Dimension of linear models

DEFF Research Database (Denmark)

Høskuldsson, Agnar

1996-01-01

Determination of the proper dimension of a given linear model is one of the most important tasks in the applied modeling work. We consider here eight criteria that can be used to determine the dimension of the model, or equivalently, the number of components to use in the model. Four of these cri......Determination of the proper dimension of a given linear model is one of the most important tasks in the applied modeling work. We consider here eight criteria that can be used to determine the dimension of the model, or equivalently, the number of components to use in the model. Four...... the basic problems in determining the dimension of linear models. Then each of the eight measures are treated. The results are illustrated by examples....

Extending the linear model with R generalized linear, mixed effects and nonparametric regression models

CERN Document Server

Faraway, Julian J

2005-01-01

Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...

A primer on linear models

CERN Document Server

Monahan, John F

2008-01-01

Preface Examples of the General Linear Model Introduction One-Sample Problem Simple Linear Regression Multiple Regression One-Way ANOVA First Discussion The Two-Way Nested Model Two-Way Crossed Model Analysis of Covariance Autoregression Discussion The Linear Least Squares Problem The Normal Equations The Geometry of Least Squares Reparameterization Gram-Schmidt Orthonormalization Estimability and Least Squares Estimators Assumptions for the Linear Mean Model Confounding, Identifiability, and Estimability Estimability and Least Squares Estimators F

Considering linear generator copper losses on model predictive control for a point absorber wave energy converter

International Nuclear Information System (INIS)

Montoya Andrade, Dan-El; Villa Jaén, Antonio de la; García Santana, Agustín

2014-01-01

Highlights: • We considered the linear generator copper losses in the proposed MPC strategy. • We maximized the power transferred to the generator side power converter. • The proposed MPC increases the useful average power injected into the grid. • The stress level of the PTO system can be reduced by the proposed MPC. - Abstract: The amount of energy that a wave energy converter can extract depends strongly on the control strategy applied to the power take-off system. It is well known that, ideally, the reactive control allows for maximum energy extraction from waves. However, the reactive control is intrinsically noncausal in practice and requires some kind of causal approach to be applied. Moreover, this strategy does not consider physical constraints and this could be a problem because the system could achieve unacceptable dynamic values. These, and other control techniques have focused on the wave energy extraction problem in order to maximize the energy absorbed by the power take-off device without considering the possible losses in intermediate devices. In this sense, a reactive control that considers the linear generator copper losses has been recently proposed to increase the useful power injected into the grid. Among the control techniques that have emerged recently, the model predictive control represents a promising strategy. This approach performs an optimization process on a time prediction horizon incorporating dynamic constraints associated with the physical features of the power take-off system. This paper proposes a model predictive control technique that considers the copper losses in the control optimization process of point absorbers with direct drive linear generators. This proposal makes the most of reactive control as it considers the copper losses, and it makes the most of the model predictive control, as it considers the system constraints. This means that the useful power transferred from the linear generator to the power

Modelling of reactive fluid transport in deformable porous rocks

Science.gov (United States)

Yarushina, V. M.; Podladchikov, Y. Y.

2009-04-01

representative volume element and subsequent averaging of microscopic constitutive laws. Micromechanical and thermodynamic modelling is performed in such a way that the consistency of the obtained rheology and thermodynamically admissible closed system of equations with the exact Gassman's relationship and Terzaghi effective stress law in the simplified case of poroelasticity is guaranteed. In such environments as subduction zones or mid-ocean ridge, metamorphic rocks exhibit a lack of chemical homogenisation. Geochemistry suggests that in order to produce chemical heterogeneity, the fluids generated during high-pressure metamorphism must have been strongly channelled. The following three major mechanisms of fluid flow focusing have been proposed: fluid flow in open fractures and two different types of flow instabilities that do not require the pre-existing fracture network. Of the latter, the first represents a purely mechanical instability of Darcian flow through the deformable porous rock while the second is reactive infiltration instability. Both mechanical and reactive instabilities are expected to occur in the mantle and should probably reinforce each other. However, little research has been done in this direction. In order to investigate how the focusing of a fluid flow occurs, how mechanical and reactive infiltration instabilities influence each other, and what their relative importance in rocks with different rheologies is, linear and non-linear stability analysis is applied to derived governing equations.

Unifying Model-Based and Reactive Programming within a Model-Based Executive

Science.gov (United States)

Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

1999-01-01

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

Science.gov (United States)

Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

2011-03-25

The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

Science.gov (United States)

Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

2011-03-01

The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

Science.gov (United States)

Ker, H. W.

2014-01-01

Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

Modeling Single-Phase Inverter and Its Decentralized Coordinated Control by Using Feedback Linearization

Directory of Open Access Journals (Sweden)

Renke Han

2014-01-01

Full Text Available It is a very crucial problem to make a microgrid operated reasonably and stably. Considering the nonlinear mathematics model of inverter established in this paper, the input-output feedback linearization method is used to transform the nonlinear mathematics model of inverters to a linear tracking synchronization and consensus regulation control problem. Based on the linear mathematics model and multiagent consensus algorithm, a decentralized coordinated controller is proposed to make amplitudes and angles of voltages from inverters be consensus and active and reactive power shared in the desired ratio. The proposed control is totally distributed because each inverter only requires local and one neighbor’s information with sparse communication structure based on multiagent system. The hybrid consensus algorithm is used to keep the amplitude of the output voltages following the leader and the angles of output voltage as consensus. Then the microgrid can be operated more efficiently and the circulating current between DGs can be effectively suppressed. The effectiveness of the proposed method is proved through simulation results of a typical microgrid system.

Impact of reactive settler models on simulated WWTP performance

DEFF Research Database (Denmark)

Gernaey, Krist; Jeppsson, Ulf; Batstone, Damien J.

2006-01-01

for an ASM1 case study. Simulations with a whole plant model including the non-reactive Takacs settler model are used as a reference, and are compared to simulation results considering two reactive settler models. The first is a return sludge model block removing oxygen and a user-defined fraction of nitrate......, combined with a non-reactive Takacs settler. The second is a fully reactive ASM1 Takacs settler model. Simulations with the ASM1 reactive settler model predicted a 15.3% and 7.4% improvement of the simulated N removal performance, for constant (steady-state) and dynamic influent conditions respectively....... The oxygen/nitrate return sludge model block predicts a 10% improvement of N removal performance under dynamic conditions, and might be the better modelling option for ASM1 plants: it is computationally more efficient and it will not overrate the importance of decay processes in the settler....

Delocalization model of regioselectivity and reactivity of free radicals in reactions of addition to olefins

International Nuclear Information System (INIS)

Volovik, S.V.; Dyadyusha, G.G.; Staninets, V.I.

1987-01-01

On the basis of the concept of polarity (philicity) of free radicals as proposed by the authors, within the framework of methods of qualitative surfaces of potential energy (linear combinations of configurations of fragments) and stabilization energy, an effective model has been developed for the regioselectivity and reactivity of radicals in processes of addition. A critical examination is made of certain key aspects of the change in regiochemistry and reactivity with changes in the electronic structure of the free radical and substrate. The dominant trends in regioselectivity and reactivity in processes of free-radical addition to olefins are controlled by electronic effects and can be predicted by analyzing interactions of diabatic potential energy surfaces or orbital interactions for a system consisting of a free radical and an unsaturated substrate

From spiking neuron models to linear-nonlinear models.

Science.gov (United States)

Ostojic, Srdjan; Brunel, Nicolas

2011-01-20

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

A new computational method for reactive power market clearing

International Nuclear Information System (INIS)

Zhang, T.; Elkasrawy, A.; Venkatesh, B.

2009-01-01

After deregulation of electricity markets, ancillary services such as reactive power supply are priced separately. However, unlike real power supply, procedures for costing and pricing reactive power supply are still evolving and spot markets for reactive power do not exist as of now. Further, traditional formulations proposed for clearing reactive power markets use a non-linear mixed integer programming formulation that are difficult to solve. This paper proposes a new reactive power supply market clearing scheme. Novelty of this formulation lies in the pricing scheme that rewards transformers for tap shifting while participating in this market. The proposed model is a non-linear mixed integer challenge. A significant portion of the manuscript is devoted towards the development of a new successive mixed integer linear programming (MILP) technique to solve this formulation. The successive MILP method is computationally robust and fast. The IEEE 6-bus and 300-bus systems are used to test the proposed method. These tests serve to demonstrate computational speed and rigor of the proposed method. (author)

What makes ecological systems reactive?

Science.gov (United States)

Snyder, Robin E

2010-06-01

Although perturbations from a stable equilibrium must ultimately vanish, they can grow initially, and the maximum initial growth rate is called reactivity. Reactivity thus identifies systems that may undergo transient population surges or drops in response to perturbations; however, we lack biological and mathematical intuition about what makes a system reactive. This paper presents upper and lower bounds on reactivity for an arbitrary linearized model, explores their strictness, and discusses their biological implications. I find that less stable systems (i.e. systems with long transients) have a smaller possible range of reactivities for which no perturbations grow. Systems with more species have a higher capacity to be reactive, assuming species interactions do not weaken too rapidly as the number of species increases. Finally, I find that in discrete time, reactivity is determined largely by mean interaction strength and neither discrete nor continuous time reactivity are sensitive to food web topology. 2010 Elsevier Inc. All rights reserved.

Reactive transport models and simulation with ALLIANCES

International Nuclear Information System (INIS)

Leterrier, N.; Deville, E.; Bary, B.; Trotignon, L.; Hedde, T.; Cochepin, B.; Stora, E.

2009-01-01

Many chemical processes influence the evolution of nuclear waste storage. As a result, simulations based only upon transport and hydraulic processes fail to describe adequately some industrial scenarios. We need to take into account complex chemical models (mass action laws, kinetics...) which are highly non-linear. In order to simulate the coupling of these chemical reactions with transport, we use a classical Sequential Iterative Approach (SIA), with a fixed point algorithm, within the mainframe of the ALLIANCES platform. This approach allows us to use the various transport and chemical modules available in ALLIANCES, via an operator-splitting method based upon the structure of the chemical system. We present five different applications of reactive transport simulations in the context of nuclear waste storage: 1. A 2D simulation of the lixiviation by rain water of an underground polluted zone high in uranium oxide; 2. The degradation of the steel envelope of a package in contact with clay. Corrosion of the steel creates corrosion products and the altered package becomes a porous medium. We follow the degradation front through kinetic reactions and the coupling with transport; 3. The degradation of a cement-based material by the injection of an aqueous solution of zinc and sulphate ions. In addition to the reactive transport coupling, we take into account in this case the hydraulic retroaction of the porosity variation on the Darcy velocity; 4. The decalcification of a concrete beam in an underground storage structure. In this case, in addition to the reactive transport simulation, we take into account the interaction between chemical degradation and the mechanical forces (cracks...), and the retroactive influence on the structure changes on transport; 5. The degradation of the steel envelope of a package in contact with a clay material under a temperature gradient. In this case the reactive transport simulation is entirely directed by the temperature changes and

A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions

International Nuclear Information System (INIS)

Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C.; Brooks, Scott C; Pace, Molly; Kim, Young Jin; Jardine, Philip M.; Watson, David B.

2007-01-01

This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M. partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M. species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing NE equilibrium reactions and a set of reactive transport equations of M-NE kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions

A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions.

Science.gov (United States)

Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C; Brooks, Scott C; Pace, Molly N; Kim, Young-Jin; Jardine, Philip M; Watson, David B

2007-06-16

This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing N(E) equilibrium reactions and a set of reactive transport equations of M-N(E) kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.

Linear Models

CERN Document Server

Searle, Shayle R

2012-01-01

This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.

Simulations of reactive transport and precipitation with smoothed particle hydrodynamics

Science.gov (United States)

Tartakovsky, Alexandre M.; Meakin, Paul; Scheibe, Timothy D.; Eichler West, Rogene M.

2007-03-01

A numerical model based on smoothed particle hydrodynamics (SPH) was developed for reactive transport and mineral precipitation in fractured and porous materials. Because of its Lagrangian particle nature, SPH has several advantages for modeling Navier-Stokes flow and reactive transport including: (1) in a Lagrangian framework there is no non-linear term in the momentum conservation equation, so that accurate solutions can be obtained for momentum dominated flows and; (2) complicated physical and chemical processes such as surface growth due to precipitation/dissolution and chemical reactions are easy to implement. In addition, SPH simulations explicitly conserve mass and linear momentum. The SPH solution of the diffusion equation with fixed and moving reactive solid-fluid boundaries was compared with analytical solutions, Lattice Boltzmann [Q. Kang, D. Zhang, P. Lichtner, I. Tsimpanogiannis, Lattice Boltzmann model for crystal growth from supersaturated solution, Geophysical Research Letters, 31 (2004) L21604] simulations and diffusion limited aggregation (DLA) [P. Meakin, Fractals, scaling and far from equilibrium. Cambridge University Press, Cambridge, UK, 1998] model simulations. To illustrate the capabilities of the model, coupled three-dimensional flow, reactive transport and precipitation in a fracture aperture with a complex geometry were simulated.

Dynamic Linear Models with R

CERN Document Server

Campagnoli, Patrizia; Petris, Giovanni

2009-01-01

State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.

Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.

Science.gov (United States)

de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo

2018-03-01

Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.

Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots

Science.gov (United States)

Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.

2013-01-01

Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…

Local and linear chemical reactivity response functions at finite temperature in density functional theory

International Nuclear Information System (INIS)

Franco-Pérez, Marco; Ayers, Paul W.; Gázquez, José L.; Vela, Alberto

2015-01-01

We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model

Sequence homology: A poor predictive value for profilins cross-reactivity

Directory of Open Access Journals (Sweden)

Pazouki Nazanin

2005-09-01

Full Text Available Summary Background Profilins are highly cross-reactive allergens which bind IgE antibodies of almost 20% of plant-allergic patients. This study is aimed at investigating cross-reactivity of melon profilin with other plant profilins and the role of the linear and conformational epitopes in human IgE cross-reactivity. Methods Seventeen patients with melon allergy were selected based on clinical history and a positive skin prick test to melon extract. Melon profilin has been cloned and expressed in E. coli. The IgE binding and cross-reactivity of the recombinant profilin were measured by ELISA and inhibition ELISA. The amino acid sequence of melon profilin was compared with other profilin sequences. A combination of chemical cleavage and immunoblotting techniques were used to define the role of conformational and linear epitopes in IgE binding. Comparative modeling was used to construct three-dimensional models of profilins and to assess theoretical impact of amino acid differences on conformational structure. Results Profilin was identified as a major IgE-binding component of melon. Alignment of amino acid sequences of melon profilin with other profilins showed the most identity with watermelon profilin. This melon profilin showed substantial cross-reactivity with the tomato, peach, grape and Cynodon dactylon (Bermuda grass pollen profilins. Cantaloupe, watermelon, banana and Poa pratensis (Kentucky blue grass displayed no notable inhibition. Our experiments also indicated human IgE only react with complete melon profilin. Immunoblotting analysis with rabbit polyclonal antibody shows the reaction of the antibody to the fragmented and complete melon profilin. Although, the well-known linear epitope of profilins were identical in melon and watermelon, comparison of three-dimensional models of watermelon and melon profilins indicated amino acid differences influence the electric potential and accessibility of the solvent-accessible surface of

Dimension of linear models

DEFF Research Database (Denmark)

Høskuldsson, Agnar

1996-01-01

Determination of the proper dimension of a given linear model is one of the most important tasks in the applied modeling work. We consider here eight criteria that can be used to determine the dimension of the model, or equivalently, the number of components to use in the model. Four...... the basic problems in determining the dimension of linear models. Then each of the eight measures are treated. The results are illustrated by examples....... of these criteria are widely used ones, while the remaining four are ones derived from the H-principle of mathematical modeling. Many examples from practice show that the criteria derived from the H-principle function better than the known and popular criteria for the number of components. We shall briefly review...

Ordinal Log-Linear Models for Contingency Tables

Directory of Open Access Journals (Sweden)

Brzezińska Justyna

2016-12-01

Full Text Available A log-linear analysis is a method providing a comprehensive scheme to describe the association for categorical variables in a contingency table. The log-linear model specifies how the expected counts depend on the levels of the categorical variables for these cells and provide detailed information on the associations. The aim of this paper is to present theoretical, as well as empirical, aspects of ordinal log-linear models used for contingency tables with ordinal variables. We introduce log-linear models for ordinal variables: linear-by-linear association, row effect model, column effect model and RC Goodman’s model. Algorithm, advantages and disadvantages will be discussed in the paper. An empirical analysis will be conducted with the use of R.

Parameterized Linear Longitudinal Airship Model

Science.gov (United States)

Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph

2010-01-01

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

Linear and non-linear autoregressive models for short-term wind speed forecasting

International Nuclear Information System (INIS)

Lydia, M.; Suresh Kumar, S.; Immanuel Selvakumar, A.; Edwin Prem Kumar, G.

2016-01-01

Highlights: • Models for wind speed prediction at 10-min intervals up to 1 h built on time-series wind speed data. • Four different multivariate models for wind speed built based on exogenous variables. • Non-linear models built using three data mining algorithms outperform the linear models. • Autoregressive models based on wind direction perform better than other models. - Abstract: Wind speed forecasting aids in estimating the energy produced from wind farms. The soaring energy demands of the world and minimal availability of conventional energy sources have significantly increased the role of non-conventional sources of energy like solar, wind, etc. Development of models for wind speed forecasting with higher reliability and greater accuracy is the need of the hour. In this paper, models for predicting wind speed at 10-min intervals up to 1 h have been built based on linear and non-linear autoregressive moving average models with and without external variables. The autoregressive moving average models based on wind direction and annual trends have been built using data obtained from Sotavento Galicia Plc. and autoregressive moving average models based on wind direction, wind shear and temperature have been built on data obtained from Centre for Wind Energy Technology, Chennai, India. While the parameters of the linear models are obtained using the Gauss–Newton algorithm, the non-linear autoregressive models are developed using three different data mining algorithms. The accuracy of the models has been measured using three performance metrics namely, the Mean Absolute Error, Root Mean Squared Error and Mean Absolute Percentage Error.

Correlations and Non-Linear Probability Models

DEFF Research Database (Denmark)

Breen, Richard; Holm, Anders; Karlson, Kristian Bernt

2014-01-01

the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....

