the sample. Finally, an example is given to show how the algorithm can be used to change the desired profile with time according to a prescribed temperature-time evolution.
Directory of Open Access Journals (Sweden)
Hyein Lim
2013-01-01
Full Text Available Spin-torque oscillator (STO is a promising new technology for the future RF oscillators, which is based on the spin-transfer torque (STT effect in magnetic multilayered nanostructure. It is expected to provide a larger tunability, smaller size, lower power consumption, and higher level of integration than the semiconductor-based oscillators. In our previous work, a circuit-level model of the giant magnetoresistance (GMR STO was proposed. In this paper, we present a physics-based circuit-level model of the magnetic tunnel junction (MTJ-based STO. MTJ-STO model includes the effect of perpendicular torque that has been ignored in the GMR-STO model. The variations of three major characteristics, generation frequency, mean oscillation power, and generation linewidth of an MTJ-STO with respect to the amount of perpendicular torque, are investigated, and the results are applied to our model. The operation of the model was verified by HSPICE simulation, and the results show an excellent agreement with the experimental data. The results also prove that a full circuit-level simulation with MJT-STO devices can be made with our proposed model.
Boynton, RJ; Balikhin, MA; Billings, SA; Amariutei, OA
2013-01-01
The nonlinear autoregressive moving average with exogenous inputs (NARMAX) system identification technique is applied to various aspects of the magnetospheres dynamics. It is shown, from an example system, how the inputs to a system can be found from the error reduction ratio (ERR) analysis, a key concept of the NARMAX approach. The application of the NARMAX approach to the Dst (disturbance storm time) index and the electron fluxes at geostationary Earth orbit (GEO) are reviewed, revealing ne...
Including Finite Surface Span Effects in Empirical Jet-Surface Interaction Noise Models
Brown, Clifford A.
2016-01-01
The effect of finite span on the jet-surface interaction noise source and the jet mixing noise shielding and reflection effects is considered using recently acquired experimental data. First, the experimental setup and resulting data are presented with particular attention to the role of surface span on far-field noise. These effects are then included in existing empirical models that have previously assumed that all surfaces are semi-infinite. This extended abstract briefly describes the experimental setup and data leaving the empirical modeling aspects for the final paper.
Energy Technology Data Exchange (ETDEWEB)
Maclaurin, Galen [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sengupta, Manajit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Xie, Yu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gilroy, Nicholas [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2016-12-01
A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance) broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the
Energy Technology Data Exchange (ETDEWEB)
Wharton, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bulaevskaya, V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Irons, Z. [Enel Green Power North America, Andover, MA (United States); Qualley, G. [Infigen Energy, Dallas, TX (United States); Newman, J. F. [Univ. of Oklahoma, Norman, OK (United States); Miller, W. O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-09-28
The goal of our FY15 project was to explore the use of statistical models and high-resolution atmospheric input data to develop more accurate prediction models for turbine power generation. We modeled power for two operational wind farms in two regions of the country. The first site is a 235 MW wind farm in Northern Oklahoma with 140 GE 1.68 turbines. Our second site is a 38 MW wind farm in the Altamont Pass Region of Northern California with 38 Mitsubishi 1 MW turbines. The farms are very different in topography, climatology, and turbine technology; however, both occupy high wind resource areas in the U.S. and are representative of typical wind farms found in their respective areas.
Modeling of Temperature-Dependent Noise in Silicon Nanowire FETs including Self-Heating Effects
Directory of Open Access Journals (Sweden)
P. Anandan
2014-01-01
Full Text Available Silicon nanowires are leading the CMOS era towards the downsizing limit and its nature will be effectively suppress the short channel effects. Accurate modeling of thermal noise in nanowires is crucial for RF applications of nano-CMOS emerging technologies. In this work, a perfect temperature-dependent model for silicon nanowires including the self-heating effects has been derived and its effects on device parameters have been observed. The power spectral density as a function of thermal resistance shows significant improvement as the channel length decreases. The effects of thermal noise including self-heating of the device are explored. Moreover, significant reduction in noise with respect to channel thermal resistance, gate length, and biasing is analyzed.
Producing high-accuracy lattice models from protein atomic coordinates including side chains.
Mann, Martin; Saunders, Rhodri; Smith, Cameron; Backofen, Rolf; Deane, Charlotte M
2012-01-01
Lattice models are a common abstraction used in the study of protein structure, folding, and refinement. They are advantageous because the discretisation of space can make extensive protein evaluations computationally feasible. Various approaches to the protein chain lattice fitting problem have been suggested but only a single backbone-only tool is available currently. We introduce LatFit, a new tool to produce high-accuracy lattice protein models. It generates both backbone-only and backbone-side-chain models in any user defined lattice. LatFit implements a new distance RMSD-optimisation fitting procedure in addition to the known coordinate RMSD method. We tested LatFit's accuracy and speed using a large nonredundant set of high resolution proteins (SCOP database) on three commonly used lattices: 3D cubic, face-centred cubic, and knight's walk. Fitting speed compared favourably to other methods and both backbone-only and backbone-side-chain models show low deviation from the original data (~1.5 Å RMSD in the FCC lattice). To our knowledge this represents the first comprehensive study of lattice quality for on-lattice protein models including side chains while LatFit is the only available tool for such models.
A High-Rate, Single-Crystal Model including Phase Transformations, Plastic Slip, and Twinning
Energy Technology Data Exchange (ETDEWEB)
Addessio, Francis L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division; Bronkhorst, Curt Allan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division; Bolme, Cynthia Anne [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Explosive Science and Shock Physics Division; Brown, Donald William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Materials Science and Technology Division; Cerreta, Ellen Kathleen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Materials Science and Technology Division; Lebensohn, Ricardo A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Materials Science and Technology Division; Lookman, Turab [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division; Luscher, Darby Jon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division; Mayeur, Jason Rhea [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division; Morrow, Benjamin M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Materials Science and Technology Division; Rigg, Paulo A. [Washington State Univ., Pullman, WA (United States). Dept. of Physics. Inst. for Shock Physics
2016-08-09
An anisotropic, rate-dependent, single-crystal approach for modeling materials under the conditions of high strain rates and pressures is provided. The model includes the effects of large deformations, nonlinear elasticity, phase transformations, and plastic slip and twinning. It is envisioned that the model may be used to examine these coupled effects on the local deformation of materials that are subjected to ballistic impact or explosive loading. The model is formulated using a multiplicative decomposition of the deformation gradient. A plate impact experiment on a multi-crystal sample of titanium was conducted. The particle velocities at the back surface of three crystal orientations relative to the direction of impact were measured. Molecular dynamics simulations were conducted to investigate the details of the high-rate deformation and pursue issues related to the phase transformation for titanium. Simulations using the single crystal model were conducted and compared to the high-rate experimental data for the impact loaded single crystals. The model was found to capture the features of the experiments.
He, L Z; Dong, X Y; Sun, Y
1998-01-01
Affinity filtration is a developing protein purification technique that combines the high selectivity of affinity chromatography and the high processing speed of membrane filtration. In this work a lumped kinetic model was developed to describe the whole affinity filtration process, including broth feeding, contaminant washing, and elution steps. Affinity filtration experiments were conducted to evaluate the model using bovine serum albumin as a model protein and a highly substituted Blue Sepharose as an affinity adsorbent. The model with nonadjustable parameters agreed fairly to the experimental results. Thus, the performance of the affinity filtration in processing a crude broth containing contaminant proteins was analyzed by computer simulations using the lumped model. The simulation results show that there is an optimal protein loading for obtaining the maximum recovery yield of the desired protein with a constant purity at each operating condition. The concentration of a crude broth is beneficial in increasing the recovery yield of the desired protein. Using a constant amount of the affinity adsorbent, the recovery yield can be enhanced by decreasing the solution volume in the stirred tank due to the increase of the adsorbent weight fraction. It was found that the lumped kinetic model was simple and useful in analyzing the whole affinity filtration process.
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-12-01
Several safety reports will be produced in the process of planning and constructing the system for disposal of high-level radioactive waste in Sweden. The present report gives a model, with detailed examples, of how these reports should be organized and what steps they should include. In the near future safety reports will deal with the encapsulation plant and the repository. Later reports will treat operation of the handling systems and the repository.
He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong
2015-09-01
In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Collisional-radiative model including recombination processes for W27+ ion★
Murakami, Izumi; Sasaki, Akira; Kato, Daiji; Koike, Fumihiro
2017-10-01
We have constructed a collisional-radiative (CR) model for W27+ ions including 226 configurations with n ≤ 9 and ł ≤ 5 for spectroscopic diagnostics. We newly include recombination processes in the model and this is the first result of extreme ultraviolet spectrum calculated for recombining plasma component. Calculated spectra in 40-70 Å range in ionizing and recombining plasma components show similar 3 strong lines and 1 line weak in recombining plasma component at 45-50 Å and many weak lines at 50-65 Å for both components. Recombination processes do not contribute much to the spectrum at around 60 Å for W27+ ion. Dielectronic satellite lines are also minor contribution to the spectrum of recombining plasma component. Dielectronic recombination (DR) rate coefficient from W28+ to W27+ ions is also calculated with the same atomic data in the CR model. We found that larger set of energy levels including many autoionizing states gave larger DR rate coefficients but our rate agree within factor 6 with other works at electron temperature around 1 keV in which W27+ and W28+ ions are usually observed in plasmas. Contribution to the Topical Issue "Atomic and Molecular Data and their Applications", edited by Gordon W.F. Drake, Jung-Sik Yoon, Daiji Kato, and Grzegorz Karwasz.
