WorldWideScience

Sample records for model inputs included

  1. 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 the load torque estimator. An input-output linearising control is used to achieve better tracking performances. It is based on the mixed 'stator current - rotor flux linkage' induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with saturation included behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

  2. An improved robust model predictive control for linear parameter-varying input-output models

    NARCIS (Netherlands)

    Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.

    2018-01-01

    This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal

  3. Modeling inputs to computer models used in risk assessment

    International Nuclear Information System (INIS)

    Iman, R.L.

    1987-01-01

    Computer models for various risk assessment applications are closely scrutinized both from the standpoint of questioning the correctness of the underlying mathematical model with respect to the process it is attempting to model and from the standpoint of verifying that the computer model correctly implements the underlying mathematical model. A process that receives less scrutiny, but is nonetheless of equal importance, concerns the individual and joint modeling of the inputs. This modeling effort clearly has a great impact on the credibility of results. Model characteristics are reviewed in this paper that have a direct bearing on the model input process and reasons are given for using probabilities-based modeling with the inputs. The authors also present ways to model distributions for individual inputs and multivariate input structures when dependence and other constraints may be present

  4. Robust input design for nonlinear dynamic modeling of AUV.

    Science.gov (United States)

    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.

  5. Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity.

    Science.gov (United States)

    Lin, I-Chun; Xing, Dajun; Shapley, Robert

    2012-12-01

    One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

  6. Description of the CONTAIN input model for the Dodewaard nuclear power plant

    International Nuclear Information System (INIS)

    Velema, E.J.

    1992-02-01

    This report describes the ECN standard CONTAIN input model for the Dodewaard Nuclear Power Plant (NPP) that has been developed by ECN. This standard input model will serve as a basis for analyses of the phenomena which may occur inside the Dodewaard containment in the event of a postulated severe accident. Boundary conditions for specific containment analyses can easily be implemented in the input model. as a result ECN will be able to respond quickly on requests for analyses from the utilities of the authorities. The report also includes brief descriptions of the Dodewaard NPP and the CONTAIN computer program. (author). 7 refs.; 5 figs.; 3 tabs

  7. 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

  8. 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.

  9. An extended TRANSCAR model including ionospheric convection: simulation of EISCAT observations using inputs from AMIE

    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.

  10. 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

  11. A new interpretation and validation of variance based importance measures for models with correlated inputs

    Science.gov (United States)

    Hao, Wenrui; Lu, Zhenzhou; Li, Luyi

    2013-05-01

    In order to explore the contributions by correlated input variables to the variance of the output, a novel interpretation framework of importance measure indices is proposed for a model with correlated inputs, which includes the indices of the total correlated contribution and the total uncorrelated contribution. The proposed indices accurately describe the connotations of the contributions by the correlated input to the variance of output, and they can be viewed as the complement and correction of the interpretation about the contributions by the correlated inputs presented in "Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, 183 (2012) 937-946". Both of them contain the independent contribution by an individual input. Taking the general form of quadratic polynomial as an illustration, the total correlated contribution and the independent contribution by an individual input are derived analytically, from which the components and their origins of both contributions of correlated input can be clarified without any ambiguity. In the special case that no square term is included in the quadratic polynomial model, the total correlated contribution by the input can be further decomposed into the variance contribution related to the correlation of the input with other inputs and the independent contribution by the input itself, and the total uncorrelated contribution can be further decomposed into the independent part by interaction between the input and others and the independent part by the input itself. Numerical examples are employed and their results demonstrate that the derived analytical expressions of the variance-based importance measure are correct, and the clarification of the correlated input contribution to model output by the analytical derivation is very important for expanding the theory and solutions of uncorrelated input to those of the correlated one.

  12. 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.

  13. An extended TRANSCAR model including ionospheric convection: simulation of EISCAT observations using inputs from AMIE

    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.

  14. 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

  15. Input modeling with phase-type distributions and Markov models theory and applications

    CERN Document Server

    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...

  16. Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

    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)

  17. Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.

    Science.gov (United States)

    Kotz, Kaylee; Cinar, Ali; Mei, Yong; Roggendorf, Amy; Littlejohn, Elizabeth; Quinn, Laurie; Rollins, Derrick K

    2014-11-26

    The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC.

  18. The use of synthetic input sequences in time series modeling

    International Nuclear Information System (INIS)

    Oliveira, Dair Jose de; Letellier, Christophe; Gomes, Murilo E.D.; Aguirre, Luis A.

    2008-01-01

    In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure

  19. Statistical Analysis of Input Parameters Impact on the Modelling of Underground Structures

    Directory of Open Access Journals (Sweden)

    M. Hilar

    2008-01-01

    Full Text Available The behaviour of a geomechanical model and its final results are strongly affected by the input parameters. As the inherent variability of rock mass is difficult to model, engineers are frequently forced to face the question “Which input values should be used for analyses?” The correct answer to such a question requires a probabilistic approach, considering the uncertainty of site investigations and variation in the ground. This paper describes the statistical analysis of input parameters for FEM calculations of traffic tunnels in the city of Prague. At the beginning of the paper, the inaccuracy in the geotechnical modelling is discussed. In the following part the Fuzzy techniques are summarized, including information about an application of the Fuzzy arithmetic on the shotcrete parameters. The next part of the paper is focused on the stochastic simulation – Monte Carlo Simulation is briefly described, Latin Hypercubes method is described more in details. At the end several practical examples are described: statistical analysis of the input parameters on the numerical modelling of the completed Mrázovka tunnel (profile West Tunnel Tube km 5.160 and modelling of the constructed tunnel Špejchar – Pelc Tyrolka. 

  20. Analytic uncertainty and sensitivity analysis of models with input correlations

    Science.gov (United States)

    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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions

    Science.gov (United States)

    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.

  6. 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.

  7. 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])

  8. 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

  9. Development of the RETRAN input model for Ulchin 3/4 visual system analyzer

    International Nuclear Information System (INIS)

    Lee, S. W.; Kim, K. D.; Lee, Y. J.; Lee, W. J.; Chung, B. D.; Jeong, J. J.; Hwang, M. K.

    2004-01-01

    As a part of the Long-Term Nuclear R and D program, KAERI has developed the so-called Visual System Analyzer (ViSA) based on best-estimate codes. The MARS and RETRAN codes are used as the best-estimate codes for ViSA. Between these two codes, the RETRAN code is used for realistic analysis of Non-LOCA transients and small-break loss-of-coolant accidents, of which break size is less than 3 inch diameter. So it is necessary to develop the RETRAN input model for Ulchin 3/4 plants (KSNP). In recognition of this, the RETRAN input model for Ulchin 3/4 plants has been developed. This report includes the input model requirements and the calculation note for the input data generation (see the Appendix). In order to confirm the validity of the input data, the calculations are performed for a steady state at 100 % power operation condition, inadvertent reactor trip and RCP trip. The results of the steady-state calculation agree well with the design data. The results of the other transient calculations seem to be reasonable and consistent with those of other best-estimate calculations. Therefore, the RETRAN input data can be used as a base input deck for the RETRAN transient analyzer for Ulchin 3/4. Moreover, it is found that Core Protection Calculator (CPC) module, which is modified by Korea Electric Power Research Institute (KEPRI), is well adapted to ViSA

  10. Effects of input uncertainty on cross-scale crop modeling

    Science.gov (United States)

    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

  11. Pandemic recovery analysis using the dynamic inoperability input-output model.

    Science.gov (United States)

    Santos, Joost R; Orsi, Mark J; Bond, Erik J

    2009-12-01

    Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model((1,2)) and the dynamic inoperability input-output model (DIIM).((3)) These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.

  12. Comparison of different snow model formulations and their responses to input uncertainties in the Upper Indus Basin

    Science.gov (United States)

    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.

  13. Agricultural and Environmental Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    Kaylie Rasmuson; Kurt Rautenstrauch

    2003-01-01

    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

  14. Sensitivity analysis of complex models: Coping with dynamic and static inputs

    International Nuclear Information System (INIS)

    Anstett-Collin, F.; Goffart, J.; Mara, T.; Denis-Vidal, L.

    2015-01-01

    In this paper, we address the issue of conducting a sensitivity analysis of complex models with both static and dynamic uncertain inputs. While several approaches have been proposed to compute the sensitivity indices of the static inputs (i.e. parameters), the one of the dynamic inputs (i.e. stochastic fields) have been rarely addressed. For this purpose, we first treat each dynamic as a Gaussian process. Then, the truncated Karhunen–Loève expansion of each dynamic input is performed. Such an expansion allows to generate independent Gaussian processes from a finite number of independent random variables. Given that a dynamic input is represented by a finite number of random variables, its variance-based sensitivity index is defined by the sensitivity index of this group of variables. Besides, an efficient sampling-based strategy is described to estimate the first-order indices of all the input factors by only using two input samples. The approach is applied to a building energy model, in order to assess the impact of the uncertainties of the material properties (static inputs) and the weather data (dynamic inputs) on the energy performance of a real low energy consumption house. - Highlights: • Sensitivity analysis of models with uncertain static and dynamic inputs is performed. • Karhunen–Loève (KL) decomposition of the spatio/temporal inputs is performed. • The influence of the dynamic inputs is studied through the modes of the KL expansion. • The proposed approach is applied to a building energy model. • Impact of weather data and material properties on performance of real house is given

  15. 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

  16. Modeling Recognition Memory Using the Similarity Structure of Natural Input

    Science.gov (United States)

    Lacroix, Joyca P. W.; Murre, Jaap M. J.; Postma, Eric O.; van den Herik, H. Jaap

    2006-01-01

    The natural input memory (NAM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During recognition, the model compares incoming preprocessed…

  17. 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

  18. Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

    Science.gov (United States)

    Han, Feng; Zheng, Yi

    2018-06-01

    Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

  19. 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.

  20. 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

  1. 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

  2. Modeling recognition memory using the similarity structure of natural input

    NARCIS (Netherlands)

    Lacroix, J.P.W.; Murre, J.M.J.; Postma, E.O.; van den Herik, H.J.

    2006-01-01

    The natural input memory (NIM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During

  3. Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

    Science.gov (United States)

    Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

    2017-09-01

    A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

  4. 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

  5. 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

  6. Evaluating the uncertainty of input quantities in measurement models

    Science.gov (United States)

    Possolo, Antonio; Elster, Clemens

    2014-06-01

    The Guide to the Expression of Uncertainty in Measurement (GUM) gives guidance about how values and uncertainties should be assigned to the input quantities that appear in measurement models. This contribution offers a concrete proposal for how that guidance may be updated in light of the advances in the evaluation and expression of measurement uncertainty that were made in the course of the twenty years that have elapsed since the publication of the GUM, and also considering situations that the GUM does not yet contemplate. Our motivation is the ongoing conversation about a new edition of the GUM. While generally we favour a Bayesian approach to uncertainty evaluation, we also recognize the value that other approaches may bring to the problems considered here, and focus on methods for uncertainty evaluation and propagation that are widely applicable, including to cases that the GUM has not yet addressed. In addition to Bayesian methods, we discuss maximum-likelihood estimation, robust statistical methods, and measurement models where values of nominal properties play the same role that input quantities play in traditional models. We illustrate these general-purpose techniques in concrete examples, employing data sets that are realistic but that also are of conveniently small sizes. The supplementary material available online lists the R computer code that we have used to produce these examples (stacks.iop.org/Met/51/3/339/mmedia). Although we strive to stay close to clause 4 of the GUM, which addresses the evaluation of uncertainty for input quantities, we depart from it as we review the classes of measurement models that we believe are generally useful in contemporary measurement science. We also considerably expand and update the treatment that the GUM gives to Type B evaluations of uncertainty: reviewing the state-of-the-art, disciplined approach to the elicitation of expert knowledge, and its encapsulation in probability distributions that are usable in

  7. Calibration of uncertain inputs to computer models using experimentally measured quantities and the BMARS emulator

    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)

  8. 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

  9. 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

  10. Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City

    OpenAIRE

    Priska Arindya Purnama

    2017-01-01

    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)...

  11. PLEXOS Input Data Generator

    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.

  12. Simplifying BRDF input data for optical signature modeling

    Science.gov (United States)

    Hallberg, Tomas; Pohl, Anna; Fagerström, Jan

    2017-05-01

    Scene simulations of optical signature properties using signature codes normally requires input of various parameterized measurement data of surfaces and coatings in order to achieve realistic scene object features. Some of the most important parameters are used in the model of the Bidirectional Reflectance Distribution Function (BRDF) and are normally determined by surface reflectance and scattering measurements. Reflectance measurements of the spectral Directional Hemispherical Reflectance (DHR) at various incident angles can normally be performed in most spectroscopy labs, while measuring the BRDF is more complicated or may not be available at all in many optical labs. We will present a method in order to achieve the necessary BRDF data directly from DHR measurements for modeling software using the Sandford-Robertson BRDF model. The accuracy of the method is tested by modeling a test surface by comparing results from using estimated and measured BRDF data as input to the model. These results show that using this method gives no significant loss in modeling accuracy.

  13. 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.

  14. 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.

  15. 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.

  16. Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.

    Science.gov (United States)

    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.

  17. 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

  18. 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.

  19. Evaluating nuclear physics inputs in core-collapse supernova models

    Science.gov (United States)

    Lentz, E.; Hix, W. R.; Baird, M. L.; Messer, O. E. B.; Mezzacappa, A.

    Core-collapse supernova models depend on the details of the nuclear and weak interaction physics inputs just as they depend on the details of the macroscopic physics (transport, hydrodynamics, etc.), numerical methods, and progenitors. We present preliminary results from our ongoing comparison studies of nuclear and weak interaction physics inputs to core collapse supernova models using the spherically-symmetric, general relativistic, neutrino radiation hydrodynamics code Agile-Boltztran. We focus on comparisons of the effects of the nuclear EoS and the effects of improving the opacities, particularly neutrino--nucleon interactions.

  20. Development of an Input Model to MELCOR 1.8.5 for the Ringhals 3 PWR

    International Nuclear Information System (INIS)

    Nilsson, Lars

    2004-12-01

    An input file to the severe accident code MELCOR 1.8.5 has been developed for the Swedish pressurized water reactor Ringhals 3. The aim was to produce a file that can be used for calculations of various postulated severe accident scenarios, although the first application is specifically on cases involving large hydrogen production. The input file is rather detailed with individual modelling of all three cooling loops. The report describes the basis for the Ringhals 3 model and the input preparation step by step and is illustrated by nodalization schemes of the different plant systems. Present version of the report is restricted to the fundamental MELCOR input preparation, and therefore most of the figures of Ringhals 3 measurements and operating parameters are excluded here. These are given in another, complete version of the report, for limited distribution, which includes tables for pertinent data of all components. That version contains appendices with a complete listing of the input files as well as tables of data compiled from a RELAP5 file, that was a major basis for the MELCOR input for the cooling loops. The input was tested in steady-state calculations in order to simulate the initial conditions at current nominal operating conditions in Ringhals 3 for 2775 MW thermal power. The results of the steady-state calculations are presented in the report. Calculations with the MELCOR model will then be carried out of certain accident sequences for comparison with results from earlier MAAP4 calculations. That work will be reported separately

  1. 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.

  2. 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

  3. Motivation Monitoring and Assessment Extension for Input-Process-Outcome Game Model

    Science.gov (United States)

    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…

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Variance-based sensitivity indices for stochastic models with correlated inputs

    Energy Technology Data Exchange (ETDEWEB)

    Kala, Zdeněk [Brno University of Technology, Faculty of Civil Engineering, Department of Structural Mechanics Veveří St. 95, ZIP 602 00, Brno (Czech Republic)

    2015-03-10

    The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics.

  9. Variance-based sensitivity indices for stochastic models with correlated inputs

    International Nuclear Information System (INIS)

    Kala, Zdeněk

    2015-01-01

    The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics

  10. Model reduction of nonlinear systems subject to input disturbances

    KAUST Repository

    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.

  11. Input Uncertainty and its Implications on Parameter Assessment in Hydrologic and Hydroclimatic Modelling Studies

    Science.gov (United States)

    Chowdhury, S.; Sharma, A.

    2005-12-01

    Hydrological model inputs are often derived from measurements at point locations taken at discrete time steps. The nature of uncertainty associated with such inputs is thus a function of the quality and number of measurements available in time. A change in these characteristics (such as a change in the number of rain-gauge inputs used to derive spatially averaged rainfall) results in inhomogeneity in the associated distributional profile. Ignoring such uncertainty can lead to models that aim to simulate based on the observed input variable instead of the true measurement, resulting in a biased representation of the underlying system dynamics as well as an increase in both bias and the predictive uncertainty in simulations. This is especially true of cases where the nature of uncertainty likely in the future is significantly different to that in the past. Possible examples include situations where the accuracy of the catchment averaged rainfall has increased substantially due to an increase in the rain-gauge density, or accuracy of climatic observations (such as sea surface temperatures) increased due to the use of more accurate remote sensing technologies. We introduce here a method to ascertain the true value of parameters in the presence of additive uncertainty in model inputs. This method, known as SIMulation EXtrapolation (SIMEX, [Cook, 1994]) operates on the basis of an empirical relationship between parameters and the level of additive input noise (or uncertainty). The method starts with generating a series of alternate realisations of model inputs by artificially adding white noise in increasing multiples of the known error variance. The alternate realisations lead to alternate sets of parameters that are increasingly biased with respect to the truth due to the increased variability in the inputs. Once several such realisations have been drawn, one is able to formulate an empirical relationship between the parameter values and the level of additive noise

  12. Constituency Input into Budget Management.

    Science.gov (United States)

    Miller, Norman E.

    1995-01-01

    Presents techniques for ensuring constituency involvement in district- and site-level budget management. Outlines four models for securing constituent input and focuses on strategies to orchestrate the more complex model for staff and community participation. Two figures are included. (LMI)

  13. How model and input uncertainty impact maize yield simulations in West Africa

    Science.gov (United States)

    Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

    2015-02-01

    Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

  14. A Water-Withdrawal Input-Output Model of the Indian Economy.

    Science.gov (United States)

    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.

  15. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    Science.gov (United States)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  16. 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.

  17. Screening important inputs in models with strong interaction properties

    International Nuclear Information System (INIS)

    Saltelli, Andrea; Campolongo, Francesca; Cariboni, Jessica

    2009-01-01

    We introduce a new method for screening inputs in mathematical or computational models with large numbers of inputs. The method proposed here represents an improvement over the best available practice for this setting when dealing with models having strong interaction effects. When the sample size is sufficiently high the same design can also be used to obtain accurate quantitative estimates of the variance-based sensitivity measures: the same simulations can be used to obtain estimates of the variance-based measures according to the Sobol' and the Jansen formulas. Results demonstrate that Sobol' is more efficient for the computation of the first-order indices, while Jansen performs better for the computation of the total indices.

  18. Screening important inputs in models with strong interaction properties

    Energy Technology Data Exchange (ETDEWEB)

    Saltelli, Andrea [European Commission, Joint Research Centre, 21020 Ispra, Varese (Italy); Campolongo, Francesca [European Commission, Joint Research Centre, 21020 Ispra, Varese (Italy)], E-mail: francesca.campolongo@jrc.it; Cariboni, Jessica [European Commission, Joint Research Centre, 21020 Ispra, Varese (Italy)

    2009-07-15

    We introduce a new method for screening inputs in mathematical or computational models with large numbers of inputs. The method proposed here represents an improvement over the best available practice for this setting when dealing with models having strong interaction effects. When the sample size is sufficiently high the same design can also be used to obtain accurate quantitative estimates of the variance-based sensitivity measures: the same simulations can be used to obtain estimates of the variance-based measures according to the Sobol' and the Jansen formulas. Results demonstrate that Sobol' is more efficient for the computation of the first-order indices, while Jansen performs better for the computation of the total indices.

  19. Specification and Aggregation Errors in Environmentally Extended Input-Output Models

    NARCIS (Netherlands)

    Bouwmeester, Maaike C.; Oosterhaven, Jan

    This article considers the specification and aggregation errors that arise from estimating embodied emissions and embodied water use with environmentally extended national input-output (IO) models, instead of with an environmentally extended international IO model. Model specification errors result

  20. Inputs and spatial distribution patterns of Cr in Jiaozhou Bay

    Science.gov (United States)

    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.

  1. Characteristic length scale of input data in distributed models: implications for modeling grid size

    Science.gov (United States)

    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.

  2. Characteristic length scale of input data in distributed models: implications for modeling grain size

    Science.gov (United States)

    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.

  3. A PRODUCTIVITY EVALUATION MODEL BASED ON INPUT AND OUTPUT ORIENTATIONS

    Directory of Open Access Journals (Sweden)

    C.O. Anyaeche

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Many productivity models evaluate either the input or the output performances using standalone techniques. This sometimes gives divergent views of the same system’s results. The work reported in this article, which simultaneously evaluated productivity from both orientations, was applied on real life data. The results showed losses in productivity (–2% and price recovery (–8% for the outputs; the inputs showed productivity gain (145% but price recovery loss (–63%. These imply losses in product performances but a productivity gain in inputs. The loss in the price recovery of inputs indicates a problem in the pricing policy. This model is applicable in product diversification.

    AFRIKAANSE OPSOMMING: Die meeste produktiwiteitsmodelle evalueer of die inset- of die uitsetverrigting deur gebruik te maak van geïsoleerde tegnieke. Dit lei soms tot uiteenlopende perspektiewe van dieselfde sisteem se verrigting. Hierdie artikel evalueer verrigting uit beide perspektiewe en gebruik ware data. Die resultate toon ‘n afname in produktiwiteit (-2% en prysherwinning (-8% vir die uitsette. Die insette toon ‘n toename in produktiwiteit (145%, maar ‘n afname in prysherwinning (-63%. Dit impliseer ‘n afname in produkverrigting, maar ‘n produktiwiteitstoename in insette. Die afname in die prysherwinning van insette dui op ‘n problem in die prysvasstellingbeleid. Hierdie model is geskik vir produkdiversifikasie.

  4. Wideband Small-Signal Input dq Admittance Modeling of Six-Pulse Diode Rectifiers

    DEFF Research Database (Denmark)

    Yue, Xiaolong; Wang, Xiongfei; Blaabjerg, Frede

    2018-01-01

    This paper studies the wideband small-signal input dq admittance of six-pulse diode rectifiers. Considering the frequency coupling introduced by ripple frequency harmonics of d-and q-channel switching function, the proposed model successfully predicts the small-signal input dq admittance of six......-pulse diode rectifiers in high frequency regions that existing models fail to explain. Simulation and experimental results verify the accuracy of the proposed model....

  5. 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.

  6. Design, Fabrication, and Modeling of a Novel Dual-Axis Control Input PZT Gyroscope.

    Science.gov (United States)

    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.

  7. 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.

  8. Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

    Science.gov (United States)

    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.

  9. Sensitivity of a complex urban air quality model to input data

    International Nuclear Information System (INIS)

    Seigneur, C.; Tesche, T.W.; Roth, P.M.; Reid, L.E.

    1981-01-01

    In recent years, urban-scale photochemical simulation models have been developed that are of practical value for predicting air quality and analyzing the impacts of alternative emission control strategies. Although the performance of some urban-scale models appears to be acceptable, the demanding data requirements of such models have prompted concern about the costs of data acquistion, which might be high enough to preclude use of photochemical models for many urban areas. To explore this issue, sensitivity studies with the Systems Applications, Inc. (SAI) Airshed Model, a grid-based time-dependent photochemical dispersion model, have been carried out for the Los Angeles basin. Reductions in the amount and quality of meteorological, air quality and emission data, as well as modifications of the model gridded structure, have been analyzed. This paper presents and interprets the results of 22 sensitivity studies. A sensitivity-uncertainty index is defined to rank input data needs for an urban photochemical model. The index takes into account the sensitivity of model predictions to the amount of input data, the costs of data acquistion, and the uncertainties in the air quality model input variables. The results of these sensitivity studies are considered in light of the limitations of specific attributes of the Los Angeles basin and of the modeling conditions (e.g., choice of wind model, length of simulation time). The extent to which the results may be applied to other urban areas also is discussed

  10. Calibration of controlling input models for pavement management system.

    Science.gov (United States)

    2013-07-01

    The Oklahoma Department of Transportation (ODOT) is currently using the Deighton Total Infrastructure Management System (dTIMS) software for pavement management. This system is based on several input models which are computational backbones to dev...

  11. Quality assurance of weather data for agricultural system model input

    Science.gov (United States)

    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...

  12. Categorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models

    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.

  13. Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

    Science.gov (United States)

    Rothenberger, Michael J.

    This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input

  14. A Design Method of Robust Servo Internal Model Control with Control Input Saturation

    OpenAIRE

    山田, 功; 舩見, 洋祐

    2001-01-01

    In the present paper, we examine a design method of robust servo Internal Model Control with control input saturation. First of all, we clarify the condition that Internal Model Control has robust servo characteristics for the system with control input saturation. From this consideration, we propose new design method of Internal Model Control with robust servo characteristics. A numerical example to illustrate the effectiveness of the proposed method is shown.

  15. Extended Fitts' model of pointing time in eye-gaze input system - Incorporating effects of target shape and movement direction into modeling.

    Science.gov (United States)

    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.

  16. 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.

  17. 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

  18. Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input

    OpenAIRE

    Addo, Peter Martey

    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.

  19. 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.

  20. GASFLOW computer code (physical models and input data)

    International Nuclear Information System (INIS)

    Muehlbauer, Petr

    2007-11-01

    The GASFLOW computer code was developed jointly by the Los Alamos National Laboratory, USA, and Forschungszentrum Karlsruhe, Germany. The code is primarily intended for calculations of the transport, mixing, and combustion of hydrogen and other gases in nuclear reactor containments and in other facilities. The physical models and the input data are described, and a commented simple calculation is presented

  1. 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.

  2. International trade inoperability input-output model (IT-IIM): theory and application.

    Science.gov (United States)

    Jung, Jeesang; Santos, Joost R; Haimes, Yacov Y

    2009-01-01

    The inoperability input-output model (IIM) has been used for analyzing disruptions due to man-made or natural disasters that can adversely affect the operation of economic systems or critical infrastructures. Taking economic perturbation for each sector as inputs, the IIM provides the degree of economic production impacts on all industry sectors as the outputs for the model. The current version of the IIM does not provide a separate analysis for the international trade component of the inoperability. If an important port of entry (e.g., Port of Los Angeles) is disrupted, then international trade inoperability becomes a highly relevant subject for analysis. To complement the current IIM, this article develops the International Trade-IIM (IT-IIM). The IT-IIM investigates the resulting international trade inoperability for all industry sectors resulting from disruptions to a major port of entry. Similar to traditional IIM analysis, the inoperability metrics that the IT-IIM provides can be used to prioritize economic sectors based on the losses they could potentially incur. The IT-IIM is used to analyze two types of direct perturbations: (1) the reduced capacity of ports of entry, including harbors and airports (e.g., a shutdown of any port of entry); and (2) restrictions on commercial goods that foreign countries trade with the base nation (e.g., embargo).

  3. Key processes and input parameters for environmental tritium models

    International Nuclear Information System (INIS)

    Bunnenberg, C.; Taschner, M.; Ogram, G.L.

    1994-01-01

    The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs

  4. Key processes and input parameters for environmental tritium models

    Energy Technology Data Exchange (ETDEWEB)

    Bunnenberg, C; Taschner, M [Niedersaechsisches Inst. fuer Radiooekologie, Hannover (Germany); Ogram, G L [Ontario Hydro, Toronto, ON (Canada)

    1994-12-31

    The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs.

  5. Development of an Input Suite for an Orthotropic Composite Material Model

    Science.gov (United States)

    Hoffarth, Canio; Shyamsunder, Loukham; Khaled, Bilal; Rajan, Subramaniam; Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Blankenhorn, Gunther

    2017-01-01

    An orthotropic three-dimensional material model suitable for use in modeling impact tests has been developed that has three major components elastic and inelastic deformations, damage and failure. The material model has been implemented as MAT213 into a special version of LS-DYNA and uses tabulated data obtained from experiments. The prominent features of the constitutive model are illustrated using a widely-used aerospace composite the T800S3900-2B[P2352W-19] BMS8-276 Rev-H-Unitape fiber resin unidirectional composite. The input for the deformation model consists of experimental data from 12 distinct experiments at a known temperature and strain rate: tension and compression along all three principal directions, shear in all three principal planes, and off axis tension or compression tests in all three principal planes, along with other material constants. There are additional input associated with the damage and failure models. The steps in using this model are illustrated composite characterization tests, verification tests and a validation test. The results show that the developed and implemented model is stable and yields acceptably accurate results.

  6. Assessment of input function distortions on kinetic model parameters in simulated dynamic 82Rb PET perfusion studies

    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

  7. 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.

  8. Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model

    NARCIS (Netherlands)

    Chen, Quanrun; Dietzenbacher, Erik; Los, Bart; Yang, Cuihong

    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

  9. Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model

    NARCIS (Netherlands)

    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

  10. Input modelling of ASSERT-PV V2R8M1 for RUFIC fuel bundle

    Energy Technology Data Exchange (ETDEWEB)

    Park, Joo Hwan; Suk, Ho Chun

    2001-02-01

    This report describes the input modelling for subchannel analysis of CANFLEX-RU (RUFIC) fuel bundle which has been developed for an advanced fuel bundle of CANDU-6 reactor, using ASSERT-PV V2R8M1 code. Execution file of ASSERT-PV V2R8M1 code was recently transferred from AECL under JRDC agreement between KAERI and AECL. SSERT-PV V2R8M1 which is quite different from COBRA-IV-i code has been developed for thermalhydraulic analysis of CANDU-6 fuel channel by subchannel analysis method and updated so that 43-element CANDU fuel geometry can be applied. Hence, ASSERT code can be applied to the subchannel analysis of RUFIC fuel bundle. The present report was prepared for ASSERT input modelling of RUFIC fuel bundle. Since the ASSERT results highly depend on user's input modelling, the calculation results may be quite different among the user's input models. The objective of the present report is the preparation of detail description of the background information for input data and gives credibility of the calculation results.

  11. Input modelling of ASSERT-PV V2R8M1 for RUFIC fuel bundle

    International Nuclear Information System (INIS)

    Park, Joo Hwan; Suk, Ho Chun

    2001-02-01

    This report describes the input modelling for subchannel analysis of CANFLEX-RU (RUFIC) fuel bundle which has been developed for an advanced fuel bundle of CANDU-6 reactor, using ASSERT-PV V2R8M1 code. Execution file of ASSERT-PV V2R8M1 code was recently transferred from AECL under JRDC agreement between KAERI and AECL. SSERT-PV V2R8M1 which is quite different from COBRA-IV-i code has been developed for thermalhydraulic analysis of CANDU-6 fuel channel by subchannel analysis method and updated so that 43-element CANDU fuel geometry can be applied. Hence, ASSERT code can be applied to the subchannel analysis of RUFIC fuel bundle. The present report was prepared for ASSERT input modelling of RUFIC fuel bundle. Since the ASSERT results highly depend on user's input modelling, the calculation results may be quite different among the user's input models. The objective of the present report is the preparation of detail description of the background information for input data and gives credibility of the calculation results

  12. 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.

  13. 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...

  14. Logistics flows and enterprise input-output models: aggregate and disaggregate analysis

    NARCIS (Netherlands)

    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

  15. Evaluation of precipitation input for SWAT modeling in Alpine catchment: A case study in the Adige river basin (Italy).

    Science.gov (United States)

    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 © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  16. A non-linear dimension reduction methodology for generating data-driven stochastic input models

    Science.gov (United States)

    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

  17. 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

  18. The MARINA model (Model to Assess River Inputs of Nutrients to seAs)

    NARCIS (Netherlands)

    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

  19. Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models.