Generalized, Linear, and Mixed Models

CERN Document Server

McCulloch, Charles E; Neuhaus, John M

2011-01-01

An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m

Effect of nonlinear void reactivity on bifurcation characteristics of a lumped-parameter model of a BWR: A study relevant to RBMK

Energy Technology Data Exchange (ETDEWEB)

Verma, Dinkar, E-mail: dinkar@iitk.ac.in [Nuclear Engineering and Technology Program, Indian Institute of Technology Kanpur, Kanpur 208 016 (India); Kalra, Manjeet Singh, E-mail: drmanjeet.singh@dituniversity.edu.in [DIT University, Dehradun 248 009 (India); Wahi, Pankaj, E-mail: wahi@iitk.ac.in [Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016 (India)

2017-04-15

Highlights: • A simplified model with nonlinear void reactivity feedback is studied. • Method of multiple scales for nonlinear analysis and oscillation characteristics. • Second order void reactivity dominates in determining system dynamics. • Opposing signs of linear and quadratic void reactivity enhances global safety. - Abstract: In the present work, the effect of nonlinear void reactivity on the dynamics of a simplified lumped-parameter model for a boiling water reactor (BWR) is investigated. A mathematical model of five differential equations comprising of neutronics and thermal-hydraulics encompassing the nonlinearities associated with both the reactivity feedbacks and the heat transfer process has been used. To this end, we have considered parameters relevant to RBMK for which the void reactivity is known to be nonlinear. A nonlinear analysis of the model exploiting the method of multiple time scales (MMTS) predicts the occurrence of the two types of Hopf bifurcation, namely subcritical and supercritical, leading to the evolution of limit cycles for a range of parameters. Numerical simulations have been performed to verify the analytical results obtained by MMTS. The study shows that the nonlinear reactivity has a significant influence on the system dynamics. A parametric study with varying nominal reactor power and operating conditions in coolant channel has also been performed which shows the effect of change in concerned parameter on the boundary between regions of sub- and super-critical Hopf bifurcations in the space constituted by the two coefficients of reactivities viz. the void and the Doppler coefficient of reactivities. In particular, we find that introduction of a negative quadratic term in the void reactivity feedback significantly increases the supercritical region and dominates in determining the system dynamics.

Multivariate generalized linear mixed models using R

CERN Document Server

Berridge, Damon Mark

2011-01-01

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...

Modeling patterns in data using linear and related models

International Nuclear Information System (INIS)

Engelhardt, M.E.

1996-06-01

This report considers the use of linear models for analyzing data related to reliability and safety issues of the type usually associated with nuclear power plants. The report discusses some of the general results of linear regression analysis, such as the model assumptions and properties of the estimators of the parameters. The results are motivated with examples of operational data. Results about the important case of a linear regression model with one covariate are covered in detail. This case includes analysis of time trends. The analysis is applied with two different sets of time trend data. Diagnostic procedures and tests for the adequacy of the model are discussed. Some related methods such as weighted regression and nonlinear models are also considered. A discussion of the general linear model is also included. Appendix A gives some basic SAS programs and outputs for some of the analyses discussed in the body of the report. Appendix B is a review of some of the matrix theoretic results which are useful in the development of linear models

Reactivity feedback models for SSC-K

Energy Technology Data Exchange (ETDEWEB)

Han, Do Hee; Kwon, Young Min; Kim, Kyung Du; Chang, Won Pyo [Korea Atomic Energy Research Institute, Taejon (Korea)

1998-06-01

Safety of KALIMER is assured by the inherent safety of the core and passive safety of the safety-related systems. For the safety analysis of a new reactor design such as KALIMER, analysis models, which are consistent with the design, have to be developed for a plant-wide transient and safety analysis code. Efforts for the development of reactivity feedback models for SSC-K, which is now being developed for the safety analysis of KALIMER, is described in this report. Models for Doppler, sodium density/void, fuel axial expansion, core radial expansion, and CRDL expansion have been developed. Test runs have been performed for the unprotected accident for the verification of the models. Use of KALIMER reactivity coefficients and future development of models for GEM and PSDRS would make it possible to analyze the response of KALIMER under TOP as well as LOF and LOHS accident conditions using SSC-K. (author). 5 refs., 64 figs., 2 tabs.

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data.

Science.gov (United States)

Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A

2017-02-01

This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r  =  0.71-0.88, RMSE: 1.11-1.61 METs; p  >  0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r  =  0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r  =  0.88, RMSE: 1.10-1.11 METs; p  >  0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r  =  0.88, RMSE: 1.12 METs. Linear models-correlations: r  =  0.86, RMSE: 1.18-1.19 METs; p  linear models for the wrist-worn accelerometers (ANN-correlations: r  =  0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r  =  0.71-0.73, RMSE: 1.55-1.61 METs; p  models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh

An iterative method for controlling reactive power flow in boundary transformers

Energy Technology Data Exchange (ETDEWEB)

Trigo, Angel L.; Martinez, Jose L.; Riquelme, Jesus; Romero, Esther [Department of Electrical Engineering, University of Seville (Spain)

2011-02-15

This paper presents an operational tool designed to help the system operator to control the reactive power flow in transmission-subtransmission boundary transformers. The main objective is to determine the minimum number of control actions necessary to ensure that reactive power flows in transmission/subtransmission transformers remain within limits. The proposed iterative procedure combines the use of a linear programming problem and a load flow tool. The linear programming assumes a linear behaviour between dependent and control variables around an operating point, modelled with sensitivities. Experimental results regarding IEEE systems are provided comparing the performance of the proposed approach with that of a conventional optimal power flow. (author)

Regarding KUR Reactivity Measurement System

International Nuclear Information System (INIS)

Nakamori, Akira; Hasegawa, Kei; Tsuchiyama, Tatsuo; Yamamoto, Toshihiro; Okumura, Ryo; Sano, Tadafumi

2012-01-01

This article reported: (1) the outline of the reactivity measurement system of Kyoto University Research Reactor (KUR), (2) the calibration data of control rod, (3) the problems and the countermeasures for range switching of linear output meter. For the laptop PC for the reactivity measurement system, there are four input signals: (1) linear output meter, (2) logarithmic output meter, (3) core temperature gauge, and (4) control rod position. The hardware of reactivity measurement system is controlled with Labview installed on the laptop. Output, reactivity, reactor period, and the change in reactivity due to temperature effect or Xenon effect are internally calculated and displayed in real-time with Labview based on the four signals above. Calculation results are recorded in the form of a spreadsheet. At KUR, the reactor core arrangement was changed, so the control rod was re-calibrated. At this time, calculated and experimental values of reactivity based on the reactivity measurement system were compared, and it was confirmed that the reactivity calculation by Labview was accurate. The range switching of linear output meter in the nuclear instrumentation should automatically change within the laptop, however sometimes this did not function properly in the early stage. It was speculated that undefined percent values during the transition of percent value were included in the calculation and caused calculation errors. The range switching started working properly after fixing this issue. (S.K.)

Core seismic behaviour: linear and non-linear models

International Nuclear Information System (INIS)

Bernard, M.; Van Dorsselaere, M.; Gauvain, M.; Jenapierre-Gantenbein, M.

1981-08-01

The usual methodology for the core seismic behaviour analysis leads to a double complementary approach: to define a core model to be included in the reactor-block seismic response analysis, simple enough but representative of basic movements (diagrid or slab), to define a finer core model, with basic data issued from the first model. This paper presents the history of the different models of both kinds. The inert mass model (IMM) yielded a first rough diagrid movement. The direct linear model (DLM), without shocks and with sodium as an added mass, let to two different ones: DLM 1 with independent movements of the fuel and radial blanket subassemblies, and DLM 2 with a core combined movement. The non-linear (NLM) ''CORALIE'' uses the same basic modelization (Finite Element Beams) but accounts for shocks. It studies the response of a diameter on flats and takes into account the fluid coupling and the wrapper tube flexibility at the pad level. Damping consists of one modal part of 2% and one part due to shocks. Finally, ''CORALIE'' yields the time-history of the displacements and efforts on the supports, but damping (probably greater than 2%) and fluid-structures interaction are still to be precised. The validation experiments were performed on a RAPSODIE core mock-up on scale 1, in similitude of 1/3 as to SPX 1. The equivalent linear model (ELM) was developed for the SPX 1 reactor-block response analysis and a specified seismic level (SB or SM). It is composed of several oscillators fixed to the diagrid and yields the same maximum displacements and efforts than the NLM. The SPX 1 core seismic analysis with a diagrid input spectrum which corresponds to a 0,1 g group acceleration, has been carried out with these models: some aspects of these calculations are presented here

Linear Logistic Test Modeling with R

Science.gov (United States)

Baghaei, Purya; Kubinger, Klaus D.

2015-01-01

The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The…

Explorative methods in linear models

DEFF Research Database (Denmark)

Høskuldsson, Agnar

2004-01-01

The author has developed the H-method of mathematical modeling that builds up the model by parts, where each part is optimized with respect to prediction. Besides providing with better predictions than traditional methods, these methods provide with graphic procedures for analyzing different feat...... features in data. These graphic methods extend the well-known methods and results of Principal Component Analysis to any linear model. Here the graphic procedures are applied to linear regression and Ridge Regression....

Sparse Linear Identifiable Multivariate Modeling

DEFF Research Database (Denmark)

Henao, Ricardo; Winther, Ole

2011-01-01

and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...

Contributions of Child's Physiology and Maternal Behavior to Children's Trajectories of Temperamental Reactivity

Science.gov (United States)

Blandon, Alysia Y.; Calkins, Susan D.; Keane, Susan P.; O'brien, Marion

2010-01-01

Trajectories of children's temperamental reactivity (negative affectivity and surgency) were examined in a community sample of 370 children across the ages of 4 to 7 with hierarchical linear modeling. Children's physiological reactivity (respiratory sinus arrhythmia [RSA]), physiological regulation ([delta]RSA), and maternal parenting behavior…

Latent log-linear models for handwritten digit classification.

Science.gov (United States)

Deselaers, Thomas; Gass, Tobias; Heigold, Georg; Ney, Hermann

2012-06-01

We present latent log-linear models, an extension of log-linear models incorporating latent variables, and we propose two applications thereof: log-linear mixture models and image deformation-aware log-linear models. The resulting models are fully discriminative, can be trained efficiently, and the model complexity can be controlled. Log-linear mixture models offer additional flexibility within the log-linear modeling framework. Unlike previous approaches, the image deformation-aware model directly considers image deformations and allows for a discriminative training of the deformation parameters. Both are trained using alternating optimization. For certain variants, convergence to a stationary point is guaranteed and, in practice, even variants without this guarantee converge and find models that perform well. We tune the methods on the USPS data set and evaluate on the MNIST data set, demonstrating the generalization capabilities of our proposed models. Our models, although using significantly fewer parameters, are able to obtain competitive results with models proposed in the literature.

Equivalent linear damping characterization in linear and nonlinear force-stiffness muscle models.

Science.gov (United States)

Ovesy, Marzieh; Nazari, Mohammad Ali; Mahdavian, Mohammad

2016-02-01

In the current research, the muscle equivalent linear damping coefficient which is introduced as the force-velocity relation in a muscle model and the corresponding time constant are investigated. In order to reach this goal, a 1D skeletal muscle model was used. Two characterizations of this model using a linear force-stiffness relationship (Hill-type model) and a nonlinear one have been implemented. The OpenSim platform was used for verification of the model. The isometric activation has been used for the simulation. The equivalent linear damping and the time constant of each model were extracted by using the results obtained from the simulation. The results provide a better insight into the characteristics of each model. It is found that the nonlinear models had a response rate closer to the reality compared to the Hill-type models.

Shock loading and reactive flow modeling studies of void induced AP/AL/HTPB propellant

Science.gov (United States)

Miller, P. J.; Lindfors, A. J.

1998-07-01

The unreactive Hugoniot of a class 1.3 propellant has been investigated by shock compression experiments. The results are analyzed in terms of an ignition and growth reactive flow model using the DYNA2D hydrocode. The calculated shock ignition parameters of the model show a linear dependence on measured void volume which appears to reproduce the observed gauge records well. Shock waves were generated by impact in a 75 mm single stage powder gun. Manganin and PVDF pressure gauges provided pressure-time histories to 140 kbar. The propellants were of similar formulation differing only in AP particle size and the addition of a burn rate modifer (Fe2O3) from that of previous investigations. Results show neglible effect of AP particle size on shock response in contrast to the addition of Fe2O3 which appears to `stiffen' the unreactive Hugoniot and enhances significantly the reactive rates under shock. The unreactive Hugoniot, within experimental error, compares favorably to the solid AP Hugoniot. Shock experiments were performed on propellant samples strained to induce insitu voids. The material state was quantified by uniaxial tension dialatometry. The experimental records show a direct correlation between void volume (0 to 1.7%) and chemical reactivity behind the shock front. These results are discussed in terms of `hot spot' ignition resulting from the shock collapse of the voids.

Sensitivity Analysis and Parameter Estimation for a Reactive Transport Model of Uranium Bioremediation

Science.gov (United States)

Meyer, P. D.; Yabusaki, S.; Curtis, G. P.; Ye, M.; Fang, Y.

2011-12-01

A three-dimensional, variably-saturated flow and multicomponent biogeochemical reactive transport model of uranium bioremediation was used to generate synthetic data . The 3-D model was based on a field experiment at the U.S. Dept. of Energy Rifle Integrated Field Research Challenge site that used acetate biostimulation of indigenous metal reducing bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. A key assumption in past modeling studies at this site was that a comprehensive reaction network could be developed largely through one-dimensional modeling. Sensitivity analyses and parameter estimation were completed for a 1-D reactive transport model abstracted from the 3-D model to test this assumption, to identify parameters with the greatest potential to contribute to model predictive uncertainty, and to evaluate model structure and data limitations. Results showed that sensitivities of key biogeochemical concentrations varied in space and time, that model nonlinearities and/or parameter interactions have a significant impact on calculated sensitivities, and that the complexity of the model's representation of processes affecting Fe(II) in the system may make it difficult to correctly attribute observed Fe(II) behavior to modeled processes. Non-uniformity of the 3-D simulated groundwater flux and averaging of the 3-D synthetic data for use as calibration targets in the 1-D modeling resulted in systematic errors in the 1-D model parameter estimates and outputs. This occurred despite using the same reaction network for 1-D modeling as used in the data-generating 3-D model. Predictive uncertainty of the 1-D model appeared to be significantly underestimated by linear parameter uncertainty estimates.

From linear to generalized linear mixed models: A case study in repeated measures

Science.gov (United States)

Compared to traditional linear mixed models, generalized linear mixed models (GLMMs) can offer better correspondence between response variables and explanatory models, yielding more efficient estimates and tests in the analysis of data from designed experiments. Using proportion data from a designed...

Extended Linear Models with Gaussian Priors

DEFF Research Database (Denmark)

Quinonero, Joaquin

2002-01-01

In extended linear models the input space is projected onto a feature space by means of an arbitrary non-linear transformation. A linear model is then applied to the feature space to construct the model output. The dimension of the feature space can be very large, or even infinite, giving the model...... a very big flexibility. Support Vector Machines (SVM's) and Gaussian processes are two examples of such models. In this technical report I present a model in which the dimension of the feature space remains finite, and where a Bayesian approach is used to train the model with Gaussian priors...... on the parameters. The Relevance Vector Machine, introduced by Tipping, is a particular case of such a model. I give the detailed derivations of the expectation-maximisation (EM) algorithm used in the training. These derivations are not found in the literature, and might be helpful for newcomers....

Linear mixed models for longitudinal data

CERN Document Server

Molenberghs, Geert

2000-01-01

This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...

Non-linear finite element modeling

DEFF Research Database (Denmark)

Mikkelsen, Lars Pilgaard

The note is written for courses in "Non-linear finite element method". The note has been used by the author teaching non-linear finite element modeling at Civil Engineering at Aalborg University, Computational Mechanics at Aalborg University Esbjerg, Structural Engineering at the University...

Reactive magnetron sputtering model at making Ti-TiOx coatings

International Nuclear Information System (INIS)

Luchkin, A G; Kashapov, N F

2014-01-01

Mathematical model of reactive magnetron sputtering for plant VU 700-D is described. Approximating curves for experimental current-voltage characteristic for two gas input schemas are shown. Choice of gas input schema influences on model parameters (mainly on pumping speed). Reactive magnetron sputtering model allows develop technology of Ti - TiO x coatings deposition without changing atmosphere and pressure in vacuum chamber

linear-quadratic-linear model

Directory of Open Access Journals (Sweden)

Tanwiwat Jaikuna

2017-02-01

Full Text Available Purpose: To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL model. Material and methods : The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR, and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD2 was calculated using biological effective dose (BED based on the LQL model. The software calculation and the manual calculation were compared for EQD2 verification with pair t-test statistical analysis using IBM SPSS Statistics version 22 (64-bit. Results: Two and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV determined by D90%, 0.56% in the bladder, 1.74% in the rectum when determined by D2cc, and less than 1% in Pinnacle. The difference in the EQD2 between the software calculation and the manual calculation was not significantly different with 0.00% at p-values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT and 0.240, 0.320, and 0.849 for brachytherapy (BT in HR-CTV, bladder, and rectum, respectively. Conclusions : The Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

Statistical Tests for Mixed Linear Models

CERN Document Server

Khuri, André I; Sinha, Bimal K

2011-01-01

An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a

Matrix Tricks for Linear Statistical Models

CERN Document Server

Puntanen, Simo; Styan, George PH

2011-01-01

In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and

An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Poulsen, Niels Kjølstad

This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making...

Modeling of Volatility with Non-linear Time Series Model

OpenAIRE

Kim Song Yon; Kim Mun Chol

2013-01-01

In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.

Applicability of linear and non-linear potential flow models on a Wavestar float

DEFF Research Database (Denmark)

Bozonnet, Pauline; Dupin, Victor; Tona, Paolino

2017-01-01

as a model based on non-linear potential flow theory and weakscatterer hypothesis are successively considered. Simple tests, such as dip tests, decay tests and captive tests enable to highlight the improvements obtained with the introduction of nonlinearities. Float motion under wave actions and without...... control action, limited to small amplitude motion with a single float, is well predicted by the numerical models, including the linear one. Still, float velocity is better predicted by accounting for non-linear hydrostatic and Froude-Krylov forces.......Numerical models based on potential flow theory, including different types of nonlinearities are compared and validated against experimental data for the Wavestar wave energy converter technology. Exact resolution of the rotational motion, non-linear hydrostatic and Froude-Krylov forces as well...

Forecasting Volatility of Dhaka Stock Exchange: Linear Vs Non-linear models

Directory of Open Access Journals (Sweden)

Masudul Islam

2012-10-01

Full Text Available Prior information about a financial market is very essential for investor to invest money on parches share from the stock market which can strengthen the economy. The study examines the relative ability of various models to forecast daily stock indexes future volatility. The forecasting models that employed from simple to relatively complex ARCH-class models. It is found that among linear models of stock indexes volatility, the moving average model ranks first using root mean square error, mean absolute percent error, Theil-U and Linex loss function  criteria. We also examine five nonlinear models. These models are ARCH, GARCH, EGARCH, TGARCH and restricted GARCH models. We find that nonlinear models failed to dominate linear models utilizing different error measurement criteria and moving average model appears to be the best. Then we forecast the next two months future stock index price volatility by the best (moving average model.