A 3D model of the oculomotor plant including the pulley system
Viegener, A.; Armentano, R. L.
2007-11-01
Early models of the oculomotor plant only considered the eye globes and the muscles that move them. Recently, connective tissue structures have been found enveloping the extraocular muscles (EOMs) and firmly anchored to the orbital wall. These structures act as pulleys; they determine the functional origin of the EOMs and, in consequence, their effective pulling direction. A three dimensional model of the oculomotor plant, including pulleys, has been developed and simulations in Simulink were performed during saccadic eye movements. Listing's law was implemented based on the supposition that there exists an eye orientation related signal. The inclusion of the pulleys in the model makes this assumption plausible and simplifies the problem of the plant noncommutativity.
Double-gate junctionless transistor model including short-channel effects
International Nuclear Information System (INIS)
Paz, B C; Pavanello, M A; Ávila-Herrera, F; Cerdeira, A
2015-01-01
This work presents a physically based model for double-gate junctionless transistors (JLTs), continuous in all operation regimes. To describe short-channel transistors, short-channel effects (SCEs), such as increase of the channel potential due to drain bias, carrier velocity saturation and mobility degradation due to vertical and longitudinal electric fields, are included in a previous model developed for long-channel double-gate JLTs. To validate the model, an analysis is made by using three-dimensional numerical simulations performed in a Sentaurus Device Simulator from Synopsys. Different doping concentrations, channel widths and channel lengths are considered in this work. Besides that, the series resistance influence is numerically included and validated for a wide range of source and drain extensions. In order to check if the SCEs are appropriately described, besides drain current, transconductance and output conductance characteristics, the following parameters are analyzed to demonstrate the good agreement between model and simulation and the SCEs occurrence in this technology: threshold voltage (V TH ), subthreshold slope (S) and drain induced barrier lowering. (paper)
Directory of Open Access Journals (Sweden)
R. J. Wichink Kruit
2012-12-01
Full Text Available A large shortcoming of current chemistry transport models (CTM for simulating the fate of ammonia in the atmosphere is the lack of a description of the bi-directional surface–atmosphere exchange. In this paper, results of an update of the surface–atmosphere exchange module DEPAC, i.e. DEPosition of Acidifying Compounds, in the chemistry transport model LOTOS-EUROS are discussed. It is shown that with the new description, which includes bi-directional surface–atmosphere exchange, the modeled ammonia concentrations increase almost everywhere, in particular in agricultural source areas. The reason is that by using a compensation point the ammonia lifetime and transport distance is increased. As a consequence, deposition of ammonia and ammonium decreases in agricultural source areas, while it increases in large nature areas and remote regions especially in southern Scandinavia. The inclusion of a compensation point for water reduces the dry deposition over sea and allows reproducing the observed marine background concentrations at coastal locations to a better extent. A comparison with measurements shows that the model results better represent the measured ammonia concentrations. The concentrations in nature areas are slightly overestimated, while the concentrations in agricultural source areas are still underestimated. Although the introduction of the compensation point improves the model performance, the modeling of ammonia remains challenging. Important aspects are emission patterns in space and time as well as a proper approach to deal with the high concentration gradients in relation to model resolution. In short, the inclusion of a bi-directional surface–atmosphere exchange is a significant step forward for modeling ammonia.
Including policy and management in socio-hydrology models: initial conceptualizations
Hermans, Leon; Korbee, Dorien
2017-04-01
Socio-hydrology studies the interactions in coupled human-water systems. So far, the use of dynamic models that capture the direct feedback between societal and hydrological systems has been dominant. What has not yet been included with any particular emphasis, is the policy or management layer, which is a central element in for instance integrated water resources management (IWRM) or adaptive delta management (ADM). Studying the direct interactions between human-water systems generates knowledges that eventually helps influence these interactions in ways that may ensure better outcomes - for society and for the health and sustainability of water systems. This influence sometimes occurs through spontaneous emergence, uncoordinated by societal agents - private sector, citizens, consumers, water users. However, the term 'management' in IWRM and ADM also implies an additional coordinated attempt through various public actors. This contribution is a call to include the policy and management dimension more prominently into the research focus of the socio-hydrology field, and offers first conceptual variables that should be considered in attempts to include this policy or management layer in socio-hydrology models. This is done by drawing on existing frameworks to study policy processes throughout both planning and implementation phases. These include frameworks such as the advocacy coalition framework, collective learning and policy arrangements, which all emphasis longer-term dynamics and feedbacks between actor coalitions in strategic planning and implementation processes. A case about longter-term dynamics in the management of the Haringvliet in the Netherlands is used to illustrate the paper.
Moore, Aleisha M; Prescott, Mel; Marshall, Christopher J; Yip, Siew Hoong; Campbell, Rebecca E
2015-01-13
Polycystic ovarian syndrome (PCOS), the leading cause of female infertility, is associated with an increase in luteinizing hormone (LH) pulse frequency, implicating abnormal steroid hormone feedback to gonadotropin-releasing hormone (GnRH) neurons. This study investigated whether modifications in the synaptically connected neuronal network of GnRH neurons could account for this pathology. The PCOS phenotype was induced in mice following prenatal androgen (PNA) exposure. Serial blood sampling confirmed that PNA elicits increased LH pulse frequency and impaired progesterone negative feedback in adult females, mimicking the neuroendocrine abnormalities of the clinical syndrome. Imaging of GnRH neurons revealed greater dendritic spine density that correlated with increased putative GABAergic but not glutamatergic inputs in PNA mice. Mapping of steroid hormone receptor expression revealed that PNA mice had 59% fewer progesterone receptor-expressing cells in the arcuate nucleus of the hypothalamus (ARN). To address whether increased GABA innervation to GnRH neurons originates in the ARN, a viral-mediated Cre-lox approach was taken to trace the projections of ARN GABA neurons in vivo. Remarkably, projections from ARN GABAergic neurons heavily contacted and even bundled with GnRH neuron dendrites, and the density of fibers apposing GnRH neurons was even greater in PNA mice (56%). Additionally, this ARN GABA population showed significantly less colocalization with progesterone receptor in PNA animals compared with controls. Together, these data describe a robust GABAergic circuit originating in the ARN that is enhanced in a model of PCOS and may underpin the neuroendocrine pathophysiology of the syndrome.
International Nuclear Information System (INIS)
2015-11-01
The demands on nuclear fuel have recently been increasing, and include transient regimes, higher discharge burnup and longer fuel cycles. This has resulted in an increase of loads on fuel and core internals. In order to satisfy these demands while ensuring compliance with safety criteria, new national and international programmes have been launched and advanced modelling codes are being developed. The Fukushima Daiichi accident has particularly demonstrated the need for adequate analysis of all aspects of fuel performance to prevent a failure and also to predict fuel behaviour were an accident to occur.This publication presents the Proceedings of the Technical Meeting on Modelling of Water Cooled Fuel Including Design Basis and Severe Accidents, which was hosted by the Nuclear Power Institute of China (NPIC) in Chengdu, China, following the recommendation made in 2013 at the IAEA Technical Working Group on Fuel Performance and Technology. This recommendation was in agreement with IAEA mid-term initiatives, linked to the post-Fukushima IAEA Nuclear Safety Action Plan, as well as the forthcoming Coordinated Research Project (CRP) on Fuel Modelling in Accident Conditions. At the technical meeting in Chengdu, major areas and physical phenomena, as well as types of code and experiment to be studied and used in the CRP, were discussed. The technical meeting provided a forum for international experts to review the state of the art of code development for modelling fuel performance of nuclear fuel for water cooled reactors with regard to steady state and transient conditions, and for design basis and early phases of severe accidents, including experimental support for code validation. A round table discussion focused on the needs and perspectives on fuel modelling in accident conditions. This meeting was the ninth in a series of IAEA meetings, which reflects Member States’ continuing interest in nuclear fuel issues. The previous meetings were held in 1980 (jointly with
Kim, Sun Jung; Yoo, Il Young
2016-03-01
The purpose of this study was to explain the health promotion behavior of Chinese international students in Korea using a structural equation model including acculturation factors. A survey using self-administered questionnaires was employed. Data were collected from 272 Chinese students who have resided in Korea for longer than 6 months. The data were analyzed using structural equation modeling. The p value of final model is .31. The fitness parameters of the final model such as goodness of fit index, adjusted goodness of fit index, normed fit index, non-normed fit index, and comparative fit index were more than .95. Root mean square of residual and root mean square error of approximation also met the criteria. Self-esteem, perceived health status, acculturative stress and acculturation level had direct effects on health promotion behavior of the participants and the model explained 30.0% of variance. The Chinese students in Korea with higher self-esteem, perceived health status, acculturation level, and lower acculturative stress reported higher health promotion behavior. The findings can be applied to develop health promotion strategies for this population. Copyright © 2016. Published by Elsevier B.V.