    Science.gov (United States)

    Meshkat, Nicolette; Anderson, Chris; DiStefano, Joseph J

    2012-09-01

    Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the characteristic set, of which a subset, the input-output equations, is used for identifiability analysis. A simpler algorithm is proposed for this step, using Gröbner Bases, along with a proof of the method that includes a reduced upper bound on derivative requirements. Efficacy of the new algorithm is illustrated with several biosystem model examples. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. Input modelling of ASSERT-PV V2R8M1 for RUFIC fuel bundle

    Energy Technology Data Exchange (ETDEWEB)

    Park, Joo Hwan; Suk, Ho Chun

    2001-02-01

    This report describes the input modelling for subchannel analysis of CANFLEX-RU (RUFIC) fuel bundle which has been developed for an advanced fuel bundle of CANDU-6 reactor, using ASSERT-PV V2R8M1 code. Execution file of ASSERT-PV V2R8M1 code was recently transferred from AECL under JRDC agreement between KAERI and AECL. SSERT-PV V2R8M1 which is quite different from COBRA-IV-i code has been developed for thermalhydraulic analysis of CANDU-6 fuel channel by subchannel analysis method and updated so that 43-element CANDU fuel geometry can be applied. Hence, ASSERT code can be applied to the subchannel analysis of RUFIC fuel bundle. The present report was prepared for ASSERT input modelling of RUFIC fuel bundle. Since the ASSERT results highly depend on user's input modelling, the calculation results may be quite different among the user's input models. The objective of the present report is the preparation of detail description of the background information for input data and gives credibility of the calculation results.

  1. VSC Input-Admittance Modeling and Analysis Above the Nyquist Frequency for Passivity-Based Stability Assessment

    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...

  2. COGEDIF - automatic TORT and DORT input generation from MORSE combinatorial geometry models

    International Nuclear Information System (INIS)

    Castelli, R.A.; Barnett, D.A.

    1992-01-01

    COGEDIF is an interactive utility which was developed to automate the preparation of two and three dimensional geometrical inputs for the ORNL-TORT and DORT discrete ordinates programs from complex three dimensional models described using the MORSE combinatorial geometry input description. The program creates either continuous or disjoint mesh input based upon the intersections of user defined meshing planes and the MORSE body definitions. The composition overlay of the combinatorial geometry is used to create the composition mapping of the discretized geometry based upon the composition found at the centroid of each of the mesh cells. This program simplifies the process of using discrete orthogonal mesh cells to represent non-orthogonal geometries in large models which require mesh sizes of the order of a million cells or more. The program was specifically written to take advantage of the new TORT disjoint mesh option which was developed at ORNL

  3. Comprehensive Information Retrieval and Model Input Sequence (CIRMIS)

    International Nuclear Information System (INIS)

    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

  4. Framework for Modelling Multiple Input Complex Aggregations for Interactive Installations

    DEFF Research Database (Denmark)

    Padfield, Nicolas; Andreasen, Troels

    2012-01-01

    on fuzzy logic and provides a method for variably balancing interaction and user input with the intention of the artist or director. An experimental design is presented, demonstrating an intuitive interface for parametric modelling of a complex aggregation function. The aggregation function unifies...

  5. Non parametric, self organizing, scalable modeling of spatiotemporal inputs: the sign language paradigm.

    Science.gov (United States)

    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.

  6. System Identification for Nonlinear FOPDT Model with Input-Dependent Dead-Time

    DEFF Research Database (Denmark)

    Sun, Zhen; Yang, Zhenyu

    2011-01-01

    An on-line iterative method of system identification for a kind of nonlinear FOPDT system is proposed in the paper. The considered nonlinear FOPDT model is an extension of the standard FOPDT model by means that its dead time depends on the input signal and the other parameters are time dependent....

  7. Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2017-10-01

    Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

  8. 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

  9. 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

  10. 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 ...

  11. DIMITRI 1.0: Beschrijving en toepassing van een dynamisch input-output model

    NARCIS (Netherlands)

    Wilting HC; Blom WF; Thomas R; Idenburg AM; LAE

    2001-01-01

    DIMITRI, the Dynamic Input-Output Model to study the Impacts of Technology Related Innovations, was developed in the framework of the RIVM Environment and Economy project to answer questions about interrelationships between economy, technology and the environment. DIMITRI, a meso-economic model,

  12. Multi input single output model predictive control of non-linear bio-polymerization process

    Energy Technology Data Exchange (ETDEWEB)

    Arumugasamy, Senthil Kumar; Ahmad, Z. [School of Chemical Engineering, Univerisiti Sains Malaysia, Engineering Campus, Seri Ampangan,14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)

    2015-05-15

    This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

  13. Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

    Science.gov (United States)

    Morelli, Eugene A.; Klein, Vladislav

    1990-01-01

    A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

  14. An analytical model for an input/output-subsystem

    International Nuclear Information System (INIS)

    Roemgens, J.

    1983-05-01

    An input/output-subsystem of one or several computers if formed by the external memory units and the peripheral units of a computer system. For these subsystems mathematical models are established, taking into account the special properties of the I/O-subsystems, in order to avoid planning errors and to allow for predictions of the capacity of such systems. Here an analytical model is presented for the magnetic discs of a I/O-subsystem, using analytical methods for the individual waiting queues or waiting queue networks. Only I/O-subsystems of IBM-computer configurations are considered, which can be controlled by the MVS operating system. After a description of the hardware and software components of these I/O-systems, possible solutions from the literature are presented and discussed with respect to their applicability in IBM-I/O-subsystems. Based on these models a special scheme is developed which combines the advantages of the literature models and avoids the disadvantages in part. (orig./RW) [de

  15. FLUTAN input specifications

    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

  16. Harmonize input selection for sediment transport prediction

    Science.gov (United States)

    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.

  17. Including spatial data in nutrient balance modelling on dairy farms

    Science.gov (United States)

    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

  18. Scientific and technical advisory committee review of the nutrient inputs to the watershed model

    Science.gov (United States)

    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...

  19. Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models

    NARCIS (Netherlands)

    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

  20. Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

    Science.gov (United States)

    Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

    2018-05-30

    The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018

  1. 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......, modelling the performance of the PV modules at high irradiances requires a dataset of only a few hundred samples in order to obtain a power estimation accuracy of ~1-2\\%....

  2. A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

    Science.gov (United States)

    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

  3. 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.

  4. 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

    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......) with input and input-rate limits. The algorithm alternates between solving an extended LQCP and a highly structured quadratic program. These quadratic programs are solved using a Riccati iteration procedure, and a structure-exploiting interior-point method, respectively. The computational cost per iteration...... 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...

  5. Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

    Science.gov (United States)

    Aksoy, A.; Yuzugullu, O.

    2017-12-01

    Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

  6. Subsidy or subtraction: how do terrestrial inputs influence consumer production in lakes?

    Science.gov (United States)

    Jones, Stuart E.; Solomon, Christopher T.; Weidel, Brian C.

    2012-01-01

    Cross-ecosystem fluxes are ubiquitous in food webs and are generally thought of as subsidies to consumer populations. Yet external or allochthonous inputs may in fact have complex and habitat-specific effects on recipient ecosystems. In lakes, terrestrial inputs of organic carbon contribute to basal resource availability, but can also reduce resource availability via shading effects on phytoplankton and periphyton. Terrestrial inputs might therefore either subsidise or subtract from consumer production. We developed and parameterised a simple model to explore this idea. The model estimates basal resource supply and consumer production given lake-level characteristics including total phosphorus (TP) and dissolved organic carbon (DOC) concentration, and consumer-level characteristics including resource preferences and growth efficiencies. Terrestrial inputs diminished primary production and total basal resource supply at the whole-lake level, except in ultra-oligotrophic systems. However, this system-level generalisation masked complex habitat-specific effects. In the pelagic zone, dissolved and particulate terrestrial carbon inputs were available to zooplankton via several food web pathways. Consequently, zooplankton production usually increased with terrestrial inputs, even as total whole-lake resource availability decreased. In contrast, in the benthic zone the dominant, dissolved portion of the terrestrial carbon load had predominantly negative effects on resource availability via shading of periphyton. Consequently, terrestrial inputs always decreased zoobenthic production except under extreme and unrealistic parameterisations of the model. Appreciating the complex and habitat-specific effects of allochthonous inputs may be essential for resolving the effects of cross-habitat fluxes on consumers in lakes and other food webs.

  7. Data input guide for SWIFT II. The Sandia waste-isolation flow and transport model for fractured media, Release 4.84

    International Nuclear Information System (INIS)

    Reeves, M.; Ward, D.S.; Johns, N.D.; Cranwell, R.M.

    1986-04-01

    This report is one of three which describes the SWIFT II computer code. The code simulates flow and transport processes in geologic media which may be fractured. SWIFT II was developed for use in the analysis of deep geologic facilities for nuclear-waste disposal. This user's manual should permit the analyst to use the code effectively by facilitating the preparation of input data. A second companion document discusses the theory and implementation of the models employed by the SWIFT II code. A third document provides illustrative problems for instructional purposes. This report contains detailed descriptions of the input data along with an appendix of the input diagnostics. The use of auxiliary files, unit conversions, and program variable descriptors also are included in this document

  8. A quantitative approach to modeling the information processing of NPP operators under input information overload

    International Nuclear Information System (INIS)

    Kim, Jong Hyun; Seong, Poong Hyun

    2002-01-01

    This paper proposes a quantitative approach to modeling the information processing of NPP operators. The aim of this work is to derive the amount of the information processed during a certain control task under input information overload. We primarily develop the information processing model having multiple stages, which contains information flow. Then the uncertainty of the information is quantified using the Conant's model, a kind of information theory. We also investigate the applicability of this approach to quantifying the information reduction of operators under the input information overload

  9. Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) Benchmark Phase II: Identification of Influential Parameters

    International Nuclear Information System (INIS)

    Kovtonyuk, A.; Petruzzi, A.; D'Auria, F.

    2015-01-01

    The objective of the Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) benchmark is to progress on the issue of the quantification of the uncertainty of the physical models in system thermal-hydraulic codes by considering a concrete case: the physical models involved in the prediction of core reflooding. The PREMIUM benchmark consists of five phases. This report presents the results of Phase II dedicated to the identification of the uncertain code parameters associated with physical models used in the simulation of reflooding conditions. This identification is made on the basis of the Test 216 of the FEBA/SEFLEX programme according to the following steps: - identification of influential phenomena; - identification of the associated physical models and parameters, depending on the used code; - quantification of the variation range of identified input parameters through a series of sensitivity calculations. A procedure for the identification of potentially influential code input parameters has been set up in the Specifications of Phase II of PREMIUM benchmark. A set of quantitative criteria has been as well proposed for the identification of influential IP and their respective variation range. Thirteen participating organisations, using 8 different codes (7 system thermal-hydraulic codes and 1 sub-channel module of a system thermal-hydraulic code) submitted Phase II results. The base case calculations show spread in predicted cladding temperatures and quench front propagation that has been characterized. All the participants, except one, predict a too fast quench front progression. Besides, the cladding temperature time trends obtained by almost all the participants show oscillatory behaviour which may have numeric origins. Adopted criteria for identification of influential input parameters differ between the participants: some organisations used the set of criteria proposed in Specifications 'as is', some modified the quantitative thresholds

  10. Influential input parameters for reflood model of MARS code

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Deog Yeon; Bang, Young Seok [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2012-10-15

    Best Estimate (BE) calculation has been more broadly used in nuclear industries and regulations to reduce the significant conservatism for evaluating Loss of Coolant Accident (LOCA). Reflood model has been identified as one of the problems in BE calculation. The objective of the Post BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) program of OECD/NEA is to make progress the issue of the quantification of the uncertainty of the physical models in system thermal hydraulic codes, by considering an experimental result especially for reflood. It is important to establish a methodology to identify and select the parameters influential to the response of reflood phenomena following Large Break LOCA. For this aspect, a reference calculation and sensitivity analysis to select the dominant influential parameters for FEBA experiment are performed.

  11. Modelling and control of a microgrid including photovoltaic and wind generation

    Science.gov (United States)

    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.

  12. Use of regional climate model simulations as an input for hydrological models for the Hindukush-Karakorum-Himalaya region

    NARCIS (Netherlands)

    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

  13. Remote sensing inputs to water demand modeling

    Science.gov (United States)

    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.

  14. PERMODELAN INDEKS HARGA KONSUMEN INDONESIA DENGAN MENGGUNAKAN MODEL INTERVENSI MULTI INPUT

    KAUST Repository

    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.

  15. From LCC to LCA Using a Hybrid Input Output Model – A Maritime Case Study

    DEFF Research Database (Denmark)

    Kjær, Louise Laumann; Pagoropoulos, Aris; Hauschild, Michael Zwicky

    2015-01-01

    As companies try to embrace life cycle thinking, Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) have proven to be powerful tools. In this paper, an Environmental Input-Output model is used for analysis as it enables an LCA using the same economic input data as LCC. This approach helps...

  16. FLUTAN 2.0. Input specifications

    International Nuclear Information System (INIS)

    Willerding, G.; Baumann, W.

    1996-05-01

    FLUTAN is a highly vectorized computer code for 3D fluiddynamic and thermal-hydraulic analyses in Cartesian or cylinder coordinates. It is related to the family of COMMIX codes originally developed at Argonne National Laboratory, USA, and particularly to COMMIX-1A and COMMIX-1B, which were made available to FZK in the frame of cooperation contracts within the fast reactor safety field. FLUTAN 2.0 is an improved version of the FLUTAN code released in 1992. It offers some additional innovations, e.g. the QUICK-LECUSSO-FRAM techniques for reducing numerical diffusion in the k-ε turbulence model equations; a higher sophisticated wall model for specifying a mass flow outside the surface walls together with its flow path and its associated inlet and outlet flow temperatures; and a revised and upgraded pressure boundary condition to fully include the outlet cells in the solution process of the conservation equations. Last but not least, a so-called visualization option based on VISART standards has been provided. This report contains detailed input instructions, presents formulations of the various model options, and explains how to use the code by means of comprehensive sample input. (orig.) [de

  17. Transport coefficient computation based on input/output reduced order models

    Science.gov (United States)

    Hurst, Joshua L.

    The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator

  18. Synaptic inputs compete during rapid formation of the calyx of Held: a new model system for neural development.

    Science.gov (United States)

    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.

  19. Environmental impact assessment including indirect effects--a case study using input-output analysis

    International Nuclear Information System (INIS)

    Lenzen, Manfred; Murray, Shauna A.; Korte, Britta; Dey, Christopher J.

    2003-01-01

    Environmental impact assessment (EIA) is a process covered by several international standards, dictating that as many environmental aspects as possible should be identified in a project appraisal. While the ISO 14011 standard stipulates a broad-ranging study, off-site, indirect impacts are not specifically required for an Environmental Impact Statement (EIS). The reasons for this may relate to the perceived difficulty of measuring off-site impacts, or the assumption that these are a relatively insignificant component of the total impact. In this work, we describe a method that uses input-output analysis to calculate the indirect effects of a development proposal in terms of several indicator variables. The results of our case study of a Second Sydney Airport show that the total impacts are considerably higher than the on-site impacts for the indicators land disturbance, greenhouse gas emissions, water use, emissions of NO x and SO 2 , and employment. We conclude that employing input-output analysis enhances conventional EIA, as it allows for national and international effects to be taken into account in the decision-making process

  20. 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.

  1. Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs

    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.

  2. 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.

  3. The Canadian Defence Input-Output Model DIO Version 4.41

    Science.gov (United States)

    2011-09-01

    Request to develop DND tailored Input/Output Model. Electronic communication from AllenWeldon to Team Leader, Defence Economics Team onMarch 12, 2011...and similar contain- ers 166 1440 Handbags, wallets and similar personal articles such as eyeglass and cigar cases and coin purses 167 1450 Cotton yarn...408 3600 Radar and radio navigation equipment 409 3619 Semi-conductors 410 3621 Printed circuits 411 3622 Integrated circuits 412 3623 Other electronic

  4. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  5. Low-level waste shallow land disposal source term model: Data input guides

    International Nuclear Information System (INIS)

    Sullivan, T.M.; Suen, C.J.

    1989-07-01

    This report provides an input guide for the computational models developed to predict the rate of radionuclide release from shallow land disposal of low-level waste. Release of contaminants depends on four processes: water flow, container degradation, waste from leaching, and contaminant transport. The computer code FEMWATER has been selected to predict the movement of water in an unsaturated porous media. The computer code BLT (Breach, Leach, and Transport), a modification of FEMWASTE, has been selected to predict the processes of container degradation (Breach), contaminant release from the waste form (Leach), and contaminant migration (Transport). In conjunction, these two codes have the capability to account for the effects of disposal geometry, unsaturated/water flow, container degradation, waste form leaching, and migration of contaminants releases within a single disposal trench. In addition to the input requirements, this report presents the fundamental equations and relationships used to model the four different processes previously discussed. Further, the appendices provide a representative sample of data required by the different models. 14 figs., 27 tabs

  6. Temporal rainfall estimation using input data reduction and model inversion

    Science.gov (United States)

    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

  7. On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model

    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.

  8. Development of algorithm for depreciation costs allocation in dynamic input-output industrial enterprise model

    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.

  9. 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

  10. Analysis on relation between safety input and accidents

    Institute of Scientific and Technical Information of China (English)

    YAO Qing-guo; ZHANG Xue-mu; LI Chun-hui

    2007-01-01

    The number of safety input directly determines the level of safety, and there exists dialectical and unified relations between safety input and accidents. Based on the field investigation and reliable data, this paper deeply studied the dialectical relationship between safety input and accidents, and acquired the conclusions. The security situation of the coal enterprises was related to the security input rate, being effected little by the security input scale, and build the relationship model between safety input and accidents on this basis, that is the accident model.

  11. Spectral element modelling of seismic wave propagation in visco-elastoplastic media including excess-pore pressure development

    Science.gov (United States)

    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.

  12. The role of additive neurogenesis and synaptic plasticity in a hippocampal memory model with grid-cell like input.

    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

  13. Latitudinal and seasonal variability of the micrometeor input function: A study using model predictions and observations from Arecibo and PFISR

    Science.gov (United States)

    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

  14. Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

    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.

  15. SISTEM KONTROL OTOMATIK DENGAN MODEL SINGLE-INPUT-DUAL-OUTPUT DALAM KENDALI EFISIENSI UMUR-PEMAKAIAN INSTRUMEN

    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.

  16. Pre-processing of input files for the AZTRAN code

    International Nuclear Information System (INIS)

    Vargas E, S.; Ibarra, G.

    2017-09-01

    The AZTRAN code began to be developed in the Nuclear Engineering Department of the Escuela Superior de Fisica y Matematicas (ESFM) of the Instituto Politecnico Nacional (IPN) with the purpose of numerically solving various models arising from the physics and engineering of nuclear reactors. The code is still under development and is part of the AZTLAN platform: Development of a Mexican platform for the analysis and design of nuclear reactors. Due to the complexity to generate an input file for the code, a script based on D language is developed, with the purpose of making its elaboration easier, based on a new input file format which includes specific cards, which have been divided into two blocks, mandatory cards and optional cards, including a pre-processing of the input file to identify possible errors within it, as well as an image generator for the specific problem based on the python interpreter. (Author)

  17. Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

    Directory of Open Access Journals (Sweden)

    Zhen-Feng Wang

    2017-06-01

    Full Text Available Considering the importance of increasing driving safety, the study of safety is a popular and critical topic of research in the vehicle industry. Vehicle roll behavior with sudden steering input is a main source of untripped rollover. However, previous research has seldom considered road excitation and its coupled effect on vehicle lateral response when focusing on lateral and vertical dynamics. To address this issue, a novel method was used to evaluate effects of varying road level and steering wheel input on vehicle roll behavior. Then, a 9 degree of freedom (9-DOF full-car roll nonlinear model including vertical and lateral dynamics was developed to study vehicle roll dynamics with or without of road excitation. Based on a 6-DOF half-car roll model and 9-DOF full-car nonlinear model, relationship between three-dimensional (3-D road excitation and various steering wheel inputs on vehicle roll performance was studied. Finally, an E-Class (SUV level car model in CARSIM® was used, as a benchmark, with and without road input conditions. Both half-car and full-car models were analyzed under steering wheel inputs of 5°, 10° and 15°. Simulation results showed that the half-car model considering road input was found to have a maximum accuracy of 65%. Whereas, the full-car model had a minimum accuracy of 85%, which was significantly higher compared to the half-car model under the same scenario.

  18. Unitary input DEA model to identify beef cattle production systems typologies

    Directory of Open Access Journals (Sweden)

    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.

  19. Input parameters and scenarios, including economic inputs

    DEFF Research Database (Denmark)

    Boklund, Anette; Hisham Beshara Halasa, Tariq

    2012-01-01

    scenarios, we excluded hobby-type farms1 In the vaccination scenarios, herds within the vaccination zone were simulated to be vaccinated 14 days after detection of the first herd or when 10, 20, 30 or 50 herds were infected. All herds within the zones were simulated to be vaccinated. We used vaccination...... zones of either a 1, 2, 3 or 5 km. In some scenarios, hobby herds were not vaccinated. In one scenario, no sheep were vaccinated, and in another scenario no swine were vaccinated. from depopulation in zones. The resources for depopulation were estimated to 4,800 swine and 2,000 ruminants a day...

  20. 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.

  1. 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.

  2. Waste Isolation Pilot Plant environmental impact report: an outline of the input--output model and the impact projections methodology. Technical document, socioeconomic portion

    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

  3. GARFEM input deck description

    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.

  4. Linear and quadratic models of point process systems: contributions of patterned input to output.

    Science.gov (United States)

    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.

  5. The economic impact of multifunctional agriculture in Dutch regions: An input-output model

    NARCIS (Netherlands)

    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

  6. A comparison of numerical and machine-learning modeling of soil water content with limited input data

    Science.gov (United States)

    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

  7. Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

    Science.gov (United States)

    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.

  8. Efficient uncertainty quantification of a fully nonlinear and dispersive water wave model with random inputs

    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...... 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...... benchmarks often used for validation of deterministic water wave models. Based on numerical experiments and assumed uncertainties in boundary data, our analysis reveals that some of the known discrepancies from deterministic simulation in comparison with experimental measurements could be partially explained...

  9. Hierarchical Bayesian modelling of mobility metrics for hazard model input calibration

    Science.gov (United States)

    Calder, Eliza; Ogburn, Sarah; Spiller, Elaine; Rutarindwa, Regis; Berger, Jim

    2015-04-01

    In this work we present a method to constrain flow mobility input parameters for pyroclastic flow models using hierarchical Bayes modeling of standard mobility metrics such as H/L and flow volume etc. The advantage of hierarchical modeling is that it can leverage the information in global dataset for a particular mobility metric in order to reduce the uncertainty in modeling of an individual volcano, especially important where individual volcanoes have only sparse datasets. We use compiled pyroclastic flow runout data from Colima, Merapi, Soufriere Hills, Unzen and Semeru volcanoes, presented in an open-source database FlowDat (https://vhub.org/groups/massflowdatabase). While the exact relationship between flow volume and friction varies somewhat between volcanoes, dome collapse flows originating from the same volcano exhibit similar mobility relationships. Instead of fitting separate regression models for each volcano dataset, we use a variation of the hierarchical linear model (Kass and Steffey, 1989). The model presents a hierarchical structure with two levels; all dome collapse flows and dome collapse flows at specific volcanoes. The hierarchical model allows us to assume that the flows at specific volcanoes share a common distribution of regression slopes, then solves for that distribution. We present comparisons of the 95% confidence intervals on the individual regression lines for the data set from each volcano as well as those obtained from the hierarchical model. The results clearly demonstrate the advantage of considering global datasets using this technique. The technique developed is demonstrated here for mobility metrics, but can be applied to many other global datasets of volcanic parameters. In particular, such methods can provide a means to better contain parameters for volcanoes for which we only have sparse data, a ubiquitous problem in volcanology.

  10. A guidance on MELCOR input preparation : An input deck for Ul-Chin 3 and 4 Nuclear Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Song Won

    1997-02-01

    The objective of this study is to enhance the capability of assessing the severe accident sequence analyses and the containment behavior using MELCOR computer code and to provide the guideline of its efficient use. This report shows the method of the input deck preparation as well as the assessment strategy for the MELCOR code. MELCOR code is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor nuclear power plants. The code is being developed at Sandia National Laboratories for the U.S. NRC as a second generation plant risk assessment tool and the successor to the source term code package. The accident sequence of the reference input deck prepared in this study for Ulchin unit 3 and 4 nuclear power plants, is the total loss of feedwater (TLOFW) without any success of safety systems, which is similar to station blackout (TLMB). It is very useful to simulate a well-known sequence through the best estimated code or experiment, because the results of the simulation before core melt can be compared with the FSAR, but no data is available after core melt. The precalculation for the TLOFW using the reference input deck is performed successfully as expected. The other sequences will be carried out with minor changes in the reference input. This input deck will be improved continually by the adding of the safety systems not included in this input deck, and also through the sensitivity and uncertainty analyses. (author). 19 refs., 10 tabs., 55 figs.

  11. A guidance on MELCOR input preparation : An input deck for Ul-Chin 3 and 4 Nuclear Power Plant

    International Nuclear Information System (INIS)

    Cho, Song Won.

    1997-02-01

    The objective of this study is to enhance the capability of assessing the severe accident sequence analyses and the containment behavior using MELCOR computer code and to provide the guideline of its efficient use. This report shows the method of the input deck preparation as well as the assessment strategy for the MELCOR code. MELCOR code is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor nuclear power plants. The code is being developed at Sandia National Laboratories for the U.S. NRC as a second generation plant risk assessment tool and the successor to the source term code package. The accident sequence of the reference input deck prepared in this study for Ulchin unit 3 and 4 nuclear power plants, is the total loss of feedwater (TLOFW) without any success of safety systems, which is similar to station blackout (TLMB). It is very useful to simulate a well-known sequence through the best estimated code or experiment, because the results of the simulation before core melt can be compared with the FSAR, but no data is available after core melt. The precalculation for the TLOFW using the reference input deck is performed successfully as expected. The other sequences will be carried out with minor changes in the reference input. This input deck will be improved continually by the adding of the safety systems not included in this input deck, and also through the sensitivity and uncertainty analyses. (author). 19 refs., 10 tabs., 55 figs

  12. Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: a shared input DEA-model.

    Science.gov (United States)

    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.

  13. Multiregional input-output model for the evaluation of Spanish water flows.

    Science.gov (United States)

    Cazcarro, Ignacio; Duarte, Rosa; Sánchez Chóliz, Julio

    2013-01-01

    We construct a multiregional input-output model for Spain, in order to evaluate the pressures on the water resources, virtual water flows, and water footprints of the regions, and the water impact of trade relationships within Spain and abroad. The study is framed with those interregional input-output models constructed to study water flows and impacts of regions in China, Australia, Mexico, or the UK. To build our database, we reconcile regional IO tables, national and regional accountancy of Spain, trade and water data. Results show an important imbalance between origin of water resources and final destination, with significant water pressures in the South, Mediterranean, and some central regions. The most populated and dynamic regions of Madrid and Barcelona are important drivers of water consumption in Spain. Main virtual water exporters are the South and Central agrarian regions: Andalusia, Castile-La Mancha, Castile-Leon, Aragon, and Extremadura, while the main virtual water importers are the industrialized regions of Madrid, Basque country, and the Mediterranean coast. The paper shows the different location of direct and indirect consumers of water in Spain and how the economic trade and consumption pattern of certain areas has significant impacts on the availability of water resources in other different and often drier regions.

  14. On the redistribution of existing inputs using the spherical frontier dea model

    Directory of Open Access Journals (Sweden)

    José Virgilio Guedes de Avellar

    2010-04-01

    Full Text Available The Spherical Frontier DEA Model (SFM (Avellar et al., 2007 was developed to be used when one wants to fairly distribute a new and fixed input to a group of Decision Making Units (DMU's. SFM's basic idea is to distribute this new and fixed input in such a way that every DMU will be placed on an efficiency frontier with a spherical shape. We use SFM to analyze the problems that appear when one wants to redistribute an already existing input to a group of DMU's such that the total sum of this input will remain constant. We also analyze the case in which this total sum may vary.O Modelo de Fronteira Esférica (MFE (Avellar et al., 2007 foi desenvolvido para ser usado quando se deseja distribuir de maneira justa um novo insumo a um conjunto de unidades tomadoras de decisão (DMU's, da sigla em inglês, Decision Making Units. A ideia básica do MFE é a de distribuir esse novo insumo de maneira que todas as DMU's sejam colocadas numa fronteira de eficiência com um formato esférico. Neste artigo, usamos MFE para analisar o problema que surge quando se deseja redistribuir um insumo já existente para um grupo de DMU's de tal forma que a soma desse insumo para todas as DMU's se mantenha constante. Também analisamos o caso em que essa soma possa variar.

  15. 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

  16. Olkiluoto surface hydrological modelling: Update 2012 including salt transport modelling

    Energy Technology Data Exchange (ETDEWEB)

    Karvonen, T. [WaterHope, Helsinki (Finland)

    2013-11-15

    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

  17. Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

    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

  18. Artificial neural network modelling of biological oxygen demand in rivers at the national level with input selection based on Monte Carlo simulations.

    Science.gov (United States)

    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.

  19. An Approach for Generating Precipitation Input for Worst-Case Flood Modelling

    Science.gov (United States)

    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.

  20. Input/Output linearizing control of a nuclear reactor

    International Nuclear Information System (INIS)

    Perez C, V.

    1994-01-01

    The feedback linearization technique is an approach to nonlinear control design. The basic idea is to transform, by means of algebraic methods, the dynamics of a nonlinear control system into a full or partial linear system. As a result of this linearization process, the well known basic linear control techniques can be used to obtain some desired dynamic characteristics. When full linearization is achieved, the method is referred to as input-state linearization, whereas when partial linearization is achieved, the method is referred to as input-output linearization. We will deal with the latter. By means of input-output linearization, the dynamics of a nonlinear system can be decomposed into an external part (input-output), and an internal part (unobservable). Since the external part consists of a linear relationship among the output of the plant and the auxiliary control input mentioned above, it is easy to design such an auxiliary control input so that we get the output to behave in a predetermined way. Since the internal dynamics of the system is known, we can check its dynamics behavior on order of to ensure that the internal states are bounded. The linearization method described here can be applied to systems with one-input/one-output, as well as to systems with multiple-inputs/multiple-outputs. Typical control problems such as stabilization and reference path tracking can be solved using this technique. In this work, the input/output linearization theory is presented, as well as the problem of getting the output variable to track some desired trayectories. Further, the design of an input/output control system applied to the nonlinear model of a research nuclear reactor is included, along with the results obtained by computer simulation. (Author)

  1. Phylogenetic mixtures and linear invariants for equal input models.

    Science.gov (United States)

    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).

  2. Usefulness of non-linear input-output models for economic impact analyses in tourism and recreation

    NARCIS (Netherlands)

    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

  3. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    Science.gov (United States)

    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.

  4. Non-perturbative inputs for gluon distributions in the hadrons

    International Nuclear Information System (INIS)

    Ermolaev, B.I.; Troyan, S.I.

    2017-01-01

    Description of hadronic reactions at high energies is conventionally done in the framework of QCD factorization. All factorization convolutions comprise non-perturbative inputs mimicking non-perturbative contributions and perturbative evolution of those inputs. We construct inputs for the gluon-hadron scattering amplitudes in the forward kinematics and, using the optical theorem, convert them into inputs for gluon distributions in the hadrons, embracing the cases of polarized and unpolarized hadrons. In the first place, we formulate mathematical criteria which any model for the inputs should obey and then suggest a model satisfying those criteria. This model is based on a simple reasoning: after emitting an active parton off the hadron, the remaining set of spectators becomes unstable and therefore it can be described through factors of the resonance type, so we call it the resonance model. We use it to obtain non-perturbative inputs for gluon distributions in unpolarized and polarized hadrons for all available types of QCD factorization: basic, K_T-and collinear factorizations. (orig.)

  5. Non-perturbative inputs for gluon distributions in the hadrons

    Energy Technology Data Exchange (ETDEWEB)

    Ermolaev, B.I. [Ioffe Physico-Technical Institute, Saint Petersburg (Russian Federation); Troyan, S.I. [St. Petersburg Institute of Nuclear Physics, Gatchina (Russian Federation)

    2017-03-15

    Description of hadronic reactions at high energies is conventionally done in the framework of QCD factorization. All factorization convolutions comprise non-perturbative inputs mimicking non-perturbative contributions and perturbative evolution of those inputs. We construct inputs for the gluon-hadron scattering amplitudes in the forward kinematics and, using the optical theorem, convert them into inputs for gluon distributions in the hadrons, embracing the cases of polarized and unpolarized hadrons. In the first place, we formulate mathematical criteria which any model for the inputs should obey and then suggest a model satisfying those criteria. This model is based on a simple reasoning: after emitting an active parton off the hadron, the remaining set of spectators becomes unstable and therefore it can be described through factors of the resonance type, so we call it the resonance model. We use it to obtain non-perturbative inputs for gluon distributions in unpolarized and polarized hadrons for all available types of QCD factorization: basic, K{sub T}-and collinear factorizations. (orig.)