Modelling atmospheric OH-reactivity in a boreal forest ecosystem

DEFF Research Database (Denmark)

Mogensen, D.; Smolander, S.; Sogachev, Andrey

2011-01-01

We have modelled the total atmospheric OH-reactivity in a boreal forest and investigated the individual contributions from gas phase inorganic species, isoprene, monoterpenes, and methane along with other important VOCs. Daily and seasonal variation in OH-reactivity for the year 2008 was examined...

The Importance of Protons in Reactive Transport Modeling

Science.gov (United States)

McNeece, C. J.; Hesse, M. A.

2014-12-01

The importance of pH in aqueous chemistry is evident; yet, its role in reactive transport is complex. Consider a column flow experiment through silica glass beads. Take the column to be saturated and flowing with solution of a distinct pH. An instantaneous change in the influent solution pH can yield a breakthrough curve with both a rarefaction and shock component (composite wave). This behavior is unique among aqueous ions in transport and is more complex than intuition would tell. Analysis of the hyperbolic limit of this physical system can explain these first order transport phenomenon. This analysis shows that transport behavior is heavily dependent on the shape of the adsorption isotherm. Hence it is clear that accurate surface chemistry models are important in reactive transport. The proton adsorption isotherm has nonconstant concavity due to the proton's ability to partition into hydroxide. An eigenvalue analysis shows that an inflection point in the adsorption isotherm allows the development of composite waves. We use electrostatic surface complexation models to calculate realistic proton adsorption isotherms. Surface characteristics such as specific surface area, and surface site density were determined experimentally. We validate the model by comparison against silica glass bead flow through experiments. When coupled to surface complexation models, the transport equation captures the timing and behavior of breakthrough curves markedly better than with commonly used Langmuir assumptions. Furthermore, we use the adsorption isotherm to predict, a priori, the transport behavior of protons across pH composition space. Expansion of the model to multicomponent systems shows that proton adsorption can force composite waves to develop in the breakthrough curves of ions that would not otherwise exhibit such behavior. Given the abundance of reactive surfaces in nature and the nonlinearity of chemical systems, we conclude that building a greater understanding of

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

Science.gov (United States)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.

Comparing linear probability model coefficients across groups

DEFF Research Database (Denmark)

Holm, Anders; Ejrnæs, Mette; Karlson, Kristian Bernt

2015-01-01

of the following three components: outcome truncation, scale parameters and distributional shape of the predictor variable. These results point to limitations in using linear probability model coefficients for group comparisons. We also provide Monte Carlo simulations and real examples to illustrate......This article offers a formal identification analysis of the problem in comparing coefficients from linear probability models between groups. We show that differences in coefficients from these models can result not only from genuine differences in effects, but also from differences in one or more...... these limitations, and we suggest a restricted approach to using linear probability model coefficients in group comparisons....

To Model Chemical Reactivity in Heterogeneous Emulsions, Think Homogeneous Microemulsions.

Science.gov (United States)

Bravo-Díaz, Carlos; Romsted, Laurence Stuart; Liu, Changyao; Losada-Barreiro, Sonia; Pastoriza-Gallego, Maria José; Gao, Xiang; Gu, Qing; Krishnan, Gunaseelan; Sánchez-Paz, Verónica; Zhang, Yongliang; Dar, Aijaz Ahmad

2015-08-25

Two important and unsolved problems in the food industry and also fundamental questions in colloid chemistry are how to measure molecular distributions, especially antioxidants (AOs), and how to model chemical reactivity, including AO efficiency in opaque emulsions. The key to understanding reactivity in organized surfactant media is that reaction mechanisms are consistent with a discrete structures-separate continuous regions duality. Aggregate structures in emulsions are determined by highly cooperative but weak organizing forces that allow reactants to diffuse at rates approaching their diffusion-controlled limit. Reactant distributions for slow thermal bimolecular reactions are in dynamic equilibrium, and their distributions are proportional to their relative solubilities in the oil, interfacial, and aqueous regions. Our chemical kinetic method is grounded in thermodynamics and combines a pseudophase model with methods for monitoring the reactions of AOs with a hydrophobic arenediazonium ion probe in opaque emulsions. We introduce (a) the logic and basic assumptions of the pseudophase model used to define the distributions of AOs among the oil, interfacial, and aqueous regions in microemulsions and emulsions and (b) the dye derivatization and linear sweep voltammetry methods for monitoring the rates of reaction in opaque emulsions. Our results show that this approach provides a unique, versatile, and robust method for obtaining quantitative estimates of AO partition coefficients or partition constants and distributions and interfacial rate constants in emulsions. The examples provided illustrate the effects of various emulsion properties on AO distributions such as oil hydrophobicity, emulsifier structure and HLB, temperature, droplet size, surfactant charge, and acidity on reactant distributions. Finally, we show that the chemical kinetic method provides a natural explanation for the cut-off effect, a maximum followed by a sharp reduction in AO efficiency with

Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids

DEFF Research Database (Denmark)

Chen, Feixiong; Chen, Minyou; Li, Qiang

2016-01-01

of the control model, in which the uncertainty of intermittent DGs, variations in load demands, as well as impacts of time delays are considered. The simulation results demonstrate the eectiveness of the control model in proportional reactive power sharing, and the plug and play capability of the control model......In islanded microgrids (MGs), the reactive power cannot be shared proportionally among distributed generators (DGs) with conventional droop control, due to the mismatch in feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system (MAS) based distributed control...

Testing Parametric versus Semiparametric Modelling in Generalized Linear Models

NARCIS (Netherlands)

Härdle, W.K.; Mammen, E.; Müller, M.D.

1996-01-01

We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e.

Model Predictive Control for Linear Complementarity and Extended Linear Complementarity Systems

Directory of Open Access Journals (Sweden)

Bambang Riyanto

2005-11-01

Full Text Available In this paper, we propose model predictive control method for linear complementarity and extended linear complementarity systems by formulating optimization along prediction horizon as mixed integer quadratic program. Such systems contain interaction between continuous dynamics and discrete event systems, and therefore, can be categorized as hybrid systems. As linear complementarity and extended linear complementarity systems finds applications in different research areas, such as impact mechanical systems, traffic control and process control, this work will contribute to the development of control design method for those areas as well, as shown by three given examples.

Linear approximation model network and its formation via ...

Indian Academy of Sciences (India)

To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

Composite Linear Models | Division of Cancer Prevention

Science.gov (United States)

By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty

Probabilistic models for reactive behaviour in heterogeneous condensed phase media

Science.gov (United States)

Baer, M. R.; Gartling, D. K.; DesJardin, P. E.

2012-02-01

This work presents statistically-based models to describe reactive behaviour in heterogeneous energetic materials. Mesoscale effects are incorporated in continuum-level reactive flow descriptions using probability density functions (pdfs) that are associated with thermodynamic and mechanical states. A generalised approach is presented that includes multimaterial behaviour by treating the volume fraction as a random kinematic variable. Model simplifications are then sought to reduce the complexity of the description without compromising the statistical approach. Reactive behaviour is first considered for non-deformable media having a random temperature field as an initial state. A pdf transport relationship is derived and an approximate moment approach is incorporated in finite element analysis to model an example application whereby a heated fragment impacts a reactive heterogeneous material which leads to a delayed cook-off event. Modelling is then extended to include deformation effects associated with shock loading of a heterogeneous medium whereby random variables of strain, strain-rate and temperature are considered. A demonstrative mesoscale simulation of a non-ideal explosive is discussed that illustrates the joint statistical nature of the strain and temperature fields during shock loading to motivate the probabilistic approach. This modelling is derived in a Lagrangian framework that can be incorporated in continuum-level shock physics analysis. Future work will consider particle-based methods for a numerical implementation of this modelling approach.

Model-Based Testing of a Reactive System with Coloured Petri Nets

DEFF Research Database (Denmark)

Tjell, Simon

2006-01-01

In this paper, a reactive and nondeterministic system is tested. This is doneby applying a generic model that has been specified as a configurable Coloured PetriNet. In this way, model-based testing is possible for a wide class of reactive system atthe level of discrete events. Concurrently...

A reactive transport model for Marcellus shale weathering

Science.gov (United States)

Heidari, Peyman; Li, Li; Jin, Lixin; Williams, Jennifer Z.; Brantley, Susan L.

2017-11-01

Shale formations account for 25% of the land surface globally and contribute a large proportion of the natural gas used in the United States. One of the most productive shale-gas formations is the Marcellus, a black shale that is rich in organic matter and pyrite. As a first step toward understanding how Marcellus shale interacts with water in the surface or deep subsurface, we developed a reactive transport model to simulate shale weathering under ambient temperature and pressure conditions, constrained by soil and water chemistry data. The simulation was carried out for 10,000 years since deglaciation, assuming bedrock weathering and soil genesis began after the last glacial maximum. Results indicate weathering was initiated by pyrite dissolution for the first 1000 years, leading to low pH and enhanced dissolution of chlorite and precipitation of iron hydroxides. After pyrite depletion, chlorite dissolved slowly, primarily facilitated by the presence of CO2 and organic acids, forming vermiculite as a secondary mineral. A sensitivity analysis indicated that the most important controls on weathering include the presence of reactive gases (CO2 and O2), specific surface area, and flow velocity of infiltrating meteoric water. The soil chemistry and mineralogy data could not be reproduced without including the reactive gases. For example, pyrite remained in the soil even after 10,000 years if O2 was not continuously present in the soil column; likewise, chlorite remained abundant and porosity remained small if CO2 was not present in the soil gas. The field observations were only simulated successfully when the modeled specific surface areas of the reactive minerals were 1-3 orders of magnitude smaller than surface area values measured for powdered minerals. Small surface areas could be consistent with the lack of accessibility of some fluids to mineral surfaces due to surface coatings. In addition, some mineral surface is likely interacting only with equilibrated pore

Quantitative structure–reactivity study on sulfonation of amines, alcohols and phenols

Directory of Open Access Journals (Sweden)

Abolghasem Beheshti

2017-05-01

Full Text Available Quantitative structure–reactivity relationship (QSRR can be considered as a variant of quantitative structure property relationship (QSPR studies, where the chemical reactivity of reactants in a specified chemical reaction is related to chemical structure. As follows, the sulfonation reaction yield of 24 amines, alcohols and phenols with sulfonyl chloride was studied by QSRR. Quantum chemical calculations (b3lyp/6-31+g (d were carried out to obtain the optimized geometry. The suitable set of molecular descriptors was calculated to represent the molecular structures of compounds, such as constitutional, topological, geometrical, electrostatic and quantum-chemical descriptors. The genetic algorithm (GA was applied to select the variables that resulted in the best-fitted models. After the variable selection, multiple linear regression (MLR was utilized to construct linear QSRR models. The maximum relative error in prediction (5.26 showed that the predictive ability of the model was satisfactory and it can be used for designing similar reactants with efficient sulfonation reaction.

Actuarial statistics with generalized linear mixed models

NARCIS (Netherlands)

Antonio, K.; Beirlant, J.

2007-01-01

Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics

The CREST reactive-burn model for explosives

Directory of Open Access Journals (Sweden)

Maheswaran M-A.

2011-01-01

Full Text Available CREST is an innovative reactive-burn model that has been developed at AWE for simulating shock initiation and detonation propagation behaviour in explosives. The model has a different basis from other reactive-burn models in that its reaction rate is independent of local flow variables behind the shock wave e.g. pressure and temperature. The foundation for CREST, based on a detailed analysis of data from particle-velocity gauge experiments, is that the reaction rate depends only on the local shock strength and the time since the shock passed. Since a measure of shock strength is the entropy of the non-reacted explosive, which remains constant behind a shock, CREST uses an entropy-dependent reaction rate. This paper will provide an overview of the CREST model and its predictive capability. In particular, it will be shown that the model can predict a wide range of experimental phenomena for both shock initiation (e.g. the effects of porosity and initial temperature on sustained-shock and thin-flyer initiation and detonation propagation (e.g. the diameter effect curve and detonation failure cones using a single set of coefficients.

Modelling of power-reactivity coefficient measurement

International Nuclear Information System (INIS)

Strmensky, C.; Petenyi, V.; Jagrik, J.; Minarcin, M.; Hascik, R.; Toth, L.

2005-01-01

Report describes results of modeling of power-reactivity coefficient analysis on power-level. In paper we calculate values of discrepancies arisen during transient process. These discrepancies can be arisen as result of experiment evaluation and can be caused by disregard of 3D effects on neutron distribution. The results are critically discussed (Authors)

Heterotic sigma models and non-linear strings

International Nuclear Information System (INIS)

Hull, C.M.

1986-01-01

The two-dimensional supersymmetric non-linear sigma models are examined with respect to the heterotic string. The paper was presented at the workshop on :Supersymmetry and its applications', Cambridge, United Kingdom, 1985. The non-linear sigma model with Wess-Zumino-type term, the coupling of the fermionic superfields to the sigma model, super-conformal invariance, and the supersymmetric string, are all discussed. (U.K.)

Ignition-and-Growth Modeling of NASA Standard Detonator and a Linear Shaped Charge

Science.gov (United States)

Oguz, Sirri

2010-01-01

The main objective of this study is to quantitatively investigate the ignition and shock sensitivity of NASA Standard Detonator (NSD) and the shock wave propagation of a linear shaped charge (LSC) after being shocked by NSD flyer plate. This combined explosive train was modeled as a coupled Arbitrary Lagrangian-Eulerian (ALE) model with LS-DYNA hydro code. An ignition-and-growth (I&G) reactive model based on unreacted and reacted Jones-Wilkins-Lee (JWL) equations of state was used to simulate the shock initiation. Various NSD-to-LSC stand-off distances were analyzed to calculate the shock initiation (or failure to initiate) and detonation wave propagation along the shaped charge. Simulation results were verified by experimental data which included VISAR tests for NSD flyer plate velocity measurement and an aluminum target severance test for LSC performance verification. Parameters used for the analysis were obtained from various published data or by using CHEETAH thermo-chemical code.

Comparison of linear and non-linear models for the adsorption of fluoride onto geo-material: limonite.

Science.gov (United States)

Sahin, Rubina; Tapadia, Kavita

2015-01-01

The three widely used isotherms Langmuir, Freundlich and Temkin were examined in an experiment using fluoride (F⁻) ion adsorption on a geo-material (limonite) at four different temperatures by linear and non-linear models. Comparison of linear and non-linear regression models were given in selecting the optimum isotherm for the experimental results. The coefficient of determination, r², was used to select the best theoretical isotherm. The four Langmuir linear equations (1, 2, 3, and 4) are discussed. Langmuir isotherm parameters obtained from the four Langmuir linear equations using the linear model differed but they were the same when using the nonlinear model. Langmuir-2 isotherm is one of the linear forms, and it had the highest coefficient of determination (r² = 0.99) compared to the other Langmuir linear equations (1, 3 and 4) in linear form, whereas, for non-linear, Langmuir-4 fitted best among all the isotherms because it had the highest coefficient of determination (r² = 0.99). The results showed that the non-linear model may be a better way to obtain the parameters. In the present work, the thermodynamic parameters show that the absorption of fluoride onto limonite is both spontaneous (ΔG 0). Scanning electron microscope and X-ray diffraction images also confirm the adsorption of F⁻ ion onto limonite. The isotherm and kinetic study reveals that limonite can be used as an adsorbent for fluoride removal. In future we can develop new technology for fluoride removal in large scale by using limonite which is cost-effective, eco-friendly and is easily available in the study area.

A Reactive Transport Model for Marcellus Shale Weathering

Science.gov (United States)

Li, L.; Heidari, P.; Jin, L.; Williams, J.; Brantley, S.

2017-12-01

Shale formations account for 25% of the land surface globally. One of the most productive shale-gas formations is the Marcellus, a black shale that is rich in organic matter and pyrite. As a first step toward understanding how Marcellus shale interacts with water, we developed a reactive transport model to simulate shale weathering under ambient temperature and pressure conditions, constrained by soil chemistry and water data. The simulation was carried out for 10,000 years, assuming bedrock weathering and soil genesis began right after the last glacial maximum. Results indicate weathering was initiated by pyrite dissolution for the first 1,000 years, leading to low pH and enhanced dissolution of chlorite and precipitation of iron hydroxides. After pyrite depletion, chlorite dissolved slowly, primarily facilitated by the presence of CO2 and organic acids, forming vermiculite as a secondary mineral. A sensitivity analysis indicated that the most important controls on weathering include the presence of reactive gases (CO2 and O2), specific surface area, and flow velocity of infiltrating meteoric water. The soil chemistry and mineralogy data could not be reproduced without including the reactive gases. For example, pyrite remained in the soil even after 10,000 years if O2 was not continuously present in the soil column; likewise, chlorite remained abundant and porosity remained small with the presence of soil CO2. The field observations were only simulated successfully when the specific surface areas of the reactive minerals were 1-3 orders of magnitude smaller than surface area values measured for powdered minerals, reflecting the lack of accessibility of fluids to mineral surfaces and potential surface coating. An increase in the water infiltration rate enhanced weathering by removing dissolution products and maintaining far-from-equilibrium conditions. We conclude that availability of reactive surface area and transport of H2O and gases are the most important

Secure provision of reactive power ancillary services in competitive electricity markets

Science.gov (United States)

El-Samahy, Ismael

decoupled and assumed to be fixed during the reactive power dispatch procedures; however, the effect of reactive power on real power is considered in the model by calculating the required reduction in real power output of a generator due to an increase in its reactive power supply. In this case, real power generation is allowed to be rescheduled, within given limits, from the already dispatched levels obtained from the energy market clearing process. The proposed dispatch model achieves the main objective of an ISO in a competitive electricity market, which is to provide the required reactive power support from generators at least cost while ensuring a secure operation of the power system. The proposed reactive power procurement and dispatch models capture both the technical and economic aspects of power system operation in competitive electricity markets; however, from an optimization point of view, these models represent non-convex mixed integer non-linear programming (MINLP) problems due to the presence of binary variables associated with the different regions of reactive power operation in a synchronous generator. Such MINLP optimization problems are difficult to solve, especially for an actual power system. A novel Generator Reactive Power Classification (GRPC) algorithm is proposed in this thesis to address this issue, with the advantage of iteratively solving the optimization models as a series of non-linear programming (NLP) sub-problems. The proposed reactive power procurement and dispatch models are implemented and tested on the CIGRE 32-bus system, with several case studies that represent different practical operating scenarios. The developed models are also compared with other approaches for reactive power provision, and the results demonstrate the robustness and effectiveness of the proposed model. The results clearly reveal the main features of the proposed models for optimal provision of reactive power ancillary service, in order to suit the requirements of

Non linear viscoelastic models

DEFF Research Database (Denmark)

Agerkvist, Finn T.