A structural model for the in vivo human cornea including collagen-swelling interaction.
Cheng, Xi; Petsche, Steven J; Pinsky, Peter M
2015-08-06
A structural model of the in vivo cornea, which accounts for tissue swelling behaviour, for the three-dimensional organization of stromal fibres and for collagen-swelling interaction, is proposed. Modelled as a binary electrolyte gel in thermodynamic equilibrium, the stromal electrostatic free energy is based on the mean-field approximation. To account for active endothelial ionic transport in the in vivo cornea, which modulates osmotic pressure and hydration, stromal mobile ions are shown to satisfy a modified Boltzmann distribution. The elasticity of the stromal collagen network is modelled based on three-dimensional collagen orientation probability distributions for every point in the stroma obtained by synthesizing X-ray diffraction data for azimuthal angle distributions and second harmonic-generated image processing for inclination angle distributions. The model is implemented in a finite-element framework and employed to predict free and confined swelling of stroma in an ionic bath. For the in vivo cornea, the model is used to predict corneal swelling due to increasing intraocular pressure (IOP) and is adapted to model swelling in Fuchs' corneal dystrophy. The biomechanical response of the in vivo cornea to a typical LASIK surgery for myopia is analysed, including tissue fluid pressure and swelling responses. The model provides a new interpretation of the corneal active hydration control (pump-leak) mechanism based on osmotic pressure modulation. The results also illustrate the structural necessity of fibre inclination in stabilizing the corneal refractive surface with respect to changes in tissue hydration and IOP. © 2015 The Author(s).
International Nuclear Information System (INIS)
Fattebert, J.-L.; Wickett, M.E.; Turchi, P.E.A.
2014-01-01
A numerical method for the simulation of microstructure evolution during the solidification of an alloy is presented. The approach is based on a phase-field model including a phase variable, an orientation variable given by a quaternion, the alloy composition and a uniform temperature field. Energies and diffusion coefficients used in the model rely on thermodynamic and kinetic databases in the framework of the CALPHAD methodology. The numerical approach is based on a finite volume discretization and an implicit time-stepping algorithm. Numerical results for solidification and accompanying coring effect in a Au–Ni alloy are used to illustrate the methodology
A satellite relative motion model including J_2 and J_3 via Vinti's intermediary
Biria, Ashley D.; Russell, Ryan P.
2018-03-01
Vinti's potential is revisited for analytical propagation of the main satellite problem, this time in the context of relative motion. A particular version of Vinti's spheroidal method is chosen that is valid for arbitrary elliptical orbits, encapsulating J_2, J_3, and generally a partial J_4 in an orbit propagation theory without recourse to perturbation methods. As a child of Vinti's solution, the proposed relative motion model inherits these properties. Furthermore, the problem is solved in oblate spheroidal elements, leading to large regions of validity for the linearization approximation. After offering several enhancements to Vinti's solution, including boosts in accuracy and removal of some singularities, the proposed model is derived and subsequently reformulated so that Vinti's solution is piecewise differentiable. While the model is valid for the critical inclination and nonsingular in the element space, singularities remain in the linear transformation from Earth-centered inertial coordinates to spheroidal elements when the eccentricity is zero or for nearly equatorial orbits. The new state transition matrix is evaluated against numerical solutions including the J_2 through J_5 terms for a wide range of chief orbits and separation distances. The solution is also compared with side-by-side simulations of the original Gim-Alfriend state transition matrix, which considers the J_2 perturbation. Code for computing the resulting state transition matrix and associated reference frame and coordinate transformations is provided online as supplementary material.
Ngeo, Jimson G; Tamei, Tomoya; Shibata, Tomohiro
2014-08-14
Surface electromyography (EMG) signals are often used in many robot and rehabilitation applications because these reflect motor intentions of users very well. However, very few studies have focused on the accurate and proportional control of the human hand using EMG signals. Many have focused on discrete gesture classification and some have encountered inherent problems such as electro-mechanical delays (EMD). Here, we present a new method for estimating simultaneous and multiple finger kinematics from multi-channel surface EMG signals. In this study, surface EMG signals from the forearm and finger kinematic data were extracted from ten able-bodied subjects while they were tasked to do individual and simultaneous multiple finger flexion and extension movements in free space. Instead of using traditional time-domain features of EMG, an EMG-to-Muscle Activation model that parameterizes EMD was used and shown to give better estimation performance. A fast feed forward artificial neural network (ANN) and a nonparametric Gaussian Process (GP) regressor were both used and evaluated to estimate complex finger kinematics, with the latter rarely used in the other related literature. The estimation accuracies, in terms of mean correlation coefficient, were 0.85 ± 0.07, 0.78 ± 0.06 and 0.73 ± 0.04 for the metacarpophalangeal (MCP), proximal interphalangeal (PIP) and the distal interphalangeal (DIP) finger joint DOFs, respectively. The mean root-mean-square error in each individual DOF ranged from 5 to 15%. We show that estimation improved using the proposed muscle activation inputs compared to other features, and that using GP regression gave better estimation results when using fewer training samples. The proposed method provides a viable means of capturing the general trend of finger movements and shows a good way of estimating finger joint kinematics using a muscle activation model that parameterizes EMD. The results from this study demonstrates a potential control
Mohammad, S. Noor
2010-09-01
Semiconductor nanotubes, including carbon nanotubes, have vast potential for new technology development. The fundamental physics and growth kinetics of these nanotubes are still obscured. Various models developed to elucidate the growth suffer from limited applicability. An in-depth investigation of the fundamentals of nanotube growth has, therefore, been carried out. For this investigation, various features of nanotube growth, and the role of the foreign element catalytic agent (FECA) in this growth, have been considered. Observed growth anomalies have been analyzed. Based on this analysis, a new shell model and a general hypothesis have been proposed for the growth. The essential element of the shell model is the seed generated from segregation during growth. The seed structure has been defined, and the formation of droplet from this seed has been described. A modified definition of the droplet exhibiting adhesive properties has also been presented. Various characteristics of the droplet, required for alignment and organization of atoms into tubular forms, have been discussed. Employing the shell model, plausible scenarios for the formation of carbon nanotubes, and the variation in the characteristics of these carbon nanotubes have been articulated. The experimental evidences, for example, for the formation of shell around a core, dipole characteristics of the seed, and the existence of nanopores in the seed, have been presented. They appear to justify the validity of the proposed model. The diversities of nanotube characteristics, fundamentals underlying the creation of bamboo-shaped carbon nanotubes, and the impurity generation on the surface of carbon nanotubes have been elucidated. The catalytic action of FECA on growth has been quantified. The applicability of the proposed model to the nanotube growth by a variety of mechanisms has been elaborated. These mechanisms include the vapor-liquid-solid mechanism, the oxide-assisted growth mechanism, the self
A new model for including the effect of fly ash on biochemical methane potential.
Gertner, Pablo; Huiliñir, César; Pinto-Villegas, Paula; Castillo, Alejandra; Montalvo, Silvio; Guerrero, Lorna
2017-10-01
The modelling of the effect of trace elements on anaerobic digestion, and specifically the effect of fly ash, has been scarcely studied. Thus, the present work was aimed at the development of a new function that allows accumulated methane models to predict the effect of FA on the volume of methane accumulation. For this, purpose five fly ash concentrations (10, 25, 50, 250 and 500mg/L) using raw and pre-treated sewage sludge were used to calibrate the new function, while three fly ash concentrations were used (40, 150 and 350mg/L) for validation. Three models for accumulated methane volume (the modified Gompertz equation, the logistic function, and the transfer function) were evaluated. The results showed that methane production increased in the presence of FA when the sewage sludge was not pre-treated, while with pretreated sludge there is inhibition of methane production at FA concentrations higher than 50mg/L. In the calibration of the proposed function, it fits well with the experimental data under all the conditions, including the inhibition and stimulating zones, with the values of the parameters of the methane production models falling in the range of those reported in the literature. For validation experiments, the model succeeded in representing the behavior of new experiments in both the stimulating and inhibiting zones, with NRMSE and R 2 ranging from 0.3577 to 0.03714 and 0.2209 to 0.9911, respectively. Thus, the proposed model is robust and valid for the studied conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
D. O. Topping
2005-01-01
Full Text Available This paper describes the inclusion of organic particulate material within the Aerosol Diameter Dependent Equilibrium Model (ADDEM framework described in the companion paper applied to inorganic aerosol components. The performance of ADDEM is analysed in terms of its capability to reproduce the behaviour of various organic and mixed inorganic/organic systems using recently published bulk data. Within the modelling architecture already described two separate thermodynamic models are coupled in an additive approach and combined with a method for solving the Kohler equation in order to develop a tool for predicting the water content associated with an aerosol of known inorganic/organic composition and dry size. For development of the organic module, the widely used group contribution method UNIFAC is employed to explicitly deal with the non-ideality in solution. The UNIFAC predictions for components of atmospheric importance were improved considerably by using revised interaction parameters derived from electro-dynamic balance studies. Using such parameters, the model was found to adequately describe mixed systems including 5–6 dicarboxylic acids, down to low relative humidity conditions. By comparison with electrodynamic balance data, it was also found that the model was capable of capturing the behaviour of aqueous aerosols containing Suwannee River Fulvic acid, a structure previously used to represent the functionality of complex oxidised macromolecules often found in atmospheric aerosols. The additive approach for modelling mixed inorganic/organic systems worked well for a variety of mixtures. As expected, deviations between model predictions and measurements increase with increasing concentration. Available surface tension models, used in evaluating the Kelvin term, were found to reproduce measured data with varying success. Deviations from experimental data increased with increased organic compound complexity. For components only slightly
A curved multi-component aerosol hygroscopicity model framework: Part 2 Including organic compounds
Topping, D. O.; McFiggans, G. B.; Coe, H.