  6. Estimating severity of sideways fall using a generic multi linear regression model based on kinematic input variables.

    Science.gov (United States)

    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.

  7. Targeting the right input data to improve crop modeling at global level

    Science.gov (United States)

    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

  8. Detection of no-model input-output pairs in closed-loop systems.

    Science.gov (United States)

    Potts, Alain Segundo; Alvarado, Christiam Segundo Morales; Garcia, Claudio

    2017-11-01

    The detection of no-model input-output (IO) pairs is important because it can speed up the multivariable system identification process, since all the pairs with null transfer functions are previously discarded and it can also improve the identified model quality, thus improving the performance of model based controllers. In the available literature, the methods focus just on the open-loop case, since in this case there is not the effect of the controller forcing the main diagonal in the transfer matrix to one and all the other terms to zero. In this paper, a modification of a previous method able to detect no-model IO pairs in open-loop systems is presented, but adapted to perform this duty in closed-loop systems. Tests are performed by using the traditional methods and the proposed one to show its effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Neonatal intensive care nursing curriculum challenges based on context, input, process, and product evaluation model: A qualitative study

    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.

  10. Uncertainty of input data for room acoustic simulations

    DEFF Research Database (Denmark)

    Jeong, Cheol-Ho; Marbjerg, Gerd; Brunskog, Jonas

    2016-01-01

    Although many room acoustic simulation models have been well established, simulation results will never be accurate with inaccurate and uncertain input data. This study addresses inappropriateness and uncertainty of input data for room acoustic simulations. Firstly, the random incidence absorption...... and scattering coefficients are insufficient when simulating highly non-diffuse rooms. More detailed information, such as the phase and angle dependence, can greatly improve the simulation results of pressure-based geometrical and wave-based models at frequencies well below the Schroeder frequency. Phase...... summarizes potential advanced absorption measurement techniques that can improve the quality of input data for room acoustic simulations. Lastly, plenty of uncertain input data are copied from unreliable sources. Software developers and users should be careful when spreading such uncertain input data. More...

  11. Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed types

    NARCIS (Netherlands)

    Akçay, A.E.; Biller, B.

    2014-01-01

    We consider an assemble-to-order production system where the product demands and the time since the last customer arrival are not independent. The simulation of this system requires a multivariate input model that generates random input vectors with correlated discrete and continuous components. In

  12. Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network

    Directory of Open Access Journals (Sweden)

    Adam ePonzi

    2012-03-01

    Full Text Available The striatal medium spiny neuron (MSNs network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri stimulus time histograms (PSTH of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioural task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviourally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would in when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and delineate the range of parameters where this behaviour is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response

  13. Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

    Science.gov (United States)

    Ponzi, Adam; Wickens, Jeff

    2012-01-01

    The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

  14. Performance assessment of retrospective meteorological inputs for use in air quality modeling during TexAQS 2006

    Science.gov (United States)

    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.

  15. Enhanced Input in LCTL Pedagogy

    Directory of Open Access Journals (Sweden)

    Marilyn S. Manley

    2009-08-01

    Full Text Available Language materials for the more-commonly-taught languages (MCTLs often include visual input enhancement (Sharwood Smith 1991, 1993 which makes use of typographical cues like bolding and underlining to enhance the saliency of targeted forms. For a variety of reasons, this paper argues that the use of enhanced input, both visual and oral, is especially important as a tool for the lesscommonly-taught languages (LCTLs. As there continues to be a scarcity of teaching resources for the LCTLs, individual teachers must take it upon themselves to incorporate enhanced input into their own self-made materials. Specific examples of how to incorporate both visual and oral enhanced input into language teaching are drawn from the author’s own experiences teaching Cuzco Quechua. Additionally, survey results are presented from the author’s Fall 2010 semester Cuzco Quechua language students, supporting the use of both visual and oral enhanced input.

  16. Enhanced Input in LCTL Pedagogy

    Directory of Open Access Journals (Sweden)

    Marilyn S. Manley

    2010-08-01

    Full Text Available Language materials for the more-commonly-taught languages (MCTLs often include visual input enhancement (Sharwood Smith 1991, 1993 which makes use of typographical cues like bolding and underlining to enhance the saliency of targeted forms. For a variety of reasons, this paper argues that the use of enhanced input, both visual and oral, is especially important as a tool for the lesscommonly-taught languages (LCTLs. As there continues to be a scarcity of teaching resources for the LCTLs, individual teachers must take it upon themselves to incorporate enhanced input into their own self-made materials. Specific examples of how to incorporate both visual and oral enhanced input into language teaching are drawn from the author’s own experiences teaching Cuzco Quechua. Additionally, survey results are presented from the author’s Fall 2010 semester Cuzco Quechua language students, supporting the use of both visual and oral enhanced input.

  17. Comparison of plasma input and reference tissue models for analysing [(11)C]flumazenil studies

    NARCIS (Netherlands)

    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

  18. The economic impact of multifunctional agriculture in The Netherlands: A regional input-output model

    NARCIS (Netherlands)

    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

  19. On the relationship between input parameters in two-mass vocal-fold model with acoustical coupling an signal parameters of the glottal flow

    NARCIS (Netherlands)

    van Hirtum, Annemie; Lopez, Ines; Hirschberg, Abraham; Pelorson, Xavier

    2003-01-01

    In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

  20. Jointness through vessel capacity input in a multispecies fishery

    DEFF Research Database (Denmark)

    Hansen, Lars Gårn; Jensen, Carsten Lynge

    2014-01-01

    capacity. We develop a fixed but allocatable input model of purse seine fisheries capturing this particular type of jointness. We estimate the model for the Norwegian purse seine fishery and find that it is characterized by nonjointness, while estimations for this fishery using the standard models imply...... are typically modeled as either independent single species fisheries or using standard multispecies functional forms characterized by jointness in inputs. We argue that production of each species is essentially independent but that jointness may be caused by competition for fixed but allocable input of vessel...

  1. Evaluating the effects of model structure and meteorological input data on runoff modelling in an alpine headwater basin

    Science.gov (United States)

    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

  2. Modelling the long-term consequences of a hypothetical dispersal of radioactivity in an urban area including remediation alternatives

    DEFF Research Database (Denmark)

    Thiessen, K.M.; Andersson, Kasper Grann; Batandjieva, B.

    2009-01-01

    The Urban Remediation Working Group of the International Atomic Energy Agency's EMRAS (Environmental Modelling for Radiation Safety) program was organized to address issues of remediation assessment modelling for urban areas contaminated with dispersed radionuclides. The present paper describes...... the second of two modelling exercises. This exercise was based on a hypothetical dispersal of radioactivity in an urban area from a radiological dispersal device, with reference surface contamination at selected sites used as the primary input information. Modelling endpoints for the exercise included...... radionuclide concentrations and external dose rates at specified locations, contributions to the dose rates from individual surfaces, and annual and cumulative external doses to specified reference individuals. Model predictions were performed for a "no action" situation (with no remedial measures...

  3. Learning Structure of Sensory Inputs with Synaptic Plasticity Leads to Interference

    Directory of Open Access Journals (Sweden)

    Joseph eChrol-Cannon

    2015-08-01

    Full Text Available Synaptic plasticity is often explored as a form of unsupervised adaptationin cortical microcircuits to learn the structure of complex sensoryinputs and thereby improve performance of classification and prediction. The question of whether the specific structure of the input patterns is encoded in the structure of neural networks has been largely neglected. Existing studies that have analyzed input-specific structural adaptation have used simplified, synthetic inputs in contrast to complex and noisy patterns found in real-world sensory data.In this work, input-specific structural changes are analyzed forthree empirically derived models of plasticity applied to three temporal sensory classification tasks that include complex, real-world visual and auditory data. Two forms of spike-timing dependent plasticity (STDP and the Bienenstock-Cooper-Munro (BCM plasticity rule are used to adapt the recurrent network structure during the training process before performance is tested on the pattern recognition tasks.It is shown that synaptic adaptation is highly sensitive to specific classes of input pattern. However, plasticity does not improve the performance on sensory pattern recognition tasks, partly due to synaptic interference between consecutively presented input samples. The changes in synaptic strength produced by one stimulus are reversed by thepresentation of another, thus largely preventing input-specific synaptic changes from being retained in the structure of the network.To solve the problem of interference, we suggest that models of plasticitybe extended to restrict neural activity and synaptic modification to a subset of the neural circuit, which is increasingly found to be the casein experimental neuroscience.

  4. High Resolution Modeling of the Thermospheric Response to Energy Inputs During the RENU-2 Rocket Flight

    Science.gov (United States)

    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

  5. Program for the Generation of MCNP Inputs from State Files of CAREM

    International Nuclear Information System (INIS)

    Leszczynski, Francisco; Lopasso, Edmundo; Villarino, E

    2000-01-01

    The objective of this work is the development and tests of detailed input data for the Monte Carlo program MCNP, to be able of model the core of CAREM reactor, with the detail included on the updated models, for having available a calculation system that allow the production of confident results to be compared with results obtained with the system used today for designing the CAREM reactor core (CONDOR-CITVAP).The model includes the possibility of temperature and coolant density, and temperature and numeric densities of fuel.The detail consists of 21 different fuel elements (symmetry 3) and 14 axial zones.Results of comparisons of reactivity and power pick factors are presented, between MCNP and CONDOR-CITVAP.On average, these results show an acceptable agreement for all the compared parameters.It is described, also, the interface CONDOR-CITVAP-MCNP program, that has been developed for generating inputs of materials for MCNP, from outputs of CONDOR and CITVAP, for different reactor states

  6. Persistence and ergodicity of plant disease model with markov conversion and impulsive toxicant input

    Science.gov (United States)

    Zhao, Wencai; Li, Juan; Zhang, Tongqian; Meng, Xinzhu; Zhang, Tonghua

    2017-07-01

    Taking into account of both white and colored noises, a stochastic mathematical model with impulsive toxicant input is formulated. Based on this model, we investigate dynamics, such as the persistence and ergodicity, of plant infectious disease model with Markov conversion in a polluted environment. The thresholds of extinction and persistence in mean are obtained. By using Lyapunov functions, we prove that the system is ergodic and has a stationary distribution under certain sufficient conditions. Finally, numerical simulations are employed to illustrate our theoretical analysis.

  7. The sensitivity of ecosystem service models to choices of input data and spatial resolution

    Science.gov (United States)

    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.

  8. A generic method for automatic translation between input models for different versions of simulation codes

    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

  9. A generic method for automatic translation between input models for different versions of simulation codes

    Energy Technology Data Exchange (ETDEWEB)

    Serfontein, Dawid E., E-mail: Dawid.Serfontein@nwu.ac.za [School of Mechanical and Nuclear Engineering, North West University (PUK-Campus), PRIVATE BAG X6001 (Internal Post Box 360), Potchefstroom 2520 (South Africa); Mulder, Eben J. [School of Mechanical and Nuclear Engineering, North West University (South Africa); Reitsma, Frederik [Calvera Consultants (South Africa)

    2014-05-01

    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.

  10. Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: A shared input DEA-model

    International Nuclear Information System (INIS)

    Rogge, Nicky; De Jaeger, Simon

    2012-01-01

    Highlights: ► Complexity in local waste management calls for more in depth efficiency analysis. ► Shared-input Data Envelopment Analysis can provide solution. ► Considerable room for the Flemish municipalities to improve their cost efficiency. - Abstract: 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.

  11. Hydrogen Generation Rate Model Calculation Input Data

    International Nuclear Information System (INIS)

    KUFAHL, M.A.

    2000-01-01

    This report documents the procedures and techniques utilized in the collection and analysis of analyte input data values in support of the flammable gas hazard safety analyses. This document represents the analyses of data current at the time of its writing and does not account for data available since then

  12. Increasing inhibitory input increases neuronal firing rate: why and when? Diffusion process cases

    Energy Technology Data Exchange (ETDEWEB)

    Feng Jianfeng [COGS, Sussex University (United Kingdom)]. E-mail: jf218@cam.ac.uk; Wei Gang [Department of Mathematics, Hong Kong Baptist University, Hong Kong (China)]. E-mail gwei@math.hkbu.edu.hk

    2001-09-21

    Increasing inhibitory input to single neuronal models, such as the FitzHugh-Nagumo model and the Hodgkin-Huxley model, can sometimes increase their firing rates, a phenomenon which we term inhibition-boosted firing (IBF). Here we consider neuronal models with diffusion approximation inputs, i.e. they share the identical first- and second-order statistics of the corresponding Poisson process inputs. Using the integrate-and-fire model and the IF-FHN model, we explore theoretically how and when IBF can happen. For both models, it is shown that there is a critical input frequency at which the efferent firing rate is identical when the neuron receives purely excitatory inputs or exactly balanced inhibitory and excitatory inputs. When the input frequency is lower than the critical frequency, IBF occurs. (author)

  13. Economic and environmental impacts of dietary changes in Iran : an input-output analysis

    NARCIS (Netherlands)

    Rahmani, R.; Bakhshoodeh, M.; Zibaei, M.; Heijman, W.J.M.; Eftekhari, M.H.

    2012-01-01

    Iran's simple and environmentally extended commodity by commodity input-output (IO) model was used to determine the impacts of dietary changes on the Iranian economy and on the environmental load. The original model is based on the status-quo diet and was modified to include the World Health

  14. '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

    for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil...... properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation....... 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...

  15. Good Modeling Practice for PAT Applications: Propagation of Input Uncertainty and Sensitivity Analysis

    DEFF Research Database (Denmark)

    Sin, Gürkan; Gernaey, Krist; Eliasson Lantz, Anna

    2009-01-01

    The uncertainty and sensitivity analysis are evaluated for their usefulness as part of the model-building within Process Analytical Technology applications. A mechanistic model describing a batch cultivation of Streptomyces coelicolor for antibiotic production was used as case study. The input...... compared to the large uncertainty observed in the antibiotic and off-gas CO2 predictions. The output uncertainty was observed to be lower during the exponential growth phase, while higher in the stationary and death phases - meaning the model describes some periods better than others. To understand which...... promising for helping to build reliable mechanistic models and to interpret the model outputs properly. These tools make part of good modeling practice, which can contribute to successful PAT applications for increased process understanding, operation and control purposes. © 2009 American Institute...

  16. New Results on Robust Model Predictive Control for Time-Delay Systems with Input Constraints

    Directory of Open Access Journals (Sweden)

    Qing Lu

    2014-01-01

    Full Text Available This paper investigates the problem of model predictive control for a class of nonlinear systems subject to state delays and input constraints. The time-varying delay is considered with both upper and lower bounds. A new model is proposed to approximate the delay. And the uncertainty is polytopic type. For the state-feedback MPC design objective, we formulate an optimization problem. Under model transformation, a new model predictive controller is designed such that the robust asymptotical stability of the closed-loop system can be guaranteed. Finally, the applicability of the presented results are demonstrated by a practical example.

  17. 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

  18. AN ACCURATE MODELING OF DELAY AND SLEW METRICS FOR ON-CHIP VLSI RC INTERCONNECTS FOR RAMP INPUTS USING BURR’S DISTRIBUTION FUNCTION

    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.

  19. On the relationship between input parameters in the two-mass vocal-fold model with acoustical coupling and signal parameters of the glottal flow

    NARCIS (Netherlands)

    Hirtum, van A.; Lopez Arteaga, I.; Hirschberg, A.; Pelorson, X.

    2003-01-01

    In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

  20. Comparing apples and oranges: fold-change detection of multiple simultaneous inputs.

    Directory of Open Access Journals (Sweden)

    Yuval Hart

    Full Text Available Sensory systems often detect multiple types of inputs. For example, a receptor in a cell-signaling system often binds multiple kinds of ligands, and sensory neurons can respond to different types of stimuli. How do sensory systems compare these different kinds of signals? Here, we consider this question in a class of sensory systems - including bacterial chemotaxis- which have a property known as fold-change detection: their output dynamics, including amplitude and response time, depends only on the relative changes in signal, rather than absolute changes, over a range of several decades of signal. We analyze how fold-change detection systems respond to multiple signals, using mathematical models. Suppose that a step of fold F1 is made in input 1, together with a step of F2 in input 2. What total response does the system provide? We show that when both input signals impact the same receptor with equal number of binding sites, the integrated response is multiplicative: the response dynamics depend only on the product of the two fold changes, F1F2. When the inputs bind the same receptor with different number of sites n1 and n2, the dynamics depend on a product of power laws, [Formula: see text]. Thus, two input signals which vary over time in an inverse way can lead to no response. When the two inputs affect two different receptors, other types of integration may be found and generally the system is not constrained to respond according to the product of the fold-change of each signal. These predictions can be readily tested experimentally, by providing cells with two simultaneously varying input signals. The present study suggests how cells can compare apples and oranges, namely by comparing each to its own background level, and then multiplying these two fold-changes.

  1. Enhancement of information transmission with stochastic resonance in hippocampal CA1 neuron models: effects of noise input location.

    Science.gov (United States)

    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.

  2. Input-output and energy demand models for Ireland: Data collection report. Part 1: EXPLOR

    Energy Technology Data Exchange (ETDEWEB)

    Henry, E W; Scott, S

    1981-01-01

    Data are presented in support of EXPLOR, an input-output economic model for Ireland. The data follow the listing of exogenous data-sets used by Batelle in document X11/515/77. Data are given for 1974, 1980, and 1985 and consist of household consumption, final demand-production, and commodity prices. (ACR)

  3. Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

    Science.gov (United States)

    Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

    2011-09-01

    When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. Phasing Out a Polluting Input

    OpenAIRE

    Eriksson, Clas

    2015-01-01

    This paper explores economic policies related to the potential conflict between economic growth and the environment. It applies a model with directed technological change and focuses on the case with low elasticity of substitution between clean and dirty inputs in production. New technology is substituted for the polluting input, which results in a gradual decline in pollution along the optimal long-run growth path. In contrast to some recent work, the era of pollution and environmental polic...

  5. A time-resolved model of the mesospheric Na layer: constraints on the meteor input function

    Directory of Open Access Journals (Sweden)

    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.

  6. ETFOD: a point model physics code with arbitrary input

    International Nuclear Information System (INIS)

    Rothe, K.E.; Attenberger, S.E.

    1980-06-01

    ETFOD is a zero-dimensional code which solves a set of physics equations by minimization. The technique used is different than normally used, in that the input is arbitrary. The user is supplied with a set of variables from which he specifies which variables are input (unchanging). The remaining variables become the output. Presently the code is being used for ETF reactor design studies. The code was written in a manner to allow easy modificaton of equations, variables, and physics calculations. The solution technique is presented along with hints for using the code

  7. A study on the multi-dimensional spectral analysis for response of a piping model with two-seismic inputs

    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

  8. Modelling Analysis of Forestry Input-Output Elasticity in China

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2016-01-01

    Full Text Available Based on an extended economic model and space econometrics, this essay analyzed the spatial distributions and interdependent relationships of the production of forestry in China; also the input-output elasticity of forestry production were calculated. Results figure out there exists significant spatial correlation in forestry production in China. Spatial distribution is mainly manifested as spatial agglomeration. The output elasticity of labor force is equal to 0.6649, and that of capital is equal to 0.8412. The contribution of land is significantly negative. Labor and capital are the main determinants for the province-level forestry production in China. Thus, research on the province-level forestry production should not ignore the spatial effect. The policy-making process should take into consideration the effects between provinces on the production of forestry. This study provides some scientific technical support for forestry production.

  9. A new chance-constrained DEA model with birandom input and output data

    OpenAIRE

    Tavana, M.; Shiraz, R. K.; Hatami-Marbini, A.

    2013-01-01

    The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been proposed to deal with the random input and output data in DEA. In this paper, we propose a new chance-...

  10. A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

    Science.gov (United States)

    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.

  11. A Model to Determinate the Influence of Probability Density Functions (PDFs of Input Quantities in Measurements

    Directory of Open Access Journals (Sweden)

    Jesús Caja

    2016-06-01

    Full Text Available A method for analysing the effect of different hypotheses about the type of the input quantities distributions of a measurement model is presented here so that the developed algorithms can be simplified. As an example, a model of indirect measurements with optical coordinate measurement machine was employed to evaluate these different hypotheses. As a result of the different experiments, the assumption that the different variables of the model can be modelled as normal distributions is proved.

  12. Two coupled Lévy queues with independent input

    OpenAIRE

    Jevgenijs Ivanovs; Onno Boxma

    2014-01-01

    We consider a pair of coupled queues driven by independent spectrally-positive Lévy processes. With respect to the bi-variate workload process this framework includes both the coupled processor model and the two-server fluid network with independent Lévy inputs. We identify the joint transform of the stationary workload distribution in terms of Wiener-Hopf factors corresponding to two auxiliary Lévy processes with explicit Laplace exponents. We reinterpret and extend the ideas of Cohen and Bo...

  13. INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

    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

  14. Prioritizing Interdependent Production Processes using Leontief Input-Output Model

    Directory of Open Access Journals (Sweden)

    Masbad Jesah Grace

    2016-03-01

    Full Text Available This paper proposes a methodology in identifying key production processes in an interdependent production system. Previous approaches on this domain have drawbacks that may potentially affect the reliability of decision-making. The proposed approach adopts the Leontief input-output model (L-IOM which was proven successful in analyzing interdependent economic systems. The motivation behind such adoption lies in the strength of L-IOM in providing a rigorous quantitative framework in identifying key components of interdependent systems. In this proposed approach, the consumption and production flows of each process are represented respectively by the material inventory produced by the prior process and the material inventory produced by the current process, both in monetary values. A case study in a furniture production system located in central Philippines was carried out to elucidate the proposed approach. Results of the case were reported in this work

  15. 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

  16. 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

  17. PERMODELAN INDEKS HARGA KONSUMEN INDONESIA DENGAN MENGGUNAKAN MODEL INTERVENSI MULTI INPUT

    KAUST Repository

    Novianti, Putri Wikie; Suhartono, Suhartono

    2017-01-01

    -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

  18. Effective property determination for input to a geostatistical model of regional groundwater flow: Wellenberg T→K

    International Nuclear Information System (INIS)

    Lanyon, G.W.; Marschall, P.; Vomvoris, S.; Jaquet, O.; Mazurek, M.

    1998-01-01

    This paper describes the methodology used to estimate effective hydraulic properties for input into a regional geostatistical model of groundwater flow at the Wellenberg site in Switzerland. The methodology uses a geologically-based discrete fracture network model to calculate effective hydraulic properties for 100m blocks along each borehole. A description of the most transmissive features (Water Conducting Features or WCFs) in each borehole is used to determine local transmissivity distributions which are combined with descriptions of WCF extent, orientation and channelling to create fracture network models. WCF geometry is dependent on the class of WCF. WCF classes are defined for each type of geological structure associated with identified borehole inflows. Local to each borehole, models are conditioned on the observed transmissivity and occurrence of WCFs. Multiple realisations are calculated for each 100m block over approximately 400m of borehole. The results from the numerical upscaling are compared with conservative estimates of hydraulic conductivity. Results from unconditioned models are also compared to identify the consequences of conditioning and interval of boreholes that appear to be atypical. An inverse method is also described by which realisations of the geostatistical model can be used to condition discrete fracture network models away from the boreholes. The method can be used as a verification of the modelling approach by prediction of data at borehole locations. Applications of the models to estimation of post-closure repository performance, including cavern inflow and seal zone modelling, are illustrated

  19. Data Envelopment Analysis with Fixed Inputs, Undesirable Outputs and Negative Data

    Directory of Open Access Journals (Sweden)

    F. Seyed Esmaeili

    2017-03-01

    Full Text Available In Data Envelopment Analysis (DEA, different models have been measured to evaluate the performance of decision making units with multiple inputs and outputs. Revised model of Slack-based measures known as MBSM of collective models family has been introduced by Sharp et al. Slack-based measure has been introduced by Ton. In this study, a model is proposed that is able to estimate the efficiency when a number of outputs of decision making units are undesirable, inputs are fixed and some of outputs and inputs are negative. So that, level of undesirable output is reduced at the constant level of inputs in the evaluation unit and by conserving the efficiency.

  20. Multi-Input Convolutional Neural Network for Flower Grading

    Directory of Open Access Journals (Sweden)

    Yu Sun

    2017-01-01

    Full Text Available Flower grading is a significant task because it is extremely convenient for managing the flowers in greenhouse and market. With the development of computer vision, flower grading has become an interdisciplinary focus in both botany and computer vision. A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. Multi-input CNN achieves a satisfactory accuracy of 89.6% on the BjfuGloxinia after data augmentation. Compared with a single-input CNN, the accuracy of multi-input CNN is increased by 5% on average, demonstrating that multi-input convolutional neural network is a promising model for flower grading. Although data augmentation contributes to the model, the accuracy is still limited by lack of samples diversity. Majority of misclassification is derived from the medium class. The image processing based bud detection is useful for reducing the misclassification, increasing the accuracy of flower grading to approximately 93.9%.

  1. 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

  2. Modelling the soil microclimate: does the spatial or temporal resolution of input parameters matter?

    Directory of Open Access Journals (Sweden)

    Anna Carter

    2016-01-01

    Full Text Available The urgency of predicting future impacts of environmental change on vulnerable populations is advancing the development of spatially explicit habitat models. Continental-scale climate and microclimate layers are now widely available. However, most terrestrial organisms exist within microclimate spaces that are very small, relative to the spatial resolution of those layers. We examined the effects of multi-resolution, multi-extent topographic and climate inputs on the accuracy of hourly soil temperature predictions for a small island generated at a very high spatial resolution (<1 m2 using the mechanistic microclimate model in NicheMapR. Achieving an accuracy comparable to lower-resolution, continental-scale microclimate layers (within about 2–3°C of observed values required the use of daily weather data as well as high resolution topographic layers (elevation, slope, aspect, horizon angles, while inclusion of site-specific soil properties did not markedly improve predictions. Our results suggest that large-extent microclimate layers may not provide accurate estimates of microclimate conditions when the spatial extent of a habitat or other area of interest is similar to or smaller than the spatial resolution of the layers themselves. Thus, effort in sourcing model inputs should be focused on obtaining high resolution terrain data, e.g., via LiDAR or photogrammetry, and local weather information rather than in situ sampling of microclimate characteristics.

  3. Impact of magnetic saturation on the input-output linearising tracking control of an induction motor

    DEFF Research Database (Denmark)

    Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

    2004-01-01

    This paper deals with the tracking control design of an induction motor, based on input-output linearization with magnetic saturation included. Magnetic saturation is represented by the nonlinear magnetizing curve of the iron core and is used in the control design, the observer of state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances of the drive. It is based on the mixed ”stator current - rotor flux linkage” induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with the included saturation behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

  4. Analytical model for advective-dispersive transport involving flexible boundary inputs, initial distributions and zero-order productions

    Science.gov (United States)

    Chen, Jui-Sheng; Li, Loretta Y.; Lai, Keng-Hsin; Liang, Ching-Ping

    2017-11-01

    A novel solution method is presented which leads to an analytical model for the advective-dispersive transport in a semi-infinite domain involving a wide spectrum of boundary inputs, initial distributions, and zero-order productions. The novel solution method applies the Laplace transform in combination with the generalized integral transform technique (GITT) to obtain the generalized analytical solution. Based on this generalized analytical expression, we derive a comprehensive set of special-case solutions for some time-dependent boundary distributions and zero-order productions, described by the Dirac delta, constant, Heaviside, exponentially-decaying, or periodically sinusoidal functions as well as some position-dependent initial conditions and zero-order productions specified by the Dirac delta, constant, Heaviside, or exponentially-decaying functions. The developed solutions are tested against an analytical solution from the literature. The excellent agreement between the analytical solutions confirms that the new model can serve as an effective tool for investigating transport behaviors under different scenarios. Several examples of applications, are given to explore transport behaviors which are rarely noted in the literature. The results show that the concentration waves resulting from the periodically sinusoidal input are sensitive to dispersion coefficient. The implication of this new finding is that a tracer test with a periodic input may provide additional information when for identifying the dispersion coefficients. Moreover, the solution strategy presented in this study can be extended to derive analytical models for handling more complicated problems of solute transport in multi-dimensional media subjected to sequential decay chain reactions, for which analytical solutions are not currently available.

  5. Modelling the long-term consequences of a hypothetical dispersal of radioactivity in an urban area including remediation alternatives

    International Nuclear Information System (INIS)

    Thiessen, K.M.; Andersson, K.G.; Batandjieva, B.; Cheng, J.-J.; Hwang, W.T.; Kaiser, J.C.; Kamboj, S.; Steiner, M.; Tomas, J.; Trifunovic, D.; Yu, C.

    2009-01-01

    The Urban Remediation Working Group of the International Atomic Energy Agency's EMRAS (Environmental Modelling for Radiation Safety) program was organized to address issues of remediation assessment modelling for urban areas contaminated with dispersed radionuclides. The present paper describes the second of two modelling exercises. This exercise was based on a hypothetical dispersal of radioactivity in an urban area from a radiological dispersal device, with reference surface contamination at selected sites used as the primary input information. Modelling endpoints for the exercise included radionuclide concentrations and external dose rates at specified locations, contributions to the dose rates from individual surfaces, and annual and cumulative external doses to specified reference individuals. Model predictions were performed for a 'no action' situation (with no remedial measures) and for selected countermeasures. The exercise provided an opportunity for comparison of three modelling approaches, as well as a comparison of the predicted effectiveness of various countermeasures in terms of their short-term and long-term effects on predicted doses to humans.

  6. Modeling and sliding mode predictive control of the ultra-supercritical boiler-turbine system with uncertainties and input constraints.

    Science.gov (United States)

    Tian, Zhen; Yuan, Jingqi; Zhang, Xiang; Kong, Lei; Wang, Jingcheng

    2018-05-01

    The coordinated control system (CCS) serves as an important role in load regulation, efficiency optimization and pollutant reduction for coal-fired power plants. The CCS faces with tough challenges, such as the wide-range load variation, various uncertainties and constraints. This paper aims to improve the load tacking ability and robustness for boiler-turbine units under wide-range operation. To capture the key dynamics of the ultra-supercritical boiler-turbine system, a nonlinear control-oriented model is developed based on mechanism analysis and model reduction techniques, which is validated with the history operation data of a real 1000 MW unit. To simultaneously address the issues of uncertainties and input constraints, a discrete-time sliding mode predictive controller (SMPC) is designed with the dual-mode control law. Moreover, the input-to-state stability and robustness of the closed-loop system are proved. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves good tracking performance, disturbance rejection ability and compatibility to input constraints. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  7. MOS modeling hierarchy including radiation effects

    International Nuclear Information System (INIS)

    Alexander, D.R.; Turfler, R.M.

    1975-01-01

    A hierarchy of modeling procedures has been developed for MOS transistors, circuit blocks, and integrated circuits which include the effects of total dose radiation and photocurrent response. The models were developed for use with the SCEPTRE circuit analysis program, but the techniques are suitable for other modern computer aided analysis programs. The modeling hierarchy permits the designer or analyst to select the level of modeling complexity consistent with circuit size, parametric information, and accuracy requirements. Improvements have been made in the implementation of important second order effects in the transistor MOS model, in the definition of MOS building block models, and in the development of composite terminal models for MOS integrated circuits

  8. Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

    Science.gov (United States)

    Tsaur, Ruey-Chyn

    2015-02-01

    In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

  9. Six axis force feedback input device

    Science.gov (United States)

    Ohm, Timothy (Inventor)

    1998-01-01

    The present invention is a low friction, low inertia, six-axis force feedback input device comprising an arm with double-jointed, tendon-driven revolute joints, a decoupled tendon-driven wrist, and a base with encoders and motors. The input device functions as a master robot manipulator of a microsurgical teleoperated robot system including a slave robot manipulator coupled to an amplifier chassis, which is coupled to a control chassis, which is coupled to a workstation with a graphical user interface. The amplifier chassis is coupled to the motors of the master robot manipulator and the control chassis is coupled to the encoders of the master robot manipulator. A force feedback can be applied to the input device and can be generated from the slave robot to enable a user to operate the slave robot via the input device without physically viewing the slave robot. Also, the force feedback can be generated from the workstation to represent fictitious forces to constrain the input device's control of the slave robot to be within imaginary predetermined boundaries.