2011-01-01

Viscoelastic eects are often present in loudspeaker suspensions, this can be seen in the displacement transfer function which often shows a frequency dependent value below the resonance frequency. In this paper nonlinear versions of the standard linear solid model (SLS) are investigated....... The simulations show that the nonlinear version of the Maxwell SLS model can result in a time dependent small signal stiness while the Kelvin Voight version does not....

Structural and reactivity models for copper oxygenases: cooperative effects and novel reactivities.

Science.gov (United States)

Serrano-Plana, Joan; Garcia-Bosch, Isaac; Company, Anna; Costas, Miquel

2015-08-18

Dioxygen is widely used in nature as oxidant. Nature itself has served as inspiration to use O2 in chemical synthesis. However, the use of dioxygen as an oxidant is not straightforward. Its triplet ground-state electronic structure makes it unreactive toward most organic substrates. In natural systems, metalloenzymes activate O2 by reducing it to more reactive peroxide (O2(2-)) or superoxide (O2(-)) forms. Over the years, the development of model systems containing transition metals has become a convenient tool for unravelling O2-activation mechanistic aspects and reproducing the oxidative activity of enzymes. Several copper-based systems have been developed within this area. Tyrosinase is a copper-based O2-activating enzyme, whose structure and reactivity have been widely studied, and that serves as a paradigm for O2 activation at a dimetal site. It contains a dicopper center in its active site, and it catalyzes the regioselective ortho-hydroxylation of phenols to catechols and further oxidation to quinones. This represents an important step in melanin biosynthesis and it is mediated by a dicopper(II) side-on peroxo intermediate species. In the present accounts, our research in the field of copper models for oxygen activation is collected. We have developed m-xylyl linked dicopper systems that mimick structural and reactivity aspects of tyrosinase. Synergistic cooperation of the two copper(I) centers results in O2 binding and formation of bis(μ-oxo)dicopper(III) cores. These in turn bind and ortho-hydroxylate phenolates via an electrophilic attack of the oxo ligand over the arene. Interestingly the bis(μ-oxo)dicopper(III) cores can also engage in ortho-hydroxylation-defluorination of deprotonated 2-fluorophenols, substrates that are well-known enzyme inhibitors. Analysis of Cu2O2 species with different binding modes show that only the bis(μ-oxo)dicopper(III) cores can mediate the reaction. Finally, the use of unsymmetric systems for oxygen activation is a field

Genetic parameters for racing records in trotters using linear and generalized linear models.

Science.gov (United States)

Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

2012-09-01

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.

Generalised linear models for correlated pseudo-observations, with applications to multi-state models

DEFF Research Database (Denmark)

Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne

2003-01-01

Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...

6th International Workshop on Model Reduction in Reactive Flow

Science.gov (United States)

2018-01-01

reduction in reacting flow . Registration DateRegistration TypeFirst Name Middle NameLast Name Affiliation US State /Canadian ProvinceState/Province/R gion...Report: 6th International Workshop on Model Reduction in Reactive Flow The views, opinions and/or findings contained in this report are those of the...Agreement Number: W911NF-17-1-0121 Organization: Princeton University Title: 6th International Workshop on Model Reduction in Reactive Flow Report Term

Linear causal modeling with structural equations

CERN Document Server

Mulaik, Stanley A

2009-01-01

Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal

TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS

Science.gov (United States)

Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.

2017-01-01

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971

Surrogate model approach for improving the performance of reactive transport simulations

Science.gov (United States)

Jatnieks, Janis; De Lucia, Marco; Sips, Mike; Dransch, Doris

2016-04-01

Reactive transport models can serve a large number of important geoscientific applications involving underground resources in industry and scientific research. It is common for simulation of reactive transport to consist of at least two coupled simulation models. First is a hydrodynamics simulator that is responsible for simulating the flow of groundwaters and transport of solutes. Hydrodynamics simulators are well established technology and can be very efficient. When hydrodynamics simulations are performed without coupled geochemistry, their spatial geometries can span millions of elements even when running on desktop workstations. Second is a geochemical simulation model that is coupled to the hydrodynamics simulator. Geochemical simulation models are much more computationally costly. This is a problem that makes reactive transport simulations spanning millions of spatial elements very difficult to achieve. To address this problem we propose to replace the coupled geochemical simulation model with a surrogate model. A surrogate is a statistical model created to include only the necessary subset of simulator complexity for a particular scenario. To demonstrate the viability of such an approach we tested it on a popular reactive transport benchmark problem that involves 1D Calcite transport. This is a published benchmark problem (Kolditz, 2012) for simulation models and for this reason we use it to test the surrogate model approach. To do this we tried a number of statistical models available through the caret and DiceEval packages for R, to be used as surrogate models. These were trained on randomly sampled subset of the input-output data from the geochemical simulation model used in the original reactive transport simulation. For validation we use the surrogate model to predict the simulator output using the part of sampled input data that was not used for training the statistical model. For this scenario we find that the multivariate adaptive regression splines

On D-branes from gauged linear sigma models

International Nuclear Information System (INIS)

Govindarajan, S.; Jayaraman, T.; Sarkar, T.

2001-01-01

We study both A-type and B-type D-branes in the gauged linear sigma model by considering worldsheets with boundary. The boundary conditions on the matter and vector multiplet fields are first considered in the large-volume phase/non-linear sigma model limit of the corresponding Calabi-Yau manifold, where we find that we need to add a contact term on the boundary. These considerations enable to us to derive the boundary conditions in the full gauged linear sigma model, including the addition of the appropriate boundary contact terms, such that these boundary conditions have the correct non-linear sigma model limit. Most of the analysis is for the case of Calabi-Yau manifolds with one Kaehler modulus (including those corresponding to hypersurfaces in weighted projective space), though we comment on possible generalisations

Decomposable log-linear models

DEFF Research Database (Denmark)

Eriksen, Poul Svante

can be characterized by a structured set of conditional independencies between some variables given some other variables. We term the new model class decomposable log-linear models, which is illustrated to be a much richer class than decomposable graphical models.It covers a wide range of non...... The present paper considers discrete probability models with exact computational properties. In relation to contingency tables this means closed form expressions of the maksimum likelihood estimate and its distribution. The model class includes what is known as decomposable graphicalmodels, which......-hierarchical models, models with structural zeroes, models described by quasi independence and models for level merging. Also, they have a very natural interpretation as they may be formulated by a structured set of conditional independencies between two events given some other event. In relation to contingency...

Neutron density fluctuations in point reactor systems with dichotomic reactivity noise

International Nuclear Information System (INIS)

Sako, Okitsugu

1984-01-01

The exactly solvable stochastic point reactor model systems are analyzed through the stochastic Liouville equation. Three kinds of model systems are treated: (1) linear system without delayed neutrons, (2) linear system with one-group of delayed neutrons, and (3) nonlinear system with direct power feedback. The exact expressions for the fluctuations of neutron density, such as the moments, autocorrelation function and power spectral density, are derived in the case where the colored reactivity noise is described by the dichotomic, or two state, Markov process with arbitrary correlation time and intensity, and the effects of the finite correlation time and intensity of the noise on the neutron density fluctuations are investigated. The influence of presence of delayed neutrons and the effect of nonlinearity of system on the neutron density fluctuations are also elucidated. When the reactivity correlation time is very short, the correlation time has almost no effect on the power spectral density, and the relative fluctuation of neutron density in the stationary state is not affected very much by the presence of delayed neutrons and also by the nonlinearity of system. On the other hand, if the reactivity correlation time is very long, the effect of the reactivity noise on the power spectral density appears at very low frequency, and the presence of delayed neutrons has an effect of reducing the neutron density fluctuations. (author)

Modeling digital switching circuits with linear algebra

CERN Document Server

Thornton, Mitchell A

2014-01-01

Modeling Digital Switching Circuits with Linear Algebra describes an approach for modeling digital information and circuitry that is an alternative to Boolean algebra. While the Boolean algebraic model has been wildly successful and is responsible for many advances in modern information technology, the approach described in this book offers new insight and different ways of solving problems. Modeling the bit as a vector instead of a scalar value in the set {0, 1} allows digital circuits to be characterized with transfer functions in the form of a linear transformation matrix. The use of transf

Decreased reactivation of a herpes simplex virus type 1 (HSV-1) latency associated transcript (LAT) mutant using the in vivo mouse UV-B model of induced reactivation

Science.gov (United States)

BenMohamed, Lbachir; Osorio, Nelson; Srivastava, Ruchi; Khan, Arif A.; Simpson, Jennifer L.; Wechsler, Steven L.

2015-01-01

Blinding ocular herpetic disease in humans is due to herpes simplex virus type 1 (HSV-1) reactivations from latency, rather than to primary acute infection. The cellular and molecular mechanisms that control the HSV-1 latency-reactivation cycle remain to be fully elucidated. The aim of this study was to determine if reactivation of the HSV-1 latency associated transcript (LAT) deletion mutant (dLAT2903) was impaired in this model, as it is in the rabbit model of induced and spontaneous reactivation and in the explant TG induced reactivation model in mice. The eyes of mice latently infected with wild type HSV-1 strain McKrae (LAT(+) virus) or dLAT2903 (LAT(−) virus) were irradiated with UV-B and reactivation was determined. We found that compared to LAT(−) virus, LAT(+) virus reactivated at a higher rate as determined by shedding of virus in tears on days 3 to 7 after UV-B treatment. Thus, the UV-B induced reactivation model of HSV-1 appears to be a useful small animal model for studying the mechanisms involved in how LAT enhances the HSV-1 reactivation phenotype. The utility of the model for investigating the immune evasion mechanisms regulating the HSV-1 latency/reactivation cycle and for testing the protective efficacy of candidate therapeutic vaccines and drugs are discussed. PMID:26002839

Non-linear Growth Models in Mplus and SAS

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

Variance Function Partially Linear Single-Index Models1.

Science.gov (United States)

Lian, Heng; Liang, Hua; Carroll, Raymond J

2015-01-01

We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

Modeling the surface tension of complex, reactive organic-inorganic mixtures

Science.gov (United States)

Schwier, A. N.; Viglione, G. A.; Li, Z.; McNeill, V. Faye

2013-11-01

Atmospheric aerosols can contain thousands of organic compounds which impact aerosol surface tension, affecting aerosol properties such as heterogeneous reactivity, ice nucleation, and cloud droplet formation. We present new experimental data for the surface tension of complex, reactive organic-inorganic aqueous mixtures mimicking tropospheric aerosols. Each solution contained 2-6 organic compounds, including methylglyoxal, glyoxal, formaldehyde, acetaldehyde, oxalic acid, succinic acid, leucine, alanine, glycine, and serine, with and without ammonium sulfate. We test two semi-empirical surface tension models and find that most reactive, complex, aqueous organic mixtures which do not contain salt are well described by a weighted Szyszkowski-Langmuir (S-L) model which was first presented by Henning et al. (2005). Two approaches for modeling the effects of salt were tested: (1) the Tuckermann approach (an extension of the Henning model with an additional explicit salt term), and (2) a new implicit method proposed here which employs experimental surface tension data obtained for each organic species in the presence of salt used with the Henning model. We recommend the use of method (2) for surface tension modeling of aerosol systems because the Henning model (using data obtained from organic-inorganic systems) and Tuckermann approach provide similar modeling results and goodness-of-fit (χ2) values, yet the Henning model is a simpler and more physical approach to modeling the effects of salt, requiring less empirically determined parameters.

Linear latent variable models: the lava-package

DEFF Research Database (Denmark)

Holst, Klaus Kähler; Budtz-Jørgensen, Esben

2013-01-01

are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...

Coupled hydrogeological and reactive transport modelling of the Simpevarp area (Sweden)

International Nuclear Information System (INIS)

Molinero, Jorge; Raposo, Juan R.; Galindez, Juan M.; Arcos, David; Guimera, Jordi

2008-01-01

The Simpevarp area is one of the alternative sites being considered for the deep geological disposal of high level radioactive waste in Sweden. In this paper, a coupled regional groundwater flow and reactive solute transport model of the Simpevarp area is presented that integrates current hydrogeological and hydrochemical data of the area. The model simulates the current hydrochemical pattern of the groundwater system in the area. To that aim, a conceptual hydrochemical model was developed in order to represent the dominant chemical processes. Groundwater flow conditions were reproduced by taking into account fluid-density-dependent groundwater flow and regional hydrogeologic boundary conditions. Reactive solute transport calculations were performed on the basis of the velocity field so obtained. The model was calibrated and sensitivity analyses were carried out in order to investigate the effects of heterogeneities of hydraulic conductivity in the subsurface medium. Results provided by the reactive transport model are in good agreement with much of the measured hydrochemical data. This paper emphasizes the appropriateness of the use of reactive solute transport models when water-rock interaction reactions are involved, and demonstrates what powerful tools they are for the interpretation of hydrogeological and hydrochemical data from site geological repository characterization programs, by providing a qualitative framework for data analysis and testing of conceptual assumptions in a process-oriented approach

Modeling Of A Reactive Distillation Column: Methyl Tertiary Butyl Ether (Mtbe Simulation Studies

Directory of Open Access Journals (Sweden)

Ismail Mohd Saaid Abdul Rahman Mohamed and Subhash Bhatia

2012-10-01

Full Text Available A process simulation stage-wise reactive distillation column model formulated from equilibrium stage theory was developed. The algorithm for solving mathematical model represented by sets of differential-algebraic equations was based on relaxation method. Numerical integration scheme based on backward differentiation formula was selected for solving the stiffness of differential-algebraic equations. Simulations were performed on a personal computer (PC Pentium processor through a developed computer program using FORTRAN90 programming language. The proposed model was validated by comparing the simulated results with the published simulation results and with the pilot plant data from the literature. The model was capable of predicting high isobutene conversion for heterogeneous system, as desirable in industrial MTBE production process. The comparisons on temperature profiles, liquid composition profile and operating conditions of reactive distillation column also showed promising results. Therefore the proposed model can be used as a tool for the development and simulation of reactive distillation column.Keywords: Modeling, simulation, reactive distillation, relaxation method, equilibrium stage, heterogeneous, MTBE

Reactivity calculation with reduction of the nuclear power fluctuations

International Nuclear Information System (INIS)

Suescun Diaz, Daniel; Senra Martinez, Aquilino

2009-01-01

A new formulation is presented in this paper for the calculation of reactivity, which is simpler than the formulation that uses the Laplace and Z transforms. A treatment is also made to reduce the intensity of the noise found in the nuclear power signal used in the calculation of reactivity. Two classes of different filters are used for that. This treatment is based on the fact that the reactivity can be written by using the compose Simpson's rule resulting in a sum of two convolution terms with response to the impulse that is characteristic of a linear system. The linear part is calculated by using the filter named finite impulse response filter (FIR). The non-linear part is calculated using the filter exponentially adjusted by the least squares method, which does not cause attenuation in the reactivity calculation.

Reactivity calculation with reduction of the nuclear power fluctuations

Energy Technology Data Exchange (ETDEWEB)

Suescun Diaz, Daniel [COPPE/UFRJ, Programa de Engenharia Nuclear, Caixa Postal 68509, CEP 21941-914 RJ (Brazil)], E-mail: dsuescun@hotmail.com; Senra Martinez, Aquilino [COPPE/UFRJ, Programa de Engenharia Nuclear, Caixa Postal 68509, CEP 21941-914 RJ (Brazil)

2009-05-15

A new formulation is presented in this paper for the calculation of reactivity, which is simpler than the formulation that uses the Laplace and Z transforms. A treatment is also made to reduce the intensity of the noise found in the nuclear power signal used in the calculation of reactivity. Two classes of different filters are used for that. This treatment is based on the fact that the reactivity can be written by using the compose Simpson's rule resulting in a sum of two convolution terms with response to the impulse that is characteristic of a linear system. The linear part is calculated by using the filter named finite impulse response filter (FIR). The non-linear part is calculated using the filter exponentially adjusted by the least squares method, which does not cause attenuation in the reactivity calculation.

A Preliminary Assessment of the SURF Reactive Burn Model Implementation in FLAG

Energy Technology Data Exchange (ETDEWEB)

Johnson, Carl Edward [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); McCombe, Ryan Patrick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Carver, Kyle [United States Air Force, Washington, DC (United States)

2017-09-18

Properly validated and calibrated reactive burn models (RBM) can be useful engineering tools for assessing high explosive performance and safety. Experiments with high explosives are expensive. Inexpensive RBM calculations are increasingly relied on for predictive analysis for performance and safety. This report discusses the validation of Menikoff and Shaw’s SURF reactive burn model, which has recently been implemented in the FLAG code. The LANL Gapstick experiment is discussed as is its’ utility in reactive burn model validation. Data obtained from pRad for the LT-63 series is also presented along with FLAG simulations using SURF for both PBX 9501 and PBX 9502. Calibration parameters for both explosives are presented.

Linear factor copula models and their properties

KAUST Repository

Krupskii, Pavel; Genton, Marc G.

2018-01-01

We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.

Linear factor copula models and their properties

KAUST Repository

Krupskii, Pavel

2018-04-25

We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.

Modelling Loudspeaker Non-Linearities

DEFF Research Database (Denmark)

Agerkvist, Finn T.

2007-01-01

This paper investigates different techniques for modelling the non-linear parameters of the electrodynamic loudspeaker. The methods are tested not only for their accuracy within the range of original data, but also for the ability to work reasonable outside that range, and it is demonstrated...... that polynomial expansions are rather poor at this, whereas an inverse polynomial expansion or localized fitting functions such as the gaussian are better suited for modelling the Bl-factor and compliance. For the inductance the sigmoid function is shown to give very good results. Finally the time varying...

Predictive model for convective flows induced by surface reactivity contrast

Science.gov (United States)

Davidson, Scott M.; Lammertink, Rob G. H.; Mani, Ali

2018-05-01

Concentration gradients in a fluid adjacent to a reactive surface due to contrast in surface reactivity generate convective flows. These flows result from contributions by electro- and diffusio-osmotic phenomena. In this study, we have analyzed reactive patterns that release and consume protons, analogous to bimetallic catalytic conversion of peroxide. Similar systems have typically been studied using either scaling analysis to predict trends or costly numerical simulation. Here, we present a simple analytical model, bridging the gap in quantitative understanding between scaling relations and simulations, to predict the induced potentials and consequent velocities in such systems without the use of any fitting parameters. Our model is tested against direct numerical solutions to the coupled Poisson, Nernst-Planck, and Stokes equations. Predicted slip velocities from the model and simulations agree to within a factor of ≈2 over a multiple order-of-magnitude change in the input parameters. Our analysis can be used to predict enhancement of mass transport and the resulting impact on overall catalytic conversion, and is also applicable to predicting the speed of catalytic nanomotors.