2005-05-01
This paper describes the inclusion of organic particulate material within the Aerosol Diameter Dependent Equilibrium Model (ADDEM) framework described in the companion paper applied to inorganic aerosol components. The performance of ADDEM is analysed in terms of its capability to reproduce the behaviour of various organic and mixed inorganic/organic systems using recently published bulk data. Within the modelling architecture already described two separate thermodynamic models are coupled in an additive approach and combined with a method for solving the Kohler equation in order to develop a tool for predicting the water content associated with an aerosol of known inorganic/organic composition and dry size. For development of the organic module, the widely used group contribution method UNIFAC is employed to explicitly deal with the non-ideality in solution. The UNIFAC predictions for components of atmospheric importance were improved considerably by using revised interaction parameters derived from electro-dynamic balance studies. Using such parameters, the model was found to adequately describe mixed systems including 5-6 dicarboxylic acids, down to low relative humidity conditions. By comparison with electrodynamic balance data, it was also found that the model was capable of capturing the behaviour of aqueous aerosols containing Suwannee River Fulvic acid, a structure previously used to represent the functionality of complex oxidised macromolecules often found in atmospheric aerosols. The additive approach for modelling mixed inorganic/organic systems worked well for a variety of mixtures. As expected, deviations between model predictions and measurements increase with increasing concentration. Available surface tension models, used in evaluating the Kelvin term, were found to reproduce measured data with varying success. Deviations from experimental data increased with increased organic compound complexity. For components only slightly soluble in water
Empirical Validation of a Thermal Model of a Complex Roof Including Phase Change Materials
Directory of Open Access Journals (Sweden)
Stéphane Guichard
2015-12-01
Full Text Available This paper deals with the empirical validation of a building thermal model of a complex roof including a phase change material (PCM. A mathematical model dedicated to PCMs based on the heat apparent capacity method was implemented in a multi-zone building simulation code, the aim being to increase the understanding of the thermal behavior of the whole building with PCM technologies. In order to empirically validate the model, the methodology is based both on numerical and experimental studies. A parametric sensitivity analysis was performed and a set of parameters of the thermal model has been identified for optimization. The use of the generic optimization program called GenOpt® coupled to the building simulation code enabled to determine the set of adequate parameters. We first present the empirical validation methodology and main results of previous work. We then give an overview of GenOpt® and its coupling with the building simulation code. Finally, once the optimization results are obtained, comparisons of the thermal predictions with measurements are found to be acceptable and are presented.
A multiscale model for glioma spread including cell-tissue interactions and proliferation.
Engwer, Christian; Knappitsch, Markus; Surulescu, Christina
2016-04-01
Glioma is a broad class of brain and spinal cord tumors arising from glia cells, which are the main brain cells that can develop into neoplasms. They are highly invasive and lead to irregular tumor margins which are not precisely identifiable by medical imaging, thus rendering a precise enough resection very difficult. The understanding of glioma spread patterns is hence essential for both radiological therapy as well as surgical treatment. In this paper we propose a multiscale model for glioma growth including interactions of the cells with the underlying tissue network, along with proliferative effects. Our current accounting for two subpopulations of cells to accomodate proliferation according to the go-or-grow dichtomoty is an extension of the setting in [16]. As in that paper, we assume that cancer cells use neuronal fiber tracts as invasive pathways. Hence, the individual structure of brain tissue seems to be decisive for the tumor spread. Diffusion tensor imaging (DTI) is able to provide such information, thus opening the way for patient specific modeling of glioma invasion. Starting from a multiscale model involving subcellular (microscopic) and individual (mesoscale) cell dynamics, we perform a parabolic scaling to obtain an approximating reaction-diffusion-transport equation on the macroscale of the tumor cell population. Numerical simulations based on DTI data are carried out in order to assess the performance of our modeling approach.
Habitability of super-Earth planets around other suns: models including Red Giant Branch evolution.
von Bloh, W; Cuntz, M; Schröder, K-P; Bounama, C; Franck, S
2009-01-01
The unexpected diversity of exoplanets includes a growing number of super-Earth planets, i.e., exoplanets with masses of up to several Earth masses and a similar chemical and mineralogical composition as Earth. We present a thermal evolution model for a 10 Earth-mass planet orbiting a star like the Sun. Our model is based on the integrated system approach, which describes the photosynthetic biomass production and takes into account a variety of climatological, biogeochemical, and geodynamical processes. This allows us to identify a so-called photosynthesis-sustaining habitable zone (pHZ), as determined by the limits of biological productivity on the planetary surface. Our model considers solar evolution during the main-sequence stage and along the Red Giant Branch as described by the most recent solar model. We obtain a large set of solutions consistent with the principal possibility of life. The highest likelihood of habitability is found for "water worlds." Only mass-rich water worlds are able to realize pHZ-type habitability beyond the stellar main sequence on the Red Giant Branch.
Zhang, Guili; Zeller, Nancy; Griffith, Robin; Metcalf, Debbie; Williams, Jennifer; Shea, Christine; Misulis, Katherine
2011-01-01
Planning, implementing, and assessing a service-learning project can be a complex task because service-learning projects often involve multiple constituencies and aim to meet both the needs of service providers and community partners. In this article, Stufflebeam's Context, Input, Process, and Product (CIPP) evaluation model is recommended as a…
Analysis of electronic models for solar cells including energy resolved defect densities
Energy Technology Data Exchange (ETDEWEB)
Glitzky, Annegret
2010-07-01
We introduce an electronic model for solar cells including energy resolved defect densities. The resulting drift-diffusion model corresponds to a generalized van Roosbroeck system with additional source terms coupled with ODEs containing space and energy as parameters for all defect densities. The system has to be considered in heterostructures and with mixed boundary conditions from device simulation. We give a weak formulation of the problem. If the boundary data and the sources are compatible with thermodynamic equilibrium the free energy along solutions decays monotonously. In other cases it may be increasing, but we estimate its growth. We establish boundedness and uniqueness results and prove the existence of a weak solution. This is done by considering a regularized problem, showing its solvability and the boundedness of its solutions independent of the regularization level. (orig.)
Effect of including decay chains on predictions of equilibrium-type terrestrial food chain models
International Nuclear Information System (INIS)
Kirchner, G.
1990-01-01
Equilibrium-type food chain models are commonly used for assessing the radiological impact to man from environmental releases of radionuclides. Usually these do not take into account build-up of radioactive decay products during environmental transport. This may be a potential source of underprediction. For estimating consequences of this simplification, the equations of an internationally recognised terrestrial food chain model have been extended to include decay chains of variable length. Example calculations show that for releases from light water reactors as expected both during routine operation and in the case of severe accidents, the build-up of decay products during environmental transport is generally of minor importance. However, a considerable number of radionuclides of potential radiological significance have been identified which show marked contributions of decay products to calculated contamination of human food and resulting radiation dose rates. (author)
Intermediate inputs and economic productivity.
Baptist, Simon; Hepburn, Cameron
2013-03-13
Many models of economic growth exclude materials, energy and other intermediate inputs from the production function. Growing environmental pressures and resource prices suggest that this may be increasingly inappropriate. This paper explores the relationship between intermediate input intensity, productivity and national accounts using a panel dataset of manufacturing subsectors in the USA over 47 years. The first contribution is to identify sectoral production functions that incorporate intermediate inputs, while allowing for heterogeneity in both technology and productivity. The second contribution is that the paper finds a negative correlation between intermediate input intensity and total factor productivity (TFP)--sectors that are less intensive in their use of intermediate inputs have higher productivity. This finding is replicated at the firm level. We propose tentative hypotheses to explain this association, but testing and further disaggregation of intermediate inputs is left for further work. Further work could also explore more directly the relationship between material inputs and economic growth--given the high proportion of materials in intermediate inputs, the results in this paper are suggestive of further work on material efficiency. Depending upon the nature of the mechanism linking a reduction in intermediate input intensity to an increase in TFP, the implications could be significant. A third contribution is to suggest that an empirical bias in productivity, as measured in national accounts, may arise due to the exclusion of intermediate inputs. Current conventions of measuring productivity in national accounts may overstate the productivity of resource-intensive sectors relative to other sectors.