  10. Plasticity of the cis-regulatory input function of a gene.

    Directory of Open Access Journals (Sweden)

    Avraham E Mayo

    2006-04-01

    Full Text Available The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

  11. Student preparation and the power of visual input in veterinary surgical education

    DEFF Research Database (Denmark)

    Langebæk, Rikke; Nielsen, Søren Saxmose; Koch, Bodil Cathrine

    2016-01-01

    In recent years, veterinary educational institutions have implemented alternative teaching methods, including video demonstrations of surgical procedures. However, the power of the dynamic visual input from videos in relation to recollection of a surgical procedure has never been evaluated. The aim...... a basic surgical skills course, 112 fourth-year veterinary students participated in the study by completing a questionnaire regarding method of recollection, influence of individual types of educational input, and homework preparation. Furthermore, we observed students performing an orchiectomy...... in a terminal pig lab. Preparation for the pig lab consisted of homework (textbook, online material, including videos), lecture, cadaver lab, and toy animal models in a skills lab. In the instructional video, a detail was used that was not described elsewhere. Results show that 60% of the students used a visual...

  12. Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

    Directory of Open Access Journals (Sweden)

    T. Youssef

    2013-01-01

    Full Text Available This paper presents an unknown input Proportional Multiple-Integral Observer (PIO for synchronization of chaotic systems based on Takagi-Sugeno (TS fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.

  13. Data Envelopment Analysis with Uncertain Inputs and Outputs

    Directory of Open Access Journals (Sweden)

    Meilin Wen

    2014-01-01

    Full Text Available Data envelopment analysis (DEA, as a useful management and decision tool, has been widely used since it was first invented by Charnes et al. in 1978. On the one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. This paper will consider DEA in uncertain environment, thus producing a new model based on uncertain measure. Due to the complexity of the new uncertain DEA model, an equivalent deterministic model is presented. Finally, a numerical example is presented to illustrate the effectiveness of the uncertain DEA model.

  14. A new approach to modeling temperature-related mortality: Non-linear autoregressive models with exogenous input.

    Science.gov (United States)

    Lee, Cameron C; Sheridan, Scott C

    2018-07-01

    Temperature-mortality relationships are nonlinear, time-lagged, and can vary depending on the time of year and geographic location, all of which limits the applicability of simple regression models in describing these associations. This research demonstrates the utility of an alternative method for modeling such complex relationships that has gained recent traction in other environmental fields: nonlinear autoregressive models with exogenous input (NARX models). All-cause mortality data and multiple temperature-based data sets were gathered from 41 different US cities, for the period 1975-2010, and subjected to ensemble NARX modeling. Models generally performed better in larger cities and during the winter season. Across the US, median absolute percentage errors were 10% (ranging from 4% to 15% in various cities), the average improvement in the r-squared over that of a simple persistence model was 17% (6-24%), and the hit rate for modeling spike days in mortality (>80th percentile) was 54% (34-71%). Mortality responded acutely to hot summer days, peaking at 0-2 days of lag before dropping precipitously, and there was an extended mortality response to cold winter days, peaking at 2-4 days of lag and dropping slowly and continuing for multiple weeks. Spring and autumn showed both of the aforementioned temperature-mortality relationships, but generally to a lesser magnitude than what was seen in summer or winter. When compared to distributed lag nonlinear models, NARX model output was nearly identical. These results highlight the applicability of NARX models for use in modeling complex and time-dependent relationships for various applications in epidemiology and environmental sciences. Copyright © 2018 Elsevier Inc. All rights reserved.

  15. Solar Load Inputs for USARIEM Thermal Strain Models and the Solar Radiation-Sensitive Components of the WBGT Index

    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...

  16. Improved Stabilization Conditions for Nonlinear Systems with Input and State Delays via T-S Fuzzy Model

    Directory of Open Access Journals (Sweden)

    Chang Che

    2018-01-01

    Full Text Available This paper focuses on the problem of nonlinear systems with input and state delays. The considered nonlinear systems are represented by Takagi-Sugeno (T-S fuzzy model. A new state feedback control approach is introduced for T-S fuzzy systems with input delay and state delays. A new Lyapunov-Krasovskii functional is employed to derive less conservative stability conditions by incorporating a recently developed Wirtinger-based integral inequality. Based on the Lyapunov stability criterion, a series of linear matrix inequalities (LMIs are obtained by using the slack variables and integral inequality, which guarantees the asymptotic stability of the closed-loop system. Several numerical examples are given to show the advantages of the proposed results.

  17. Phonology: An Emergent Consequence of Memory Constraints and Sensory Input.

    Science.gov (United States)

    Lacerda, Francisco

    2003-01-01

    Presents a theoretical model that attempts to account for the early stages of language acquisition in terms of interaction between biological constraints and input characteristics. Notes that the model uses the implications of stochastic representations of the sensory input in a volatile and limited memory. Argues that phonological structure is a…

  18. Input-output model of regional environmental and economic impacts of nuclear power plants

    International Nuclear Information System (INIS)

    Johnson, M.H.; Bennett, J.T.

    1979-01-01

    The costs of delayed licensing of nuclear power plants calls for a more-comprehensive method of quantifying the economic and environmental impacts on a region. A traditional input-output (I-O) analysis approach is extended to assess the effects of changes in output, income, employment, pollution, water consumption, and the costs and revenues of local government disaggregated among 23 industry sectors during the construction and operating phases. Unlike earlier studies, this model uses nonlinear environmental interactions and specifies environmental feedbacks to the economic sector. 20 references

  19. The Effect of Input-Based Instruction Type on the Acquisition of Spanish Accusative Clitics

    Science.gov (United States)

    White, Justin

    2015-01-01

    The purpose of this paper is to compare structured input (SI) with other input-based instructional treatments. The input-based instructional types include: input flood (IF), text enhancement (TE), SI activities, and focused input (FI; SI without implicit negative feedback). Participants included 145 adult learners enrolled in an intermediate…

  20. ATEFlap aerodynamic model, a dynamic stall model including the effects of trailing edge flap deflection

    Energy Technology Data Exchange (ETDEWEB)

    Bergami, L.; Gaunaa, M.

    2012-02-15

    The report presents the ATEFlap aerodynamic model, which computes the unsteady lift, drag and moment on a 2D airfoil section equipped with Adaptive Trailing Edge Flap. The model captures the unsteady response related to the effects of the vorticity shed into the wake, and the dynamics of flow separation a thin-airfoil potential flow model is merged with a dynamic stall model of the Beddoes-Leishmann type. The inputs required by the model are steady data for lift, drag, and moment coefficients as function of angle of attack and flap deflection. Further steady data used by the Beddoes- Leishmann dynamic stall model are computed in an external preprocessor application, which gives the user the possibility to verify, and eventually correct, the steady data passed to the aerodynamic model. The ATEFlap aerodynamic model is integrated in the aeroelastic simulation tool HAWC2, thus al- lowing to simulate the response of a wind turbine with trailing edge flaps on the rotor. The algorithms used by the preprocessor, and by aerodynamic model are presented, and modifications to previous implementations of the aerodynamic model are briefly discussed. The performance and the validity of the model are verified by comparing the dynamic response computed by the ATEFlap with solutions from CFD simulations. (Author)

  1. Canonical multi-valued input Reed-Muller trees and forms

    Science.gov (United States)

    Perkowski, M. A.; Johnson, P. D.

    1991-01-01

    There is recently an increased interest in logic synthesis using EXOR gates. The paper introduces the fundamental concept of Orthogonal Expansion, which generalizes the ring form of the Shannon expansion to the logic with multiple-valued (mv) inputs. Based on this concept we are able to define a family of canonical tree circuits. Such circuits can be considered for binary and multiple-valued input cases. They can be multi-level (trees and DAG's) or flattened to two-level AND-EXOR circuits. Input decoders similar to those used in Sum of Products (SOP) PLA's are used in realizations of multiple-valued input functions. In the case of the binary logic the family of flattened AND-EXOR circuits includes several forms discussed by Davio and Green. For the case of the logic with multiple-valued inputs, the family of the flattened mv AND-EXOR circuits includes three expansions known from literature and two new expansions.

  2. A generalized model for optimal transport of images including dissipation and density modulation

    KAUST Repository

    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.

  3. Heat input control in coke ovens battery using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, R.; Kannan, C.; Sistla, S.; Kumar, D. [Tata Steel, Jamshedpur (India)

    2005-07-01

    Controlled heating is very essential for producing coke with certain desired properties. Controlled heating involves controlling the heat input into the battery dynamically depending on the various process parameters like current battery temperature, the set point of battery temperature, moisture in coal, ambient temperature, coal fineness, cake breakage etc. An artificial intelligence (AI) based heat input control has been developed in which currently some of the above mentioned process parameters are considered and used for calculating the pause time which is applied between reversal during the heating process. The AI based model currently considers 3 input variables, temperature deviation history, current deviation of the battery temperature from the target temperature and the actual heat input into the battery. Work is in progress to control the standard deviation of coke end temperature using this model. The new system which has been developed in-house has replaced Hoogovens supplied model. 7 figs.

  4. PERSPECTIVES ON A DOE CONSEQUENCE INPUTS FOR ACCIDENT ANALYSIS APPLICATIONS

    International Nuclear Information System (INIS)

    O'Kula, K.R.; Thoman, D.C.; Lowrie, J.; Keller, A.

    2008-01-01

    Department of Energy (DOE) accident analysis for establishing the required control sets for nuclear facility safety applies a series of simplifying, reasonably conservative assumptions regarding inputs and methodologies for quantifying dose consequences. Most of the analytical practices are conservative, have a technical basis, and are based on regulatory precedent. However, others are judgmental and based on older understanding of phenomenology. The latter type of practices can be found in modeling hypothetical releases into the atmosphere and the subsequent exposure. Often the judgments applied are not based on current technical understanding but on work that has been superseded. The objective of this paper is to review the technical basis for the major inputs and assumptions in the quantification of consequence estimates supporting DOE accident analysis, and to identify those that could be reassessed in light of current understanding of atmospheric dispersion and radiological exposure. Inputs and assumptions of interest include: Meteorological data basis; Breathing rate; and Inhalation dose conversion factor. A simple dose calculation is provided to show the relative difference achieved by improving the technical bases

  5. Input Manipulation, Enhancement and Processing: Theoretical Views and Empirical Research

    Science.gov (United States)

    Benati, Alessandro

    2016-01-01

    Researchers in the field of instructed second language acquisition have been examining the issue of how learners interact with input by conducting research measuring particular kinds of instructional interventions (input-oriented and meaning-based). These interventions include such things as input flood, textual enhancement and processing…

  6. Video-based Chinese Input System via Fingertip Tracking

    Directory of Open Access Journals (Sweden)

    Chih-Chang Yu

    2012-10-01

    Full Text Available In this paper, we propose a system to detect and track fingertips online and recognize Mandarin Phonetic Symbol (MPS for user-friendly Chinese input purposes. Using fingertips and cameras to replace pens and touch panels as input devices could reduce the cost and improve the ease-of-use and comfort of computer-human interface. In the proposed framework, particle filters with enhanced appearance models are applied for robust fingertip tracking. Afterwards, MPS combination recognition is performed on the tracked fingertip trajectories using Hidden Markov Models. In the proposed system, the fingertips of the users could be robustly tracked. Also, the challenges of entering, leaving and virtual strokes caused by video-based fingertip input can be overcome. Experimental results have shown the feasibility and effectiveness of the proposed work.

  7. 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.

  8. A Markovian model of evolving world input-output network.

    Science.gov (United States)

    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.

  9. Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

    Science.gov (United States)

    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.

  10. Dynamics of a Stage Structured Pest Control Model in a Polluted Environment with Pulse Pollution Input

    OpenAIRE

    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 ...

  11. Mars 2.2 code manual: input requirements

    International Nuclear Information System (INIS)

    Chung, Bub Dong; Lee, Won Jae; Jeong, Jae Jun; Lee, Young Jin; Hwang, Moon Kyu; Kim, Kyung Doo; Lee, Seung Wook; Bae, Sung Won

    2003-07-01

    Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This input manual provides a complete list of input required to run MARS. The manual is divided largely into two parts, namely, the one-dimensional part and the multi-dimensional part. The inputs for auxiliary parts such as minor edit requests and graph formatting inputs are shared by the two parts and as such mixed input is possible. The overall structure of the input is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS. MARS development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible

  12. MARS code manual volume II: input requirements

    International Nuclear Information System (INIS)

    Chung, Bub Dong; Kim, Kyung Doo; Bae, Sung Won; Jeong, Jae Jun; Lee, Seung Wook; Hwang, Moon Kyu

    2010-02-01

    Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-Of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This input manual provides a complete list of input required to run MARS. The manual is divided largely into two parts, namely, the one-dimensional part and the multi-dimensional part. The inputs for auxiliary parts such as minor edit requests and graph formatting inputs are shared by the two parts and as such mixed input is possible. The overall structure of the input is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS3.1. MARS3.1 development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible

  13. The input and output management of solid waste using DEA models: A case study at Jengka, Pahang

    Science.gov (United States)

    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.

  14. 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)

  15. Outsourcing, public Input provision and policy cooperation

    OpenAIRE

    Aronsson, Thomas; Koskela, Erkki

    2009-01-01

    This paper concerns public input provision as an instrument for redistribution under international outsourcing by using a model-economy comprising two countries, North and South, where firms in the North may outsource part of their low-skilled labor intensive production to the South. We consider two interrelated issues: (i) the incentives for each country to modify the provision of public input goods in response to international outsourcing, and (ii) whether international outsourcing justifie...

  16. A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors

    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.

  17. 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

  18. Numerical Modeling of the Effects of Nutrient-rich Coastal-water Input on the Phytoplankton in the Gulf of California

    Science.gov (United States)

    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.

  19. Modelling of uranium inputs and its fate in soil; Modellierung von Uraneintraegen aus Duengern und ihr Verbleib im Boden

    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.

  20. Simulation model structure numerically robust to changes in magnitude and combination of input and output variables

    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...... 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...... 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....

  1. A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

    Science.gov (United States)

    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.

  2. Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

    Science.gov (United States)

    Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

    2016-01-01

    Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly

  3. Development of Earthquake Ground Motion Input for Preclosure Seismic Design and Postclosure Performance Assessment of a Geologic Repository at Yucca Mountain, NV

    International Nuclear Information System (INIS)

    I. Wong

    2004-01-01

    This report describes a site-response model and its implementation for developing earthquake ground motion input for preclosure seismic design and postclosure assessment of the proposed geologic repository at Yucca Mountain, Nevada. The model implements a random-vibration theory (RVT), one-dimensional (1D) equivalent-linear approach to calculate site response effects on ground motions. The model provides results in terms of spectral acceleration including peak ground acceleration, peak ground velocity, and dynamically-induced strains as a function of depth. In addition to documenting and validating this model for use in the Yucca Mountain Project, this report also describes the development of model inputs, implementation of the model, its results, and the development of earthquake time history inputs based on the model results. The purpose of the site-response ground motion model is to incorporate the effects on earthquake ground motions of (1) the approximately 300 m of rock above the emplacement levels beneath Yucca Mountain and (2) soil and rock beneath the site of the Surface Facilities Area. A previously performed probabilistic seismic hazard analysis (PSHA) (CRWMS M and O 1998a [DIRS 103731]) estimated ground motions at a reference rock outcrop for the Yucca Mountain site (Point A), but those results do not include these site response effects. Thus, the additional step of applying the site-response ground motion model is required to develop ground motion inputs that are used for preclosure and postclosure purposes

  4. Development of Earthquake Ground Motion Input for Preclosure Seismic Design and Postclosure Performance Assessment of a Geologic Repository at Yucca Mountain, NV

    Energy Technology Data Exchange (ETDEWEB)

    I. Wong

    2004-11-05

    This report describes a site-response model and its implementation for developing earthquake ground motion input for preclosure seismic design and postclosure assessment of the proposed geologic repository at Yucca Mountain, Nevada. The model implements a random-vibration theory (RVT), one-dimensional (1D) equivalent-linear approach to calculate site response effects on ground motions. The model provides results in terms of spectral acceleration including peak ground acceleration, peak ground velocity, and dynamically-induced strains as a function of depth. In addition to documenting and validating this model for use in the Yucca Mountain Project, this report also describes the development of model inputs, implementation of the model, its results, and the development of earthquake time history inputs based on the model results. The purpose of the site-response ground motion model is to incorporate the effects on earthquake ground motions of (1) the approximately 300 m of rock above the emplacement levels beneath Yucca Mountain and (2) soil and rock beneath the site of the Surface Facilities Area. A previously performed probabilistic seismic hazard analysis (PSHA) (CRWMS M&O 1998a [DIRS 103731]) estimated ground motions at a reference rock outcrop for the Yucca Mountain site (Point A), but those results do not include these site response effects. Thus, the additional step of applying the site-response ground motion model is required to develop ground motion inputs that are used for preclosure and postclosure purposes.

  5. Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

    Science.gov (United States)

    Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish

    2018-06-01

    Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.

  6. PCC/SRC, PCC and SRC Calculation from Multivariate Input for Sensitivity Analysis

    International Nuclear Information System (INIS)

    Iman, R.L.; Shortencarier, M.J.; Johnson, J.D.

    1995-01-01

    1 - Description of program or function: PCC/SRC is designed for use in conjunction with sensitivity analyses of complex computer models. PCC/SRC calculates the partial correlation coefficients (PCC) and the standardized regression coefficients (SRC) from the multivariate input to, and output from, a computer model. 2 - Method of solution: PCC/SRC calculates the coefficients on either the original observations or on the ranks of the original observations. These coefficients provide alternative measures of the relative contribution (importance) of each of the various input variables to the observed variations in output. Relationships between the coefficients and differences in their interpretations are identified. If the computer model output has an associated time or spatial history, PCC/SRC will generate a graph of the coefficients over time or space for each input-variable, output- variable combination of interest, indicating the importance of each input value over time or space. 3 - Restrictions on the complexity of the problem - Maxima of: 100 observations, 100 different time steps or intervals between successive dependent variable readings, 50 independent variables (model input), 20 dependent variables (model output). 10 ordered triples specifying intervals between dependent variable readings

  7. Noise and crosstalk in two quorum-sensing inputs of Vibrio fischeri

    Directory of Open Access Journals (Sweden)

    Weiss Joel T

    2011-09-01

    Full Text Available Abstract Background One of the puzzles in bacterial quorum sensing is understanding how an organism integrates the information gained from multiple input signals. The marine bacterium Vibrio fischeri regulates its bioluminescence through a quorum sensing mechanism that receives input from three pheromone signals, including two acyl homoserine lactone (HSL signals. While the role of the 3-oxo-C6 homoserine lactone (3OC6HSL signal in activating the lux genes has been extensively studied and modeled, the role of the C8 homoserine lactone (C8HSL is less obvious, as it can either activate luminescence or block its activation. It remains unclear how crosstalk between C8HSL and 3OC6HSL affects the information that the bacterium obtains through quorum sensing. Results We have used microfluidic methods to measure the response of individual V.fischeri cells to combinations of C8HSL and 3OC6HSL. By measuring the fluorescence of individual V.fischeri cells containing a chromosomal gfp-reporter for the lux genes, we study how combinations of exogenous HSLs affect both the population average and the cell-to-cell variability of lux activation levels. At the level of a population average, the crosstalk between the C8HSL and 3OC6HSL inputs is well-described by a competitive inhibition model. At the level of individual cells, the heterogeneity in the lux response depends only on the average degree of activation, so that the noise in the output is not reduced by the presence of the second HSL signal. Overall we find that the mutual information between the signal inputs and the lux output is less than one bit. A nonlinear correlation between fluorescence and bioluminescence outputs from lux leads to different noise properties for these reporters. Conclusions The lux genes in V.fischeri do not appear to distinguish between the two HSL inputs, and even with two signal inputs the regulation of lux is extremely noisy. Hence the role of crosstalk from the C8HSL input

  8. TART input manual

    International Nuclear Information System (INIS)

    Kimlinger, J.R.; Plechaty, E.F.

    1982-01-01

    The TART code is a Monte Carlo neutron/photon transport code that is only on the CRAY computer. All the input cards for the TART code are listed, and definitions for all input parameters are given. The execution and limitations of the code are described, and input for two sample problems are given

  9. Effects of allochthonous inputs in the control of infectious disease of prey

    International Nuclear Information System (INIS)

    Sahoo, Banshidhar; Poria, Swarup

    2015-01-01

    Highlights: •Infected predator–prey model with allochthonous inputs is proposed. •Stability and persistence conditions are derived. •Bifurcation is determined with respect to allochthonous inputs. •Results show that system can not be disease free without allochthonous inputs. •Hopf and its continuation bifurcation is analysed numerically. -- Abstract: Allochthonous inputs are important sources of productivity in many food webs and their influences on food chain model demand further investigations. In this paper, assuming the existence of allochthonous inputs for intermediate predator, a food chain model is formulated with disease in the prey. The stability and persistence conditions of the equilibrium points are determined. Extinction criterion for infected prey population is obtained. It is shown that suitable amount of allochthonous inputs to intermediate predator can control infectious disease of prey population, provided initial intermediate predator population is above a critical value. This critical intermediate population size increases monotonically with the increase of infection rate. It is also shown that control of infectious disease of prey is possible in some cases of seasonally varying contact rate. Dynamical behaviours of the model are investigated numerically through one and two parameter bifurcation analysis using MATCONT 2.5.1 package. The occurrence of Hopf and its continuation curves are noted with the variation of infection rate and allochthonous food availability. The continuation curves of limit point cycle and Neimark Sacker bifurcation are drawn by varying the rate of infection and allochthonous inputs. This study introduces a novel natural non-toxic method for controlling infectious disease of prey in a food chain model

  10. History of nutrient inputs to the northeastern United States, 1930-2000

    Science.gov (United States)

    Hale, Rebecca L.; Hoover, Joseph H.; Wollheim, Wilfred M.; Vörösmarty, Charles J.

    2013-04-01

    Humans have dramatically altered nutrient cycles at local to global scales. We examined changes in anthropogenic nutrient inputs to the northeastern United States (NE) from 1930 to 2000. We created a comprehensive time series of anthropogenic N and P inputs to 437 counties in the NE at 5 year intervals. Inputs included atmospheric N deposition, biological N2 fixation, fertilizer, detergent P, livestock feed, and human food. Exports included exports of feed and food and volatilization of ammonia. N inputs to the NE increased throughout the study period, primarily due to increases in atmospheric deposition and fertilizer. P inputs increased until 1970 and then declined due to decreased fertilizer and detergent inputs. Livestock consistently consumed the majority of nutrient inputs over time and space. The area of crop agriculture declined during the study period but consumed more nutrients as fertilizer. We found that stoichiometry (N:P) of inputs and absolute amounts of N matched nutritional needs (livestock, humans, crops) when atmospheric components (N deposition, N2 fixation) were not included. Differences between N and P led to major changes in N:P stoichiometry over time, consistent with global trends. N:P decreased from 1930 to 1970 due to increased inputs of P, and increased from 1970 to 2000 due to increased N deposition and fertilizer and decreases in P fertilizer and detergent use. We found that nutrient use is a dynamic product of social, economic, political, and environmental interactions. Therefore, future nutrient management must take into account these factors to design successful and effective nutrient reduction measures.

  11. 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.

  12. Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

    Energy Technology Data Exchange (ETDEWEB)

    Lamboni, Matieyendou [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Monod, Herve, E-mail: herve.monod@jouy.inra.f [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Makowski, David [INRA, UMR Agronomie INRA/AgroParisTech (UMR 211), BP 01, F78850 Thiverval-Grignon (France)

    2011-04-15

    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.

  13. BLT-EC (Breach, Leach and Transport-Equilibrium Chemistry) data input guide. A computer model for simulating release and coupled geochemical transport of contaminants from a subsurface disposal facility

    International Nuclear Information System (INIS)

    MacKinnon, R.J.; Sullivan, T.M.; Kinsey, R.R.

    1997-05-01

    The BLT-EC computer code has been developed, implemented, and tested. BLT-EC is a two-dimensional finite element computer code capable of simulating the time-dependent release and reactive transport of aqueous phase species in a subsurface soil system. BLT-EC contains models to simulate the processes (container degradation, waste-form performance, transport, chemical reactions, and radioactive production and decay) most relevant to estimating the release and transport of contaminants from a subsurface disposal system. Water flow is provided through tabular input or auxiliary files. Container degradation considers localized failure due to pitting corrosion and general failure due to uniform surface degradation processes. Waste-form performance considers release to be limited by one of four mechanisms: rinse with partitioning, diffusion, uniform surface degradation, and solubility. Transport considers the processes of advection, dispersion, diffusion, chemical reaction, radioactive production and decay, and sources (waste form releases). Chemical reactions accounted for include complexation, sorption, dissolution-precipitation, oxidation-reduction, and ion exchange. Radioactive production and decay in the waste form is simulated. To improve the usefulness of BLT-EC, a pre-processor, ECIN, which assists in the creation of chemistry input files, and a post-processor, BLTPLOT, which provides a visual display of the data have been developed. BLT-EC also includes an extensive database of thermodynamic data that is also accessible to ECIN. This document reviews the models implemented in BLT-EC and serves as a guide to creating input files and applying BLT-EC

  14. Physical-mathematical model for cybernetic description of the human organs with trace element concentrations as input variables

    International Nuclear Information System (INIS)

    Mihai, Maria; Popescu, I.V.

    2003-01-01

    In this paper we report a physical-mathematical model for studying the organs and humans fluids by cybernetic principle. The input variables represent the trace elements which are determined by atomic and nuclear methods of elemental analysis. We have determined the health limits between which the organs might function. (authors)

  15. 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.

  16. The effect of adjusting model inputs to achieve mass balance on time-dynamic simulations in a food-web model of Lake Huron

    Science.gov (United States)

    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

  17. High organic inputs explain shallow and deep SOC storage in a long-term agroforestry system - combining experimental and modeling approaches

    Science.gov (United States)

    Cardinael, Rémi; Guenet, Bertrand; Chevallier, Tiphaine; Dupraz, Christian; Cozzi, Thomas; Chenu, Claire

    2018-01-01

    Agroforestry is an increasingly popular farming system enabling agricultural diversification and providing several ecosystem services. In agroforestry systems, soil organic carbon (SOC) stocks are generally increased, but it is difficult to disentangle the different factors responsible for this storage. Organic carbon (OC) inputs to the soil may be larger, but SOC decomposition rates may be modified owing to microclimate, physical protection, or priming effect from roots, especially at depth. We used an 18-year-old silvoarable system associating hybrid walnut trees (Juglans regia × nigra) and durum wheat (Triticum turgidum L. subsp. durum) and an adjacent agricultural control plot to quantify all OC inputs to the soil - leaf litter, tree fine root senescence, crop residues, and tree row herbaceous vegetation - and measured SOC stocks down to 2 m of depth at varying distances from the trees. We then proposed a model that simulates SOC dynamics in agroforestry accounting for both the whole soil profile and the lateral spatial heterogeneity. The model was calibrated to the control plot only. Measured OC inputs to soil were increased by about 40 % (+ 1.11 t C ha-1 yr-1) down to 2 m of depth in the agroforestry plot compared to the control, resulting in an additional SOC stock of 6.3 t C ha-1 down to 1 m of depth. However, most of the SOC storage occurred in the first 30 cm of soil and in the tree rows. The model was strongly validated, properly describing the measured SOC stocks and distribution with depth in agroforestry tree rows and alleys. It showed that the increased inputs of fresh biomass to soil explained the observed additional SOC storage in the agroforestry plot. Moreover, only a priming effect variant of the model was able to capture the depth distribution of SOC stocks, suggesting the priming effect as a possible mechanism driving deep SOC dynamics. This result questions the potential of soils to store large amounts of carbon, especially at depth. Deep

  18. Pilot monitoring program: geologic input for the hillslope component (includes a discussion of Caspar Creek geology and geomorphology)

    Science.gov (United States)

    T. E. Spittler

    1995-01-01

    The California Department of Conservation, Division of Mines and Geology (DMG) is submitting this report and accompanying maps to the California Department of Forestry and Fire Protection (CDF) to fulfill Interagency Agreement number 8CA38400, Pilot Monitoring Program -- Geologic Input for the Hillslope Component. Under this agreement, DMG has assisted CDF in the...

  19. Quantum Mechanical Noise in a Michelson Interferometer with Nonclassical Inputs: Nonperturbative Treatment

    Science.gov (United States)

    King, Sun-Kun

    1996-01-01

    The variances of the quantum-mechanical noise in a two-input-port Michelson interferometer within the framework of the Loudon-Ni model were solved exactly in two general cases: (1) one coherent state input and one squeezed state input, and (2) two photon number states inputs. Low intensity limit, exponential decaying signal and the noise due to mixing were discussed briefly.

  20. Stabilization of (state, input)-disturbed CSTRs through the port-Hamiltonian systems approach

    OpenAIRE

    Lu, Yafei; Fang, Zhou; Gao, Chuanhou

    2017-01-01

    It is a universal phenomenon that the state and input of the continuous stirred tank reactor (CSTR) systems are both disturbed. This paper proposes a (state, input)-disturbed port-Hamiltonian framework that can be used to model and further designs a stochastic passivity based controller to asymptotically stabilize in probability the (state, input)-disturbed CSTR (sidCSTR) systems. The opposite entropy function and the availability function are selected as the Hamiltonian for the model and con...

  1. Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

    Science.gov (United States)

    Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

    2016-02-01

    The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.

  2. 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.

  3. 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...... (CMEs), but in order to predict the caused effects, we need to be able to model their propagation from their origin in the solar corona to the point of interest, e.g., Earth. Many such models exist, but to understand the models in detail we must understand the primary input parameters. Here we...... 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...

  4. Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions.

    Science.gov (United States)

    Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli

    2017-10-01

    Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1  yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.

  5. A Practical pedestrian approach to parsimonious regression with inaccurate inputs

    Directory of Open Access Journals (Sweden)

    Seppo Karrila

    2014-04-01

    Full Text Available A measurement result often dictates an interval containing the correct value. Interval data is also created by roundoff, truncation, and binning. We focus on such common interval uncertainty in data. Inaccuracy in model inputs is typically ignored on model fitting. We provide a practical approach for regression with inaccurate data: the mathematics is easy, and the linear programming formulations simple to use even in a spreadsheet. This self-contained elementary presentation introduces interval linear systems and requires only basic knowledge of algebra. Feature selection is automatic; but can be controlled to find only a few most relevant inputs; and joint feature selection is enabled for multiple modeled outputs. With more features than cases, a novel connection to compressed sensing emerges: robustness against interval errors-in-variables implies model parsimony, and the input inaccuracies determine the regularization term. A small numerical example highlights counterintuitive results and a dramatic difference to total least squares.

  6. WORM: A general-purpose input deck specification language

    International Nuclear Information System (INIS)

    Jones, T.

    1999-01-01

    Using computer codes to perform criticality safety calculations has become common practice in the industry. The vast majority of these codes use simple text-based input decks to represent the geometry, materials, and other parameters that describe the problem. However, the data specified in input files are usually processed results themselves. For example, input decks tend to require the geometry specification in linear dimensions and materials in atom or weight fractions, while the parameter of interest might be mass or concentration. The calculations needed to convert from the item of interest to the required parameter in the input deck are usually performed separately and then incorporated into the input deck. This process of calculating, editing, and renaming files to perform a simple parameter study is tedious at best. In addition, most computer codes require dimensions to be specified in centimeters, while drawings or other materials used to create the input decks might be in other units. This also requires additional calculation or conversion prior to composition of the input deck. These additional calculations, while extremely simple, introduce a source for error in both the calculations and transcriptions. To overcome these difficulties, WORM (Write One, Run Many) was created. It is an easy-to-use programming language to describe input decks and can be used with any computer code that uses standard text files for input. WORM is available, via the Internet, at worm.lanl.gov. A user's guide, tutorials, example models, and other WORM-related materials are also available at this Web site. Questions regarding WORM should be directed to wormatlanl.gov

  7. Methodology for deriving hydrogeological input parameters for safety-analysis models - application to fractured crystalline rocks of Northern Switzerland

    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

  8. Input-output supervisor

    International Nuclear Information System (INIS)

    Dupuy, R.