Log-normal frailty models fitted as Poisson generalized linear mixed models.

Science.gov (United States)

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Linearized models for a new magnetic control in MAST

International Nuclear Information System (INIS)

Artaserse, G.; Maviglia, F.; Albanese, R.; McArdle, G.J.; Pangione, L.

2013-01-01

Highlights: ► We applied linearized models for a new magnetic control on MAST tokamak. ► A suite of procedures, conceived to be machine independent, have been used. ► We carried out model-based simulations, taking into account eddy currents effects. ► Comparison with the EFIT flux maps and the experimental magnetic signals are shown. ► A current driven model for the dynamic simulations of the experimental data have been performed. -- Abstract: The aim of this work is to provide reliable linearized models for the design and assessment of a new magnetic control system for MAST (Mega Ampère Spherical Tokamak) using rtEFIT, which can easily be exported to MAST Upgrade. Linearized models for magnetic control have been obtained using the 2D axisymmetric finite element code CREATE L. MAST linearized models include equivalent 2D axisymmetric schematization of poloidal field (PF) coils, vacuum vessel, and other conducting structures. A plasmaless and a double null configuration have been chosen as benchmark cases for the comparison with experimental data and EFIT reconstructions. Good agreement has been found with the EFIT flux map and the experimental signals coming from magnetic probes with only few mismatches probably due to broken sensors. A suite of procedures (equipped with a user friendly interface to be run even remotely) to provide linearized models for magnetic control is now available on the MAST linux machines. A new current driven model has been used to obtain a state space model having the PF coil currents as inputs. Dynamic simulations of experimental data have been carried out using linearized models, including modelling of the effects of the passive structures, showing a fair agreement. The modelling activity has been useful also to reproduce accurately the interaction between plasma current and radial position control loops

Linearized models for a new magnetic control in MAST

Energy Technology Data Exchange (ETDEWEB)

Artaserse, G., E-mail: giovanni.artaserse@enea.it [Associazione Euratom-ENEA sulla Fusione, Via Enrico Fermi 45, I-00044 Frascati (RM) (Italy); Maviglia, F.; Albanese, R. [Associazione Euratom-ENEA-CREATE sulla Fusione, Via Claudio 21, I-80125 Napoli (Italy); McArdle, G.J.; Pangione, L. [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon, OX14 3DB (United Kingdom)

2013-10-15

Highlights: ► We applied linearized models for a new magnetic control on MAST tokamak. ► A suite of procedures, conceived to be machine independent, have been used. ► We carried out model-based simulations, taking into account eddy currents effects. ► Comparison with the EFIT flux maps and the experimental magnetic signals are shown. ► A current driven model for the dynamic simulations of the experimental data have been performed. -- Abstract: The aim of this work is to provide reliable linearized models for the design and assessment of a new magnetic control system for MAST (Mega Ampère Spherical Tokamak) using rtEFIT, which can easily be exported to MAST Upgrade. Linearized models for magnetic control have been obtained using the 2D axisymmetric finite element code CREATE L. MAST linearized models include equivalent 2D axisymmetric schematization of poloidal field (PF) coils, vacuum vessel, and other conducting structures. A plasmaless and a double null configuration have been chosen as benchmark cases for the comparison with experimental data and EFIT reconstructions. Good agreement has been found with the EFIT flux map and the experimental signals coming from magnetic probes with only few mismatches probably due to broken sensors. A suite of procedures (equipped with a user friendly interface to be run even remotely) to provide linearized models for magnetic control is now available on the MAST linux machines. A new current driven model has been used to obtain a state space model having the PF coil currents as inputs. Dynamic simulations of experimental data have been carried out using linearized models, including modelling of the effects of the passive structures, showing a fair agreement. The modelling activity has been useful also to reproduce accurately the interaction between plasma current and radial position control loops.

Reactive Kripke semantics

CERN Document Server

Gabbay, Dov M

2013-01-01

This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke models change their accessibility relation as we progress in the evaluation process of formulas in the model. This feature makes the reactive Kripke semantics strictly stronger and more applicable than the traditional one. Here we investigate the properties and axiomatisations of this new and most effective semantics, and we offer a wide landscape of applications of the idea of reactivity. Applied topics include reactive automata, reactive grammars, rea

Modeling Non-Linear Material Properties in Composite Materials

Science.gov (United States)

2016-06-28

Technical Report ARWSB-TR-16013 MODELING NON-LINEAR MATERIAL PROPERTIES IN COMPOSITE MATERIALS Michael F. Macri Andrew G...REPORT TYPE Technical 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE MODELING NON-LINEAR MATERIAL PROPERTIES IN COMPOSITE MATERIALS ...systems are increasingly incorporating composite materials into their design. Many of these systems subject the composites to environmental conditions

Modeling the dynamics of Plasmodium vivax infection and hypnozoite reactivation in vivo.

Directory of Open Access Journals (Sweden)

Adeshina I Adekunle

2015-03-01

Full Text Available The dynamics of Plasmodium vivax infection is characterized by reactivation of hypnozoites at varying time intervals. The relative contribution of new P. vivax infection and reactivation of dormant liver stage hypnozoites to initiation of blood stage infection is unclear. In this study, we investigate the contribution of new inoculations of P. vivax sporozoites to primary infection versus reactivation of hypnozoites by modeling the dynamics of P. vivax infection in Thailand in patients receiving treatment for either blood stage infection alone (chloroquine, or the blood and liver stages of infection (chloroquine + primaquine. In addition, we also analysed rates of infection in a study in Papua New Guinea (PNG where patients were treated with either artesunate, or artesunate + primaquine. Our results show that up to 96% of the P. vivax infection is due to hypnozoite reactivation in individuals living in endemic areas in Thailand. Similar analysis revealed the around 70% of infections in the PNG cohort were due to hypnozoite reactivation. We show how the age of the cohort, primaquine drug failure, and seasonality may affect estimates of the ratio of primary P. vivax infection to hypnozoite reactivation. Modeling of P. vivax primary infection and hypnozoite reactivation provides important insights into infection dynamics, and suggests that 90-96% of blood stage infections arise from hypnozoite reactivation. Major differences in infection kinetics between Thailand and PNG suggest the likelihood of drug failure in PNG.

Reactive transport modeling of the ABM experiment with Comsol Multiphysics

International Nuclear Information System (INIS)

Pekala, Marek; Idiart, Andres; Arcos, David

2012-01-01

solution) in a stack of 30 bentonite blocks of 11 distinct initial compositions. In the model, ion diffusion is allowed between the individual bentonite blocks and between the bentonite blocks and a sand layer filling the bentonite-rock gap. The effective diffusion coefficient values for individual bentonite blocks were estimated based on the dry density of the bentonite, and the temperature-dependent evolution of the diffusion coefficients is approximated in the course of the simulation. In order to solve the problem, a set of non-linear algebraic equations (mass action law for the cation-exchange reactions, and charge and mass balance equations) have been coupled with Fickian diffusion equations. As mentioned above, the Finite Element code COMSOL Multiphysics has been used to carry out the simulations. Preliminary results for the studied problem indicate that the effect of diffusion for the studied cations and chloride is significant and has the potential to explain quantitatively the observed patterns of homogenisation in the chemical composition in the bentonite package. However, the work is currently in progress and further analyses, including a sensitivity study of variables such as diffusion coefficients and boundary conditions, are on-going. A model simulating coupled cation-exchange and diffusion of major ions in the Package 1 of the ABM field experiment has been developed. This work demonstrates the feasibility of implementing a reactive transport model directly into Comsol Multiphysics using conservation and mass action equations. Comsol offers an intuitive and at the same time powerful modelling environment for simulating coupled multiphase, multi-species reactive transport phenomena and mechanical effects in complex geometries. For this reason, Amphos 21 has been involved in work aiming to couple Comsol with other codes such as the geochemical code PHREEQC. Such code integration has the potential to provide tools uniquely suited to solving complicated reactive

Non-linear Loudspeaker Unit Modelling

DEFF Research Database (Denmark)

Pedersen, Bo Rohde; Agerkvist, Finn T.

2008-01-01

Simulations of a 6½-inch loudspeaker unit are performed and compared with a displacement measurement. The non-linear loudspeaker model is based on the major nonlinear functions and expanded with time-varying suspension behaviour and flux modulation. The results are presented with FFT plots of thr...... frequencies and different displacement levels. The model errors are discussed and analysed including a test with loudspeaker unit where the diaphragm is removed....

Comparison between linear quadratic and early time dose models

International Nuclear Information System (INIS)

Chougule, A.A.; Supe, S.J.

1993-01-01

During the 70s, much interest was focused on fractionation in radiotherapy with the aim of improving tumor control rate without producing unacceptable normal tissue damage. To compare the radiobiological effectiveness of various fractionation schedules, empirical formulae such as Nominal Standard Dose, Time Dose Factor, Cumulative Radiation Effect and Tumour Significant Dose, were introduced and were used despite many shortcomings. It has been claimed that a recent linear quadratic model is able to predict the radiobiological responses of tumours as well as normal tissues more accurately. We compared Time Dose Factor and Tumour Significant Dose models with the linear quadratic model for tumour regression in patients with carcinomas of the cervix. It was observed that the prediction of tumour regression estimated by the Tumour Significant Dose and Time Dose factor concepts varied by 1.6% from that of the linear quadratic model prediction. In view of the lack of knowledge of the precise values of the parameters of the linear quadratic model, it should be applied with caution. One can continue to use the Time Dose Factor concept which has been in use for more than a decade as its results are within ±2% as compared to that predicted by the linear quadratic model. (author). 11 refs., 3 figs., 4 tabs

A Note on the Identifiability of Generalized Linear Mixed Models

DEFF Research Database (Denmark)

Labouriau, Rodrigo

2014-01-01

I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity...... conditions, and, therefore, is extensible to quasi-likelihood based generalized linear models. In particular, binomial and Poisson mixed models with dispersion parameter are identifiable when equipped with the standard parametrization...

A non-linear state space approach to model groundwater fluctuations

NARCIS (Netherlands)

Berendrecht, W.L.; Heemink, A.W.; Geer, F.C. van; Gehrels, J.C.

2006-01-01

A non-linear state space model is developed for describing groundwater fluctuations. Non-linearity is introduced by modeling the (unobserved) degree of water saturation of the root zone. The non-linear relations are based on physical concepts describing the dependence of both the actual

Reactive transport modeling in the subsurface environment with OGS-IPhreeqc

Science.gov (United States)

He, Wenkui; Beyer, Christof; Fleckenstein, Jan; Jang, Eunseon; Kalbacher, Thomas; Naumov, Dimitri; Shao, Haibing; Wang, Wenqing; Kolditz, Olaf

2015-04-01

Worldwide, sustainable water resource management becomes an increasingly challenging task due to the growth of population and extensive applications of fertilizer in agriculture. Moreover, climate change causes further stresses to both water quantity and quality. Reactive transport modeling in the coupled soil-aquifer system is a viable approach to assess the impacts of different land use and groundwater exploitation scenarios on the water resources. However, the application of this approach is usually limited in spatial scale and to simplified geochemical systems due to the huge computational expense involved. Such computational expense is not only caused by solving the high non-linearity of the initial boundary value problems of water flow in the unsaturated zone numerically with rather fine spatial and temporal discretization for the correct mass balance and numerical stability, but also by the intensive computational task of quantifying geochemical reactions. In the present study, a flexible and efficient tool for large scale reactive transport modeling in variably saturated porous media and its applications are presented. The open source scientific software OpenGeoSys (OGS) is coupled with the IPhreeqc module of the geochemical solver PHREEQC. The new coupling approach makes full use of advantages from both codes: OGS provides a flexible choice of different numerical approaches for simulation of water flow in the vadose zone such as the pressure-based or mixed forms of Richards equation; whereas the IPhreeqc module leads to a simplification of data storage and its communication with OGS, which greatly facilitates the coupling and code updating. Moreover, a parallelization scheme with MPI (Message Passing Interface) is applied, in which the computational task of water flow and mass transport is partitioned through domain decomposition, whereas the efficient parallelization of geochemical reactions is achieved by smart allocation of computational workload over

Effective connectivity between superior temporal gyrus and Heschl's gyrus during white noise listening: linear versus non-linear models.

Science.gov (United States)

Hamid, Ka; Yusoff, An; Rahman, Mza; Mohamad, M; Hamid, Aia

2012-04-01

This fMRI study is about modelling the effective connectivity between Heschl's gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. MATERIALS #ENTITYSTARTX00026; Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity. Group results indicated significant asymmetrical activation (p(uncorr) Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself. We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with

Web-based reactive transport modeling using PFLOTRAN

Science.gov (United States)

Zhou, H.; Karra, S.; Lichtner, P. C.; Versteeg, R.; Zhang, Y.

2017-12-01

Actionable understanding of system behavior in the subsurface is required for a wide spectrum of societal and engineering needs by both commercial firms and government entities and academia. These needs include, for example, water resource management, precision agriculture, contaminant remediation, unconventional energy production, CO2 sequestration monitoring, and climate studies. Such understanding requires the ability to numerically model various coupled processes that occur across different temporal and spatial scales as well as multiple physical domains (reservoirs - overburden, surface-subsurface, groundwater-surface water, saturated-unsaturated zone). Currently, this ability is typically met through an in-house approach where computational resources, model expertise, and data for model parameterization are brought together to meet modeling needs. However, such an approach has multiple drawbacks which limit the application of high-end reactive transport codes such as the Department of Energy funded[?] PFLOTRAN code. In addition, while many end users have a need for the capabilities provided by high-end reactive transport codes, they do not have the expertise - nor the time required to obtain the expertise - to effectively use these codes. We have developed and are actively enhancing a cloud-based software platform through which diverse users are able to easily configure, execute, visualize, share, and interpret PFLOTRAN models. This platform consists of a web application and available on-demand HPC computational infrastructure. The web application consists of (1) a browser-based graphical user interface which allows users to configure models and visualize results interactively, and (2) a central server with back-end relational databases which hold configuration, data, modeling results, and Python scripts for model configuration, and (3) a HPC environment for on-demand model execution. We will discuss lessons learned in the development of this platform, the

Linear Equating for the NEAT Design: Parameter Substitution Models and Chained Linear Relationship Models

Science.gov (United States)

Kane, Michael T.; Mroch, Andrew A.; Suh, Youngsuk; Ripkey, Douglas R.

2009-01-01

This paper analyzes five linear equating models for the "nonequivalent groups with anchor test" (NEAT) design with internal anchors (i.e., the anchor test is part of the full test). The analysis employs a two-dimensional framework. The first dimension contrasts two general approaches to developing the equating relationship. Under a "parameter…

Reactivity and Power Distribution Management in LEU-loaded Linear B and BR

International Nuclear Information System (INIS)

Hartanto, Donny; Kim, Yonghee

2013-01-01

In this paper, the relatively high excess reactivity issue during the initial transitional period was addressed. The design target is to achieve a maximum excess reactivity of about 1.0 dollar to prevent the possibility of the prompt jump critical accident. The initial core is divided into 2 radial Zr-zones in order to reduce the excess reactivity. By doing this, the power profile at the BOC can also be flattened. After the optimum initial core configuration has been found, the blanket region is also divided into 2 radial Zr-zones in order to flatten the power distribution at EOC. The neutronic analyses were all performed using the Monte Carlo code McCARD with ENDF-B/VII.0 library. It was found that by using the concave Zr-zoning in the initial core of B and BR, the maximum excess reactivity can be effectively lowered. The radial power profile can also be successfully flattened by using the Zr-zoning and concave initial core. The concave concept deserves more investigations for better performances of the B and BR core

Recent Updates to the GEOS-5 Linear Model

Science.gov (United States)

Holdaway, Dan; Kim, Jong G.; Errico, Ron; Gelaro, Ronald; Mahajan, Rahul

2014-01-01

Global Modeling and Assimilation Office (GMAO) is close to having a working 4DVAR system and has developed a linearized version of GEOS-5.This talk outlines a series of improvements made to the linearized dynamics, physics and trajectory.Of particular interest is the development of linearized cloud microphysics, which provides the framework for 'all-sky' data assimilation.

Abiotic/biotic coupling in the rhizosphere: a reactive transport modeling analysis

Science.gov (United States)

Lawrence, Corey R.; Steefel, Carl; Maher, Kate

2014-01-01

A new generation of models is needed to adequately simulate patterns of soil biogeochemical cycling in response changing global environmental drivers. For example, predicting the influence of climate change on soil organic matter storage and stability requires models capable of addressing complex biotic/abiotic interactions of rhizosphere and weathering processes. Reactive transport modeling provides a powerful framework simulating these interactions and the resulting influence on soil physical and chemical characteristics. Incorporation of organic reactions in an existing reactive transport model framework has yielded novel insights into soil weathering and development but much more work is required to adequately capture root and microbial dynamics in the rhizosphere. This endeavor provides many advantages over traditional soil biogeochemical models but also many challenges.

Non-linear calibration models for near infrared spectroscopy

DEFF Research Database (Denmark)

Ni, Wangdong; Nørgaard, Lars; Mørup, Morten

2014-01-01

by ridge regression (RR). The performance of the different methods is demonstrated by their practical applications using three real-life near infrared (NIR) data sets. Different aspects of the various approaches including computational time, model interpretability, potential over-fitting using the non-linear...... models on linear problems, robustness to small or medium sample sets, and robustness to pre-processing, are discussed. The results suggest that GPR and BANN are powerful and promising methods for handling linear as well as nonlinear systems, even when the data sets are moderately small. The LS......-SVM), relevance vector machines (RVM), Gaussian process regression (GPR), artificial neural network (ANN), and Bayesian ANN (BANN). In this comparison, partial least squares (PLS) regression is used as a linear benchmark, while the relationship of the methods is considered in terms of traditional calibration...

[From clinical judgment to linear regression model.

Science.gov (United States)

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

Nucleic acid reactivity: challenges for next-generation semiempirical quantum models.