Including sugar cane in the agro-ecosystem model ORCHIDEE-STICS
Valade, A.; Vuichard, N.; Ciais, P.; Viovy, N.
2010-12-01
With 4 million ha currently grown for ethanol in Brazil only, approximately half the global bioethanol production in 2005 (Smeets 2008), and a devoted land area expected to expand globally in the years to come, sugar cane is at the heart of the biofuel debate. Indeed, ethanol made from biomass is currently the most widespread option for alternative transportation fuels. It was originally promoted as a carbon neutral energy resource that could bring energy independence to countries and local opportunities to farmers, until attention was drawn to its environmental and socio-economical drawbacks. It is still not clear to which extent it is a solution or a contributor to climate change mitigation. Dynamic Global Vegetation models can help address these issues and quantify the potential impacts of biofuels on ecosystems at scales ranging from on-site to global. The global agro-ecosystem model ORCHIDEE describes water, carbon and energy exchanges at the soil-atmosphere interface for a limited number of natural and agricultural vegetation types. In order to integrate agricultural management to the simulations and to capture more accurately the specificity of crops' phenology, ORCHIDEE has been coupled with the agronomical model STICS. The resulting crop-oriented vegetation model ORCHIDEE-STICS has been used so far to simulate temperate crops such as wheat, corn and soybean. As a generic ecosystem model, each grid cell can include several vegetation types with their own phenology and management practices, making it suitable to spatial simulations. Here, ORCHIDEE-STICS is altered to include sugar cane as a new agricultural Plant functional Type, implemented and parametrized using the STICS approach. An on-site calibration and validation is then performed based on biomass and flux chamber measurements in several sites in Australia and variables such as LAI, dry weight, heat fluxes and respiration are used to evaluate the ability of the model to simulate the specific
International Nuclear Information System (INIS)
Oblozinsky, P.
1996-03-01
The present report contains the summary of the Second Research Co-ordination Meeting on ''Development of Reference Input Parameter Library for Nuclear Model Calculations of Nuclear Data'', held in Vienna, Austria, from 30 October to 3 November 1995. The library should serve the input for theoretical calculations of nuclear reaction data induced primarily with neutrons in the incident energy range below 30 MeV. Summarized are conclusions and recommendations of the meeting together with a detailed list of actions and deadlines. Attached is the agenda of the meeting, list of participants, and titles and abstracts of their presentations. (author)
Liang, Sai; Zhang, Tianzhu; Xu, Yijian
2012-03-01
Waste recycling for paper production is an important component of waste management. This study constructs a physical input-output life-cycle assessment (PIO-LCA) model. The PIO-LCA model is used to investigate environmental impacts of four categories of waste recycling in China's paper industry: crop straws, bagasse, textile wastes and scrap paper. Crop straw recycling and wood utilization for paper production have small total intensity of environmental impacts. Moreover, environmental impacts reduction of crop straw recycling and wood utilization benefits the most from technology development. Thus, using crop straws and wood (including wood wastes) for paper production should be promoted. Technology development has small effects on environmental impacts reduction of bagasse recycling, textile waste recycling and scrap paper recycling. In addition, bagasse recycling and textile waste recycling have big total intensity of environmental impacts. Thus, the development of bagasse recycling and textile waste recycling should be properly limited. Other pathways for reusing bagasse and textile wastes should be explored and evaluated. Moreover, imports of scrap paper should be encouraged to reduce large indirect impacts of scrap paper recycling on domestic environment. Copyright © 2011 Elsevier Ltd. All rights reserved.
SDR Input Power Estimation Algorithms
Nappier, Jennifer M.; Briones, Janette C.
2013-01-01
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Moretti, Rocco; Lyskov, Sergey; Das, Rhiju; Meiler, Jens; Gray, Jeffrey J
2018-01-01
The Rosetta molecular modeling software package provides a large number of experimentally validated tools for modeling and designing proteins, nucleic acids, and other biopolymers, with new protocols being added continually. While freely available to academic users, external usage is limited by the need for expertise in the Unix command line environment. To make Rosetta protocols available to a wider audience, we previously created a web server called Rosetta Online Server that Includes Everyone (ROSIE), which provides a common environment for hosting web-accessible Rosetta protocols. Here we describe a simplification of the ROSIE protocol specification format, one that permits easier implementation of Rosetta protocols. Whereas the previous format required creating multiple separate files in different locations, the new format allows specification of the protocol in a single file. This new, simplified protocol specification has more than doubled the number of Rosetta protocols available under ROSIE. These new applications include pK a determination, lipid accessibility calculation, ribonucleic acid redesign, protein-protein docking, protein-small molecule docking, symmetric docking, antibody docking, cyclic toxin docking, critical binding peptide determination, and mapping small molecule binding sites. ROSIE is freely available to academic users at http://rosie.rosettacommons.org. © 2017 The Protein Society.
International Nuclear Information System (INIS)
Yoon, C.; Rhee, B. W.; Chung, B. D.; Ahn, S. H.; Kim, M. W.
2009-01-01
Korea currently has four operating units of the CANDU-6 type reactor in Wolsong. However, the safety assessment system for CANDU reactors has not been fully established due to a lack of self-reliance technology. Although the CATHENA code had been introduced from AECL, it is undesirable to use a vendor's code for a regulatory auditing analysis. In Korea, the MARS code has been developed for decades and is being considered by KINS as a thermal hydraulic regulatory auditing tool for nuclear power plants. Before this decision, KINS (Korea Institute of Nuclear Safety) had developed the RELAP5/MOD3/CANDU code for CANDU safety analyses by modifying the model of the existing PWR auditing tool, RELAP5/MOD3. The main purpose of this study is to transplant the CANDU models of the RELAP5/MOD3/CANDU code to the MARS code including a quality assurance of the developed models
A curved multi-component aerosol hygroscopicity model framework: 2 Including organics
Topping, D. O.; McFiggans, G. B.; Coe, H.
2004-12-01
This paper describes the inclusion of organic particulate material within the Aerosol Diameter Dependent Equilibrium Model (ADDEM) framework described in the companion paper applied to inorganic aerosol components. The performance of ADDEM is analysed in terms of its capability to reproduce the behaviour of various organic and mixed inorganic/organic systems using recently published bulk data. Within the modelling architecture already described two separate thermodynamic models are coupled in an additive approach and combined with a method for solving the Köhler equation in order to develop a tool for predicting the water content associated with an aerosol of known inorganic/organic composition and dry size. For development of the organic module, the widely used group contribution method UNIFAC is employed to explicitly deal with the non-ideality in solution. The UNIFAC predictions for components of atmospheric importance were improved considerably by using revised interaction parameters derived from electro-dynamic balance studies. Using such parameters, the model was found to adequately describe mixed systems including 5-6 dicarboxylic acids, down to low relative humidity conditions. The additive approach for modelling mixed inorganic/organic systems worked well for a variety of mixtures. As expected, deviations between predicted and measured data increase with increasing concentration. Available surface tension models, used in evaluating the Kelvin term, were found to reproduce measured data with varying success. Deviations from experimental data increased with increased organic compound complexity. For components only slightly soluble in water, significant deviations from measured surface tension depression behaviour were predicted with both model formalisms tested. A Sensitivity analysis showed that such variation is likely to lead to predicted growth factors within the measurement uncertainty for growth factor taken in the sub-saturated regime. Greater
A Hydrological Concept including Lateral Water Flow Compatible with the Biogeochemical Model ForSAFE
Directory of Open Access Journals (Sweden)
Giuliana Zanchi
2016-03-01
Full Text Available The study presents a hydrology concept developed to include lateral water flow in the biogeochemical model ForSAFE. The hydrology concept was evaluated against data collected at Svartberget in the Vindeln Research Forest in Northern Sweden. The results show that the new concept allows simulation of a saturated and an unsaturated zone in the soil as well as water flow that reaches the stream comparable to measurements. The most relevant differences compared to streamflow measurements are that the model simulates a higher base flow in winter and lower flow peaks after snowmelt. These differences are mainly caused by the assumptions made to regulate the percolation at the bottom of the simulated soil columns. The capability for simulating lateral flows and a saturated zone in ForSAFE can greatly improve the simulation of chemical exchange in the soil and export of elements from the soil to watercourses. Such a model can help improve the understanding of how environmental changes in the forest landscape will influence chemical loads to surface waters.
International Nuclear Information System (INIS)
Wang, Y. T.; Xu, L. X.; Gui, Y. X.