    1970-01-01

    The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr

  9. Measuring Input Thresholds on an Existing Board

    Science.gov (United States)

    Kuperman, Igor; Gutrich, Daniel G.; Berkun, Andrew C.

    2011-01-01

    A critical PECL (positive emitter-coupled logic) interface to Xilinx interface needed to be changed on an existing flight board. The new Xilinx input interface used a CMOS (complementary metal-oxide semiconductor) type of input, and the driver could meet its thresholds typically, but not in worst-case, according to the data sheet. The previous interface had been based on comparison with an external reference, but the CMOS input is based on comparison with an internal divider from the power supply. A way to measure what the exact input threshold was for this device for 64 inputs on a flight board was needed. The measurement technique allowed an accurate measurement of the voltage required to switch a Xilinx input from high to low for each of the 64 lines, while only probing two of them. Directly driving an external voltage was considered too risky, and tests done on any other unit could not be used to qualify the flight board. The two lines directly probed gave an absolute voltage threshold calibration, while data collected on the remaining 62 lines without probing gave relative measurements that could be used to identify any outliers. The PECL interface was forced to a long-period square wave by driving a saturated square wave into the ADC (analog to digital converter). The active pull-down circuit was turned off, causing each line to rise rapidly and fall slowly according to the input s weak pull-down circuitry. The fall time shows up as a change in the pulse width of the signal ready by the Xilinx. This change in pulse width is a function of capacitance, pulldown current, and input threshold. Capacitance was known from the different trace lengths, plus a gate input capacitance, which is the same for all inputs. The pull-down current is the same for all inputs including the two that are probed directly. The data was combined, and the Excel solver tool was used to find input thresholds for the 62 lines. This was repeated over different supply voltages and

  10. Distribution of return point memory states for systems with stochastic inputs

    International Nuclear Information System (INIS)

    Amann, A; Brokate, M; Rachinskii, D; Temnov, G

    2011-01-01

    We consider the long term effect of stochastic inputs on the state of an open loop system which exhibits the so-called return point memory. An example of such a system is the Preisach model; more generally, systems with the Preisach type input-state relationship, such as in spin-interaction models, are considered. We focus on the characterisation of the expected memory configuration after the system has been effected by the input for sufficiently long period of time. In the case where the input is given by a discrete time random walk process, or the Wiener process, simple closed form expressions for the probability density of the vector of the main input extrema recorded by the memory state, and scaling laws for the dimension of this vector, are derived. If the input is given by a general continuous Markov process, we show that the distribution of previous memory elements can be obtained from a Markov chain scheme which is derived from the solution of an associated one-dimensional escape type problem. Formulas for transition probabilities defining this Markov chain scheme are presented. Moreover, explicit formulas for the conditional probability densities of previous main extrema are obtained for the Ornstein-Uhlenbeck input process. The analytical results are confirmed by numerical experiments.

  11. Water resources and environmental input-output analysis and its key study issues: a review

    Science.gov (United States)

    YANG, Z.; Xu, X.

    2013-12-01

    Used to study the material and energy flow in socioeconomic system, Input-Output Analysis(IOA) had been an effective analysis tool since its appearance. The research fields of Input-Output Analysis were increasingly expanded and studied in depth with the development of fundamental theory. In this paper, starting with introduction of theory development, the water resources input-output analysis and environmental input-output analysis had been specifically reviewed, and two key study issues mentioned as well. Input-Occupancy-Output Analysis and Grey Input-Output Analysis whose proposal and development were introduced firstly could be regard as the effective complements of traditional IOA theory. Because of the hypotheses of homogeneity, stability and proportionality, Input-Occupancy-Output Analysis and Grey Input-Output Analysis always had been restricted in practical application inevitably. In the applied study aspect, with investigation of abundant literatures, research of water resources input-output analysis and environmental input-output analysis had been comprehensively reviewed and analyzed. The regional water resources flow between different economic sectors had been systematically analyzed and stated, and several types of environmental input-output analysis models combined with other effective analysis tools concluded. In two perspectives in terms of external and inland aspect, the development of water resources and environmental input-output analysis model had been explained, and several typical study cases in recent years listed respectively. By the aid of sufficient literature analysis, the internal development tendency and study hotspot had also been summarized. In recent years, Chinese literatures reporting water resources consumption analysis and virtue water study had occupied a large share. Water resources consumption analysis had always been the emphasis of inland water resources IOA. Virtue water study had been considered as the new hotspot of

  12. A consumption-based, regional input-output analysis of greenhouse gas emissions and the carbon regional index

    DEFF Research Database (Denmark)

    Boyd, Britta; Mangalagiu, Diana; Straatman, Bas

    2018-01-01

    This paper presents a consumption-based method accounting for greenhouse gas emissions at regional level based on a multi-region input-output model. The method is based on regional consumption and includes imports and exports of emissions, factual emission developments, green investments as well...

  13. Jointness through fishing days input in a multi-species fishery

    DEFF Research Database (Denmark)

    Hansen, Lars Gårn; Jensen, Carsten Lynge

    .g. translog, normalized quadratic). In this paper we argue that jointness in the latter, essentially separable fishery is caused by allocation of fishing days input among harvested species. We developed a structural model of a multi-species fishery where the allocation of fishing days input causes production...

  14. Shaped input distributions for structural damage localization

    DEFF Research Database (Denmark)

    Ulriksen, Martin Dalgaard; Bernal, Dionisio; Damkilde, Lars

    2018-01-01

    localization method is cast that operates on the premise of shaping inputs—whose spatial distribution is fixed—by use of a model, such that these inputs, in one structural subdomain at a time, suppress certain steady-state vibration quantities (depending on the type of damage one seeks to interrogate for......). 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...

  15. 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.

  16. INPUT-OUTPUT STRUCTURE OF LINEAR-DIFFERENTIAL ALGEBRAIC SYSTEMS

    NARCIS (Netherlands)

    KUIJPER, M; SCHUMACHER, JM

    Systems of linear differential and algebraic equations occur in various ways, for instance, as a result of automated modeling procedures and in problems involving algebraic constraints, such as zero dynamics and exact model matching. Differential/algebraic systems may represent an input-output

  17. Improved quality of input data for maintenance optimization using expert judgment

    International Nuclear Information System (INIS)

    Oien, Knut

    1998-01-01

    Most maintenance optimization models need an estimate of the so-called 'naked' failure rate function as input. In practice it is very difficult to estimate the 'naked' failure rate, because overhauls and other preventive maintenance actions tend to 'corrupt' the recorded lifelengths. The purpose of this paper is to stress the importance of utilizing the knowledge of maintenance engineers, i.e., expert judgment, in addition to recorded equipment lifelengths, in order to get credible input data. We have shown that without utilizing expert judgment, the estimated mean time to failure may be strongly biased, often by a factor of 2-3, depending on the life distribution that is assumed. We recommend including a simple question about the mean remaining lifelength on the work-order forms. By this approach the knowledge of maintenance engineers may be incorporated in a simple and cost-effective way

  18. Tritium Records to Trace Stratospheric Moisture Inputs in Antarctica

    Science.gov (United States)

    Fourré, E.; Landais, A.; Cauquoin, A.; Jean-Baptiste, P.; Lipenkov, V.; Petit, J.-R.

    2018-03-01

    Better assessing the dynamic of stratosphere-troposphere exchange is a key point to improve our understanding of the climate dynamic in the East Antarctica Plateau, a region where stratospheric inputs are expected to be important. Although tritium (3H or T), a nuclide naturally produced mainly in the stratosphere and rapidly entering the water cycle as HTO, seems a first-rate tracer to study these processes, tritium data are very sparse in this region. We present the first high-resolution measurements of tritium concentration over the last 50 years in three snow pits drilled at the Vostok station. Natural variability of the tritium records reveals two prominent frequencies, one at about 10 years (to be related to the solar Schwabe cycles) and the other one at a shorter periodicity: despite dating uncertainty at this short scale, a good correlation is observed between 3H and Na+ and an anticorrelation between 3H and δ18O measured on an individual pit. The outputs from the LMDZ Atmospheric General Circulation Model including stable water isotopes and tritium show the same 3H-δ18O anticorrelation and allow further investigation on the associated mechanism. At the interannual scale, the modeled 3H variability matches well with the Southern Annular Mode index. At the seasonal scale, we show that modeled stratospheric tritium inputs in the troposphere are favored in winter cold and dry conditions.

  19. ANALISIS KEBERHASILAN PRAKTIK KERJA INDUSTRI (PRAKERIN SEBAGAI IMPLEMENTASI PENDIDIKAN SISTEM GANDA (PSG DENGAN MODEL EVALUASI CIPP (CONTEXT, INPUT, PROCESS, PRODUCT DI SMK BARDAN WASALAMAN BATANG

    Directory of Open Access Journals (Sweden)

    Ikke Tutiana Mustiany

    2017-02-01

    Full Text Available Industrial Work Practices (Prakerin is a implementation of the Dual System Education. Prakerin for vocational students is very important to do, because the purpose of vocational education is to prepare students to be ready and independent in the face of the work world. The purpose of this research is to analyze the success of prakerin in vocational Bardan Wasalaman with models CIPP (Context, Input, Process, Product. This type of research used in this study is an evaluative research with quantitative descriptive analysis. This study is a population, where there are 91 respondents composed of 27 people from the accounting and 64 people from the pharmacy. And to support the respondents researchers also conducted interviews with five speakers consisting of Vice Principal of Public Relations, Chairman of Pharmacy Department, Chairman of the Accounting Studies Program, Teacher of Productive Pharmacy and Accounting. Data analysis techniques used in this study presented is the percentage descriptive statistics.The results showed that the average aspect in the context prakerin of 32.54 is included in the excellent category. Average in the input aspects of 48.07 is included in the good categories. Aspects process in prakerin showed an average of 33.65 is included in the good categories. As for the average product in prakerin aspects of 24.79 is included in the high category.

  20. Influence of deleting some of the inputs and outputs on efficiency status of units in DEA

    Directory of Open Access Journals (Sweden)

    Abbas ali Noora

    2013-06-01

    Full Text Available One of the important issues in data envelopment analysis (DEA is sensitivity analysis. This study discusses about deleting some of the inputs and outputs and investigates the influence of it on efficiency status of Decision Making Units (DMUs. To this end some models are presented for recognizing this influence on efficient DMUs. Model 2 (Model 3 in section 3 investigates the influence of deleting i(th input (r(th output on an efficient DMU. Thereafter these models are improved for deleting multiple inputs and outputs. Furthermore, a model is presented for recognizing the maximum number of inputs and (or outputs from among specified inputs and outputs which can be deleted, whereas an efficient DMU preserves its efficiency. Finally, the presented models are utilized for a set of DMUs and the results are reported.

  1. A single point of pressure approach as input for injury models with respect to complex blast loading conditions

    NARCIS (Netherlands)

    Teland, J.A.; Doormaal, J.C.A.M. van; Horst, M.J. van der; Svinsås, E.

    2010-01-01

    Blast injury models, like Axelsson and Stuhmiller, require four pressure signals as input. Those pressure signals must be acquired by a Blast Test Device (BTD) that has four pressure transducers placed in a horizontal plane at intervals of 90 degrees. This can be either in a physical test setup or

  2. A parallel input composite transimpedance amplifier

    Science.gov (United States)

    Kim, D. J.; Kim, C.

    2018-01-01

    A new approach to high performance current to voltage preamplifier design is presented. The design using multiple operational amplifiers (op-amps) has a parasitic capacitance compensation network and a composite amplifier topology for fast, precision, and low noise performance. The input stage consisting of a parallel linked JFET op-amps and a high-speed bipolar junction transistor (BJT) gain stage driving the output in the composite amplifier topology, cooperating with the capacitance compensation feedback network, ensures wide bandwidth stability in the presence of input capacitance above 40 nF. The design is ideal for any two-probe measurement, including high impedance transport and scanning tunneling microscopy measurements.

  3. 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.

  4. Linear and Non-linear Multi-Input Multi-Output Model Predictive Control of Continuous Stirred Tank Reactor

    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.

  5. Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance.

    Science.gov (United States)

    Rotstein, Horacio G

    2014-01-01

    We investigate the dynamic mechanisms of generation of subthreshold and phase resonance in two-dimensional linear and linearized biophysical (conductance-based) models, and we extend our analysis to account for the effect of simple, but not necessarily weak, types of nonlinearities. Subthreshold resonance refers to the ability of neurons to exhibit a peak in their voltage amplitude response to oscillatory input currents at a preferred non-zero (resonant) frequency. Phase-resonance refers to the ability of neurons to exhibit a zero-phase (or zero-phase-shift) response to oscillatory input currents at a non-zero (phase-resonant) frequency. We adapt the classical phase-plane analysis approach to account for the dynamic effects of oscillatory inputs and develop a tool, the envelope-plane diagrams, that captures the role that conductances and time scales play in amplifying the voltage response at the resonant frequency band as compared to smaller and larger frequencies. We use envelope-plane diagrams in our analysis. We explain why the resonance phenomena do not necessarily arise from the presence of imaginary eigenvalues at rest, but rather they emerge from the interplay of the intrinsic and input time scales. We further explain why an increase in the time-scale separation causes an amplification of the voltage response in addition to shifting the resonant and phase-resonant frequencies. This is of fundamental importance for neural models since neurons typically exhibit a strong separation of time scales. We extend this approach to explain the effects of nonlinearities on both resonance and phase-resonance. We demonstrate that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model. The differences between the nonlinear response and the linear prediction increase with increasing levels of the time scale separation between

  6. Model analysis of riparian buffer effectiveness for reducing nutrient inputs to streams in agricultural landscapes

    Science.gov (United States)

    McKane, R. B.; M, S.; F, P.; Kwiatkowski, B. L.; Rastetter, E. B.

    2006-12-01

    Federal and state agencies responsible for protecting water quality rely mainly on statistically-based methods to assess and manage risks to the nation's streams, lakes and estuaries. Although statistical approaches provide valuable information on current trends in water quality, process-based simulation models are essential for understanding and forecasting how changes in human activities across complex landscapes impact the transport of nutrients and contaminants to surface waters. To address this need, we developed a broadly applicable, process-based watershed simulator that links a spatially-explicit hydrologic model and a terrestrial biogeochemistry model (MEL). See Stieglitz et al. and Pan et al., this meeting, for details on the design and verification of this simulator. Here we apply the watershed simulator to a generalized agricultural setting to demonstrate its potential for informing policy and management decisions concerning water quality. This demonstration specifically explores the effectiveness of riparian buffers for reducing the transport of nitrogenous fertilizers from agricultural fields to streams. The interaction of hydrologic and biogeochemical processes represented in our simulator allows several important questions to be addressed. (1) For a range of upland fertilization rates, to what extent do riparian buffers reduce nitrogen inputs to streams? (2) How does buffer effectiveness change over time as the plant-soil system approaches N-saturation? (3) How can buffers be managed to increase their effectiveness, e.g., through periodic harvest and replanting? The model results illustrate that, while the answers to these questions depend to some extent on site factors (climatic regime, soil properties and vegetation type), in all cases riparian buffers have a limited capacity to reduce nitrogen inputs to streams where fertilization rates approach those typically used for intensive agriculture (e.g., 200 kg N per ha per year for corn in the U

  7. Response sensitivity of barrel neuron subpopulations to simulated thalamic input.

    Science.gov (United States)

    Pesavento, Michael J; Rittenhouse, Cynthia D; Pinto, David J

    2010-06-01

    Our goal is to examine the relationship between neuron- and network-level processing in the context of a well-studied cortical function, the processing of thalamic input by whisker-barrel circuits in rodent neocortex. Here we focus on neuron-level processing and investigate the responses of excitatory and inhibitory barrel neurons to simulated thalamic inputs applied using the dynamic clamp method in brain slices. Simulated inputs are modeled after real thalamic inputs recorded in vivo in response to brief whisker deflections. Our results suggest that inhibitory neurons require more input to reach firing threshold, but then fire earlier, with less variability, and respond to a broader range of inputs than do excitatory neurons. Differences in the responses of barrel neuron subtypes depend on their intrinsic membrane properties. Neurons with a low input resistance require more input to reach threshold but then fire earlier than neurons with a higher input resistance, regardless of the neuron's classification. Our results also suggest that the response properties of excitatory versus inhibitory barrel neurons are consistent with the response sensitivities of the ensemble barrel network. The short response latency of inhibitory neurons may serve to suppress ensemble barrel responses to asynchronous thalamic input. Correspondingly, whereas neurons acting as part of the barrel circuit in vivo are highly selective for temporally correlated thalamic input, excitatory barrel neurons acting alone in vitro are less so. These data suggest that network-level processing of thalamic input in barrel cortex depends on neuron-level processing of the same input by excitatory and inhibitory barrel neurons.

  8. Time domain contact model for tyre/road interaction including nonlinear contact stiffness due to small-scale roughness

    Science.gov (United States)

    Andersson, P. B. U.; Kropp, W.

    2008-11-01

    Rolling resistance, traction, wear, excitation of vibrations, and noise generation are all attributes to consider in optimisation of the interaction between automotive tyres and wearing courses of roads. The key to understand and describe the interaction is to include a wide range of length scales in the description of the contact geometry. This means including scales on the order of micrometres that have been neglected in previous tyre/road interaction models. A time domain contact model for the tyre/road interaction that includes interfacial details is presented. The contact geometry is discretised into multiple elements forming pairs of matching points. The dynamic response of the tyre is calculated by convolving the contact forces with pre-calculated Green's functions. The smaller-length scales are included by using constitutive interfacial relations, i.e. by using nonlinear contact springs, for each pair of contact elements. The method is presented for normal (out-of-plane) contact and a method for assessing the stiffness of the nonlinear springs based on detailed geometry and elastic data of the tread is suggested. The governing equations of the nonlinear contact problem are solved with the Newton-Raphson iterative scheme. Relations between force, indentation, and contact stiffness are calculated for a single tread block in contact with a road surface. The calculated results have the same character as results from measurements found in literature. Comparison to traditional contact formulations shows that the effect of the small-scale roughness is large; the contact stiffness is only up to half of the stiffness that would result if contact is made over the whole element directly to the bulk of the tread. It is concluded that the suggested contact formulation is a suitable model to include more details of the contact interface. Further, the presented result for the tread block in contact with the road is a suitable input for a global tyre/road interaction model

  9. Preparation and documentation of a CATHENA input file for Darlington NGS

    International Nuclear Information System (INIS)

    1989-03-01

    A CATHENA input model has been developed and documented for the heat transport system of the Darlington Nuclear Generating Station. CATHENA, an advanced two-fluid thermalhydraulic computer code, has been designed for analysis of postulated loss-of-coolant accidents (LOCA) and upset conditions in the CANDU system. This report describes the Darlington input model (or idealization), and gives representative results for a simulation of a small break at an inlet header

  10. Chance Constrained Input Relaxation to Congestion in Stochastic DEA. An Application to Iranian Hospitals.

    Science.gov (United States)

    Kheirollahi, Hooshang; Matin, Behzad Karami; Mahboubi, Mohammad; Alavijeh, Mehdi Mirzaei

    2015-01-01

    This article developed an approached model of congestion, based on relaxed combination of inputs, in stochastic data envelopment analysis (SDEA) with chance constrained programming approaches. Classic data envelopment analysis models with deterministic data have been used by many authors to identify congestion and estimate its levels; however, data envelopment analysis with stochastic data were rarely used to identify congestion. This article used chance constrained programming approaches to replace stochastic models with "deterministic equivalents". This substitution leads us to non-linear problems that should be solved. Finally, the proposed method based on relaxed combination of inputs was used to identify congestion input in six Iranian hospital with one input and two outputs in the period of 2009 to 2012.

  11. Forecasting the development of regional economy on the basis of input — output tables

    Directory of Open Access Journals (Sweden)

    Yury Konstantinovich Mashunin

    2014-06-01

    Full Text Available The article presents a practical technology of forecasting the development of the regional economy, including the statement of the problem, the construction of a mathematical model, and its implementation. At the constructing of a model, the standard statistical data for the previous period (2011, built on the basis of the table “input — output” are used. A unit of output of final demand, resulting from investments is added. As a result, a model of the regional economy made in the form of a vector mathematical programming problem that takes into account the investment processes in a region is obtained. Its purpose is to maximize the production of final demand in a region (all industries in a region within the constraints of the input-output balance, investments, resource costs and capacities. For solving linear programming problems of vector, methods, based on the principle of normalization criteria and guaranteed result are used. Vector dynamics problem is solved in a specified number of years. The factors taking into account the rate of growth: gross volumes (resources, final demand, investment in every sector of the region are introduced. Numerical implementation of the prediction is shown in the test case economic modeling of Primorsky Krai, including fifteen branches of a three-year period in accordance with the requirements of the Budget Code. Results of the solution include the major economic indicators for a region: gross, gross regional product (GRP, investments (including broken by industry, as well as payroll taxes and other. All these economic indicators are the basis for the formation of budget revenues in a region.

  12. Self-Structured Organizing Single-Input CMAC Control for Robot Manipulator

    Directory of Open Access Journals (Sweden)

    ThanhQuyen Ngo

    2011-09-01

    Full Text Available This paper represents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of proposed control system so that the stability of the system can be guaranteed. The simulation results of robot manipulator are provided to verify the effectiveness of the proposed control methodology.

  13. Load Estimation from Natural input Modal Analysis

    DEFF Research Database (Denmark)

    Aenlle, Manuel López; Brincker, Rune; Canteli, Alfonso Fernández

    2005-01-01

    One application of Natural Input Modal Analysis consists in estimating the unknown load acting on structures such as wind loads, wave loads, traffic loads, etc. In this paper, a procedure to determine loading from a truncated modal model, as well as the results of an experimental testing programme...... estimation. In the experimental program a small structure subjected to vibration was used to estimate the loading from the measurements and the experimental modal space. The modal parameters were estimated by Natural Input Modal Analysis and the scaling factors of the mode shapes obtained by the mass change...

  14. ColloInputGenerator

    DEFF Research Database (Denmark)

    2013-01-01

    This is a very simple program to help you put together input files for use in Gries' (2007) R-based collostruction analysis program. It basically puts together a text file with a frequency list of lexemes in the construction and inserts a column where you can add the corpus frequencies. It requires...... it as input for basic collexeme collostructional analysis (Stefanowitsch & Gries 2003) in Gries' (2007) program. ColloInputGenerator is, in its current state, based on programming commands introduced in Gries (2009). Projected updates: Generation of complete work-ready frequency lists....

  15. Industrial and ecological cumulative exergy consumption of the United States via the 1997 input-output benchmark model

    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

  16. Predicting musically induced emotions from physiological inputs: linear and neural network models.

    Science.gov (United States)

    Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M

    2013-01-01

    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 (HR), 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 non-linear 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 non-linear 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 non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.

  17. 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.

  18. Impact of environmental inputs on reverse-engineering approach to network structures.

    Science.gov (United States)

    Wu, Jianhua; Sinfield, James L; Buchanan-Wollaston, Vicky; Feng, Jianfeng

    2009-12-04

    Uncovering complex network structures from a biological system is one of the main topic in system biology. The network structures can be inferred by the dynamical Bayesian network or Granger causality, but neither techniques have seriously taken into account the impact of environmental inputs. With considerations of natural rhythmic dynamics of biological data, we propose a system biology approach to reveal the impact of environmental inputs on network structures. We first represent the environmental inputs by a harmonic oscillator and combine them with Granger causality to identify environmental inputs and then uncover the causal network structures. We also generalize it to multiple harmonic oscillators to represent various exogenous influences. This system approach is extensively tested with toy models and successfully applied to a real biological network of microarray data of the flowering genes of the model plant Arabidopsis Thaliana. The aim is to identify those genes that are directly affected by the presence of the sunlight and uncover the interactive network structures associating with flowering metabolism. We demonstrate that environmental inputs are crucial for correctly inferring network structures. Harmonic causal method is proved to be a powerful technique to detect environment inputs and uncover network structures, especially when the biological data exhibit periodic oscillations.

  19. Response of the Black Sea methane budget to massive short-term submarine inputs of methane

    DEFF Research Database (Denmark)

    Schmale, O.; Haeckel, M.; McGinnis, D. F.

    2011-01-01

    A steady state box model was developed to estimate the methane input into the Black Sea water column at various water depths. Our model results reveal a total input of methane of 4.7 Tg yr(-1). The model predicts that the input of methane is largest at water depths between 600 and 700 m (7......% of the total input), suggesting that the dissociation of methane gas hydrates at water depths equivalent to their upper stability limit may represent an important source of methane into the water column. In addition we discuss the effects of massive short-term methane inputs (e. g. through eruptions of deep......-water mud volcanoes or submarine landslides at intermediate water depths) on the water column methane distribution and the resulting methane emission to the atmosphere. Our non-steady state simulations predict that these inputs will be effectively buffered by intense microbial methane consumption...

  20. Input Shaping to Reduce Solar Array Structural Vibrations

    Science.gov (United States)

    Doherty, Michael J.; Tolson, Robert J.

    1998-01-01

    Structural vibrations induced by actuators can be minimized using input shaping. Input shaping is a feedforward method in which actuator commands are convolved with shaping functions to yield a shaped set of commands. These commands are designed to perform the maneuver while minimizing the residual structural vibration. In this report, input shaping is extended to stepper motor actuators. As a demonstration, an input-shaping technique based on pole-zero cancellation was used to modify the Solar Array Drive Assembly (SADA) actuator commands for the Lewis satellite. A series of impulses were calculated as the ideal SADA output for vibration control. These impulses were then discretized for use by the SADA stepper motor actuator and simulated actuator outputs were used to calculate the structural response. The effectiveness of input shaping is limited by the accuracy of the knowledge of the modal frequencies. Assuming perfect knowledge resulted in significant vibration reduction. Errors of 10% in the modal frequencies caused notably higher levels of vibration. Controller robustness was improved by incorporating additional zeros in the shaping function. The additional zeros did not require increased performance from the actuator. Despite the identification errors, the resulting feedforward controller reduced residual vibrations to the level of the exactly modeled input shaper and well below the baseline cases. These results could be easily applied to many other vibration-sensitive applications involving stepper motor actuators.

  1. Including investment risk in large-scale power market models

    DEFF Research Database (Denmark)

    Lemming, Jørgen Kjærgaard; Meibom, P.

    2003-01-01

    Long-term energy market models can be used to examine investments in production technologies, however, with market liberalisation it is crucial that such models include investment risks and investor behaviour. This paper analyses how the effect of investment risk on production technology selection...... 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...

  2. Decision aids for multiple-decision disease management as affected by weather input errors.

    Science.gov (United States)

    Pfender, W F; Gent, D H; Mahaffee, W F; Coop, L B; Fox, A D

    2011-06-01

    Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.

  3. Seismic evaluation of a cooling water reservoir facility including fluid-structure and soil-structure interaction effects

    International Nuclear Information System (INIS)

    Kabir, A.F.; Maryak, M.E.

    1991-01-01

    Seismic analyses and structural evaluations were performed for a cooling water reservoir of a nuclear reactor facility. The horizontal input seismic motion was the NRC Reg. guide 1.60 spectrum shape anchored at 0.20g zero period acceleration. Vertical input was taken as two-thirds of the horizontal input. Soil structure interaction and hydrodynamic effects were addressed in the seismic analyses. Uncertainties in the soil properties were accounted for by considering three soil profiles. Two 2-dimensional SSI models and a 3-dimensional static model. Representing different areas of the reservoir structures were developed and analyzed to obtain seismic forces and moments, and accelerations at various locations. The results included in this paper indicated that both hydrodynamic and soil-structure interaction effects are significant contributors to the seismic responses of the water-retaining walls of the reservoir

  4. A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System

    Science.gov (United States)

    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.

  5. CBM first-level event selector input interface

    Energy Technology Data Exchange (ETDEWEB)

    Hutter, Dirk [Frankfurt Institute for Advanced Studies, Goethe University, Frankfurt (Germany); Collaboration: CBM-Collaboration

    2016-07-01

    The CBM First-level Event Selector (FLES) is the central event selection system of the upcoming CBM experiment at FAIR. Designed as a high-performance computing cluster, its task is an online analysis of the physics data at a total data rate exceeding 1 TByte/s. To allow efficient event selection, the FLES performs timeslice building, which combines the data from all given input links to self-contained, overlapping processing intervals and distributes them to compute nodes. Partitioning the input data streams into specialized containers allows to perform this task very efficiently. The FLES Input Interface defines the linkage between FEE and FLES data transport framework. Utilizing a custom FPGA board, it receives data via optical links, prepares them for subsequent timeslice building, and transfers the data via DMA to the PC's memory. An accompanying HDL module implements the front-end logic interface and FLES link protocol in the front-end FPGAs. Prototypes of all Input Interface components have been implemented and integrated into the FLES framework. In contrast to earlier prototypes, which included components to work without a FPGA layer between FLES and FEE, the structure matches the foreseen final setup. This allows the implementation and evaluation of the final CBM read-out chain. An overview of the FLES Input Interface as well as studies on system integration and system start-up are presented.

  6. Nitrogen input inventory in the Nooksack-Abbotsford-Sumas ...

    Science.gov (United States)

    Nitrogen (N) is an essential biological element, so optimizing N use for food production while minimizing the release of N and co-pollutants to the environment is an important challenge. The Nooksack-Abbotsford-Sumas Transboundary (NAS) Region, spanning a portion of the western interface of British Columbia, Washington state, and the Lummi Nation and the Nooksack Tribe, supports agriculture, fisheries, diverse wildlife, and vibrant urban areas. Groundwater nitrate contamination affects thousands of households in this region. Fisheries and air quality are also affected including periodic closures of shellfish harvest. To reduce the release of N to the environment, successful approaches are needed that partner all stakeholders with appropriate institutions to integrate science, outreach and management efforts. Our goal is to determine the distribution and quantities of N inventories of the watershed. This work synthesizes publicly available data on N sources including deposition, sewage and septic inputs, fertilizer and manure applications, marine-derived N from salmon, and more. The information on cross-boundary N inputs to the landscape will be coupled with stream monitoring data and existing knowledge about N inputs and exports from the watershed to estimate the N residual and inform N management in the search for the environmentally and economically viable and effective solutions. We will estimate the N inputs into the NAS region and transfers within

  7. Safety analysis code input automation using the Nuclear Plant Data Bank

    International Nuclear Information System (INIS)

    Kopp, H.; Leung, J.; Tajbakhsh, A.; Viles, F.