Science.gov (United States)

Huang, Ming; Giese, Timothy J; York, Darrin M

2015-07-05

Semiempirical quantum models are routinely used to study mechanisms of RNA catalysis and phosphoryl transfer reactions using combined quantum mechanical (QM)/molecular mechanical methods. Herein, we provide a broad assessment of the performance of existing semiempirical quantum models to describe nucleic acid structure and reactivity to quantify their limitations and guide the development of next-generation quantum models with improved accuracy. Neglect of diatomic differential overlap and self-consistent density-functional tight-binding semiempirical models are evaluated against high-level QM benchmark calculations for seven biologically important datasets. The datasets include: proton affinities, polarizabilities, nucleobase dimer interactions, dimethyl phosphate anion, nucleoside sugar and glycosidic torsion conformations, and RNA phosphoryl transfer model reactions. As an additional baseline, comparisons are made with several commonly used density-functional models, including M062X and B3LYP (in some cases with dispersion corrections). The results show that, among the semiempirical models examined, the AM1/d-PhoT model is the most robust at predicting proton affinities. AM1/d-PhoT and DFTB3-3ob/OPhyd reproduce the MP2 potential energy surfaces of 6 associative RNA phosphoryl transfer model reactions reasonably well. Further, a recently developed linear-scaling "modified divide-and-conquer" model exhibits the most accurate results for binding energies of both hydrogen bonded and stacked nucleobase dimers. The semiempirical models considered here are shown to underestimate the isotropic polarizabilities of neutral molecules by approximately 30%. The semiempirical models also fail to adequately describe torsion profiles for the dimethyl phosphate anion, the nucleoside sugar ring puckers, and the rotations about the nucleoside glycosidic bond. The modeling of pentavalent phosphorus, particularly with thio substitutions often used experimentally as mechanistic

Association between Depression and C-Reactive Protein

Directory of Open Access Journals (Sweden)

Yunsheng Ma

2011-01-01

Full Text Available Objective. Depression has been associated with increased cardiovascular disease risk, and a depression-related elevation of high sensitivity C-reactive protein (hs-CRP has been proposed as a possible mechanism. The objective of this paper is to examine association between depression and high sensitivity C-reactive protein (hs-CRP. Methods. Subjects consisted of 508 healthy adults (mean age 48.5 years; 49% women, 88% white residing in central Massachusetts. Data were collected at baseline and at quarterly intervals over a one-year period per individual. Multivariable linear mixed models were used to assess the association for the entire sample and by gender. Results. The mean Beck Depression Inventory score was 5.8 (standard deviation (SD 5.4; median 4.3, and average serum hs-CRP was 1.8 mg/L (SD 1.7; median 1.2. Results from the multivariable linear mixed models show that individuals with higher depression scores have higher levels of hs-CRP. Analyses by gender show persistence of an independent association among women, but not among men. Body mass index (BMI = weight(kg/height(m2 appears to be a partial mediator of this relationship. Conclusion. Depression score was correlated to hs-CRP levels in women. Further studies are required to elucidate the biological mechanisms underlying these associations and their implications.

Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables

Science.gov (United States)

Henson, Robert A.; Templin, Jonathan L.; Willse, John T.

2009-01-01

This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…

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).

Forecasting the EMU inflation rate: Linear econometric vs. non-linear computational models using genetic neural fuzzy systems

DEFF Research Database (Denmark)

Kooths, Stefan; Mitze, Timo Friedel; Ringhut, Eric

2004-01-01

This paper compares the predictive power of linear econometric and non-linear computational models for forecasting the inflation rate in the European Monetary Union (EMU). Various models of both types are developed using different monetary and real activity indicators. They are compared according...

A BEHAVIORAL-APPROACH TO LINEAR EXACT MODELING

NARCIS (Netherlands)

ANTOULAS, AC; WILLEMS, JC

1993-01-01

The behavioral approach to system theory provides a parameter-free framework for the study of the general problem of linear exact modeling and recursive modeling. The main contribution of this paper is the solution of the (continuous-time) polynomial-exponential time series modeling problem. Both

Isothermal CO2 Gasification Reactivity and Kinetic Models of Biomass Char/Anthracite Char

Directory of Open Access Journals (Sweden)

Hai-Bin Zuo

2015-07-01

Full Text Available Gasification of four biomass chars and anthracite char were investigated under a CO2 atmosphere using a thermo-gravimetric analyzer. Reactivity differences of chars were considered in terms of pyrolysis temperature, char types, crystallinity, and inherent minerals. The results show that the gasification reactivity of char decreased with the increase of pyrolysis temperature. Char gasification reactivity followed the order of anthracite coal char (AC-char ˂ pine sawdust char (PS-char ˂ peanut hull char (PH-char ˂ wheat straw char (WS-char ˂ corncob char (CB-char under the same pyrolysis temperature. Two repesentative gas-solid models, the random pore model (RPM and the modified random pore model (MRPM, were applied to describe the reactive behaviour of chars. The results indicate RPM performs well to describe gasification rates of chars but cannot predict the phenomenon that there appears to exist a peak conversion for biomass chars at a high conversion rate, where the MRPM performs better.

Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.

Science.gov (United States)

Nolte, Daniel; Tsang, Chui Kit; Zhang, Kai Yu; Ding, Ziyun; Kedgley, Angela E; Bull, Anthony M J

2016-10-03

Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank - up to 26mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Preisach hysteresis model for non-linear 2D heat diffusion

International Nuclear Information System (INIS)

Jancskar, Ildiko; Ivanyi, Amalia

2006-01-01

This paper analyzes a non-linear heat diffusion process when the thermal diffusivity behaviour is a hysteretic function of the temperature. Modelling this temperature dependence, the discrete Preisach algorithm as general hysteresis model has been integrated into a non-linear multigrid solver. The hysteretic diffusion shows a heating-cooling asymmetry in character. The presented type of hysteresis speeds up the thermal processes in the modelled systems by a very interesting non-linear way

Tip-tilt disturbance model identification based on non-linear least squares fitting for Linear Quadratic Gaussian control

Science.gov (United States)

Yang, Kangjian; Yang, Ping; Wang, Shuai; Dong, Lizhi; Xu, Bing

2018-05-01

We propose a method to identify tip-tilt disturbance model for Linear Quadratic Gaussian control. This identification method based on Levenberg-Marquardt method conducts with a little prior information and no auxiliary system and it is convenient to identify the tip-tilt disturbance model on-line for real-time control. This identification method makes it easy that Linear Quadratic Gaussian control runs efficiently in different adaptive optics systems for vibration mitigation. The validity of the Linear Quadratic Gaussian control associated with this tip-tilt disturbance model identification method is verified by experimental data, which is conducted in replay mode by simulation.

On-line validation of linear process models using generalized likelihood ratios

International Nuclear Information System (INIS)

Tylee, J.L.

1981-12-01

A real-time method for testing the validity of linear models of nonlinear processes is described and evaluated. Using generalized likelihood ratios, the model dynamics are continually monitored to see if the process has moved far enough away from the nominal linear model operating point to justify generation of a new linear model. The method is demonstrated using a seventh-order model of a natural circulation steam generator

Simulation of reactive nanolaminates using reduced models: II. Normal propagation

Energy Technology Data Exchange (ETDEWEB)

Salloum, Maher; Knio, Omar M. [Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD 21218-2686 (United States)

2010-03-15

Transient normal flame propagation in reactive Ni/Al multilayers is analyzed computationally. Two approaches are implemented, based on generalization of earlier methodology developed for axial propagation, and on extension of the model reduction formalism introduced in Part I. In both cases, the formulation accommodates non-uniform layering as well as the presence of inert layers. The equations of motion for the reactive system are integrated using a specially-tailored integration scheme, that combines extended-stability, Runge-Kutta-Chebychev (RKC) integration of diffusion terms with exact treatment of the chemical source term. The detailed and reduced models are first applied to the analysis of self-propagating fronts in uniformly-layered materials. Results indicate that both the front velocities and the ignition threshold are comparable for normal and axial propagation. Attention is then focused on analyzing the effect of a gap composed of inert material on reaction propagation. In particular, the impacts of gap width and thermal conductivity are briefly addressed. Finally, an example is considered illustrating reaction propagation in reactive composites combining regions corresponding to two bilayer widths. This setup is used to analyze the effect of the layering frequency on the velocity of the corresponding reaction fronts. In all cases considered, good agreement is observed between the predictions of the detailed model and the reduced model, which provides further support for adoption of the latter. (author)

A heuristic model for planning problem solution of reactive in electric power systems; Um modelo heuristico para solucao do problema de planejamento de reativos em sistemas de energia eletrica

Energy Technology Data Exchange (ETDEWEB)

Mantovani, Jose Roberto Sanches

1995-02-01

This work introduces a model to solve the planning problem of reactive in electric power systems. The proposed method uses mixed integer linear programming and is solved using implicit enumeration (binary search). The special heuristics to reduce candidates' initial set and to obtain discreet solutions are adopted. They were going accomplished two algorithm implementations, one sequential and other parallel. The implementation parallel uses an asynchronous programming model and is adjusted for distributed memory computer. Defined a bars candidates set for the new reactive sources allocation, the developed program supplies the location and the reactive sources magnitude that must be allocated in the system, considering safety and operation restrictions. The implementation parallel performance is evaluated for three real systems of 309, 725 and 810 bars. The results for the test systems IEEE30 and IEEE118, and the three real systems used in the implementation parallel evaluation are also presented.

A heuristic model for planning problem solution of reactive in electric power systems; Um modelo heuristico para solucao do problema de planejamento de reativos em sistemas de energia eletrica

Energy Technology Data Exchange (ETDEWEB)

Mantovani, Jose Roberto Sanches

1995-02-01

This work introduces a model to solve the planning problem of reactive in electric power systems. The proposed method uses mixed integer linear programming and is solved using implicit enumeration (binary search). The special heuristics to reduce candidates' initial set and to obtain discreet solutions are adopted. They were going accomplished two algorithm implementations, one sequential and other parallel. The implementation parallel uses an asynchronous programming model and is adjusted for distributed memory computer. Defined a bars candidates set for the new reactive sources allocation, the developed program supplies the location and the reactive sources magnitude that must be allocated in the system, considering safety and operation restrictions. The implementation parallel performance is evaluated for three real systems of 309, 725 and 810 bars. The results for the test systems IEEE30 and IEEE118, and the three real systems used in the implementation parallel evaluation are also presented.

Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and non-linear methods.

Science.gov (United States)

Ho, Yuh-Shan

2006-01-01

A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.

Identification of an Equivalent Linear Model for a Non-Linear Time-Variant RC-Structure

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Andersen, P.; Brincker, Rune

are investigated and compared with ARMAX models used on a running window. The techniques are evaluated using simulated data generated by the non-linear finite element program SARCOF modeling a 10-storey 3-bay concrete structure subjected to amplitude modulated Gaussian white noise filtered through a Kanai......This paper considers estimation of the maximum softening for a RC-structure subjected to earthquake excitation. The so-called Maximum Softening damage indicator relates the global damage state of the RC-structure to the relative decrease of the fundamental eigenfrequency in an equivalent linear...

On-line control models for the Stanford Linear Collider

International Nuclear Information System (INIS)

Sheppard, J.C.; Helm, R.H.; Lee, M.J.; Woodley, M.D.

1983-03-01

Models for computer control of the SLAC three-kilometer linear accelerator and damping rings have been developed as part of the control system for the Stanford Linear Collider. Some of these models have been tested experimentally and implemented in the control program for routine linac operations. This paper will describe the development and implementation of these models, as well as some of the operational results

Evidence of fast non-linear feedback in EBR-II rod-drop measurements

International Nuclear Information System (INIS)

Grimm, K.N.; Meneghetti, D.

1987-06-01

Feedback reactivities determine the time dependence of a reactor during and after a transient initiating event. Recent analysis of control-rod drops in the Experimental Breeder Reactor II (EBR-II) Reactor has indicated that some relatively fast feedback may exist which cannot be accounted for by the linear feedback mechanisms. The linear and deduced non-linear feedback reactivities from a control-rod drop in EBR-II run 93A using detailed temperature coefficients of reactivity in the EROS kinetics code have been reported. The transient analyses have now been examined in more detail for times close to the drop to ascertain if additional positive reactivity is being built-in early in the drop which could be gradually released later in the drop

Vortices, semi-local vortices in gauged linear sigma model

International Nuclear Information System (INIS)

Kim, Namkwon

1998-11-01

We consider the static (2+1)D gauged linear sigma model. By analyzing the governing system of partial differential equations, we investigate various aspects of the model. We show the existence of energy finite vortices under a partially broken symmetry on R 2 with the necessary condition suggested by Y. Yang. We also introduce generalized semi-local vortices and show the existence of energy finite semi-local vortices under a certain condition. The vacuum manifold for the semi-local vortices turns out to be graded. Besides, with a special choice of a representation, we show that the O(3) sigma model of which target space is nonlinear is a singular limit of the gauged linear sigma model of which target space is linear. (author)

Modeling and processing of laser Doppler reactive hyperaemia signals

Science.gov (United States)

Humeau, Anne; Saumet, Jean-Louis; L'Huiller, Jean-Pierre

2003-07-01

Laser Doppler flowmetry is a non-invasive method used in the medical domain to monitor the microvascular blood cell perfusion through tissue. Most commercial laser Doppler flowmeters use an algorithm calculating the first moment of the power spectral density to give the perfusion value. Many clinical applications measure the perfusion after a vascular provocation such as a vascular occlusion. The response obtained is then called reactive hyperaemia. Target pathologies include diabetes, hypertension and peripheral arterial occlusive diseases. In order to have a deeper knowledge on reactive hyperaemia acquired by the laser Doppler technique, the present work first proposes two models (one analytical and one numerical) of the observed phenomenon. Then, a study on the multiple scattering between photons and red blood cells occurring during reactive hyperaemia is carried out. Finally, a signal processing that improves the diagnosis of peripheral arterial occlusive diseases is presented.

Treating experimental data of inverse kinetic method by unitary linear regression analysis

International Nuclear Information System (INIS)

Zhao Yusen; Chen Xiaoliang

2009-01-01

The theory of treating experimental data of inverse kinetic method by unitary linear regression analysis was described. Not only the reactivity, but also the effective neutron source intensity could be calculated by this method. Computer code was compiled base on the inverse kinetic method and unitary linear regression analysis. The data of zero power facility BFS-1 in Russia were processed and the results were compared. The results show that the reactivity and the effective neutron source intensity can be obtained correctly by treating experimental data of inverse kinetic method using unitary linear regression analysis and the precision of reactivity measurement is improved. The central element efficiency can be calculated by using the reactivity. The result also shows that the effect to reactivity measurement caused by external neutron source should be considered when the reactor power is low and the intensity of external neutron source is strong. (authors)

Modeling biogechemical reactive transport in a fracture zone

Energy Technology Data Exchange (ETDEWEB)

Molinero, Jorge; Samper, Javier; Yang, Chan Bing, and Zhang, Guoxiang; Guoxiang, Zhang

2005-01-14

A coupled model of groundwater flow, reactive solute transport and microbial processes for a fracture zone of the Aspo site at Sweden is presented. This is the model of the so-called Redox Zone Experiment aimed at evaluating the effects of tunnel construction on the geochemical conditions prevailing in a fracture granite. It is found that a model accounting for microbially-mediated geochemical processes is able to reproduce the unexpected measured increasing trends of dissolved sulfate and bicarbonate. The model is also useful for testing hypotheses regarding the role of microbial processes and evaluating the sensitivity of model results to changes in biochemical parameters.

Modeling biogeochemical reactive transport in a fracture zone

International Nuclear Information System (INIS)

Molinero, Jorge; Samper, Javier; Yang, Chan Bing; Zhang, Guoxiang; Guoxiang, Zhang

2005-01-01

A coupled model of groundwater flow, reactive solute transport and microbial processes for a fracture zone of the Aspo site at Sweden is presented. This is the model of the so-called Redox Zone Experiment aimed at evaluating the effects of tunnel construction on the geochemical conditions prevailing in a fracture granite. It is found that a model accounting for microbially-mediated geochemical processes is able to reproduce the unexpected measured increasing trends of dissolved sulfate and bicarbonate. The model is also useful for testing hypotheses regarding the role of microbial processes and evaluating the sensitivity of model results to changes in biochemical parameters

Model Selection with the Linear Mixed Model for Longitudinal Data

Science.gov (United States)

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

Application of linearized model to the stability analysis of the pressurized water reactor

International Nuclear Information System (INIS)

Li Haipeng; Huang Xiaojin; Zhang Liangju

2008-01-01

A Linear Time-Invariant model of the Pressurized Water Reactor is formulated through the linearization of the nonlinear model. The model simulation results show that the linearized model agrees well with the nonlinear model under small perturbation. Based upon the Lyapunov's First Method, the linearized model is applied to the stability analysis of the Pressurized Water Reactor. The calculation results show that the methodology of linearization to stability analysis is conveniently feasible. (authors)

A Non-linear Stochastic Model for an Office Building with Air Infiltration

DEFF Research Database (Denmark)

Thavlov, Anders; Madsen, Henrik

2015-01-01

This paper presents a non-linear heat dynamic model for a multi-room office building with air infiltration. Several linear and non-linear models, with and without air infiltration, are investigated and compared. The models are formulated using stochastic differential equations and the model...

Stress and sleep reactivity: a prospective investigation of the stress-diathesis model of insomnia.

Science.gov (United States)

Drake, Christopher L; Pillai, Vivek; Roth, Thomas

2014-08-01

To prospectively assess sleep reactivity as a diathesis of insomnia, and to delineate the interaction between this diathesis and naturalistic stress in the development of insomnia among normal sleepers. Longitudinal. Community-based. 2,316 adults from the Evolution of Pathways to Insomnia Cohort (EPIC) with no history of insomnia or depression (46.8 ± 13.2 y; 60% female). None. Participants reported the number of stressful events they encountered at baseline (Time 1), as well as the level of cognitive intrusion they experienced in response to each stressor. Stressful events (OR = 1.13; P stress-induced cognitive intrusion (OR = 1.61; P stressful events on risk for insomnia (P sleep reactivity significantly increased risk for insomnia (OR = 1.78; P sleep reactivity moderated the effects of stress-induced intrusion (P sleep reactivity. Trait sleep reactivity also constituted a significant risk for depression (OR = 1.67; P sleep reactivity is a significant risk factor for incident insomnia, and that it triggers insomnia by exacerbating the effects of stress-induced intrusion. Sleep reactivity is also a precipitant of depression, as mediated by insomnia. These findings support the stress-diathesis model of insomnia, while highlighting sleep reactivity as an important diathesis. Drake CL, Pillai V, Roth T. Stress and sleep reactivity: a prospective investigation of the stress-diathesis model of insomnia.

Stochastic linear programming models, theory, and computation

CERN Document Server

Kall, Peter

2011-01-01

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...

Multivariate covariance generalized linear models

DEFF Research Database (Denmark)

Bonat, W. H.; Jørgensen, Bent

2016-01-01

are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...

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

Genomic prediction based on data from three layer lines using non-linear regression models.