2010-01-01
In this paper, we investigate the integrated Sachs-Wolfe effect in the quintessence cold dark matter model with constant equation of state and constant speed of sound in dark energy rest frame, including dark energy perturbation and its anisotropic stress. Comparing with the ΛCDM model, we find that the integrated Sachs-Wolfe (ISW)-power spectrums are affected by different background evolutions and dark energy perturbation. As we change the speed of sound from 1 to 0 in the quintessence cold dark matter model with given state parameters, it is found that the inclusion of dark energy anisotropic stress makes the variation of magnitude of the ISW source uncertain due to the anticorrelation between the speed of sound and the ratio of dark energy density perturbation contrast to dark matter density perturbation contrast in the ISW-source term. Thus, the magnitude of the ISW-source term is governed by the competition between the alterant multiple of (1+3/2xc-circumflex s 2 ) and that of δ de /δ m with the variation of c-circumflex s 2 .
Expanded rock blast modeling capabilities of DMC{_}BLAST, including buffer blasting
Energy Technology Data Exchange (ETDEWEB)
Preece, D.S. [Sandia National Labs., Albuquerque, NM (United States); Tidman, J.P.; Chung, S.H. [ICI Explosives (Canada)
1996-12-31
A discrete element computer program named DMC{_}BLAST (Distinct Motion Code) has been under development since 1987 for modeling rock blasting. This program employs explicit time integration and uses spherical or cylindrical elements that are represented as circles in 2-D. DMC{_}BLAST calculations compare favorably with data from actual bench blasts. The blast modeling capabilities of DMC{_}BLAST have been expanded to include independently dipping geologic layers, top surface, bottom surface and pit floor. The pit can also now be defined using coordinates based on the toe of the bench. A method for modeling decked explosives has been developed which allows accurate treatment of the inert materials (stemming) in the explosive column and approximate treatment of different explosives in the same blasthole. A DMC{_}BLAST user can specify decking through a specific geologic layer with either inert material or a different explosive. Another new feature of DMC{_}BLAST is specification of an uplift angle which is the angle between the normal to the blasthole and a vector defining the direction of explosive loading on particles adjacent to the blasthole. A buffer (choke) blast capability has been added for situations where previously blasted material is adjacent to the free face of the bench preventing any significant lateral motion during the blast.
Divers, Marion T; Elliott, Emily M; Bain, Daniel J
2013-02-19
Leaking sewer infrastructure contributes nonpoint nitrogen pollution to groundwater and surface water in urban watersheds. However, these inputs are poorly quantified in watershed budgets, potentially underestimating pollutant loadings. In this study, we used inverse methods to constrain dissolved inorganic nitrogen (DIN) inputs from sewage to Nine Mile Run (NMR), an urban watershed (1570 ha) in Pittsburgh, Pennsylvania (USA) characterized by extensive impervious surface cover (38%). Water samples were collected biweekly over two years and intensive sampling was conducted during one summer storm. A nitrogen budget for the NMR watershed was constructed, ultimately inverted, and sewage DIN inputs constrained using Monte Carlo simulation. Results reveal substantial DIN contributions from sewage ranging from 6 to 14 kg ha-1 yr-1. When conservative estimates of DIN from sewage are included in input calculations, DIN retention in NMR is comparable to high rates observed in other suburban/urban nutrient budgets (84%). These results suggest a pervasive influence of leaking sewers during baseflow conditions and indicate that sewage-sourced DIN is not limited to sewer overflow events. Further, they highlight the importance of sewage inputs to DIN budgets in urban streams, particularly as sewer systems age across the U.S.
Directory of Open Access Journals (Sweden)
Connor Hyunju Kim
2016-01-01
Full Text Available The magnetosphere is a major source of energy for the Earth’s ionosphere and thermosphere (IT system. Current IT models drive the upper atmosphere using empirically calculated magnetospheric energy input. Thus, they do not sufficiently capture the storm-time dynamics, particularly at high latitudes. To improve the prediction capability of IT models, a physics-based magnetospheric input is necessary. Here, we use the Open Global General Circulation Model (OpenGGCM coupled with the Coupled Thermosphere Ionosphere Model (CTIM. OpenGGCM calculates a three-dimensional global magnetosphere and a two-dimensional high-latitude ionosphere by solving resistive magnetohydrodynamic (MHD equations with solar wind input. CTIM calculates a global thermosphere and a high-latitude ionosphere in three dimensions using realistic magnetospheric inputs from the OpenGGCM. We investigate whether the coupled model improves the storm-time IT responses by simulating a geomagnetic storm that is preceded by a strong solar wind pressure front on August 24, 2005. We compare the OpenGGCM-CTIM results with low-earth-orbit satellite observations and with the model results of Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe. CTIPe is an up-to-date version of CTIM that incorporates more IT dynamics such as a low-latitude ionosphere and a plasmasphere, but uses empirical magnetospheric input. OpenGGCM-CTIM reproduces localized neutral density peaks at ~ 400 km altitude in the high-latitude dayside regions in agreement with in situ observations during the pressure shock and the early phase of the storm. Although CTIPe is in some sense a much superior model than CTIM, it misses these localized enhancements. Unlike the CTIPe empirical input models, OpenGGCM-CTIM more faithfully produces localized increases of both auroral precipitation and ionospheric electric fields near the high-latitude dayside region after the pressure shock and after the storm onset
Hettrick, D A; Pagel, P S; Warltier, D C
1995-08-01
Systemic vascular resistance (the ratio of mean aortic pressure [AP] and mean aortic blood flow [AQ]) does not completely describe left ventricular (LV) afterload because of the phasic nature of pressure and blood flow. Aortic input impedance (Zin) is an established experimental description of LV afterload that incorporates the frequency-dependent characteristics and viscoelastic properties of the arterial system. Zin is most often interpreted through an analytical model known as the three-element Windkessel. This investigation examined the effects of isoflurane, halothane, and sodium nitroprusside (SNP) on Zin. Changes in Zin were quantified using three variables derived from the Windkessel: characteristic aortic impedance (Zc), total arterial compliance (C), and total arterial resistance (R). Sixteen experiments were conducted in eight dogs chronically instrumented for measurement of AP, LV pressure, maximum rate of change in left ventricular pressure, subendocardial segment length, and AQ. AP and AQ waveforms were recorded in the conscious state and after 30 min equilibration at 1.25, 1.5, and 1.75 minimum alveolar concentration (MAC) isoflurane and halothane. Zin spectra were obtained by power spectral analysis of AP and AQ waveforms and corrected for the phase responses of the transducers. Zc and R were calculated as the mean of Zin between 2 and 15 Hz and the difference between Zin at zero frequency and Zc, respectively. C was determined using the formula C = (Ad.MAP).[MAQ.(Pes-Ped)]-1, where Ad = diastolic AP area; MAP and MAQ = mean AP and mean AQ, respectively; and Pes and Ped = end-systolic and end-diastolic AP, respectively. Parameters describing the net site and magnitude of arterial wave reflection were also calculated from Zin. Eight additional dogs were studied in the conscious state before and after 15 min equilibration at three equihypotensive infusions of SNP. Isoflurane decreased R (3,205 +/- 315 during control to 2,340 +/- 2.19 dyn.s.cm-5 during
Energy Technology Data Exchange (ETDEWEB)
Chen, Lingen; Kan, Xuxian; Sun, Fengrui; Wu, Feng [College of Naval Architecture and Power, Naval University of Engineering, Wuhan 430033 (China)
2013-07-01
The operation of a universal steady flow endoreversible refrigeration cycle model consisting of a constant thermal-capacity heating branch, two constant thermal-capacity cooling branches and two adiabatic branches is viewed as a production process with exergy as its output. The finite time exergoeconomic performance optimization of the refrigeration cycle is investigated by taking profit rate optimization criterion as the objective. The relations between the profit rate and the temperature ratio of working fluid, between the COP (coefficient of performance) and the temperature ratio of working fluid, as well as the optimal relation between profit rate and the COP of the cycle are derived. The focus of this paper is to search the compromised optimization between economics (profit rate) and the utilization factor (COP) for endoreversible refrigeration cycles, by searching the optimum COP at maximum profit, which is termed as the finite-time exergoeconomic performance bound. Moreover, performance analysis and optimization of the model are carried out in order to investigate the effect of cycle process on the performance of the cycles using numerical example. The results obtained herein include the performance characteristics of endoreversible Carnot, Diesel, Otto, Atkinson, Dual and Brayton refrigeration cycles.
Zhang, Yan; Liu, Hong; Chen, Bin; Zheng, Hongmei; Li, Yating
2014-06-01
Discovering ways in which to increase the sustainability of the metabolic processes involved in urbanization has become an urgent task for urban design and management in China. As cities are analogous to living organisms, the disorders of their metabolic processes can be regarded as the cause of "urban disease". Therefore, identification of these causes through metabolic process analysis and ecological element distribution through the urban ecosystem's compartments will be helpful. By using Beijing as an example, we have compiled monetary input-output tables from 1997, 2000, 2002, 2005, and 2007 and calculated the intensities of the embodied ecological elements to compile the corresponding implied physical input-output tables. We then divided Beijing's economy into 32 compartments and analyzed the direct and indirect ecological intensities embodied in the flows of ecological elements through urban metabolic processes. Based on the combination of input-output tables and ecological network analysis, the description of multiple ecological elements transferred among Beijing's industrial compartments and their distribution has been refined. This hybrid approach can provide a more scientific basis for management of urban resource flows. In addition, the data obtained from distribution characteristics of ecological elements may provide a basic data platform for exploring the metabolic mechanism of Beijing.