    1985-01-01

    The Nuclear Plant Data Bank (NPDB) is a computer-based system that organizes a nuclear power plant's technical data, providing mechanisms for data storage, retrieval, and computer-aided engineering analysis. It has the specific objective to describe thermohydraulic systems in order to support: rapid information retrieval and display, and thermohydraulic analysis modeling. The Nuclear Plant Data Bank (NPBD) system fully automates the storage and analysis based on this data. The system combines the benefits of a structured data base system and computer-aided modeling with links to large scale codes for engineering analysis. Emphasis on a friendly and very graphically oriented user interface facilitates both initial use and longer term efficiency. Specific features are: organization and storage of thermohydraulic data items, ease in locating specific data items, graphical and tabular display capabilities, interactive model construction, organization and display of model input parameters, input deck construction for TRAC and RELAP analysis programs, and traceability of plant data, user model assumptions, and codes used in the input deck construction process. The major accomplishments of this past year were the development of a RELAP model generation capability and the development of a CRAY version of the code

  8. High organic inputs explain shallow and deep SOC storage in a long-term agroforestry system – combining experimental and modeling approaches

    Directory of Open Access Journals (Sweden)

    R. Cardinael

    2018-01-01

    Full Text Available Agroforestry is an increasingly popular farming system enabling agricultural diversification and providing several ecosystem services. In agroforestry systems, soil organic carbon (SOC stocks are generally increased, but it is difficult to disentangle the different factors responsible for this storage. Organic carbon (OC inputs to the soil may be larger, but SOC decomposition rates may be modified owing to microclimate, physical protection, or priming effect from roots, especially at depth. We used an 18-year-old silvoarable system associating hybrid walnut trees (Juglans regia  ×  nigra and durum wheat (Triticum turgidum L. subsp. durum and an adjacent agricultural control plot to quantify all OC inputs to the soil – leaf litter, tree fine root senescence, crop residues, and tree row herbaceous vegetation – and measured SOC stocks down to 2 m of depth at varying distances from the trees. We then proposed a model that simulates SOC dynamics in agroforestry accounting for both the whole soil profile and the lateral spatial heterogeneity. The model was calibrated to the control plot only. Measured OC inputs to soil were increased by about 40 % (+ 1.11 t C ha−1 yr−1 down to 2 m of depth in the agroforestry plot compared to the control, resulting in an additional SOC stock of 6.3 t C ha−1 down to 1 m of depth. However, most of the SOC storage occurred in the first 30 cm of soil and in the tree rows. The model was strongly validated, properly describing the measured SOC stocks and distribution with depth in agroforestry tree rows and alleys. It showed that the increased inputs of fresh biomass to soil explained the observed additional SOC storage in the agroforestry plot. Moreover, only a priming effect variant of the model was able to capture the depth distribution of SOC stocks, suggesting the priming effect as a possible mechanism driving deep SOC dynamics. This result questions the potential of soils to

  9. RELAP5/MOD3 code manual: User's guide and input requirements. Volume 2

    International Nuclear Information System (INIS)

    1995-08-01

    The RELAP5 code has been developed for best estimate transient simulation of light water reactor coolant systems during postulated accidents. The code models the coupled behavior of the reactor coolant system and the core for loss-of-coolant accidents, and operational transients, such as anticipated transient without scram, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits simulating a variety of thermal hydraulic systems. Control system and secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater systems. Volume II contains detailed instructions for code application and input data preparation

  10. Input and Age-Dependent Variation in Second Language Learning: A Connectionist Account.

    Science.gov (United States)

    Janciauskas, Marius; Chang, Franklin

    2017-07-26

    Language learning requires linguistic input, but several studies have found that knowledge of second language (L2) rules does not seem to improve with more language exposure (e.g., Johnson & Newport, 1989). One reason for this is that previous studies did not factor out variation due to the different rules tested. To examine this issue, we reanalyzed grammaticality judgment scores in Flege, Yeni-Komshian, and Liu's (1999) study of L2 learners using rule-related predictors and found that, in addition to the overall drop in performance due to a sensitive period, L2 knowledge increased with years of input. Knowledge of different grammar rules was negatively associated with input frequency of those rules. To better understand these effects, we modeled the results using a connectionist model that was trained using Korean as a first language (L1) and then English as an L2. To explain the sensitive period in L2 learning, the model's learning rate was reduced in an age-related manner. By assigning different learning rates for syntax and lexical learning, we were able to model the difference between early and late L2 learners in input sensitivity. The model's learning mechanism allowed transfer between the L1 and L2, and this helped to explain the differences between different rules in the grammaticality judgment task. This work demonstrates that an L1 model of learning and processing can be adapted to provide an explicit account of how the input and the sensitive period interact in L2 learning. © 2017 The Authors. Cognitive Science - A Multidisciplinary Journal published by Wiley Periodicals, Inc.

  11. Total dose induced increase in input offset voltage in JFET input operational amplifiers

    International Nuclear Information System (INIS)

    Pease, R.L.; Krieg, J.; Gehlhausen, M.; Black, J.

    1999-01-01

    Four different types of commercial JFET input operational amplifiers were irradiated with ionizing radiation under a variety of test conditions. All experienced significant increases in input offset voltage (Vos). Microprobe measurement of the electrical characteristics of the de-coupled input JFETs demonstrates that the increase in Vos is a result of the mismatch of the degraded JFETs. (authors)

  12. DUSTMS-D: DISPOSAL UNIT SOURCE TERM - MULTIPLE SPECIES - DISTRIBUTED FAILURE DATA INPUT GUIDE.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN, T.M.

    2006-01-01

    Performance assessment of a low-level waste (LLW) disposal facility begins with an estimation of the rate at which radionuclides migrate out of the facility (i.e., the source term). The focus of this work is to develop a methodology for calculating the source term. In general, the source term is influenced by the radionuclide inventory, the wasteforms and containers used to dispose of the inventory, and the physical processes that lead to release from the facility (fluid flow, container degradation, wasteform leaching, and radionuclide transport). Many of these physical processes are influenced by the design of the disposal facility (e.g., how the engineered barriers control infiltration of water). The complexity of the problem and the absence of appropriate data prevent development of an entirely mechanistic representation of radionuclide release from a disposal facility. Typically, a number of assumptions, based on knowledge of the disposal system, are used to simplify the problem. This has been done and the resulting models have been incorporated into the computer code DUST-MS (Disposal Unit Source Term-Multiple Species). The DUST-MS computer code is designed to model water flow, container degradation, release of contaminants from the wasteform to the contacting solution and transport through the subsurface media. Water flow through the facility over time is modeled using tabular input. Container degradation models include three types of failure rates: (a) instantaneous (all containers in a control volume fail at once), (b) uniformly distributed failures (containers fail at a linear rate between a specified starting and ending time), and (c) gaussian failure rates (containers fail at a rate determined by a mean failure time, standard deviation and gaussian distribution). Wasteform release models include four release mechanisms: (a) rinse with partitioning (inventory is released instantly upon container failure subject to equilibrium partitioning (sorption) with

  13. SPheno 3.1: extensions including flavour, CP-phases and models beyond the MSSM

    Science.gov (United States)

    Porod, W.; Staub, F.

    2012-11-01

    We describe recent extensions of the program SPhenoincluding flavour aspects, CP-phases, R-parity violation and low energy observables. In case of flavour mixing all masses of supersymmetric particles are calculated including the complete flavour structure and all possible CP-phases at the 1-loop level. We give details on implemented seesaw models, low energy observables and the corresponding extension of the SUSY Les Houches Accord. Moreover, we comment on the possibilities to include MSSM extensions in SPheno. Catalogue identifier: ADRV_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADRV_v2_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 154062 No. of bytes in distributed program, including test data, etc.: 1336037 Distribution format: tar.gz Programming language: Fortran95. Computer: PC running under Linux, should run in every Unix environment. Operating system: Linux, Unix. Classification: 11.6. Catalogue identifier of previous version: ADRV_v1_0 Journal reference of previous version: Comput. Phys. Comm. 153(2003)275 Does the new version supersede the previous version?: Yes Nature of problem: The first issue is the determination of the masses and couplings of supersymmetric particles in various supersymmetric models, the R-parity conserved MSSM with generation mixing and including CP-violating phases, various seesaw extensions of the MSSM and the MSSM with bilinear R-parity breaking. Low energy data on Standard Model fermion masses, gauge couplings and electroweak gauge boson masses serve as constraints. Radiative corrections from supersymmetric particles to these inputs must be calculated. Theoretical constraints on the soft SUSY breaking parameters from a high scale theory are imposed and the parameters at the electroweak scale are obtained from the

  14. 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.)

  15. Sensitivity of modeled estuarine circulation to spatial and temporal resolution of input meteorological forcing of a cold frontal passage

    Science.gov (United States)

    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.

  16. Econometric models for biohydrogen development.

    Science.gov (United States)

    Lee, Duu-Hwa; Lee, Duu-Jong; Veziroglu, Ayfer

    2011-09-01

    Biohydrogen is considered as an attractive clean energy source due to its high energy content and environmental-friendly conversion. Analyzing various economic scenarios can help decision makers to optimize development strategies for the biohydrogen sector. This study surveys econometric models of biohydrogen development, including input-out models, life-cycle assessment approach, computable general equilibrium models, linear programming models and impact pathway approach. Fundamentals of each model were briefly reviewed to highlight their advantages and disadvantages. The input-output model and the simplified economic input-output life-cycle assessment model proved most suitable for economic analysis of biohydrogen energy development. A sample analysis using input-output model for forecasting biohydrogen development in the United States is given. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. Pre-processing of input files for the AZTRAN code; Pre procesamiento de archivos de entrada para el codigo AZTRAN

    Energy Technology Data Exchange (ETDEWEB)

    Vargas E, S. [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico); Ibarra, G., E-mail: samuel.vargas@inin.gob.mx [IPN, Av. Instituto Politecnico Nacional s/n, 07738 Ciudad de Mexico (Mexico)

    2017-09-15

    The AZTRAN code began to be developed in the Nuclear Engineering Department of the Escuela Superior de Fisica y Matematicas (ESFM) of the Instituto Politecnico Nacional (IPN) with the purpose of numerically solving various models arising from the physics and engineering of nuclear reactors. The code is still under development and is part of the AZTLAN platform: Development of a Mexican platform for the analysis and design of nuclear reactors. Due to the complexity to generate an input file for the code, a script based on D language is developed, with the purpose of making its elaboration easier, based on a new input file format which includes specific cards, which have been divided into two blocks, mandatory cards and optional cards, including a pre-processing of the input file to identify possible errors within it, as well as an image generator for the specific problem based on the python interpreter. (Author)

  18. Input measurements in reprocessing plants

    International Nuclear Information System (INIS)

    Trincherini, P.R.; Facchetti, S.

    1980-01-01

    The aim of this work is to give a review of the methods and the problems encountered in measurements in 'input accountability tanks' of irradiated fuel treatment plants. This study was prompted by the conviction that more and more precise techniques and methods should be at the service of safeguards organizations and that ever greater efforts should be directed towards promoting knowledge of them among operators and all those general area of interest includes the nuclear fuel cycle. The overall intent is to show the necessity of selecting methods which produce measurements which are not only more precise but are absolutely reliable both for routine plant operation and for safety checks in the input area. A description and a critical evaluation of the most common physical and chemical methods are provided, together with an estimate of the precision and accuracy obtained in real operating conditions

  19. 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

  20. A two-input sliding-mode controller for a planar arm actuated by four pneumatic muscle groups.

    Science.gov (United States)

    Lilly, John H; Quesada, Peter M

    2004-09-01

    Multiple-input sliding-mode techniques are applied to a planar arm actuated by four groups of pneumatic muscle (PM) actuators in opposing pair configuration. The control objective is end-effector tracking of a desired path in Cartesian space. The inputs to the system are commanded input pressure differentials for the two opposing PM groups. An existing model for the muscle is incorporated into the arm equations of motion to arrive at a two-input, two-output nonlinear model of the planar arm that is affine in the input and, therefore, suitable for sliding-mode techniques. Relationships between static input pressures are derived for suitable arm behavior in the absence of a control signal. Simulation studies are reported.

  1. Structural consequences of carbon taxes: An input-output analysis

    International Nuclear Information System (INIS)

    Che Yuhu.

    1992-01-01

    A model system is provided for examining for examining the structural consequences of carbon taxes on economic, energy, and environmental issues. The key component is the Iterative Multi-Optimization (IMO) Process model which describes, using an Input-Output (I-O) framework, the feedback between price changes and substitution. The IMO process is designed to assure this feedback process when the input coefficients in an I-O table can be changed while holding the I-O price model. The theoretical problems of convergence to a limit in the iterative process and uniqueness (which requires all IMO processes starting from different initial prices to converge to a unique point for a given level of carbon taxes) are addressed. The empirical analysis also examines the effects of carbon taxes on the US economy as described by a 78 sector I-O model. Findings are compared with those of other models that assess the effects of carbon taxes, and the similarities and differences with them are interpreted in terms of differences in the scope, sectoral detail, time frame, and policy assumptions among the models

  2. Improvement of Meteorological Inputs for TexAQS-II Air Quality Simulations

    Science.gov (United States)

    Ngan, F.; Byun, D.; Kim, H.; Cheng, F.; Kim, S.; Lee, D.

    2008-12-01

    An air quality forecasting system (UH-AQF) for Eastern Texas, which is in operation by the Institute for Multidimensional Air Quality Studies (IMAQS) at the University of Houston, uses the Fifth-Generation PSU/NCAR Mesoscale Model MM5 model as the meteorological driver for modeling air quality with the Community Multiscale Air Quality (CMAQ) model. While the forecasting system was successfully used for the planning and implementation of various measurement activities, evaluations of the forecasting results revealed a few systematic problems in the numerical simulations. From comparison with observations, we observe some times over-prediction of northerly winds caused by inaccurate synoptic inputs and other times too strong southerly winds caused by local sea breeze development. Discrepancies in maximum and minimum temperature are also seen for certain days. Precipitation events, as well as clouds, are simulated at the incorrect locations and times occasionally. Model simulatednrealistic thunderstorms are simulated, causing sometimes cause unrealistically strong outflows. To understand physical and chemical processes influencing air quality measures, a proper description of real world meteorological conditions is essential. The objective of this study is to generate better meteorological inputs than the AQF results to support the chemistry modeling. We utilized existing objective analysis and nudging tools in the MM5 system to develop the MUltiscale Nest-down Data Assimilation System (MUNDAS), which incorporates extensive meteorological observations available in the simulated domain for the retrospective simulation of the TexAQS-II period. With the re-simulated meteorological input, we are able to better predict ozone events during TexAQS-II period. In addition, base datasets in MM5 such as land use/land cover, vegetation fraction, soil type and sea surface temperature are updated by satellite data to represent the surface features more accurately. They are key

  3. Evaluation of globally available precipitation data products as input for water balance models

    Science.gov (United States)

    Lebrenz, H.; Bárdossy, A.

    2009-04-01

    Subject of this study is the evaluation of globally available precipitation data products, which are intended to be used as input variables for water balance models in ungauged basins. The selected data sources are a) the Global Precipitation Climatology Centre (GPCC), b) the Global Precipitation Climatology Project (GPCP) and c) the Climate Research Unit (CRU), resulting into twelve globally available data products. The data products imply different data bases, different derivation routines and varying resolutions in time and space. For validation purposes, the ground data from South Africa were screened on homogeneity and consistency by various tests and an outlier detection using multi-linear regression was performed. External Drift Kriging was subsequently applied on the ground data and the resulting precipitation arrays were compared to the different products with respect to quantity and variance.

  4. Effects of Input Data Content on the Uncertainty of Simulating Water Resources

    Directory of Open Access Journals (Sweden)

    Carla Camargos

    2018-05-01

    Full Text Available The widely used, partly-deterministic Soil and Water Assessment Tool (SWAT requires a large amount of spatial input data, such as a digital elevation model (DEM, land use, and soil maps. Modelers make an effort to apply the most specific data possible for the study area to reflect the heterogeneous characteristics of landscapes. Regional data, especially with fine resolution, is often preferred. However, such data is not always available and can be computationally demanding. Despite being coarser, global data are usually free and available to the public. Previous studies revealed the importance for single investigations of different input maps. However, it remains unknown whether higher-resolution data can lead to reliable results. This study investigates how global and regional input datasets affect parameter uncertainty when estimating river discharges. We analyze eight different setups for the SWAT model for a catchment in Luxembourg, combining different land-use, elevation, and soil input data. The Metropolis–Hasting Markov Chain Monte Carlo (MCMC algorithm is used to infer posterior model parameter uncertainty. We conclude that our higher resolved DEM improves the general model performance in reproducing low flows by 10%. The less detailed soil-map improved the fit of low flows by 25%. In addition, more detailed land-use maps reduce the bias of the model discharge simulations by 50%. Also, despite presenting similar parameter uncertainty (P-factor ranging from 0.34 to 0.41 and R-factor from 0.41 to 0.45 for all setups, the results show a disparate parameter posterior distribution. This indicates that no assessment of all sources of uncertainty simultaneously is compensated by the fitted parameter values. We conclude that our result can give some guidance for future SWAT applications in the selection of the degree of detail for input data.

  5. H∞ memory feedback control with input limitation minimization for offshore jacket platform stabilization

    Science.gov (United States)

    Yang, Jia Sheng

    2018-06-01

    In this paper, we investigate a H∞ memory controller with input limitation minimization (HMCIM) for offshore jacket platforms stabilization. The main objective of this study is to reduce the control consumption as well as protect the actuator when satisfying the requirement of the system performance. First, we introduce a dynamic model of offshore platform with low order main modes based on mode reduction method in numerical analysis. Then, based on H∞ control theory and matrix inequality techniques, we develop a novel H∞ memory controller with input limitation. Furthermore, a non-convex optimization model to minimize input energy consumption is proposed. Since it is difficult to solve this non-convex optimization model by optimization algorithm, we use a relaxation method with matrix operations to transform this non-convex optimization model to be a convex optimization model. Thus, it could be solved by a standard convex optimization solver in MATLAB or CPLEX. Finally, several numerical examples are given to validate the proposed models and methods.

  6. Review of input stages used in front end electronics for particle detectors

    CERN Document Server

    Kaplon, J

    2015-01-01

    In this paper we present noise analysis of the input stages most commonly used in front end electronics for particle detectors. Analysis shows the calculation of the input referenced noise related to the active devices. It identifies the type, parallel or series, of the equivalent noise sources related to the input transistors, which is the important input for the further choice of the signal processing method. Moreover we calculate the input impedance of amplifiers employed in applications where the particle detector is connected to readout electronics by means of transmission line. We present schematics, small signal models,a complete set of equations, and results of the major steps of calculations for all discussed circuits.

  7. The effect of long-term changes in plant inputs on soil carbon stocks

    Science.gov (United States)

    Georgiou, K.; Li, Z.; Torn, M. S.

    2017-12-01

    Soil organic carbon (SOC) is the largest actively-cycling terrestrial reservoir of C and an integral component of thriving natural and managed ecosystems. C input interventions (e.g., litter removal or organic amendments) are common in managed landscapes and present an important decision for maintaining healthy soils in sustainable agriculture and forestry. Furthermore, climate and land-cover change can also affect the amount of plant C inputs that enter the soil through changes in plant productivity, allocation, and rooting depth. Yet, the processes that dictate the response of SOC to such changes in C inputs are poorly understood and inadequately represented in predictive models. Long-term litter manipulations are an invaluable resource for exploring key controls of SOC storage and validating model representations. Here we explore the response of SOC to long-term changes in plant C inputs across a range of biomes and soil types. We synthesize and analyze data from long-term litter manipulation field experiments, and focus our meta-analysis on changes to total SOC stocks, microbial biomass carbon, and mineral-associated (`protected') carbon pools and explore the relative contribution of above- versus below-ground C inputs. Our cross-site data comparison reveals that divergent SOC responses are observed between forest sites, particularly for treatments that increase C inputs to the soil. We explore trends among key variables (e.g., microbial biomass to SOC ratios) that inform soil C model representations. The assembled dataset is an important benchmark for evaluating process-based hypotheses and validating divergent model formulations.

  8. Modeling DPOAE input/output function compression: comparisons with hearing thresholds.

    Science.gov (United States)

    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.

  9. Incorporation of Damage and Failure into an Orthotropic Elasto-Plastic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

    Science.gov (United States)

    Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Khaled, Bilal; Rajan, Subramaniam; Blankenhorn, Gunther

    2016-01-01

    A material model which incorporates several key capabilities which have been identified by the aerospace community as lacking in the composite impact models currently available in LS-DYNA(Registered Trademark) is under development. In particular, the material model, which is being implemented as MAT 213 into a tailored version of LS-DYNA being jointly developed by the FAA and NASA, incorporates both plasticity and damage within the material model, utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength), and is able to analyze the response of composites composed with a variety of fiber architectures. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. The capability to account for the rate and temperature dependent deformation response of composites has also been incorporated into the material model. For the damage model, a strain equivalent formulation is utilized to allow for the uncoupling of the deformation and damage analyses. In the damage model, a diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, in composites it has been found that loading in one direction can lead to damage in multiple coordinate directions. To account for this phenomena, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. The onset of material failure, and thus element deletion, is being developed to be a function of the stresses and plastic strains in the various coordinate directions. Systematic procedures are being developed to generate the required input parameters based on the results of

  10. Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

    Energy Technology Data Exchange (ETDEWEB)

    Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

    2016-07-15

    In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

  11. Unsteady panel method for complex configurations including wake modeling

    CSIR Research Space (South Africa)

    Van Zyl, Lourens H

    2008-01-01

    Full Text Available implementations of the DLM are however not very versatile in terms of geometries that can be modeled. The ZONA6 code offers a versatile surface panel body model including a separated wake model, but uses a pressure panel method for lifting surfaces. This paper...

  12. Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding.

    Science.gov (United States)

    Ponce, Carlos R; Lomber, Stephen G; Livingstone, Margaret S

    2017-05-10

    In the macaque monkey brain, posterior inferior temporal (PIT) cortex cells contribute to visual object recognition. They receive concurrent inputs from visual areas V4, V3, and V2. We asked how these different anatomical pathways shape PIT response properties by deactivating them while monitoring PIT activity in two male macaques. We found that cooling of V4 or V2|3 did not lead to consistent changes in population excitatory drive; however, population pattern analyses showed that V4-based pathways were more important than V2|3-based pathways. We did not find any image features that predicted decoding accuracy differences between both interventions. Using the HMAX hierarchical model of visual recognition, we found that different groups of simulated "PIT" units with different input histories (lacking "V2|3" or "V4" input) allowed for comparable levels of object-decoding performance and that removing a large fraction of "PIT" activity resulted in similar drops in performance as in the cooling experiments. We conclude that distinct input pathways to PIT relay similar types of shape information, with V1-dependent V4 cells providing more quantitatively useful information for overall encoding than cells in V2 projecting directly to PIT. SIGNIFICANCE STATEMENT Convolutional neural networks are the best models of the visual system, but most emphasize input transformations across a serial hierarchy akin to the primary "ventral stream" (V1 → V2 → V4 → IT). However, the ventral stream also comprises parallel "bypass" pathways: V1 also connects to V4, and V2 to IT. To explore the advantages of mixing long and short pathways in the macaque brain, we used cortical cooling to silence inputs to posterior IT and compared the findings with an HMAX model with parallel pathways. Copyright © 2017 the authors 0270-6474/17/375019-16$15.00/0.

  13. Cost efficiency with triangular fuzzy number input prices: An application of DEA

    International Nuclear Information System (INIS)

    Bagherzadeh Valami, H.

    2009-01-01

    The cost efficiency model (CE) has been considered by researchers as a Data Envelopment Analysis (DEA) model for evaluating the efficiency of DMUs. In this model, the possibility of producing the outputs of a target DMU is evaluated by the input prices of the DMU. This provides a criterion for evaluating the CE of DMUs. The main contribution of this paper is to provide an approach for generalizing the CE of DMUs when their input prices are triangular fuzzy numbers, where preliminary concepts of fuzzy theory and CE, are directly used.

  14. Input and execution

    International Nuclear Information System (INIS)

    Carr, S.; Lane, G.; Rowling, G.

    1986-11-01

    This document describes the input procedures, input data files and operating instructions for the SYVAC A/C 1.03 computer program. SYVAC A/C 1.03 simulates the groundwater mediated movement of radionuclides from underground facilities for the disposal of low and intermediate level wastes to the accessible environment, and provides an estimate of the subsequent radiological risk to man. (author)

  15. Computer code ANISN multiplying media and shielding calculation 2. Code description (input/output)

    International Nuclear Information System (INIS)

    Maiorino, J.R.

    1991-01-01

    The new code CCC-0514-ANISN/PC is described, as well as a ''GENERAL DESCRIPTION OF ANISN/PC code''. In addition to the ANISN/PC code, the transmittal package includes an interactive input generation programme called APE (ANISN Processor and Evaluator), which facilitates the work of the user in giving input. Also, a 21 group photon cross section master library FLUNGP.LIB in ISOTX format, which can be edited by an executable file LMOD.EXE, is included in the package. The input and output subroutines are reviewed. 6 refs, 1 fig., 1 tab

  16. Determination of the arterial input function in mouse-models using clinical MRI

    International Nuclear Information System (INIS)

    Theis, D.; Fachhochschule Giessen-Friedberg; Keil, B.; Heverhagen, J.T.; Klose, K.J.; Behe, M.; Fiebich, M.

    2008-01-01

    Dynamic contrast enhanced magnetic resonance imaging is a promising method for quantitative analysis of tumor perfusion and is increasingly used in study of cancer in small animal models. In those studies the determination of the arterial input function (AIF) of the target tissue can be the first step. Series of short-axis images of the heart were acquired during administration of a bolus of Gd-DTPA using saturation-recovery gradient echo pulse sequences. The AIF was determined from the changes of the signal intensity in the left ventricle. The native T1 relaxation times and AIF were determined for 11 mice. An average value of (1.16 ± 0.09) s for the native T1 relaxation time was measured. However, the AIF showed significant inter animal variability, as previously observed by other authors. The inter-animal variability shows, that a direct measurement of the AIF is reasonable to avoid significant errors. The proposed method for determination of the AIF proved to be reliable. (orig.)

  17. Analysis of Input and Output Ripples of PWM AC Choppers

    Directory of Open Access Journals (Sweden)

    Pekik Argo Dahono

    2008-11-01

    Full Text Available This paper presents an analysis of input and output ripples of PWM AC choppers. Expressions of input and output current and voltage ripples of single-phase PWM AC choppers are first derived. The derived expressions are then extended to three-phase PWM AC choppers. As input current and output voltage ripples specification alone cannot be used to determine the unique values of inductance and capacitance of the LC filters, an additional criterion based on the minimum reactive power is proposed. Experimental results are included in this paper to show the validity of the proposed analysis method.

  18. Better temperature predictions in geothermal modelling by improved quality of input parameters: a regional case study from the Danish-German border region

    Science.gov (United States)

    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

  19. Investigating gaze-controlled input in a cognitive selection test

    OpenAIRE

    Gayraud, Katja; Hasse, Catrin; Eißfeldt, Hinnerk; Pannasch, Sebastian

    2017-01-01

    In the field of aviation, there is a growing interest in developing more natural forms of interaction between operators and systems to enhance safety and efficiency. These efforts also include eye gaze as an input channel for human-machine interaction. The present study investigates the application of gaze-controlled input in a cognitive selection test called Eye Movement Conflict Detection Test. The test enables eye movements to be studied as an indicator for psychological test performance a...

  20. IFF, Full-Screen Input Menu Generator for FORTRAN Program

    International Nuclear Information System (INIS)

    Seidl, Albert

    1991-01-01

    1 - Description of program or function: The IFF-package contains input modules for use within FORTRAN programs. This package enables the programmer to easily include interactive menu-directed data input (module VTMEN1) and command-word processing (module INPCOM) into a FORTRAN program. 2 - Method of solution: No mathematical operations are performed. 3 - Restrictions on the complexity of the problem: Certain restrictions of use may arise from the dimensioning of arrays. Field lengths are defined via PARAMETER-statements

  1. Super-Efficiency and Sensitivity Analysis Based on Input-Oriented DEA-R

    Directory of Open Access Journals (Sweden)

    M. R. Mozaffari∗

    2012-03-01

    Full Text Available This paper suggests a method of finding super-efficiency scores and modification of input-oriented models for sensitivity analysis of decision making units. First, by using DEA-R (ratiobased DEA models in the input orientation, the models of superefficiency and also models of super-efficiency modification are suggested. Second, the worst-case scenarios are considered where the efficiency of the test DMU is deteriorating while the efficiencies of the other DMUs are improving. Then, by combining these two ideas, a model is suggested which increases the super-efficiency score and modifies the change ranges in order to preserve the performance class. In the end, the super-efficiency and change interval of efficient decision making units for 23 branches of Zone 1 of the Islamic Azad University are calculated

  2. Noise guidelines across Canada : a practical look at the key inputs

    International Nuclear Information System (INIS)

    Marshall, J.

    2010-01-01

    Methods of applying noise guidelines in Canada to wind turbine siting plans were discussed. A noise impact analysis is a critical feature of wind turbine siting. However, noise impacts at the receptor (dBA) and their relation to the sound power levels emitted from wind turbines are not well-understood by wind power operators. Decibel and perceived sound levels were discussed, and issues related to noise modelling at the basic component level were reviewed. The inputs defined by different noise guidelines across Canada were outlined in order to determine the impact that inputs may have on the results of noise modelling studies. Various Canadian noise models were evaluated and compared. Noise modelling techniques were also discussed in relation to constraint maps and turbine siting strategies. tabs., figs.

  3. Control rod drive WWER 1000 – tuning of input parameters

    Directory of Open Access Journals (Sweden)

    Markov P.

    2007-10-01

    Full Text Available The article picks up on the contributions presented at the conferences Computational Mechanics 2005 and 2006, in which a calculational model of an upgraded control rod linear stepping drive for the reactors WWER 1000 (LKP-M/3 was described and results of analysis of dynamical response of its individual parts when moving up- and downwards were included. The contribution deals with the tuning of input parameters of the 3rd generation drive with the objective of reaching its running as smooth as possible so as to get a minimum wear of its parts as a result and hence to achieve maximum life-time.

  4. Cluster consensus in discrete-time networks of multiagents with inter-cluster nonidentical inputs.

    Science.gov (United States)

    Han, Yujuan; Lu, Wenlian; Chen, Tianping

    2013-04-01

    In this paper, cluster consensus of multiagent systems is studied via inter-cluster nonidentical inputs. Here, we consider general graph topologies, which might be time-varying. The cluster consensus is defined by two aspects: intracluster synchronization, the state at which differences between each pair of agents in the same cluster converge to zero, and inter-cluster separation, the state at which agents in different clusters are separated. For intra-cluster synchronization, the concepts and theories of consensus, including the spanning trees, scramblingness, infinite stochastic matrix product, and Hajnal inequality, are extended. As a result, it is proved that if the graph has cluster spanning trees and all vertices self-linked, then the static linear system can realize intra-cluster synchronization. For the time-varying coupling cases, it is proved that if there exists T > 0 such that the union graph across any T-length time interval has cluster spanning trees and all graphs has all vertices self-linked, then the time-varying linear system can also realize intra-cluster synchronization. Under the assumption of common inter-cluster influence, a sort of inter-cluster nonidentical inputs are utilized to realize inter-cluster separation, such that each agent in the same cluster receives the same inputs and agents in different clusters have different inputs. In addition, the boundedness of the infinite sum of the inputs can guarantee the boundedness of the trajectory. As an application, we employ a modified non-Bayesian social learning model to illustrate the effectiveness of our results.

  5. The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, T., E-mail: timo.ikonen@vtt.fi; Tulkki, V.

    2014-08-15

    Highlights: • Uncertainty and sensitivity analysis of modeled nuclear fuel behavior is performed. • Burnup dependency of the uncertainties and sensitivities is characterized. • Input interactions significantly increase output uncertainties for irradiated fuel. • Identification of uncertainty sources is greatly improved with higher order methods. • Results stress the importance of using methods that take interactions into account. - Abstract: The propagation of uncertainties in a PWR fuel rod under steady-state irradiation is analyzed by computational means. A hypothetical steady-state scenario of the Three Mile Island 1 reactor fuel rod is modeled with the fuel performance FRAPCON, using realistic input uncertainties for the fabrication and model parameters, boundary conditions and material properties. The uncertainty and sensitivity analysis is performed by extensive Monte Carlo sampling of the inputs’ probability distribution and by applying correlation coefficient and Sobol’ variance decomposition analyses. The latter includes evaluation of the second order and total effect sensitivity indices, allowing the study of interactions between input variables. The results show that the interactions play a large role in the propagation of uncertainties, and first order methods such as the correlation coefficient analyses are in general insufficient for sensitivity analysis of the fuel rod. Significant improvement over the first order methods can be achieved by using higher order methods. The results also show that both the magnitude of the uncertainties and their propagation depends not only on the output in question, but also on burnup. The latter is due to onset of new phenomena (such as the fission gas release) and the gradual closure of the pellet-cladding gap with increasing burnup. Increasing burnup also affects the importance of input interactions. Interaction effects are typically highest in the moderate burnup (of the order of 10–40 MWd

  6. Effects of Textual Enhancement and Input Enrichment on L2 Development

    Science.gov (United States)

    Rassaei, Ehsan

    2015-01-01

    Research on second language (L2) acquisition has recently sought to include formal instruction into second and foreign language classrooms in a more unobtrusive and implicit manner. Textual enhancement and input enrichment are two techniques which are aimed at drawing learners' attention to specific linguistic features in input and at the same…

  7. Calcium Input Frequency, Duration and Amplitude Differentially Modulate the Relative Activation of Calcineurin and CaMKII

    Science.gov (United States)

    Li, Lu; Stefan, Melanie I.; Le Novère, Nicolas

    2012-01-01

    NMDA receptor dependent long-term potentiation (LTP) and long-term depression (LTD) are two prominent forms of synaptic plasticity, both of which are triggered by post-synaptic calcium elevation. To understand how calcium selectively stimulates two opposing processes, we developed a detailed computational model and performed simulations with different calcium input frequencies, amplitudes, and durations. We show that with a total amount of calcium ions kept constant, high frequencies of calcium pulses stimulate calmodulin more efficiently. Calcium input activates both calcineurin and Ca2+/calmodulin-dependent protein kinase II (CaMKII) at all frequencies, but increased frequencies shift the relative activation from calcineurin to CaMKII. Irrespective of amplitude and duration of the inputs, the total amount of calcium ions injected adjusts the sensitivity of the system to calcium input frequencies. At a given frequency, the quantity of CaMKII activated is proportional to the total amount of calcium. Thus, an input of a small amount of calcium at high frequencies can induce the same activation of CaMKII as a larger amount, at lower frequencies. Finally, the extent of activation of CaMKII signals with high calcium frequency is further controlled by other factors, including the availability of calmodulin, and by the potency of phosphatase inhibitors. PMID:22962589

  8. 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)

  9. Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

    Energy Technology Data Exchange (ETDEWEB)

    Biyanto, Totok R. [Department of Engineering Physics, Institute Technology of Sepuluh Nopember Surabaya, Surabaya, Indonesia 60111 (Indonesia)

    2016-06-03

    Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.