Science.gov (United States)

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional

Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

Science.gov (United States)

Luo, Wen; Azen, Razia

2013-01-01

Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

General mirror pairs for gauged linear sigma models

Energy Technology Data Exchange (ETDEWEB)

Aspinwall, Paul S.; Plesser, M. Ronen [Departments of Mathematics and Physics, Duke University,Box 90320, Durham, NC 27708-0320 (United States)

2015-11-05

We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

General mirror pairs for gauged linear sigma models

International Nuclear Information System (INIS)

Aspinwall, Paul S.; Plesser, M. Ronen

2015-01-01

We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

Half-trek criterion for generic identifiability of linear structural equation models

NARCIS (Netherlands)

Foygel, R.; Draisma, J.; Drton, M.

2012-01-01

A linear structural equation model relates random variables of interest and corresponding Gaussian noise terms via a linear equation system. Each such model can be represented by a mixed graph in which directed edges encode the linear equations, and bidirected edges indicate possible correlations

Half-trek criterion for generic identifiability of linear structural equation models

NARCIS (Netherlands)

Foygel, R.; Draisma, J.; Drton, M.

2011-01-01

A linear structural equation model relates random variables of interest and corresponding Gaussian noise terms via a linear equation system. Each such model can be represented by a mixed graph in which directed edges encode the linear equations, and bidirected edges indicate possible correlations

Reactive transport modeling in variably saturated porous media with OGS-IPhreeqc

Science.gov (United States)

He, W.; Beyer, C.; Fleckenstein, J. H.; Jang, E.; Kalbacher, T.; Shao, H.; Wang, W.; Kolditz, O.

2014-12-01

Worldwide, sustainable water resource management becomes an increasingly challenging task due to the growth of population and extensive applications of fertilizer in agriculture. Moreover, climate change causes further stresses to both water quantity and quality. Reactive transport modeling in the coupled soil-aquifer system is a viable approach to assess the impacts of different land use and groundwater exploitation scenarios on the water resources. However, the application of this approach is usually limited in spatial scale and to simplified geochemical systems due to the huge computational expense involved. Such computational expense is not only caused by solving the high non-linearity of the initial boundary value problems of water flow in the unsaturated zone numerically with rather fine spatial and temporal discretization for the correct mass balance and numerical stability, but also by the intensive computational task of quantifying geochemical reactions. In the present study, a flexible and efficient tool for large scale reactive transport modeling in variably saturated porous media and its applications are presented. The open source scientific software OpenGeoSys (OGS) is coupled with the IPhreeqc module of the geochemical solver PHREEQC. The new coupling approach makes full use of advantages from both codes: OGS provides a flexible choice of different numerical approaches for simulation of water flow in the vadose zone such as the pressure-based or mixed forms of Richards equation; whereas the IPhreeqc module leads to a simplification of data storage and its communication with OGS, which greatly facilitates the coupling and code updating. Moreover, a parallelization scheme with MPI (Message Passing Interface) is applied, in which the computational task of water flow and mass transport is partitioned through domain decomposition, whereas the efficient parallelization of geochemical reactions is achieved by smart allocation of computational workload over

Generalized Linear Models with Applications in Engineering and the Sciences

CERN Document Server

Myers, Raymond H; Vining, G Geoffrey; Robinson, Timothy J

2012-01-01

Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities."-Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Ma

Detailed characterization of a Comparative Reactivity Method (CRM) instrument for ambient OH reactivity measurements: experiments vs. modeling

Science.gov (United States)

Michoud, Vincent; Locoge, Nadine; Dusanter, Sébastien

2015-04-01

The Hydroxyl radical (OH) is the main daytime oxidant in the troposphere, leading to the oxidation of Volatile Organic Compounds (VOCs) and the formation of harmful pollutants such as ozone (O3) and Secondary Organic Aerosols (SOA). While OH plays a key role in tropospheric chemistry, recent studies have highlighted that there are still uncertainties associated with the OH budget, i.e the identification of sources and sinks and the quantification of production and loss rates of this radical. It has been demonstrated that ambient measurements of the total OH loss rate (also called total OH reactivity) can be used to identify and reduce these uncertainties. In this context, the Comparative Reactivity Method (CRM), developed by Sinha et al. (ACP, 2008), is a promising technique to measure total OH reactivity in ambient air and has already been used during several field campaigns. This technique relies on monitoring competitive reactions of OH with ambient trace gases and a reference compound (pyrrole) in a sampling reactor to derive ambient OH reactivity. However, this technique requires a complex data processing chain that has yet to be carefully investigated in the laboratory. In this study, we present a detailed characterization of a CRM instrument developed at Mines Douai, France. Experiments have been performed to investigate the dependence of the CRM response on humidity, ambient NOx levels, and the pyrrole-to-OH ratio inside the sampling reactor. Box modelling of the chemistry occurring in the reactor has also been performed to assess our theoretical understanding of the CRM measurement. This work shows that the CRM response is sensitive to both humidity and NOx, which can be accounted for during data processing using parameterizations depending on the pyrrole-to-OH ratio. The agreement observed between laboratory studies and model results suggests a good understanding of the chemistry occurring in the sampling reactor and gives confidence in the CRM

Development of a model for the synthesis of unsaturated polyester by reactive distillation

NARCIS (Netherlands)

Shah, M.R.; Zondervan, E.; Oudshoorn, M.L.; Haan, de A.B.; Haan, de A.B.; Kooijman, H.; Górak, A.

2010-01-01

Traditionally polyester production is done in a batch reactor equipped with a separation column for batch distillation. A promising alternative for the intensification of this process is reactive distillation. In this paper, a reactive distillation model is developed for the synthesis of an

A mobile-mobile transport model for simulating reactive transport in connected heterogeneous fields

Science.gov (United States)

Lu, Chunhui; Wang, Zhiyuan; Zhao, Yue; Rathore, Saubhagya Singh; Huo, Jinge; Tang, Yuening; Liu, Ming; Gong, Rulan; Cirpka, Olaf A.; Luo, Jian

2018-05-01

Mobile-immobile transport models can be effective in reproducing heavily tailed breakthrough curves of concentration. However, such models may not adequately describe transport along multiple flow paths with intermediate velocity contrasts in connected fields. We propose using the mobile-mobile model for simulating subsurface flow and associated mixing-controlled reactive transport in connected fields. This model includes two local concentrations, one in the fast- and the other in the slow-flow domain, which predict both the concentration mean and variance. The normalized total concentration variance within the flux is found to be a non-monotonic function of the discharge ratio with a maximum concentration variance at intermediate values of the discharge ratio. We test the mobile-mobile model for mixing-controlled reactive transport with an instantaneous, irreversible bimolecular reaction in structured and connected random heterogeneous domains, and compare the performance of the mobile-mobile to the mobile-immobile model. The results indicate that the mobile-mobile model generally predicts the concentration breakthrough curves (BTCs) of the reactive compound better. Particularly, for cases of an elliptical inclusion with intermediate hydraulic-conductivity contrasts, where the travel-time distribution shows bimodal behavior, the prediction of both the BTCs and maximum product concentration is significantly improved. Our results exemplify that the conceptual model of two mobile domains with diffusive mass transfer in between is in general good for predicting mixing-controlled reactive transport, and particularly so in cases where the transfer in the low-conductivity zones is by slow advection rather than diffusion.

A penalized framework for distributed lag non-linear models.

Science.gov (United States)

Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G

2017-09-01

Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling.

Science.gov (United States)

Kawashima, Issaku; Kumano, Hiroaki

2017-01-01

Mind-wandering (MW), task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG) variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR) to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.

Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling

Directory of Open Access Journals (Sweden)

Issaku Kawashima

2017-07-01

Full Text Available Mind-wandering (MW, task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.

Game Theory and its Relationship with Linear Programming Models ...

African Journals Online (AJOL)

Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

Science.gov (United States)

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19

Double generalized linear compound poisson models to insurance claims data

DEFF Research Database (Denmark)

Andersen, Daniel Arnfeldt; Bonat, Wagner Hugo

2017-01-01

This paper describes the specification, estimation and comparison of double generalized linear compound Poisson models based on the likelihood paradigm. The models are motivated by insurance applications, where the distribution of the response variable is composed by a degenerate distribution...... implementation and illustrate the application of double generalized linear compound Poisson models using a data set about car insurances....

Modeling food matrix effects on chemical reactivity: Challenges and perspectives.

Science.gov (United States)

Capuano, Edoardo; Oliviero, Teresa; van Boekel, Martinus A J S

2017-06-29

The same chemical reaction may be different in terms of its position of the equilibrium (i.e., thermodynamics) and its kinetics when studied in different foods. The diversity in the chemical composition of food and in its structural organization at macro-, meso-, and microscopic levels, that is, the food matrix, is responsible for this difference. In this viewpoint paper, the multiple, and interconnected ways the food matrix can affect chemical reactivity are summarized. Moreover, mechanistic and empirical approaches to explain and predict the effect of food matrix on chemical reactivity are described. Mechanistic models aim to quantify the effect of food matrix based on a detailed understanding of the chemical and physical phenomena occurring in food. Their applicability is limited at the moment to very simple food systems. Empirical modeling based on machine learning combined with data-mining techniques may represent an alternative, useful option to predict the effect of the food matrix on chemical reactivity and to identify chemical and physical properties to be further tested. In such a way the mechanistic understanding of the effect of the food matrix on chemical reactions can be improved.

Rigorous Multicomponent Reactive Separations Modelling: Complete Consideration of Reaction-Diffusion Phenomena

International Nuclear Information System (INIS)

Ahmadi, A.; Meyer, M.; Rouzineau, D.; Prevost, M.; Alix, P.; Laloue, N.

2010-01-01

This paper gives the first step of the development of a rigorous multicomponent reactive separation model. Such a model is highly essential to further the optimization of acid gases removal plants (CO 2 capture, gas treating, etc.) in terms of size and energy consumption, since chemical solvents are conventionally used. Firstly, two main modelling approaches are presented: the equilibrium-based and the rate-based approaches. Secondly, an extended rate-based model with rigorous modelling methodology for diffusion-reaction phenomena is proposed. The film theory and the generalized Maxwell-Stefan equations are used in order to characterize multicomponent interactions. The complete chain of chemical reactions is taken into account. The reactions can be kinetically controlled or at chemical equilibrium, and they are considered for both liquid film and liquid bulk. Thirdly, the method of numerical resolution is described. Coupling the generalized Maxwell-Stefan equations with chemical equilibrium equations leads to a highly non-linear Differential-Algebraic Equations system known as DAE index 3. The set of equations is discretized with finite-differences as its integration by Gear method is complex. The resulting algebraic system is resolved by the Newton- Raphson method. Finally, the present model and the associated methods of numerical resolution are validated for the example of esterification of methanol. This archetype non-electrolytic system permits an interesting analysis of reaction impact on mass transfer, especially near the phase interface. The numerical resolution of the model by Newton-Raphson method gives good results in terms of calculation time and convergence. The simulations show that the impact of reactions at chemical equilibrium and that of kinetically controlled reactions with high kinetics on mass transfer is relatively similar. Moreover, the Fick's law is less adapted for multicomponent mixtures where some abnormalities such as counter

Reliability modelling and simulation of switched linear system ...

African Journals Online (AJOL)

Reliability modelling and simulation of switched linear system control using temporal databases. ... design of fault-tolerant real-time switching systems control and modelling embedded micro-schedulers for complex systems maintenance.

SeSBench - An initiative to benchmark reactive transport models for environmental subsurface processes

Science.gov (United States)

Jacques, Diederik

2017-04-01

As soil functions are governed by a multitude of interacting hydrological, geochemical and biological processes, simulation tools coupling mathematical models for interacting processes are needed. Coupled reactive transport models are a typical example of such coupled tools mainly focusing on hydrological and geochemical coupling (see e.g. Steefel et al., 2015). Mathematical and numerical complexity for both the tool itself or of the specific conceptual model can increase rapidly. Therefore, numerical verification of such type of models is a prerequisite for guaranteeing reliability and confidence and qualifying simulation tools and approaches for any further model application. In 2011, a first SeSBench -Subsurface Environmental Simulation Benchmarking- workshop was held in Berkeley (USA) followed by four other ones. The objective is to benchmark subsurface environmental simulation models and methods with a current focus on reactive transport processes. The final outcome was a special issue in Computational Geosciences (2015, issue 3 - Reactive transport benchmarks for subsurface environmental simulation) with a collection of 11 benchmarks. Benchmarks, proposed by the participants of the workshops, should be relevant for environmental or geo-engineering applications; the latter were mostly related to radioactive waste disposal issues - excluding benchmarks defined for pure mathematical reasons. Another important feature is the tiered approach within a benchmark with the definition of a single principle problem and different sub problems. The latter typically benchmarked individual or simplified processes (e.g. inert solute transport, simplified geochemical conceptual model) or geometries (e.g. batch or one-dimensional, homogeneous). Finally, three codes should be involved into a benchmark. The SeSBench initiative contributes to confidence building for applying reactive transport codes. Furthermore, it illustrates the use of those type of models for different

Mixed models, linear dependency, and identification in age-period-cohort models.

Science.gov (United States)

O'Brien, Robert M

2017-07-20

This paper examines the identification problem in age-period-cohort models that use either linear or categorically coded ages, periods, and cohorts or combinations of these parameterizations. These models are not identified using the traditional fixed effect regression model approach because of a linear dependency between the ages, periods, and cohorts. However, these models can be identified if the researcher introduces a single just identifying constraint on the model coefficients. The problem with such constraints is that the results can differ substantially depending on the constraint chosen. Somewhat surprisingly, age-period-cohort models that specify one or more of ages and/or periods and/or cohorts as random effects are identified. This is the case without introducing an additional constraint. I label this identification as statistical model identification and show how statistical model identification comes about in mixed models and why which effects are treated as fixed and which are treated as random can substantially change the estimates of the age, period, and cohort effects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A fuzzy Bi-linear management model in reverse logistic chains

Directory of Open Access Journals (Sweden)

Tadić Danijela

2016-01-01

Full Text Available The management of the electrical and electronic waste (WEEE problem in the uncertain environment has a critical effect on the economy and environmental protection of each region. The considered problem can be stated as a fuzzy non-convex optimization problem with linear objective function and a set of linear and non-linear constraints. The original problem is reformulated by using linear relaxation into a fuzzy linear programming problem. The fuzzy rating of collecting point capacities and fix costs of recycling centers are modeled by triangular fuzzy numbers. The optimal solution of the reformulation model is found by using optimality concept. The proposed model is verified through an illustrative example with real-life data. The obtained results represent an input for future research which should include a good benchmark base for tested reverse logistic chains and their continuous improvement. [Projekat Ministarstva nauke Republike Srbije, br. 035033: Sustainable development technology and equipment for the recycling of motor vehicles

Identification of Influential Points in a Linear Regression Model

Directory of Open Access Journals (Sweden)

Jan Grosz

2011-03-01

Full Text Available The article deals with the detection and identification of influential points in the linear regression model. Three methods of detection of outliers and leverage points are described. These procedures can also be used for one-sample (independentdatasets. This paper briefly describes theoretical aspects of several robust methods as well. Robust statistics is a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. A simulation model of the simple linear regression is presented.

Reactivation of latent herpes simplex virus infection by ultraviolet light: a human model

International Nuclear Information System (INIS)

Perna, J.J.; Mannix, M.L.; Rooney, J.F.; Notkins, A.L.; Straus, S.E.

1987-01-01

Infection with herpes simplex virus often results in a latent infection of local sensory ganglia and a disease characterized by periodic viral reactivation and mucocutaneous lesions. The factors that trigger reactivation in humans are still poorly defined. In our study, five patients with documented histories of recurrent herpes simplex virus infection on the buttocks or sacrum were exposed to three times their minimal erythema dose of ultraviolet light. Site-specific cutaneous herpes simplex virus infection occurred at 4.4 +/- 0.4 days after exposure to ultraviolet light in 8 of 13 attempts at reactivation. We conclude that ultraviolet light can reactivate herpes simplex virus under experimentally defined conditions. This model in humans should prove useful in evaluating the pathophysiology and prevention of viral reactivation

Linear regression crash prediction models : issues and proposed solutions.

Science.gov (United States)

2010-05-01

The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...

Matrix model and time-like linear dila ton matter

International Nuclear Information System (INIS)

Takayanagi, Tadashi

2004-01-01

We consider a matrix model description of the 2d string theory whose matter part is given by a time-like linear dilaton CFT. This is equivalent to the c=1 matrix model with a deformed, but very simple Fermi surface. Indeed, after a Lorentz transformation, the corresponding 2d spacetime is a conventional linear dila ton background with a time-dependent tachyon field. We show that the tree level scattering amplitudes in the matrix model perfectly agree with those computed in the world-sheet theory. The classical trajectories of fermions correspond to the decaying D-boranes in the time-like linear dilaton CFT. We also discuss the ground ring structure. Furthermore, we study the properties of the time-like Liouville theory by applying this matrix model description. We find that its ground ring structure is very similar to that of the minimal string. (author)

Nucleic acid reactivity : challenges for next-generation semiempirical quantum models

OpenAIRE

Huang, Ming; Giese, Timothy J.; York, Darrin M.

2015-01-01

Semiempirical quantum models are routinely used to study mechanisms of RNA catalysis and phosphoryl transfer reactions using combined quantum mechanical/molecular mechanical methods. Herein, we provide a broad assessment of the performance of existing semiempirical quantum models to describe nucleic acid structure and reactivity in order to quantify their limitations and guide the development of next-generation quantum models with improved accuracy. Neglect of diatomic diffierential overlap (...

Linear Power-Flow Models in Multiphase Distribution Networks: Preprint

Energy Technology Data Exchange (ETDEWEB)

Bernstein, Andrey; Dall' Anese, Emiliano

2017-05-26

This paper considers multiphase unbalanced distribution systems and develops approximate power-flow models where bus-voltages, line-currents, and powers at the point of common coupling are linearly related to the nodal net power injections. The linearization approach is grounded on a fixed-point interpretation of the AC power-flow equations, and it is applicable to distribution systems featuring (i) wye connections; (ii) ungrounded delta connections; (iii) a combination of wye-connected and delta-connected sources/loads; and, (iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. The proposed linear models can facilitate the development of computationally-affordable optimization and control applications -- from advanced distribution management systems settings to online and distributed optimization routines. Performance of the proposed models is evaluated on different test feeders.

Coupled Modeling of Rhizosphere and Reactive Transport Processes

Science.gov (United States)

Roque-Malo, S.; Kumar, P.