Onishi, Janet C; Park, Joong-Wook; Prado, Julio; Eades, Susan C; Mirza, Mustajab H; Fugaro, Michael N; Häggblom, Max M; Reinemeyer, Craig R
2012-10-12
Carbohydrate overload models of equine acute laminitis are used to study the development of lameness. It is hypothesized that a diet-induced shift in cecal bacterial communities contributes to the development of the pro-inflammatory state that progresses to laminar failure. It is proposed that vasoactive amines, protease activators and endotoxin, all bacterial derived bioactive metabolites, play a role in disease development. Questions regarding the oral bioavailability of many of the bacterial derived bioactive metabolites remain. This study evaluates the possibility that a carbohydrate-induced overgrowth of potentially pathogenic cecal bacteria occurs and that bacterial translocation contributes toward the development of the pro-inflammatory state. Two groups of mixed-breed horses were used, those with laminitis induced by cornstarch (n=6) or oligofructan (n=6) and non-laminitic controls (n=8). Cecal fluid and tissue homogenates of extra-intestinal sites including the laminae were used to enumerate Gram-negative and -positive bacteria. Horses that developed Obel grade2 lameness, revealed a significant overgrowth of potentially pathogenic Gram-positive and Gram-negative intestinal bacteria within the cecal fluid. Although colonization of extra-intestinal sites with potentially pathogenic bacteria was not detected, results of this study indicate that cecal/colonic lymphadenopathy and eosinophilia develop in horses progressing to lameness. It is hypothesized that the pro-inflammatory state in carbohydrate overload models of equine acute laminitis is driven by an immune response to the rapid overgrowth of Gram-positive and Gram-negative cecal bacterial communities in the gut. Further equine research is indicated to study the immunological response, involving the lymphatic system that develops in the model. Copyright © 2012 Elsevier B.V. All rights reserved.
CFD simulations and reduced order modeling of a refrigerator compartment including radiation effects
International Nuclear Information System (INIS)
Bayer, Ozgur; Oskay, Ruknettin; Paksoy, Akin; Aradag, Selin
2013-01-01
Highlights: ► Free convection in a refrigerator is simulated including radiation effects. ► Heat rates are affected drastically when radiation effects are considered. ► 95% of the flow energy can be represented by using one spatial POD mode. - Abstract: Considering the engineering problem of natural convection in domestic refrigerator applications, this study aims to simulate the fluid flow and temperature distribution in a single commercial refrigerator compartment by using the experimentally determined temperature values as the specified constant wall temperature boundary conditions. The free convection in refrigerator applications is evaluated as a three-dimensional (3D), turbulent, transient and coupled non-linear flow problem. Radiation heat transfer mode is also included in the analysis. According to the results, taking radiation effects into consideration does not change the temperature distribution inside the refrigerator significantly; however the heat rates are affected drastically. The flow inside the compartment is further analyzed with a reduced order modeling method called Proper Orthogonal Decomposition (POD) and the energy contents of several spatial and temporal modes that exist in the flow are examined. The results show that approximately 95% of all the flow energy can be represented by only using one spatial mode
Shaped input distributions for structural damage localization
DEFF Research Database (Denmark)
Ulriksen, Martin Dalgaard; Bernal, Dionisio; Damkilde, Lars
2018-01-01
). Accordingly, damage is localized when the vibration signature induced by the shaped inputs in the damaged state corresponds to that in the reference state, hereby implying that the approach does not point directly to damage. Instead, it operates with interrogation based on postulated damage patterns......, resulting in a system identification-free procedure whose primary merits, besides avoiding the typical bottleneck of system identification, include a low demand on output sensors, robustness towards noise, and conceptual simplicity. The price paid for these merits is reliance on a relatively accurate model...... of the structure in its reference state and the need for multiple controllable inputs....
de Smet, J.H.
1999-01-01
This thesis elaborates on the evolution of the continental upper mantle based on numerical modelling results. The descriptive and explanatory basis is formed by a numerical thermo-chemical convection model. The model evolution starts in the early Archaean about 4 billion years ago. The model follows
Smet, J.H. de
1999-01-01
This thesis elaborates on the evolution of the continental upper mantle based on numerical modelling results. The descriptive and explanatory basis is formed by a numerical thermo-chemical convection model. The model evolution starts in the early Archaean about 4 billion years ago. The model
DEFF Research Database (Denmark)
Brandt, J.; Bastrup-Birk, A.; Christensen, J.H.
1998-01-01
A tracer model, the DREAM, which is based on a combination of a near-range Lagrangian model and a long-range Eulerian model, has been developed. The meteorological meso-scale model, MM5V1, is implemented as a meteorological driver for the tracer model. The model system is used for studying...
Höning, D.; Spohn, T.
2014-12-01
By harvesting solar energy and converting it to chemical energy, photosynthetic life plays an important role in the energy budget of Earth [2]. This leads to alterations of chemical reservoirs eventually affecting the Earth's interior [4]. It further has been speculated [3] that the formation of continents may be a consequence of the evolution life. A steady state model [1] suggests that the Earth without its biosphere would evolve to a steady state with a smaller continent coverage and a dryer mantle than is observed today. We present a model including (i) parameterized thermal evolution, (ii) continental growth and destruction, and (iii) mantle water regassing and outgassing. The biosphere enhances the production rate of sediments which eventually are subducted. These sediments are assumed to (i) carry water to depth bound in stable mineral phases and (ii) have the potential to suppress shallow dewatering of the underlying sediments and crust due to their low permeability. We run a Monte Carlo simulation for various initial conditions and treat all those parameter combinations as success which result in the fraction of continental crust coverage observed for present day Earth. Finally, we simulate the evolution of an abiotic Earth using the same set of parameters but a reduced rate of continental weathering and erosion. Our results suggest that the origin and evolution of life could have stabilized the large continental surface area of the Earth and its wet mantle, leading to the relatively low mantle viscosity we observe at present. Without photosynthetic life on our planet, the Earth would be geodynamical less active due to a dryer mantle, and would have a smaller fraction of continental coverage than observed today. References[1] Höning, D., Hansen-Goos, H., Airo, A., Spohn, T., 2014. Biotic vs. abiotic Earth: A model for mantle hydration and continental coverage. Planetary and Space Science 98, 5-13. [2] Kleidon, A., 2010. Life, hierarchy, and the
Fuchs, Sven; Bording, Thue S.; Balling, Niels
2015-04-01
Thermal modelling is used to examine the subsurface temperature field and geothermal conditions at various scales (e.g. sedimentary basins, deep crust) and in the framework of different problem settings (e.g. scientific or industrial use). In such models, knowledge of rock thermal properties is prerequisites for the parameterisation of boundary conditions and layer properties. In contrast to hydrogeological ground-water models, where parameterization of the major rock property (i.e. hydraulic conductivity) is generally conducted considering lateral variations within geological layers, parameterization of thermal models (in particular regarding thermal conductivity but also radiogenic heat production and specific heat capacity) in most cases is conducted using constant parameters for each modelled layer. For such constant thermal parameter values, moreover, initial values are normally obtained from rare core measurements and/or literature values, which raise questions for their representativeness. Some few studies have considered lithological composition or well log information, but still keeping the layer values constant. In the present thermal-modelling scenario analysis, we demonstrate how the use of different parameter input type (from literature, well logs and lithology) and parameter input style (constant or laterally varying layer values) affects the temperature model prediction in sedimentary basins. For this purpose, rock thermal properties are deduced from standard petrophysical well logs and lithological descriptions for several wells in a project area. Statistical values of thermal properties (mean, standard deviation, moments, etc.) are calculated at each borehole location for each geological formation and, moreover, for the entire dataset. Our case study is located at the Danish-German border region (model dimension: 135 x115 km, depth: 20 km). Results clearly show that (i) the use of location-specific well-log derived rock thermal properties and (i
Lu, Wei; Yang, Qingchun; Martín, Jordi D.; Juncosa, Ricardo
2013-04-01
During the 1990s, groundwater overexploitation has resulted in seawater intrusion in the coastal aquifer of the Shenzhen city, China. Although water supply facilities have been improved and alleviated seawater intrusion in recent years, groundwater overexploitation is still of great concern in some local areas. In this work we present a three-dimensional density-dependent numerical model developed with the FEFLOW code, which is aimed at simulating the extent of seawater intrusion while including tidal effects and different groundwater pumping scenarios. Model calibration, using waterheads and reported chloride concentration, has been performed based on the data from 14 boreholes, which were monitored from May 2008 to December 2009. A fairly good fitness between the observed and computed values was obtained by a manual trial-and-error method. Model prediction has been carried out forward 3 years with the calibrated model taking into account high, medium and low tide levels and different groundwater exploitation schemes. The model results show that tide-induced seawater intrusion significantly affects the groundwater levels and concentrations near the estuarine of the Dasha river, which implies that an important hydraulic connection exists between this river and groundwater, even considering that some anti-seepage measures were taken in the river bed. Two pumping scenarios were considered in the calibrated model in order to predict the future changes in the water levels and chloride concentration. The numerical results reveal a decreased tendency of seawater intrusion if groundwater exploitation does not reach an upper bound of about 1.32 × 104 m3/d. The model results provide also insights for controlling seawater intrusion in such coastal aquifer systems.