  10. Discrete Input Signaling for MISO Visible Light Communication Channels

    KAUST Repository

    Arfaoui, Mohamed Amine

    2017-05-12

    In this paper, we study the achievable secrecy rate of visible light communication (VLC) links for discrete input distributions. We consider single user single eavesdropper multiple-input single-output (MISO) links. In addition, both beamforming and robust beamforming are considered. In the former case, the location of the eavesdropper is assumed to be known, whereas in the latter case, the location of the eavesdropper is unknown. We compare the obtained results with those achieved by some continuous distributions including the truncated generalized normal (TGN) distribution and the uniform distribution. We numerically show that the secrecy rate achieved by the discrete input distribution with a finite support is significantly improved as compared to those achieved by the TGN and the uniform distributions.

  11. On Optimal Input Design for Feed-forward Control

    OpenAIRE

    Hägg, Per; Wahlberg, Bo

    2013-01-01

    This paper considers optimal input design when the intended use of the identified model is to construct a feed-forward controller based on measurable disturbances. The objective is to find a minimum power excitation signal to be used in a system identification experiment, such that the corresponding model-based feed-forward controller guarantees, with a given probability, that the variance of the output signal is within given specifications. To start with, some low order model problems are an...

  12. Energy Input Flux in the Global Quiet-Sun Corona

    Energy Technology Data Exchange (ETDEWEB)

    Mac Cormack, Cecilia; Vásquez, Alberto M.; López Fuentes, Marcelo; Nuevo, Federico A. [Instituto de Astronomía y Física del Espacio (IAFE), CONICET-UBA, CC 67—Suc 28, (C1428ZAA) Ciudad Autónoma de Buenos Aires (Argentina); Landi, Enrico; Frazin, Richard A. [Department of Climate and Space Sciences and Engineering (CLaSP), University of Michigan, 2455 Hayward Street, Ann Arbor, MI 48109-2143 (United States)

    2017-07-01

    We present first results of a novel technique that provides, for the first time, constraints on the energy input flux at the coronal base ( r ∼ 1.025 R {sub ⊙}) of the quiet Sun at a global scale. By combining differential emission measure tomography of EUV images, with global models of the coronal magnetic field, we estimate the energy input flux at the coronal base that is required to maintain thermodynamically stable structures. The technique is described in detail and first applied to data provided by the Extreme Ultraviolet Imager instrument, on board the Solar TErrestrial RElations Observatory mission, and the Atmospheric Imaging Assembly instrument, on board the Solar Dynamics Observatory mission, for two solar rotations with different levels of activity. Our analysis indicates that the typical energy input flux at the coronal base of magnetic loops in the quiet Sun is in the range ∼0.5–2.0 × 10{sup 5} (erg s{sup −1} cm{sup −2}), depending on the structure size and level of activity. A large fraction of this energy input, or even its totality, could be accounted for by Alfvén waves, as shown by recent independent observational estimates derived from determinations of the non-thermal broadening of spectral lines in the coronal base of quiet-Sun regions. This new tomography product will be useful for the validation of coronal heating models in magnetohydrodinamic simulations of the global corona.

  13. Multiregional input-output model for China's farm land and water use.

    Science.gov (United States)

    Guo, Shan; Shen, Geoffrey Qiping

    2015-01-06

    Land and water are the two main drivers of agricultural production. Pressure on farm land and water resources is increasing in China due to rising food demand. Domestic trade affects China's regional farm land and water use by distributing resources associated with the production of goods and services. This study constructs a multiregional input-output model to simultaneously analyze China's farm land and water uses embodied in consumption and interregional trade. Results show a great similarity for both China's farm land and water endowments. Shandong, Henan, Guangdong, and Yunnan are the most important drivers of farm land and water consumption in China, even though they have relatively few land and water resource endowments. Significant net transfers of embodied farm land and water flows are identified from the central and western areas to the eastern area via interregional trade. Heilongjiang is the largest farm land and water supplier, in contrast to Shanghai as the largest receiver. The results help policy makers to comprehensively understand embodied farm land and water flows in a complex economy network. Improving resource utilization efficiency and reshaping the embodied resource trade nexus should be addressed by considering the transfer of regional responsibilities.

  14. Assessing the suitability of input-output analysis for enhancing our understanding of potential economic effects of Peak Oil

    International Nuclear Information System (INIS)

    Kerschner, Christian; Hubacek, Klaus

    2009-01-01

    Given recent developments on energy markets and skyrocketing oil prices, we argue for an urgent need to study the potential effects of world oil production reaching a maximum (Peak Oil) in order to facilitate the development of adaptation policies. We consider input-output (IO) modelling as a powerful tool for this purpose. However, the standard Leontief type model implicitly assumes that all necessary inputs to satisfy a given demand can and will be supplied. This is problematic if the availability of certain key inputs becomes restricted and it is therefore only of limited usefulness for the study of the phenomenon of Peak Oil. Hence this paper firstly reviews two alternative modelling tools within the IO framework: supply-driven and mixed models. The former has been severely criticised for its problematic assumption of perfect factor substitution and perfect elasticity of demand as revealed by Oosterhaven [Oosterhaven J. On the plausibility of the supply-driven IO model. J Reg Sci 1988; 28:203-17. ]. The supply-constrained model on the other hand proved well suited to analyse the quantity dimension of Peak Oil and is therefore applied empirically in the second part of the paper, using data for the UK, Japanese and Chilean economy. Results show how differences in net-oil exporting and net-oil importing countries are clearly visible in terms of final demand. Industries, most affected in all countries, include transportation, electricity production and financial and trade services. (author)

  15. SSYST-3. Input description

    International Nuclear Information System (INIS)

    Meyder, R.

    1983-12-01

    The code system SSYST-3 is designed to analyse the thermal and mechanical behaviour of a fuel rod during a LOCA. The report contains a complete input-list for all modules and several tested inputs for a LOCA analysis. (orig.)

  16. Method of fuzzy inference for one class of MISO-structure systems with non-singleton inputs

    Science.gov (United States)

    Sinuk, V. G.; Panchenko, M. V.

    2018-03-01

    In fuzzy modeling, the inputs of the simulated systems can receive both crisp values and non-Singleton. Computational complexity of fuzzy inference with fuzzy non-Singleton inputs corresponds to an exponential. This paper describes a new method of inference, based on the theorem of decomposition of a multidimensional fuzzy implication and a fuzzy truth value. This method is considered for fuzzy inputs and has a polynomial complexity, which makes it possible to use it for modeling large-dimensional MISO-structure systems.

  17. High Flux Isotope Reactor system RELAP5 input model

    International Nuclear Information System (INIS)

    Morris, D.G.; Wendel, M.W.

    1993-01-01

    A thermal-hydraulic computational model of the High Flux Isotope Reactor (HFIR) has been developed using the RELAP5 program. The purpose of the model is to provide a state-of-the art thermal-hydraulic simulation tool for analyzing selected hypothetical accident scenarios for a revised HFIR Safety Analysis Report (SAR). The model includes (1) a detailed representation of the reactor core and other vessel components, (2) three heat exchanger/pump cells, (3) pressurizing pumps and letdown valves, and (4) secondary coolant system (with less detail than the primary system). Data from HFIR operation, component tests, tests in facility mockups and the HFIR, HFIR specific experiments, and other pertinent experiments performed independent of HFIR were used to construct the model and validate it to the extent permitted by the data. The detailed version of the model has been used to simulate loss-of-coolant accidents (LOCAs), while the abbreviated version has been developed for the operational transients that allow use of a less detailed nodalization. Analysis of station blackout with core long-term decay heat removal via natural convection has been performed using the core and vessel portions of the detailed model

  18. Material input of nuclear fuel

    International Nuclear Information System (INIS)

    Rissanen, S.; Tarjanne, R.

    2001-01-01

    The Material Input (MI) of nuclear fuel, expressed in terms of the total amount of natural material needed for manufacturing a product, is examined. The suitability of the MI method for assessing the environmental impacts of fuels is also discussed. Material input is expressed as a Material Input Coefficient (MIC), equalling to the total mass of natural material divided by the mass of the completed product. The material input coefficient is, however, only an intermediate result, which should not be used as such for the comparison of different fuels, because the energy contents of nuclear fuel is about 100 000-fold compared to the energy contents of fossil fuels. As a final result, the material input is expressed in proportion to the amount of generated electricity, which is called MIPS (Material Input Per Service unit). Material input is a simplified and commensurable indicator for the use of natural material, but because it does not take into account the harmfulness of materials or the way how the residual material is processed, it does not alone express the amount of environmental impacts. The examination of the mere amount does not differentiate between for example coal, natural gas or waste rock containing usually just sand. Natural gas is, however, substantially more harmful for the ecosystem than sand. Therefore, other methods should also be used to consider the environmental load of a product. The material input coefficient of nuclear fuel is calculated using data from different types of mines. The calculations are made among other things by using the data of an open pit mine (Key Lake, Canada), an underground mine (McArthur River, Canada) and a by-product mine (Olympic Dam, Australia). Furthermore, the coefficient is calculated for nuclear fuel corresponding to the nuclear fuel supply of Teollisuuden Voima (TVO) company in 2001. Because there is some uncertainty in the initial data, the inaccuracy of the final results can be even 20-50 per cent. The value

  19. Sensory Synergy as Environmental Input Integration

    Directory of Open Access Journals (Sweden)

    Fady eAlnajjar

    2015-01-01

    Full Text Available The development of a method to feed proper environmental inputs back to the central nervous system (CNS remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with 9 healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis’ sensory system to make the controller simpler

  20. Sensory synergy as environmental input integration.

    Science.gov (United States)

    Alnajjar, Fady; Itkonen, Matti; Berenz, Vincent; Tournier, Maxime; Nagai, Chikara; Shimoda, Shingo

    2014-01-01

    The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with nine healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis' sensory system to make the controller simpler.

  1. Chemical sensors are hybrid-input memristors

    Science.gov (United States)

    Sysoev, V. I.; Arkhipov, V. E.; Okotrub, A. V.; Pershin, Y. V.

    2018-04-01

    Memristors are two-terminal electronic devices whose resistance depends on the history of input signal (voltage or current). Here we demonstrate that the chemical gas sensors can be considered as memristors with a generalized (hybrid) input, namely, with the input consisting of the voltage, analyte concentrations and applied temperature. The concept of hybrid-input memristors is demonstrated experimentally using a single-walled carbon nanotubes chemical sensor. It is shown that with respect to the hybrid input, the sensor exhibits some features common with memristors such as the hysteretic input-output characteristics. This different perspective on chemical gas sensors may open new possibilities for smart sensor applications.

  2. Modeling imbalanced economic recovery following a natural disaster using input-output analysis.

    Science.gov (United States)

    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.

  3. How input fluctuations reshape the dynamics of a biological switching system

    Science.gov (United States)

    Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

    2012-12-01

    An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

  4. Descending projections from the dysgranular zone of rat primary somatosensory cortex processing deep somatic input.

    Science.gov (United States)

    Lee, Taehee; Kim, Uhnoh

    2012-04-01

    In the mammalian somatic system, peripheral inputs from cutaneous and deep receptors ascend via different subcortical channels and terminate in largely separate regions of the primary somatosensory cortex (SI). How these inputs are processed in SI and then projected back to the subcortical relay centers is critical for understanding how SI may regulate somatic information processing in the subcortex. Although it is now relatively well understood how SI cutaneous areas project to the subcortical structures, little is known about the descending projections from SI areas processing deep somatic input. We examined this issue by using the rodent somatic system as a model. In rat SI, deep somatic input is processed mainly in the dysgranular zone (DSZ) enclosed by the cutaneous barrel subfields. By using biotinylated dextran amine (BDA) as anterograde tracer, we characterized the topography of corticostriatal and corticofugal projections arising in the DSZ. The DSZ projections terminate mainly in the lateral subregions of the striatum that are also known as the target of certain SI cutaneous areas. This suggests that SI processing of deep and cutaneous information may be integrated, to a certain degree, in this striatal region. By contrast, at both thalamic and prethalamic levels as far as the spinal cord, descending projections from DSZ terminate in areas largely distinguishable from those that receive input from SI cutaneous areas. These subcortical targets of DSZ include not only the sensory but also motor-related structures, suggesting that SI processing of deep input may engage in regulating somatic and motor information flow between the cortex and periphery. Copyright © 2011 Wiley-Liss, Inc.

  5. DETERMINANTS OF FARMERS’ WILLINGNESS TO PAYFOR SUBSIDISED FARM INPUTS IN MALAWI

    Directory of Open Access Journals (Sweden)

    Laston Petro Manja

    2015-01-01

    Full Text Available Most recently, citing low price elasticity of demand for inputs in theagro-based Malawian economy, economists and non-economistshave advocated for increasing prices forsubsidizedinputs. However,elasticities alone arenot enoughto make inferencessince knowledgeof whether higher prices are indeed affordableby farmers is ofspecialsignificance. This study uses the standard The results revealthat smallholder farmers are willing to pay for more inputs in theFarm Input Subsidy Programme (FISP withthe mean WTP for eachhouseholdat MK 1000beingabout ten50kgfertilizerbags and thetotal WTP at the same price being46891 bags per yearfor4742 observedhouseholds. Using datafrom the Malawi 2011/12 FarmInput Subsidy Study (FISS4, the model identifies age,sexandeducationof household head, farm size,food securityas well asradioownershipas positivedeterminants ofWTP;withcoupon receipt andfarm incomes as negative determinants.

  6. Enhancement of regional wet deposition estimates based on modeled precipitation inputs

    Science.gov (United States)

    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....

  7. How to Manage Inputs from Co-production Processes in Emergy Accounting

    DEFF Research Database (Denmark)

    Kamp, Andreas; Østergård, Hanne

    2012-01-01

    In life cycle assessments it is a challenge to allocate resource use and environmental impact in processes with multiple outputs. This is especially the case when systems include agricultural products that in their production cannot be separated from each other. For emergy accounting, Bastianoni...... with systems that do not depend on joint production processes is still lacking. As a consequence, a product relying on inputs from joint production processes appears to compete poorly with a similar product that does not have to account for co-products appearing upstream. This is counter to perceived benefits...... and Marchettini (2000) suggested how to calculate transformities and other indices for joint production systems. Their proposals however, do not include how to manage inputs from joint production systems. Thus a practical method for making systems with inputs from joint production processes comparable...

  8. How to manage inputs from joint production processes in emergy accounting

    DEFF Research Database (Denmark)

    Kamp, Andreas; Østergård, Hanne

    In life-cycle assessments it is a challenge to allocate resource use and environmental impact in processes with multiple outputs. This is especially the case when systems include agricultural products that in their production cannot be separated from each other. For emergy accounting, Bastianoni...... with systems that do not depend on joint production processes is still lacking. As a consequence, a product relying on inputs from joint production processes appears to compete poorly with a similar product that does not have to account for by-products appearing upstream. This is counter to perceived benefits...... and Marchettini (2000) suggested how to calculate transformities and other indices for joint production systems. Their proposals however, do not include how to manage inputs from joint production systems. Thus a practical method for making systems with inputs from joint production processes comparable...

  9. Decision Aids for Multiple-Decision Disease Management as Affected by Weather Input Errors

    Science.gov (United States)

    Many disease management decision support systems (DSS) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation or estimation from off-site sources, may affect model calculations and manage...

  10. Input subsidies and demand for improved maize : relative prices and household heterogeneity matter!

    OpenAIRE

    Holden, Stein Terje

    2013-01-01

    This study uses simple non-separable farm household models calibrated to household, market, farming and policy context conditions in Central and Southern Malawi. The models are used to simulate how household characteristics, design and access to input subsidies affect the demand for improved maize seeds; how increasing land scarcity affects the cropping system and demand for improved maize; and how access to improved maize seeds affects household welfare with varying access to input subsidies...

  11. Testing accelerometer rectification error caused by multidimensional composite inputs with double turntable centrifuge.

    Science.gov (United States)

    Guan, W; Meng, X F; Dong, X M

    2014-12-01

    Rectification error is a critical characteristic of inertial accelerometers. Accelerometers working in operational situations are stimulated by composite inputs, including constant acceleration and vibration, from multiple directions. However, traditional methods for evaluating rectification error only use one-dimensional vibration. In this paper, a double turntable centrifuge (DTC) was utilized to produce the constant acceleration and vibration simultaneously and we tested the rectification error due to the composite accelerations. At first, we deduced the expression of the rectification error with the output of the DTC and a static model of the single-axis pendulous accelerometer under test. Theoretical investigation and analysis were carried out in accordance with the rectification error model. Then a detailed experimental procedure and testing results were described. We measured the rectification error with various constant accelerations at different frequencies and amplitudes of the vibration. The experimental results showed the distinguished characteristics of the rectification error caused by the composite accelerations. The linear relation between the constant acceleration and the rectification error was proved. The experimental procedure and results presented in this context can be referenced for the investigation of the characteristics of accelerometer with multiple inputs.

  12. 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...... for symmetric and asymmetric multi-species electrolytes and is not limited to a range of surface potentials. Numerical simulations are presented, for the case of a CaCO3 electrolyte solution in contact with a surface with rate-controlled protonation/deprotonation reactions. The surface charge and potential...... are determined by the surface reactions, and therefore they depends on the bulk solution composition and concentration...

  13. Metacognitive Instruction: Global and Local Shifts in Considering Listening Input

    Directory of Open Access Journals (Sweden)

    Hossein Bozorgian

    2013-01-01

    Full Text Available A key shift of thinking for effective learning and teaching of listening input has been seen and organized in education locally and globally. This study has probed whether metacognitive instruction through a pedagogical cycle shifts high-intermediate students' English language learning and English as a second language (ESL teacher's teaching focus on listening input. Twenty male Iranian students with an age range of 18 to 24 received a guided methodology including metacognitive strategies (planning, monitoring, and evaluation for a period of three months. This study has used the strategies and probed the importance of metacognitive instruction through interviewing both the teacher and the students. The results have shown that metacognitive instruction helped both the ESL teacher's and the students' shift of thinking about teaching and learning listening input. This key shift of thinking has implications globally and locally for classroom practices of listening input.

  14. A response analysis with effective stress model by using vertical input motions

    International Nuclear Information System (INIS)

    Yamanouchi, H.; Ohkawa, I.; Chiba, O.; Tohdo, M.; Kaneko, O.

    1987-01-01

    The nuclear power plant reactor buildings are to be directly supported on a hard soil as a rule in Japan. In case of determining the input motions in order to design those buildings, the amplifications of the hard soil deposits are examined by the total stress analysis in general. However, when the supporting hard soil is replaced with the slightly softer medium such as sandy or gravelly soil, the existence of pore water, in other words, the contribution of the pore water pressure to the total stress cannot be ignored even in a practical sense. In this paper the authors defined an analytical model considering the effective stress-strain relation. In the analyses, the response in the vertical direction is used to evaluate the confining pressure, at first. In the next step, the process of the generation and dissipation of the pore water pressure, is taken into account, together with the effect of the confining pressure. They applied these procedures for the response computations of the horizontally layered soil deposits

  15. SCDAP/RELAP5/MOD 3.1 code manual: User's guide and input manual. Volume 3

    International Nuclear Information System (INIS)

    Coryell, E.W.; Johnsen, E.C.; Allison, C.M.

    1995-06-01

    The SCDAP/RELAP5 code has been developed for best estimate transient simulation of light water reactor coolant systems during a severe accident. The code models the coupled behavior of the reactor coolant system, core, fission product released during a severe accident transient as well as large and small break loss of coolant accidents, operational transients such as anticipated transient without SCRAM, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits as much of a particular system to be modeled as necessary. Control system and secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater conditioning systems. This volume provides guidelines to code users based upon lessons learned during the developmental assessment process. A description of problem control and the installation process is included. Appendix a contains the description of the input requirements

  16. Asymmetric Temporal Integration of Layer 4 and Layer 2/3 Inputs in Visual Cortex

    OpenAIRE

    Hang, Giao B.; Dan, Yang

    2010-01-01

    Neocortical neurons in vivo receive concurrent synaptic inputs from multiple sources, including feedforward, horizontal, and feedback pathways. Layer 2/3 of the visual cortex receives feedforward input from layer 4 and horizontal input from layer 2/3. Firing of the pyramidal neurons, which carries the output to higher cortical areas, depends critically on the interaction of these pathways. Here we examined synaptic integration of inputs from layer 4 and layer 2/3 in rat visual cortical slices...

  17. Road simulation for four-wheel vehicle whole input power spectral density

    Science.gov (United States)

    Wang, Jiangbo; Qiang, Baomin

    2017-05-01

    As the vibration of running vehicle mainly comes from road and influence vehicle ride performance. So the road roughness power spectral density simulation has great significance to analyze automobile suspension vibration system parameters and evaluate ride comfort. Firstly, this paper based on the mathematical model of road roughness power spectral density, established the integral white noise road random method. Then in the MATLAB/Simulink environment, according to the research method of automobile suspension frame from simple two degree of freedom single-wheel vehicle model to complex multiple degrees of freedom vehicle model, this paper built the simple single incentive input simulation model. Finally the spectrum matrix was used to build whole vehicle incentive input simulation model. This simulation method based on reliable and accurate mathematical theory and can be applied to the random road simulation of any specified spectral which provides pavement incentive model and foundation to vehicle ride performance research and vibration simulation.

  18. The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs

    Science.gov (United States)

    Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei

    This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

  19. Statistical analysis of two-degree of freedom systems to time history inputs with different durations

    International Nuclear Information System (INIS)

    Lin, C.W.; Li, D.L.

    1987-01-01

    A statistical study is conducted to determine the effect of input time history duration on the response of systems supported by the structure. The model used in the study is a one-degree-of-freedom system mass supported by another one degree of freedom structure mass. The input used is generated from a Monte-Carlo simulation procedure with a prescribed power spectrum density such that the input response spectrum matched the Reg. Guide 1.60 response spectrum. The models were analyzed for different combinations of mass ratios and frequency ratios (ratios of the system versus the supporting structure). Time history inputs used vary from 5 to 20 seconds. Only the 20 second time history matched the Reg. Guide 1.60 response spectrum. Time history inputs shorter than 20 seconds were simply truncated at the tail end. The results of the study indicate that it is necessary to increase the response magnitude by about 20% if a 5-second time history is to be used. For a 10-second input, an increase of 10% will suffice. Whereas for a 15-second input, no adjustment is necessary. (orig./HP)

  20. IAEA nuclear data for applications: Cross section standards and the reference input parameter library (RIPL)

    International Nuclear Information System (INIS)

    Capote Noy, Roberto; Nichols, Alan L.; Pronyaev, Vladimir G.

    2003-01-01

    An integral part of the activities of the IAEA Nuclear Data Section involves the development of nuclear data for a wide range of user applications. When considering low-energy nuclear reactions induced by neutrons, photons and charged particles, a detailed knowledge is required of the production cross sections over a wide energy range, spectra of emitted particles and their angular distributions. Two highly relevant IAEA data development projects are considered in this paper. Neutron reaction cross-section standards represent the basic quantities needed in nuclear reaction cross-section measurements and evaluations. These standards and the covariance matrices of their uncertainties were previously evaluated and released in 1987. However, the derived uncertainties were subsequently considered to be unrealistic low due to the effect of the low uncertainties obtained in fitting the light element standards to the R-matrix model; as a result, evaluators were forced to scale up the uncertainties to 'expected values'. An IAEA Coordinated Research Project (CRP) entitled 'Improvement of the Standard Cross Sections for Light Elements' was initiated in 2002 to improve the evaluation methodology for the covariance matrix of uncertainty in the R-matrix model fits, and to produce R-matrix evaluations of the important light element standards. The scope of this CRP has been substantially extended to include the preparation of a full set of evaluated standard reactions and covariance matrices of their uncertainties. While almost all requests for nuclear data were originally addressed through measurement programmes, our theoretical understanding of nuclear phenomena has reached a reasonable degree of reliability and nuclear modeling has become standard practice in nuclear data evaluations (with measurements remaining crucial for data testing and benchmarking). Since nuclear model codes require a considerable amount of numerical input, the IAEA has instigated extensive efforts to

  1. Combining symbolic cues with sensory input and prior experience in an iterative Bayesian framework

    Directory of Open Access Journals (Sweden)

    Frederike Hermi Petzschner

    2012-08-01

    Full Text Available Perception and action are the result of an integration of various sources of information, such as current sensory input, prior experience, or the context in which a stimulus occurs. Often, the interpretation is not trivial hence needs to be learned from the co-occurrence of stimuli. Yet, how do we combine such diverse information to guide our action?Here we use a distance production-reproduction task to investigate the influence of auxiliary, symbolic cues, sensory input, and prior experience on human performance under three different conditions that vary in the information provided. Our results indicate that subjects can (1 learn the mapping of a verbal, symbolic cue onto the stimulus dimension and (2 integrate symbolic information and prior experience into their estimate of displacements.The behavioral results are explained by to two distinct generative models that represent different structural approaches of how a Bayesian observer would combine prior experience, sensory input, and symbolic cue information into a single estimate of displacement. The first model interprets the symbolic cue in the context of categorization, assuming that it reflects information about a distinct underlying stimulus range (categorical model. The second model applies a multi-modal integration approach and treats the symbolic cue as additional sensory input to the system, which is combined with the current sensory measurement and the subjects’ prior experience (cue-combination model. Notably, both models account equally well for the observed behavior despite their different structural assumptions. The present work thus provides evidence that humans can interpret abstract symbolic information and combine it with other types of information such as sensory input and prior experience. The similar explanatory power of the two models further suggest that issues such as categorization and cue-combination could be explained by alternative probabilistic approaches.

  2. MODEL OF THE TOKAMAK EDGE DENSITY PEDESTAL INCLUDING DIFFUSIVE NEUTRALS

    International Nuclear Information System (INIS)

    BURRELL, K.H.

    2003-01-01

    OAK-B135 Several previous analytic models of the tokamak edge density pedestal have been based on diffusive transport of plasma plus free-streaming of neutrals. This latter neutral model includes only the effect of ionization and neglects charge exchange. The present work models the edge density pedestal using diffusive transport for both the plasma and the neutrals. In contrast to the free-streaming model, a diffusion model for the neutrals includes the effect of both charge exchange and ionization and is valid when charge exchange is the dominant interaction. Surprisingly, the functional forms for the electron and neutral density profiles from the present calculation are identical to the results of the previous analytic models. There are some differences in the detailed definition of various parameters in the solution. For experimentally relevant cases where ionization and charge exchange rate are comparable, both models predict approximately the same width for the edge density pedestal

  3. Identification and Quantification of Uncertainties Related to Using Distributed X-band Radar Estimated Precipitation as input in Urban Drainage Models

    DEFF Research Database (Denmark)

    Pedersen, Lisbeth

    The Local Area Weather Radar (LAWR) is a small scale weather radar providing distributed measurements of rainfall primarily for use as input in hydrological applications. As any other weather radar the LAWR measurement of the rainfall is an indirect measurement since it does not measure the rainf......The Local Area Weather Radar (LAWR) is a small scale weather radar providing distributed measurements of rainfall primarily for use as input in hydrological applications. As any other weather radar the LAWR measurement of the rainfall is an indirect measurement since it does not measure...... are quantified using statistical methods. Furthermore, the present calibration method is reviewed and a new extended calibration method has been developed and tested resulting in improved rainfall estimates. As part of the calibration analysis a number of elements affecting the LAWR performance were identified...... in connection with boundary assignment besides general improved understanding of the benefits and pitfalls in using distributed rainfall data as input to models. In connection with the use of LAWR data in urban drainage context, the potential for using LAWR data for extreme rainfall statistics has been studied...

  4. Identifying weaknesses in undergraduate programs within the context input process product model framework in view of faculty and library staff in 2014

    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.

  5. Automatic individual arterial input functions calculated from PCA outperform manual and population-averaged approaches for the pharmacokinetic modeling of DCE-MR images.

    Science.gov (United States)

    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.

  6. MDS MIC Catalog Inputs

    Science.gov (United States)

    Johnson-Throop, Kathy A.; Vowell, C. W.; Smith, Byron; Darcy, Jeannette

    2006-01-01

    This viewgraph presentation reviews the inputs to the MDS Medical Information Communique (MIC) catalog. The purpose of the group is to provide input for updating the MDS MIC Catalog and to request that MMOP assign Action Item to other working groups and FSs to support the MITWG Process for developing MIC-DDs.

  7. Opening the "Black Box" of efficiency measurement : Input allocation in multi-output settings

    NARCIS (Netherlands)

    Dierynck, B.; Cherchye, L.J.H.; Sabbe, J.; Roodhooft, F.; de Rock, B.

    2013-01-01

    We develop a new data envelopment analysis (DEA)-based methodology for measuring the efficiency of decision-making units (DMUs) characterized by multiple inputs and multiple outputs. The distinguishing feature of our method is that it explicitly includes information about output-specific inputs and

  8. WE-FG-206-06: Dual-Input Tracer Kinetic Modeling and Its Analog Implementation for Dynamic Contrast-Enhanced (DCE-) MRI of Malignant Mesothelioma (MPM)

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S; Rimner, A; Hayes, S; Hunt, M; Deasy, J; Zauderer, M; Rusch, V; Tyagi, N [Memorial Sloan Kettering Cancer Center, New York, NY (United States)

    2016-06-15

    Purpose: To use dual-input tracer kinetic modeling of the lung for mapping spatial heterogeneity of various kinetic parameters in malignant MPM Methods: Six MPM patients received DCE-MRI as part of their radiation therapy simulation scan. 5 patients had the epitheloid subtype of MPM, while one was biphasic. A 3D fast-field echo sequence with TR/TE/Flip angle of 3.62ms/1.69ms/15° was used for DCE-MRI acquisition. The scan was collected for 5 minutes with a temporal resolution of 5-9 seconds depending on the spatial extent of the tumor. A principal component analysis-based groupwise deformable registration was used to co-register all the DCE-MRI series for motion compensation. All the images were analyzed using five different dual-input tracer kinetic models implemented in analog continuous-time formalism: the Tofts-Kety (TK), extended TK (ETK), two compartment exchange (2CX), adiabatic approximation to the tissue homogeneity (AATH), and distributed parameter (DP) models. The following parameters were computed for each model: total blood flow (BF), pulmonary flow fraction (γ), pulmonary blood flow (BF-pa), systemic blood flow (BF-a), blood volume (BV), mean transit time (MTT), permeability-surface area product (PS), fractional interstitial volume (vi), extraction fraction (E), volume transfer constant (Ktrans) and efflux rate constant (kep). Results: Although the majority of patients had epitheloid histologies, kinetic parameter values varied across different models. One patient showed a higher total BF value in all models among the epitheloid histologies, although the γ value was varying among these different models. In one tumor with a large area of necrosis, the TK and ETK models showed higher E, Ktrans, and kep values and lower interstitial volume as compared to AATH and DP and 2CX models. Kinetic parameters such as BF-pa, BF-a, PS, Ktrans values were higher in surviving group compared to non-surviving group across most models. Conclusion: Dual-input tracer

  9. Dose uncertainties for large solar particle events: Input spectra variability and human geometry approximations

    International Nuclear Information System (INIS)

    Townsend, Lawrence W.; Zapp, E. Neal

    1999-01-01

    The true uncertainties in estimates of body organ absorbed dose and dose equivalent, from exposures of interplanetary astronauts to large solar particle events (SPEs), are essentially unknown. Variations in models used to parameterize SPE proton spectra for input into space radiation transport and shielding computer codes can result in uncertainty about the reliability of dose predictions for these events. Also, different radiation transport codes and their input databases can yield significant differences in dose predictions, even for the same input spectra. Different results may also be obtained for the same input spectra and transport codes if different spacecraft and body self-shielding distributions are assumed. Heretofore there have been no systematic investigations of the variations in dose and dose equivalent resulting from these assumptions and models. In this work we present a study of the variability in predictions of organ dose and dose equivalent arising from the use of different parameters to represent the same incident SPE proton data and from the use of equivalent sphere approximations to represent human body geometry. The study uses the BRYNTRN space radiation transport code to calculate dose and dose equivalent for the skin, ocular lens and bone marrow using the October 1989 SPE as a model event. Comparisons of organ dose and dose equivalent, obtained with a realistic human geometry model and with the oft-used equivalent sphere approximation, are also made. It is demonstrated that variations of 30-40% in organ dose and dose equivalent are obtained for slight variations in spectral fitting parameters obtained when various data points are included or excluded from the fitting procedure. It is further demonstrated that extrapolating spectra from low energy (≤30 MeV) proton fluence measurements, rather than using fluence data extending out to 100 MeV results in dose and dose equivalent predictions that are underestimated by factors as large as 2

  10. BALANCED SCORECARDS EVALUATION MODEL THAT INCLUDES ELEMENTS OF ENVIRONMENTAL MANAGEMENT SYSTEM USING AHP MODEL

    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.

  11. 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)

  12. Whole-Brain Monosynaptic Afferent Inputs to Basal Forebrain Cholinergic System

    Directory of Open Access Journals (Sweden)

    Rongfeng Hu

    2016-10-01

    Full Text Available The basal forebrain cholinergic system (BFCS robustly modulates many important behaviors, such as arousal, attention, learning and memory, through heavy projections to cortex and hippocampus. However, the presynaptic partners governing BFCS activity still remain poorly understood. Here, we utilized a recently developed rabies virus-based cell-type-specific retrograde tracing system to map the whole-brain afferent inputs of the BFCS. We found that the BFCS receives inputs from multiple cortical areas, such as orbital frontal cortex, motor cortex, and insular cortex, and that the BFCS also receives dense inputs from several subcortical nuclei related to motivation and stress, including lateral septum (LS, central amygdala (CeA, paraventricular nucleus of hypothalamus (PVH, dorsal raphe (DRN and parabrachial nucleus (PBN. Interestingly, we found that the BFCS receives inputs from the olfactory areas and the entorhinal-hippocampal system. These results greatly expand our knowledge about the connectivity of the mouse BFCS and provided important preliminary indications for future exploration of circuit function.

  13. Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

    Science.gov (United States)

    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

  14. Adaptive distributed parameter and input estimation in linear parabolic PDEs

    KAUST Repository

    Mechhoud, Sarra

    2016-01-01

    First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.

  15. Analysis of inter-country input-output table based on bibliographic coupling network: How industrial sectors on the GVC compete for production resources

    Science.gov (United States)

    Guan, Jun; Xu, Xiaoyu; Xing, Lizhi

    2018-03-01

    The input-output table is comprehensive and detailed in describing national economic systems with abundance of economic relationships depicting information of supply and demand among industrial sectors. This paper focuses on how to quantify the degree of competition on the global value chain (GVC) from the perspective of econophysics. Global Industrial Strongest Relevant Network models are established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output (ICIO) tables and then have them transformed into Global Industrial Resource Competition Network models to analyze the competitive relationships based on bibliographic coupling approach. Three indicators well suited for the weighted and undirected networks with self-loops are introduced here, including unit weight for competitive power, disparity in the weight for competitive amplitude and weighted clustering coefficient for competitive intensity. Finally, these models and indicators were further applied empirically to analyze the function of industrial sectors on the basis of the latest World Input-Output Database (WIOD) in order to reveal inter-sector competitive status during the economic globalization.

  16. Model for safety reports including descriptive examples

    International Nuclear Information System (INIS)

    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

  17. Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding.

    Science.gov (United States)

    Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

    2015-02-01

    Fine-scale temporal organization of cortical activity in the gamma range (∼25-80Hz) may play a significant role in information processing, for example by neural grouping ('binding') and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes

  18. Modelling a linear PM motor including magnetic saturation

    NARCIS (Netherlands)

    Polinder, H.; Slootweg, J.G.; Compter, J.C.; Hoeijmakers, M.J.

    2002-01-01

    The use of linear permanent-magnet (PM) actuators increases in a wide variety of applications because of the high force density, robustness and accuracy. The paper describes the modelling of a linear PM motor applied in, for example, wafer steppers, including magnetic saturation. This is important

  19. The prioritisation of invasive alien plant control projects using a multi-criteria decision model informed by stakeholder input and spatial data.

    Science.gov (United States)

    Forsyth, G G; Le Maitre, D C; O'Farrell, P J; van Wilgen, B W

    2012-07-30

    Invasions by alien plants are a significant threat to the biodiversity and functioning of ecosystems and the services they provide. The South African Working for Water program was established to address this problem. It needs to formulate objective and transparent priorities for clearing in the face of multiple and sometimes conflicting demands. This study used the analytic hierarchy process (a multi-criteria decision support technique) to develop and rank criteria for prioritising alien plant control operations in the Western Cape, South Africa. Stakeholder workshops were held to identify a goal and criteria and to conduct pair-wise comparisons to weight the criteria with respect to invasive alien plant control. The combination of stakeholder input (to develop decision models) with data-driven model solutions enabled us to include many alternatives (water catchments), that would otherwise not have been feasible. The most important criteria included the capacity to maintain gains made through control operations, the potential to enhance water resources and conserve biodiversity, and threats from priority invasive alien plant species. We selected spatial datasets and used them to generate weights that could be used to objectively compare alternatives with respect to agreed criteria. The analysis showed that there are many high priority catchments which are not receiving any funding and low priority catchments which are receiving substantial allocations. Clearly, there is a need for realigning priorities, including directing sufficient funds to the highest priority catchments to provide effective control. This approach provided a tractable, consensus-based solution that can be used to direct clearing operations. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

    Science.gov (United States)

    Wang, G.

    2017-12-01

    Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

  1. Critical carbon input to maintain current soil organic carbon stocks in global wheat systems.

    Science.gov (United States)

    Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

    2016-01-13

    Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha(-1) yr(-1), with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

  2. Input filter compensation for switching regulators

    Science.gov (United States)

    Lee, F. C.; Kelkar, S. S.

    1982-01-01

    The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.

  3. A new quantum flux parametron logic gate with large input margin

    International Nuclear Information System (INIS)

    Hioe, W.; Hosoya, M.; Goto, E.

    1991-01-01

    This paper reports on the Quantum Flux Parametron (QFP) which is a flux transfer, flux activated Josephson logic device which realizes much lower power dissipation than other Josephson logic devices. Being a two-terminal device its correct operation may be affected by coupling to other QFPs. The problems include backcoupling from active QFPs through inactive QFPs (relay noise), coupling between QFPs activated at different times because of clock skew (homophase noise), and interaction between active QFPs (reaction hazard). Previous QFP circuits worked by wired-majority, which being a linear input logic, has low input margin. A new logic gate (D-gate) using a QFP to perform logic operations has been analyzed and tested by computer simulation. Relay noise, homophase noise and reaction hazard are substantially reduced. Moreover, the input have little interaction hence input margin is greatly improved

  4. Including local rainfall dynamics and uncertain boundary conditions into a 2-D regional-local flood modelling cascade

    Science.gov (United States)

    Bermúdez, María; Neal, Jeffrey C.; Bates, Paul D.; Coxon, Gemma; Freer, Jim E.; Cea, Luis; Puertas, Jerónimo

    2016-04-01

    Flood inundation models require appropriate boundary conditions to be specified at the limits of the domain, which commonly consist of upstream flow rate and downstream water level. These data are usually acquired from gauging stations on the river network where measured water levels are converted to discharge via a rating curve. Derived streamflow estimates are therefore subject to uncertainties in this rating curve, including extrapolating beyond the maximum observed ratings magnitude. In addition, the limited number of gauges in reach-scale studies often requires flow to be routed from the nearest upstream gauge to the boundary of the model domain. This introduces additional uncertainty, derived not only from the flow routing method used, but also from the additional lateral rainfall-runoff contributions downstream of the gauging point. Although generally assumed to have a minor impact on discharge in fluvial flood modeling, this local hydrological input may become important in a sparse gauge network or in events with significant local rainfall. In this study, a method to incorporate rating curve uncertainty and the local rainfall-runoff dynamics into the predictions of a reach-scale flood inundation model is proposed. Discharge uncertainty bounds are generated by applying a non-parametric local weighted regression approach to stage-discharge measurements for two gauging stations, while measured rainfall downstream from these locations is cascaded into a hydrological model to quantify additional inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these inputs and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Improvements in model performance when incorporating these processes are quantified using observed

  5. PENDUGAAN ELASTISITAS PENAWARAN OUTPUT DAN PERMINTAAN INPUT USAHATANI JAGUNG

    Directory of Open Access Journals (Sweden)

    Adang Agustian

    2012-12-01

    Full Text Available This study aims to determine the effect of changes in output and input prices, corn research expenditures and road infrastructure on output supply and input demand for corn in the Province of East Java and West Java. The data that are analyzed are those of structure of costs of corn farming in the Province of East Java and West Java in 1985-2009. Estimation model employed is the method of Seemingly Unrelated Regression. The results showed that the output supply of corn both in the province of East Java and West Java are elastic to its price changes, however it is inelastic to the price changes of: seed, urea, TSP and labor. Input demand of seed, urea, TSP and labor area inelastic to their price changes. Policy implications of this research is efforts to increase the supply of corn can be carried out by increasing its price, expenditures of corn research, and road infrastructure.

  6. 7 CFR 3430.607 - Stakeholder input.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Stakeholder input. 3430.607 Section 3430.607 Agriculture Regulations of the Department of Agriculture (Continued) COOPERATIVE STATE RESEARCH, EDUCATION... § 3430.607 Stakeholder input. CSREES shall seek and obtain stakeholder input through a variety of forums...

  7. Automation of Geometry Input for Building Code Compliance Check

    DEFF Research Database (Denmark)

    Petrova, Ekaterina Aleksandrova; Johansen, Peter Lind; Jensen, Rasmus Lund

    2017-01-01

    Documentation of compliance with the energy performance regulations at the end of the detailed design phase is mandatory for building owners in Denmark. Therefore, besides multidisciplinary input, the building design process requires various iterative analyses, so that the optimal solutions can....... That has left the industry in constant pursuit of possibilities for integration of the tool within the Building Information Modelling environment so that the potential provided by the latter can be harvested and the processed can be optimized. This paper presents a solution for automated data extraction...... from building geometry created in Autodesk Revit and its translation to input for compliance check analysis....

  8. World Input-Output Network.

    Directory of Open Access Journals (Sweden)

    Federica Cerina

    Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

  9. Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects

    International Nuclear Information System (INIS)

    Yu, C.F.; van Sark, W.G.J.H.M.; Alsema, E.A.

    2011-01-01

    In a large number of energy models, the use of learning curves for estimating technological improvements has become popular. This is based on the assumption that technological development can be monitored by following cost development as a function of market size. However, recent data show that in some stages of photovoltaic technology (PV) production, the market price of PV modules stabilizes even though the cumulative capacity increases. This implies that no technological improvement takes place in these periods: the cost predicted by the learning curve in the PV study is lower than the market one. We propose that this bias results from ignoring the effects of input prices and scale effects, and that incorporating the input prices and scale effects into the learning curve theory is an important issue in making cost predictions more reliable. In this paper, a methodology is described to incorporate the scale and input-prices effect as the additional variables into the one factor learning curve, which leads to the definition of the multi-factor learning curve. This multi-factor learning curve is not only derived from economic theories, but also supported by an empirical study. The results clearly show that input prices and scale effects are to be included, and that, although market prices are stabilizing, learning is still taking place. (author)

  10. Incorporation of Plasticity and Damage Into an Orthotropic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

    Science.gov (United States)

    Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Rajan,Subramaniam; Blackenhorn, Gunther

    2015-01-01

    The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. While there are several composite material models currently available within commercial transient dynamic finite element codes, several features have been identified as being lacking in the currently available material models that could substantially enhance the predictive capability of the impact simulations. A specific desired feature pertains to the incorporation of both plasticity and damage within the material model. Another desired feature relates to using experimentally based tabulated stress-strain input to define the evolution of plasticity and damage as opposed to specifying discrete input properties (such as modulus and strength) and employing analytical functions to track the response of the material. To begin to address these needs, a combined plasticity and damage model suitable for use with both solid and shell elements is being developed for implementation within the commercial code LS-DYNA. The plasticity model is based on extending the Tsai-Wu composite failure model into a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The evolution of the yield surface is determined based on tabulated stress-strain curves in the various normal and shear directions and is tracked using the effective plastic strain. The effective plastic strain is computed by using the non-associative flow rule in combination with appropriate numerical methods. To compute the evolution of damage, a strain equivalent semi-coupled formulation is used, in which a load in one direction results in a stiffness reduction in multiple coordinate directions. A specific laminated composite is examined to demonstrate the process of characterizing and analyzing the response of a composite using the developed

  11. 7 CFR 3430.15 - Stakeholder input.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Stakeholder input. 3430.15 Section 3430.15... Stakeholder input. Section 103(c)(2) of the Agricultural Research, Extension, and Education Reform Act of 1998... RFAs for competitive programs. CSREES will provide instructions for submission of stakeholder input in...

  12. Inverse Tasks In The Tsunami Problem: Nonlinear Regression With Inaccurate Input Data

    Science.gov (United States)

    Lavrentiev, M.; Shchemel, A.; Simonov, K.

    A variant of modified training functional that allows considering inaccurate input data is suggested. A limiting case when a part of input data is completely undefined, and, therefore, a problem of reconstruction of hidden parameters should be solved, is also considered. Some numerical experiments are presented. It is assumed that a dependence of known output variables on known input ones should be found is the classic problem definition, which is widely used in the majority of neural nets algorithms. The quality of approximation is evaluated as a performance function. Often the error of the task is evaluated as squared distance between known input data and predicted data multiplied by weighed coefficients. These coefficients may be named "precision coefficients". When inputs are not known exactly, natural generalization of performance function is adding member that responsible for distance between known inputs and shifted inputs, which lessen model's error. It is desirable that the set of variable parameters is compact for training to be con- verging. In the above problem it is possible to choose variants of demands of a priori compactness, which allow meaningful interpretation in the smoothness of the model dependence. Two kinds of regularization was used, first limited squares of coefficients responsible for nonlinearity and second limited multiplication of the above coeffi- cients and linear coefficients. Asymptotic universality of neural net ability to approxi- mate various smooth functions with any accuracy by increase of the number of tunable parameters is often the base for selecting a type of neural net approximation. It is pos- sible to show that used neural net will approach to Fourier integral transform, which approximate abilities are known, with increasing of the number of tunable parameters. In the limiting case, when input data is set with zero precision, the problem of recon- struction of hidden parameters with observed output data appears. The

  13. Impact of Infralimbic Inputs on Intercalated Amygdale Neurons: A Biophysical Modeling Study

    Science.gov (United States)

    Li, Guoshi; Amano, Taiju; Pare, Denis; Nair, Satish S.

    2011-01-01

    Intercalated (ITC) amygdala neurons regulate fear expression by controlling impulse traffic between the input (basolateral amygdala; BLA) and output (central nucleus; Ce) stations of the amygdala for conditioned fear responses. Previously, stimulation of the infralimbic (IL) cortex was found to reduce fear expression and the responsiveness of Ce…

  14. Input description for BIOPATH

    International Nuclear Information System (INIS)

    Marklund, J.E.; Bergstroem, U.; Edlund, O.

    1980-01-01

    The computer program BIOPATH describes the flow of radioactivity within a given ecosystem after a postulated release of radioactive material and the resulting dose for specified population groups. The present report accounts for the input data necessary to run BIOPATH. The report also contains descriptions of possible control cards and an input example as well as a short summary of the basic theory.(author)

  15. Day-ahead load forecast using random forest and expert input selection

    International Nuclear Information System (INIS)

    Lahouar, A.; Ben Hadj Slama, J.

    2015-01-01

    Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar

  16. Optimization model of peach production relevant to input energies – Yield function in Chaharmahal va Bakhtiari province, Iran

    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

  17. Development of the GUI environments of MIDAS code for convenient input and output processing

    International Nuclear Information System (INIS)

    Kim, K. L.; Kim, D. H.

    2003-01-01

    MIDAS is being developed at KAERI as an integrated Severe Accident Analysis Code with easy model modification and addition by restructuring the data transfer scheme. In this paper, the input file management system, IEDIT and graphic simulation system, SATS, are presented as MIDAS input and output GUI systems. These two systems would form the basis of the MIDAS GUI system for input and output processing, and they are expected to be useful tools for severe accidents analysis and simulation

  18. A stock-flow consistent input-output model with applications to energy price shocks, interest rates, and heat emissions

    Science.gov (United States)

    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.

  19. EARLY GUIDANCE FOR ASSIGNING DISTRIBUTION PARAMETERS TO GEOCHEMICAL INPUT TERMS TO STOCHASTIC TRANSPORT MODELS

    International Nuclear Information System (INIS)

    Kaplan, D; Margaret Millings, M

    2006-01-01

    Stochastic modeling is being used in the Performance Assessment program to provide a probabilistic estimate of the range of risk that buried waste may pose. The objective of this task was to provide early guidance for stochastic modelers for the selection of the range and distribution (e.g., normal, log-normal) of distribution coefficients (K d ) and solubility values (K sp ) to be used in modeling subsurface radionuclide transport in E- and Z-Area on the Savannah River Site (SRS). Due to the project's schedule, some modeling had to be started prior to collecting the necessary field and laboratory data needed to fully populate these models. For the interim, the project will rely on literature values and some statistical analyses of literature data as inputs. Based on statistical analyses of some literature sorption tests, the following early guidance was provided: (1) Set the range to an order of magnitude for radionuclides with K d values >1000 mL/g and to a factor of two for K d values of sp values -6 M and to a factor of two for K d values of >10 -6 M. This decision is based on the literature. (3) The distribution of K d values with a mean >1000 mL/g will be log-normally distributed. Those with a K d value <1000 mL/g will be assigned a normal distribution. This is based on statistical analysis of non-site-specific data. Results from on-going site-specific field/laboratory research involving E-Area sediments will supersede this guidance; these results are expected in 2007

  20. Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

    Science.gov (United States)

    Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

    2016-04-01

    Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several

  1. Modeling uncertainties in workforce disruptions from influenza pandemics using dynamic input-output analysis.

    Science.gov (United States)

    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.

  2. Study of a diffusion flamelet model, with preferential diffusion effects included

    NARCIS (Netherlands)

    Delhaye, S.; Somers, L.M.T.; Bongers, H.; Oijen, van J.A.; Goey, de L.P.H.; Dias, V.

    2005-01-01

    The non-premixed flamelet model of Peters [1] (model1), which does not include preferential diffusion effects is investigated. Two similar models are presented, but without the assumption of unity Lewis numbers. One of these models was derived by Peters & Pitsch [2] (model2), while the other one was

  3. Multimedia Environmental Pollutant Assessment System (MEPAS) application guidance. Guidelines for evaluating MEPAS input parameters for Version 3.1

    International Nuclear Information System (INIS)

    Buck, J.W.; Whelan, G.; Droppo, J.G. Jr.; Strenge, D.L.; Castleton, K.J.; McDonald, J.P.; Sato, C.; Streile, G.P.

    1995-02-01

    The Multimedia Environmental Pollutant Assessment System (MEPAS) was developed by Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE) Office of Environment, Safety and Health and Office of Environmental Management and Environmental Restoration. MEPAS is a set of computer codes developed to provide decision makers with risk information integrated for hazardous, radioactive, and mixed-waste sites based on their potential hazard to public health. It is applicable to a wide range of environmental management and regulatory conditions, including inactive sites covered under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) and active air and water releases covered under the Clean Air Act, the Clean Water Act, and the Resource Conservation and Recovery Act. MEPAS integrates contaminant release, transport, and exposure models into a single system. An interactive user interface assists the investigator in defining problems, assembling data and entering input, and developing reports. PNL has compiled two documents that explain the methodology behind the MEPAS model and instruct the user in how to input, retrieve, and evaluate data. This report contains detailed guidelines for defining the input data required to conduct an analysis with MEPAS. Entries for each variable have a short definition, units, and text explaining what a variable is and how it can be quantified. As appropriate, ranges and typical values are given. This report also contains listings of the input screens (worksheets) that are used in the MEPAS user interface for these variables

  4. Beyond the Vestibulo-Ocular Reflex: Vestibular Input is Processed Centrally to Achieve Visual Stability

    Directory of Open Access Journals (Sweden)

    Edwin S. Dalmaijer

    2018-03-01

    Full Text Available The current study presents a re-analysis of data from Zink et al. (1998, Electroencephalography and Clinical Neurophysiology, 107, who administered galvanic vestibular stimulation through unipolar direct current. They placed electrodes on each mastoid and applied either right or left anodal stimulation. Ocular torsion and visual tilt were measured under different stimulation intensities. New modelling introduced here demonstrates that directly proportional linear models fit reasonably well with the relationship between vestibular input and visual tilt, but not to that between vestibular input and ocular torsion. Instead, an exponential model characterised by a decreasing slope and an asymptote fitted best. These results demonstrate that in the results presented by Zink et al. (1998, ocular torsion could not completely account for visual tilt. This suggests that vestibular input is processed centrally to stabilise vision when ocular torsion is insufficient. Potential mechanisms and seemingly conflicting literature are discussed.

  5. Sensitivity of isoprene emissions estimated using MEGAN to the time resolution of input climate data

    Directory of Open Access Journals (Sweden)

    K. Ashworth

    2010-02-01

    Full Text Available We evaluate the effect of varying the temporal resolution of the input climate data on isoprene emission estimates generated by the community emissions model MEGAN (Model of Emissions of Gases and Aerosols from Nature. The estimated total global annual emissions of isoprene is reduced from 766 Tg y−1 when using hourly input data to 746 Tg y−1 (a reduction of 3% for daily average input data and 711 Tg y−1 (down 7% for monthly average input data. The impact on a local scale can be more significant with reductions of up to 55% at some locations when using monthly average data compared with using hourly data. If the daily and monthly average temperature data are used without the imposition of a diurnal cycle the global emissions estimates fall by 27–32%, and local annual emissions by up to 77%. A similar pattern emerges if hourly isoprene fluxes are considered. In order to better simulate and predict isoprene emission rates using MEGAN, we show it is necessary to use temperature and radiation data resolved to one hour. Given the importance of land-atmosphere interactions in the Earth system and the low computational cost of the MEGAN algorithms, we recommend that chemistry-climate models and the new generation of Earth system models input biogenic emissions at the highest temporal resolution possible.

  6. Limiting labor input is an overall prerequisite for sustainability

    DEFF Research Database (Denmark)

    Nørgaard, Jørgen

    2006-01-01

    The purpose of the paper is to show by a simple, aggregate, descriptive model, how the importance of labor input to the production sector has to be revised in a future aiming at sustainable development. Despite substantial technological potentials for more eco-efficient utilization of nature...

  7. 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

  8. Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

    Science.gov (United States)

    Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

    2018-06-01

    To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

  9. On Babies and Bathwater: Input in Foreign Language Learning.

    Science.gov (United States)

    VanPatten, Bill

    1987-01-01

    A discussion of Krashen's monitor theory and its applications to foreign language teaching includes consideration of the very important role input plays in language development and examination of the relationship between the development of grammatical competence and traditional instruction in grammar. (CB)

  10. Input Shaping enhanced Active Disturbance Rejection Control for a twin rotor multi-input multi-output system (TRMS).

    Science.gov (United States)

    Yang, Xiaoyan; Cui, Jianwei; Lao, Dazhong; Li, Donghai; Chen, Junhui

    2016-05-01

    In this paper, a composite control based on Active Disturbance Rejection Control (ADRC) and Input Shaping is presented for TRMS with two degrees of freedom (DOF). The control tasks consist of accurately tracking desired trajectories and obtaining disturbance rejection in both horizontal and vertical planes. Due to un-measurable states as well as uncertainties stemming from modeling uncertainty and unknown disturbance torques, ADRC is employed, and feed-forward Input Shaping is used to improve the dynamical response. In the proposed approach, because the coupling effects are maintained in controller derivation, there is no requirement to decouple the TRMS into horizontal and vertical subsystems, which is usually performed in the literature. Finally, the proposed method is implemented on the TRMS platform, and the results are compared with those of PID and ADRC in a similar structure. The experimental results demonstrate the effectiveness of the proposed method. The operation of the controller allows for an excellent set-point tracking behavior and disturbance rejection with system nonlinearity and complex coupling conditions. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  11. 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)

  12. Wave energy input into the Ekman layer

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper is concerned with the wave energy input into the Ekman layer, based on 3 observational facts that surface waves could significantly affect the profile of the Ekman layer. Under the assumption of constant vertical diffusivity, the analytical form of wave energy input into the Ekman layer is derived. Analysis of the energy balance shows that the energy input to the Ekman layer through the wind stress and the interaction of the Stokes-drift with planetary vorticity can be divided into two kinds. One is the wind energy input, and the other is the wave energy input which is dependent on wind speed, wave characteristics and the wind direction relative to the wave direction. Estimates of wave energy input show that wave energy input can be up to 10% in high-latitude and high-wind speed areas and higher than 20% in the Antarctic Circumpolar Current, compared with the wind energy input into the classical Ekman layer. Results of this paper are of significance to the study of wave-induced large scale effects.

  13. Exclusive queueing model including the choice of service windows

    Science.gov (United States)

    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.

  14. Asymmetric temporal integration of layer 4 and layer 2/3 inputs in visual cortex.

    Science.gov (United States)

    Hang, Giao B; Dan, Yang

    2011-01-01

    Neocortical neurons in vivo receive concurrent synaptic inputs from multiple sources, including feedforward, horizontal, and feedback pathways. Layer 2/3 of the visual cortex receives feedforward input from layer 4 and horizontal input from layer 2/3. Firing of the pyramidal neurons, which carries the output to higher cortical areas, depends critically on the interaction of these pathways. Here we examined synaptic integration of inputs from layer 4 and layer 2/3 in rat visual cortical slices. We found that the integration is sublinear and temporally asymmetric, with larger responses if layer 2/3 input preceded layer 4 input. The sublinearity depended on inhibition, and the asymmetry was largely attributable to the difference between the two inhibitory inputs. Interestingly, the asymmetric integration was specific to pyramidal neurons, and it strongly affected their spiking output. Thus via cortical inhibition, the temporal order of activation of layer 2/3 and layer 4 pathways can exert powerful control of cortical output during visual processing.

  15. The UK waste input-output table: Linking waste generation to the UK economy.

    Science.gov (United States)

    Salemdeeb, Ramy; Al-Tabbaa, Abir; Reynolds, Christian

    2016-10-01

    In order to achieve a circular economy, there must be a greater understanding of the links between economic activity and waste generation. This study introduces the first version of the UK waste input-output table that could be used to quantify both direct and indirect waste arisings across the supply chain. The proposed waste input-output table features 21 industrial sectors and 34 waste types and is for the 2010 time-period. Using the waste input-output table, the study results quantitatively confirm that sectors with a long supply chain (i.e. manufacturing and services sectors) have higher indirect waste generation rates compared with industrial primary sectors (e.g. mining and quarrying) and sectors with a shorter supply chain (e.g. construction). Results also reveal that the construction, mining and quarrying sectors have the highest waste generation rates, 742 and 694 tonne per £1m of final demand, respectively. Owing to the aggregated format of the first version of the waste input-output, the model does not address the relationship between waste generation and recycling activities. Therefore, an updated version of the waste input-output table is expected be developed considering this issue. Consequently, the expanded model would lead to a better understanding of waste and resource flows in the supply chain. © The Author(s) 2016.

  16. Residential-commercial energy input estimation based on genetic algorithm (GA) approaches: an application of Turkey

    International Nuclear Information System (INIS)

    Ozturk, H.K.; Canyurt, O.E.; Hepbasli, A.; Utlu, Z.

    2004-01-01

    The main objective of the present study is to develop the energy input estimation equations for the residential-commercial sector (RCS) in order to estimate the future projections based on genetic algorithm (GA) notion and to examine the effect of the design parameters on the energy input of the sector. For this purpose, the Turkish RCS is given as an example. The GA Energy Input Estimation Model (GAEIEM) is used to estimate Turkey's future residential-commercial energy input demand based on gross domestic product (GDP), population, import, export, house production, cement production and basic house appliances consumption figures. It may be concluded that the three various forms of models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies. (author)

  17. Visualization of virtual slave manipulator using the master input device

    International Nuclear Information System (INIS)

    Kim, S. H.; Song, T. K.; Lee, J. Y.; Yoon, J. S.

    2003-01-01

    To handle the high level radioactive materials such a spent fuel, the Master-Slave Manipulators (MSM) are widely used as a remote handling device in nuclear facilities such as the hot cell with sealed and shielded space. In this paper, the Digital Mockup which simulates the remote operation of the Advanced Conditioning Process(ACP) is developed. Also, the workspace and the motion of the slave manipulator, as well as, the remote operation task should be analyzed. The process equipment of ACP and Maintenance/Handling Device are drawn in 3D CAD models using IGRIP. Modeling device of manipulator is assigned with various mobiles attributes such as a relative position, kinematics constraints, and a range of mobility. The 3D graphic simulator using the external input device of space ball displays the movement of manipulator. To connect the external input device to the graphic simulator, the interface program of external input device with 6 DOF is deigned using the Low Level Tele-operation Interface (LLTI). The experimental result shows that the developed simulation system gives much-improved human interface characteristics and shows satisfactory response characteristics in terms of synchronization speed. This should be useful for the development of work's education system in the virtual environment

  18. Residual N effects from livestock manure inputs to soils

    DEFF Research Database (Denmark)

    Schröder, Jaap; Bechini, Luca; Bittman, Shabtai

    Organic inputs including livestock manures provide nitrogen (N) to crops beyond the year of their application. This so-called residual N effect should be taken into account when making decisions on N rates for individual fields, but also when interpreting N response trials in preparation...

  19. Forecasting the Romanian sectoral economy using the input-output method

    Directory of Open Access Journals (Sweden)

    Liliana DUGULEANĂ

    2017-07-01

    Full Text Available The purpose of this paper is to forecast the sectoral output in 2013 based on the input-output structure of Romanian economy in 2010. Considering that the economic linkage mechanisms do not easily change during certain time periods, the forecasting is possible, even if not in the sequence of the time passing. Using the technical matrix of the sectoral structure described for year 2010 and some known indicators of the economic sectors, as the value added for each sector in 2013, the sectoral output is projected for 2013. The Romanian GDP in 2013 is estimated based on the input-output model. From a managerial perspective, this study is useful to forecast the sectoral output and to understand the sectoral behaviour, based on the input-output analysis of the value added, the compensation for employees and the final demand, which were considered here.

  20. Statistical identification of effective input variables

    International Nuclear Information System (INIS)

    Vaurio, J.K.

    1982-09-01

    A statistical sensitivity analysis procedure has been developed for ranking the input data of large computer codes in the order of sensitivity-importance. The method is economical for large codes with many input variables, since it uses a relatively small number of computer runs. No prior judgemental elimination of input variables is needed. The sceening method is based on stagewise correlation and extensive regression analysis of output values calculated with selected input value combinations. The regression process deals with multivariate nonlinear functions, and statistical tests are also available for identifying input variables that contribute to threshold effects, i.e., discontinuities in the output variables. A computer code SCREEN has been developed for implementing the screening techniques. The efficiency has been demonstrated by several examples and applied to a fast reactor safety analysis code (Venus-II). However, the methods and the coding are general and not limited to such applications