Geeson, Cathy; Wei, Li; Franklin, Bryony Dean
2017-06-14
Medicines optimisation is a key role for hospital pharmacists, but with ever-increasing demands on services there is a need to increase efficiency while maintaining patient safety. The aim of this study is to develop a prognostic model, the Medicines Optimisation Assessment Tool (MOAT), which can be used to target patients most in need of pharmacists' input while in hospital. The MOAT will be developed following recommendations of the Prognosis Research Strategy partnership. Using a cohort study we will prospectively include 1500 adult patients from the medical wards of two UK hospitals. Data on medication-related problems (MRPs) experienced by study patients will be collected by pharmacists at the study sites as part of their routine daily clinical assessment of patients. Data on potential risk factors such as polypharmacy, renal impairment and the use of 'high risk' medicines will be collected retrospectively from the information departments at the study sites, laboratory reporting systems and patient medical records. Multivariable logistic regression models will then be used to determine the relationship between potential risk factors and the study outcome of preventable MRPs that are at least moderate in severity. Bootstrapping will be used to adjust the MOAT for optimism, and predictive performance will be assessed using calibration and discrimination. A simplified scoring system will also be developed, which will be assessed for sensitivity and specificity. This study has been approved by the Proportionate Review Service Sub-Committee of the National Health Service Research Ethics Committee Wales REC 7 (16/WA/0016) and the Health Research Authority (project ID 197298). We plan to disseminate the results via presentations at relevant patient/public, professional, academic and scientific meetings and conferences, and will submit findings for publication in peer-reviewed journals. NCT02582463. © Article author(s) (or their employer(s) unless otherwise stated in
Including Overweight or Obese Students in Physical Education: A Social Ecological Constraint Model
Li, Weidong; Rukavina, Paul
2012-01-01
In this review, we propose a social ecological constraint model to study inclusion of overweight or obese students in physical education by integrating key concepts and assumptions from ecological constraint theory in motor development and social ecological models in health promotion and behavior. The social ecological constraint model proposes…
ETM documentation update – including modelling conventions and manual for software tools
DEFF Research Database (Denmark)
Grohnheit, Poul Erik
, it summarises the work done during 2013, and it also contains presentations for promotion of fusion as a future element in the electricity generation mix and presentations for the modelling community concerning model development and model documentation – in particular for TIAM collaboration workshops....
Conchúir, Shane Ó.; Der, Bryan S.; Drew, Kevin; Kuroda, Daisuke; Xu, Jianqing; Weitzner, Brian D.; Renfrew, P. Douglas; Sripakdeevong, Parin; Borgo, Benjamin; Havranek, James J.; Kuhlman, Brian; Kortemme, Tanja; Bonneau, Richard; Gray, Jeffrey J.; Das, Rhiju
2013-01-01
The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code’s difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step ‘serverification’ protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org. PMID:23717507
Harmonize input selection for sediment transport prediction
Afan, Haitham Abdulmohsin; Keshtegar, Behrooz; Mohtar, Wan Hanna Melini Wan; El-Shafie, Ahmed
2017-09-01
In this paper, three modeling approaches using a Neural Network (NN), Response Surface Method (RSM) and response surface method basis Global Harmony Search (GHS) are applied to predict the daily time series suspended sediment load. Generally, the input variables for forecasting the suspended sediment load are manually selected based on the maximum correlations of input variables in the modeling approaches based on NN and RSM. The RSM is improved to select the input variables by using the errors terms of training data based on the GHS, namely as response surface method and global harmony search (RSM-GHS) modeling method. The second-order polynomial function with cross terms is applied to calibrate the time series suspended sediment load with three, four and five input variables in the proposed RSM-GHS. The linear, square and cross corrections of twenty input variables of antecedent values of suspended sediment load and water discharge are investigated to achieve the best predictions of the RSM based on the GHS method. The performances of the NN, RSM and proposed RSM-GHS including both accuracy and simplicity are compared through several comparative predicted and error statistics. The results illustrated that the proposed RSM-GHS is as uncomplicated as the RSM but performed better, where fewer errors and better correlation was observed (R = 0.95, MAE = 18.09 (ton/day), RMSE = 25.16 (ton/day)) compared to the ANN (R = 0.91, MAE = 20.17 (ton/day), RMSE = 33.09 (ton/day)) and RSM (R = 0.91, MAE = 20.06 (ton/day), RMSE = 31.92 (ton/day)) for all types of input variables.
Comparison of robust input shapers
Vaughan, Joshua; Yano, Aika; Singhose, William
2008-09-01
The rapid movement of machines is a challenging control problem because it often results in high levels of vibration. As a result, flexible machines are typically moved relatively slowly. Input shaping is a control method that allows much higher speeds of motion by limiting vibration induced by the reference command. To design an input-shaping controller, estimates of the system natural frequency and damping ratio are required. However, real world systems cannot be modeled exactly, making the robustness to modeling errors an important consideration. Many robust input shapers have been developed, but robust shapers typically have longer durations that slow the system response. This creates a compromise between shaper robustness and rise time. This paper analyzes the compromise between rapidity of motion and shaper robustness for several input-shaping methods. Experimental results from a portable bridge crane verify the theoretical predictions.
Kittiwanich, Jutarat; Songsangjinda, Putth; Yamamoto, Tamiji; Fukami, Kimio; Muangyao, Pensri
2012-01-01
In the present study, a mathematical model was developed to evaluate the effect of nitrogen (N) input from feed on the N dynamics under different feeding scenarios in a well aerated and enclosed culture pond of black tiger shrimp (Penaeus monodon). Three feeding levels were examined: underfeeding, optimum feeding and overfeeding. The model was formulated using field data gathered from an earthen pond (0.69 ha) which was stocked with shrimp post larvae at a density of 340,000 individuals ha(-1...
Transverse Crack Modeling and Validation in Rotor Systems, Including Thermal Effects
Directory of Open Access Journals (Sweden)
N. Bachschmid
2003-01-01
Full Text Available This article describes a model that allows the simulation of the static behavior of a transverse crack in a horizontal rotor under the action of weight and other possible static loads and the dynamic behavior of cracked rotating shaft. The crack breathes—that is, the mechanism of the crack's opening and closing is ruled by the stress on the cracked section exerted by the external loads. In a rotor, the stresses are time-dependent and have a period equal to the period of rotation; thus, the crack periodically breathes. An original, simplified model allows cracks of various shapes to be modeled and thermal stresses to be taken into account, as they may influence the opening and closing mechanism. The proposed method was validated by using two criteria. First the crack's breathing mechanism, simulated by the model, was compared with the results obtained by a nonlinear, threedimensional finite element model calculation, and a good agreement in the results was observed. Then the proposed model allowed the development of the equivalent cracked beam. The results of this model were compared with those obtained by the three-dimensional finite element model. Also in this case, there was a good agreement in the results.
A model for firm-specific strategic wisdom : including illustrations and 49 guiding questions
van Straten, Roeland Peter
2017-01-01
This PhD thesis provides an answer to the question ‘How may one think strategically’. It does so by presenting a new prescriptive ‘Model for Firm-Specific Strategic Wisdom’. This Model aims to guide any individual strategist in his or her thinking from a state of firm-specific ‘ignorance’ to a state
Complete Loss and Thermal Model of Power Semiconductors Including Device Rating Information
DEFF Research Database (Denmark)
Ma, Ke; Bahman, Amir Sajjad; Beczkowski, Szymon
2015-01-01
models, only the electrical loadings are focused and treated as design variables, while the device rating is normally pre-defined by experience with limited design flexibility. Consequently, a more complete loss and thermal model is proposed in this paper, which takes into account not only the electrical...
Numerical models of single- and double-negative metamaterials including viscous and thermal losses
DEFF Research Database (Denmark)
Cutanda Henriquez, Vicente; Sánchez-Dehesa, José
2017-01-01
detailed understanding on how viscous and thermal losses affect the setups at different frequencies. The modeling of a simpler single-negative metamaterial also broadens this overview. Both setups have been modeled with quadratic BEM meshes. Each sample, scaled at two different sizes, has been represented...
High organic inputs explain shallow and deep SOC storage in a