2017-12-01

The rhizosphere, as a bio-diverse plant root-soil interface, hosts many hydrologic and biochemical processes, including nutrient cycling, hydraulic redistribution, and soil carbon dynamics among others. The biogeochemical function of root networks, including the facilitation of nutrient cycling through absorption and rhizodeposition, interaction with micro-organisms and fungi, contribution to biomass, etc., plays an important role in myriad Critical Zone processes. Despite this knowledge, the role of the rhizosphere on watershed-scale ecohydrologic functions in the Critical Zone has not been fully characterized, and specifically, the extensive capabilities of reactive transport models (RTMs) have not been applied to these hydrobiogeochemical dynamics. This study uniquely links rhizospheric processes with reactive transport modeling to couple soil biogeochemistry, biological processes, hydrologic flow, hydraulic redistribution, and vegetation dynamics. Key factors in the novel modeling approach are: (i) bi-directional effects of root-soil interaction, such as simultaneous root exudation and nutrient absorption; (ii) multi-state biomass fractions in soil (i.e. living, dormant, and dead biological and root materials); (iii) expression of three-dimensional fluxes to represent both vertical and lateral interconnected flows and processes; and (iv) the potential to include the influence of non-stationary external forcing and climatic factors. We anticipate that the resulting model will demonstrate the extensive effects of plant root dynamics on ecohydrologic functions at the watershed scale and will ultimately contribute to a better characterization of efflux from both agricultural and natural systems.

Linear mixed models a practical guide using statistical software

CERN Document Server

West, Brady T; Galecki, Andrzej T

2006-01-01

Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

KAUST Repository

Kabanov, Dmitry I.

2017-12-08

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

KAUST Repository

Kabanov, Dmitry; Kasimov, Aslan R.

2018-01-01

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

KAUST Repository

Kabanov, Dmitry

2018-03-20

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of

Inverse modeling of multicomponent reactive transport through single and dual porosity media

Science.gov (United States)

Samper, Javier; Zheng, Liange; Fernández, Ana María; Montenegro, Luis

2008-06-01

Compacted bentonite is foreseen as buffer material for high-level radioactive waste in deep geological repositories because it provides hydraulic isolation, chemical stability, and radionuclide sorption. A wide range of laboratory tests were performed within the framework of FEBEX ( Full-scale Engineered Barrier EXperiment) project to characterize buffer properties and develop numerical models for FEBEX bentonite. Here we present inverse single and dual-continuum multicomponent reactive transport models of a long-term permeation test performed on a 2.5 cm long sample of FEBEX bentonite. Initial saline bentonite porewater was flushed with 5.5 pore volumes of fresh granitic water. Water flux and chemical composition of effluent waters were monitored during almost 4 years. The model accounts for solute advection and diffusion and geochemical reactions such as aqueous complexation, acid-base, cation exchange, protonation/deprotonation by surface complexation and dissolution/precipitation of calcite, chalcedony and gypsum. All of these processes are assumed at local equilibrium. Similar to previous studies of bentonite porewater chemistry on batch systems which attest the relevance of protonation/deprotonation on buffering pH, our results confirm that protonation/deprotonation is a key process in maintaining a stable pH under dynamic transport conditions. Breakthrough curves of reactive species are more sensitive to initial porewater concentration than to effective diffusion coefficient. Optimum estimates of initial porewater chemistry of saturated compacted FEBEX bentonite are obtained by solving the inverse problem of multicomponent reactive transport. While the single-continuum model reproduces the trends of measured data for most chemical species, it fails to match properly the long tails of most breakthrough curves. Such limitation is overcome by resorting to a dual-continuum reactive transport model.

Expanding the role of reactive transport models in critical zone processes

Science.gov (United States)

Li, Li; Maher, Kate; Navarre-Sitchler, Alexis; Druhan, Jennifer; Meile, Christof; Lawrence, Corey; Moore, Joel; Perdrial, Julia; Sullivan, Pamela; Thompson, Aaron; Jin, Lixin; Bolton, Edward W.; Brantley, Susan L.; Dietrich, William E.; Mayer, K. Ulrich; Steefel, Carl; Valocchi, Albert J.; Zachara, John M.; Kocar, Benjamin D.; McIntosh, Jennifer; Tutolo, Benjamin M.; Kumar, Mukesh; Sonnenthal, Eric; Bao, Chen; Beisman, Joe

2017-01-01

Models test our understanding of processes and can reach beyond the spatial and temporal scales of measurements. Multi-component Reactive Transport Models (RTMs), initially developed more than three decades ago, have been used extensively to explore the interactions of geothermal, hydrologic, geochemical, and geobiological processes in subsurface systems. Driven by extensive data sets now available from intensive measurement efforts, there is a pressing need to couple RTMs with other community models to explore non-linear interactions among the atmosphere, hydrosphere, biosphere, and geosphere. Here we briefly review the history of RTM development, summarize the current state of RTM approaches, and identify new research directions, opportunities, and infrastructure needs to broaden the use of RTMs. In particular, we envision the expanded use of RTMs in advancing process understanding in the Critical Zone, the veneer of the Earth that extends from the top of vegetation to the bottom of groundwater. We argue that, although parsimonious models are essential at larger scales, process-based models offer tools to explore the highly nonlinear coupling that characterizes natural systems. We present seven testable hypotheses that emphasize the unique capabilities of process-based RTMs for (1) elucidating chemical weathering and its physical and biogeochemical drivers; (2) understanding the interactions among roots, micro-organisms, carbon, water, and minerals in the rhizosphere; (3) assessing the effects of heterogeneity across spatial and temporal scales; and (4) integrating the vast quantity of novel data, including “omics” data (genomics, transcriptomics, proteomics, metabolomics), elemental concentration and speciation data, and isotope data into our understanding of complex earth surface systems. With strong support from data-driven sciences, we are now in an exciting era where integration of RTM framework into other community models will facilitate process

Oxidation of trichloroethylene, toluene, and ethanol vapors by a partially saturated permeable reactive barrier

Science.gov (United States)

Mahmoodlu, Mojtaba G.; Hassanizadeh, S. Majid; Hartog, Niels; Raoof, Amir

2014-08-01

The mitigation of volatile organic compound (VOC) vapors in the unsaturated zone largely relies on the active removal of vapor by ventilation. In this study we considered an alternative method involving the use of solid potassium permanganate to create a horizontal permeable reactive barrier for oxidizing VOC vapors. Column experiments were carried out to investigate the oxidation of trichloroethylene (TCE), toluene, and ethanol vapors using a partially saturated mixture of potassium permanganate and sand grains. Results showed a significant removal of VOC vapors due to the oxidation. We found that water saturation has a major effect on the removal capacity of the permeable reactive layer. We observed a high removal efficiency and reactivity of potassium permanganate for all target compounds at the highest water saturation (Sw = 0.6). A change in pH within the reactive layer reduced oxidation rate of VOCs. The use of carbonate minerals increased the reactivity of potassium permanganate during the oxidation of TCE vapor by buffering the pH. Reactive transport of VOC vapors diffusing through the permeable reactive layer was modeled, including the pH effect on the oxidation rates. The model accurately described the observed breakthrough curve of TCE and toluene vapors in the headspace of the column. However, miscibility of ethanol in water in combination with produced water during oxidation made the modeling results less accurate for ethanol. A linear relationship was found between total oxidized mass of VOC vapors per unit volume of permeable reactive layer and initial water saturation. This behavior indicates that pH changes control the overall reactivity and longevity of the permeable reactive layer during oxidation of VOCs. The results suggest that field application of a horizontal permeable reactive barrier can be a viable technology against upward migration of VOC vapors through the unsaturated zone.

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Renormalization a la BRS of the non-linear σ-model

International Nuclear Information System (INIS)

Blasi, A.; Collina, R.

1987-01-01

We characterize the non-linear O(N+1) σ-model in an arbitrary parametrization with a nihilpotent BRS operator obtained from the symmetry transformation by the use of anticommuting parameters. The identity can be made compatible with the presence of a mass term in the model, so we can analyze its stability and prove that the model is anomaly free. This procedure avoids many problems encountered in the conventional analysis; in particular the introduction of an infinite number of sources coupled to the successive variations of the field is not necessary and the linear O(N) symmetry is respected as a consequence of the identity. The approach may provide useful in discussing the renormalizability of a wider class of models with non-linear symmetries. (orig.)

Robust Comparison of the Linear Model Structures in Self-tuning Adaptive Control

DEFF Research Database (Denmark)

Zhou, Jianjun; Conrad, Finn

1989-01-01

The Generalized Predictive Controller (GPC) is extended to the systems with a generalized linear model structure which contains a number of choices of linear model structures. The Recursive Prediction Error Method (RPEM) is used to estimate the unknown parameters of the linear model structures...... to constitute a GPC self-tuner. Different linear model structures commonly used are compared and evaluated by applying them to the extended GPC self-tuner as well as to the special cases of the GPC, the GMV and MV self-tuners. The simulation results show how the choice of model structure affects the input......-output behaviour of self-tuning controllers....

Analytical solution of point kinetics equations for linear reactivity variation during the start-up of a nuclear reactor

International Nuclear Information System (INIS)

Palma, Daniel A.P.; Martinez, Aquilino S.; Goncalves, Alessandro C.

2009-01-01

The analytical solution of point kinetics equations with a group of delayed neutrons is useful in predicting the variation of neutron density during the start-up of a nuclear reactor. In the practical case of an increase of nuclear reactor power resulting from the linear insertion of reactivity, the exact analytical solution cannot be obtained. Approximate solutions have been obtained in previous articles, based on considerations that need to be verifiable in practice. In the present article, an alternative analytic solution is presented for point kinetics equations in which the only approximation consists of disregarding the term of the second derivative for neutron density in relation to time. The results proved satisfactory when applied to practical situations in the start-up of a nuclear reactor through the control rods withdraw.

Analytical solution of point kinetics equations for linear reactivity variation during the start-up of a nuclear reactor

Energy Technology Data Exchange (ETDEWEB)

Palma, Daniel A.P. [CEFET QUIMICA de Nilopolis/RJ, 21941-914 Rio de Janeiro (Brazil)], E-mail: agoncalves@con.ufrj.br; Martinez, Aquilino S.; Goncalves, Alessandro C. [COPPE/UFRJ - Programa de Engenharia Nuclear, Rio de Janeiro (Brazil)

2009-09-15

The analytical solution of point kinetics equations with a group of delayed neutrons is useful in predicting the variation of neutron density during the start-up of a nuclear reactor. In the practical case of an increase of nuclear reactor power resulting from the linear insertion of reactivity, the exact analytical solution cannot be obtained. Approximate solutions have been obtained in previous articles, based on considerations that need to be verifiable in practice. In the present article, an alternative analytic solution is presented for point kinetics equations in which the only approximation consists of disregarding the term of the second derivative for neutron density in relation to time. The results proved satisfactory when applied to practical situations in the start-up of a nuclear reactor through the control rods withdraw.

Multicollinearity in hierarchical linear models.

Science.gov (United States)

Yu, Han; Jiang, Shanhe; Land, Kenneth C

2015-09-01

This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this

Low-energy limit of the extended Linear Sigma Model

Energy Technology Data Exchange (ETDEWEB)

Divotgey, Florian [Johann Wolfgang Goethe-Universitaet, Institut fuer Theoretische Physik, Frankfurt am Main (Germany); Kovacs, Peter [Wigner Research Center for Physics, Hungarian Academy of Sciences, Institute for Particle and Nuclear Physics, Budapest (Hungary); GSI Helmholtzzentrum fuer Schwerionenforschung, ExtreMe Matter Institute, Darmstadt (Germany); Giacosa, Francesco [Johann Wolfgang Goethe-Universitaet, Institut fuer Theoretische Physik, Frankfurt am Main (Germany); Jan-Kochanowski University, Institute of Physics, Kielce (Poland); Rischke, Dirk H. [Johann Wolfgang Goethe-Universitaet, Institut fuer Theoretische Physik, Frankfurt am Main (Germany); University of Science and Technology of China, Interdisciplinary Center for Theoretical Study and Department of Modern Physics, Hefei, Anhui (China)

2018-01-15

The extended Linear Sigma Model is an effective hadronic model based on the linear realization of chiral symmetry SU(N{sub f}){sub L} x SU(N{sub f}){sub R}, with (pseudo)scalar and (axial-)vector mesons as degrees of freedom. In this paper, we study the low-energy limit of the extended Linear Sigma Model (eLSM) for N{sub f} = flavors by integrating out all fields except for the pions, the (pseudo-)Nambu-Goldstone bosons of chiral symmetry breaking. The resulting low-energy effective action is identical to Chiral Perturbation Theory (ChPT) after choosing a representative for the coset space generated by chiral symmetry breaking and expanding it in powers of (derivatives of) the pion fields. The tree-level values of the coupling constants of the effective low-energy action agree remarkably well with those of ChPT. (orig.)

A national-scale model of linear features improves predictions of farmland biodiversity.

Science.gov (United States)

Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

2017-12-01

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

Modeling containment of large wildfires using generalized linear mixed-model analysis

Science.gov (United States)

Mark Finney; Isaac C. Grenfell; Charles W. McHugh

2009-01-01

Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

Model comparisons of the reactive burn model SURF in three ASC codes

Energy Technology Data Exchange (ETDEWEB)

Whitley, Von Howard [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Stalsberg, Krista Lynn [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reichelt, Benjamin Lee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Shipley, Sarah Jayne [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2018-01-12

A study of the SURF reactive burn model was performed in FLAG, PAGOSA and XRAGE. In this study, three different shock-to-detonation transition experiments were modeled in each code. All three codes produced similar model results for all the experiments modeled and at all resolutions. Buildup-to-detonation time, particle velocities and resolution dependence of the models was notably similar between the codes. Given the current PBX 9502 equations of state and SURF calibrations, each code is equally capable of predicting the correct detonation time and distance when impacted by a 1D impactor at pressures ranging from 10-16 GPa, as long as the resolution of the mesh is not too coarse.

Mechanistic modeling of reactive soil nitrogen emissions across agricultural management practices

Science.gov (United States)

Rasool, Q. Z.; Miller, D. J.; Bash, J. O.; Venterea, R. T.; Cooter, E. J.; Hastings, M. G.; Cohan, D. S.

2017-12-01

The global reactive nitrogen (N) budget has increased by a factor of 2-3 from pre-industrial levels. This increase is especially pronounced in highly N fertilized agricultural regions in summer. The reactive N emissions from soil to atmosphere can be in reduced (NH3) or oxidized (NO, HONO, N2O) forms, depending on complex biogeochemical transformations of soil N reservoirs. Air quality models like CMAQ typically neglect soil emissions of HONO and N2O. Previously, soil NO emissions estimated by models like CMAQ remained parametric and inconsistent with soil NH3 emissions. Thus, there is a need to more mechanistically and consistently represent the soil N processes that lead to reactive N emissions to the atmosphere. Our updated approach estimates soil NO, HONO and N2O emissions by incorporating detailed agricultural fertilizer inputs from EPIC, and CMAQ-modeled N deposition, into the soil N pool. EPIC addresses the nitrification, denitrification and volatilization rates along with soil N pools for agricultural soils. Suitable updates to account for factors like nitrite (NO2-) accumulation not addressed in EPIC, will also be made. The NO and N2O emissions from nitrification and denitrification are computed mechanistically using the N sub-model of DAYCENT. These mechanistic definitions use soil water content, temperature, NH4+ and NO3- concentrations, gas diffusivity and labile C availability as dependent parameters at various soil layers. Soil HONO emissions found to be most probable under high NO2- availability will be based on observed ratios of HONO to NO emissions under different soil moistures, pH and soil types. The updated scheme will utilize field-specific soil properties and N inputs across differing manure management practices such as tillage. Comparison of the modeled soil NO emission rates from the new mechanistic and existing schemes against field measurements will be discussed. Our updated framework will help to predict the diurnal and daily variability

A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

Nonlinear Modeling by Assembling Piecewise Linear Models

Science.gov (United States)

Yao, Weigang; Liou, Meng-Sing

2013-01-01

To preserve nonlinearity of a full order system over a parameters range of interest, we propose a simple modeling approach by assembling a set of piecewise local solutions, including the first-order Taylor series terms expanded about some sampling states. The work by Rewienski and White inspired our use of piecewise linear local solutions. The assembly of these local approximations is accomplished by assigning nonlinear weights, through radial basis functions in this study. The efficacy of the proposed procedure is validated for a two-dimensional airfoil moving at different Mach numbers and pitching motions, under which the flow exhibits prominent nonlinear behaviors. All results confirm that our nonlinear model is accurate and stable for predicting not only aerodynamic forces but also detailed flowfields. Moreover, the model is robustness-accurate for inputs considerably different from the base trajectory in form and magnitude. This modeling preserves nonlinearity of the problems considered in a rather simple and accurate manner.

Low cost removal of reactive dyes using wheat bran

International Nuclear Information System (INIS)

Cicek, Fatma; Ozer, Dursun; Ozer, Ahmet; Ozer, Ayla

2007-01-01

In this study, the adsorption of Reactive Blue 19 (RB 19), Reactive Red 195 (RR 195) and Reactive Yellow 145 (RY 145) onto wheat bran, generated as a by-product material from flour factory, was studied with respect to initial pH, temperature, initial dye concentration, adsorbent concentration and adsorbent size. The adsorption of RB 19, RR 195 and RY 145 onto wheat bran increased with increasing temperature and initial dye concentration while the adsorbed RB 19, RR 195 and RY 145 amounts decreased with increasing initial pH and adsorbent concentration. The Langmuir and Freundlich isotherm models were applied to the experimental equilibrium data depending on temperature and the isotherm constants were determined by using linear regression analysis. The monolayer covarage capacities of wheat bran for RB 19, RR 195 and RY 145 dyes were obtained as 117.6, 119.1 and 196.1 mg/g at 60 deg. C, respectively. It was observed that the reactive dye adsorption capacity of wheat bran decreased in the order of RY 145 > RB 19 > RR 195. The pseudo-second order kinetic and Weber-Morris models were applied to the experimental data and it was found that both the surface adsorption as well as intraparticle diffusion contributed to the actual adsorption processes of RB 19, RR 195 and RY 145. Regression coefficients (R 2 ) for the pseudo-second order kinetic model were higher than 0.99. Thermodynamic studies showed that the adsorption of RB 19, RR 195 and RY 145 dyes onto wheat bran was endothermic in nature

Portfolio optimization by using linear programing models based on genetic algorithm

Science.gov (United States)

Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

Plane answers to complex questions the theory of linear models

CERN Document Server

Christensen, Ronald

1987-01-01

This book was written to rigorously illustrate the practical application of the projective approach to linear models. To some, this may seem contradictory. I contend that it is possible to be both rigorous and illustrative and that it is possible to use the projective approach in practical applications. Therefore, unlike many other books on linear models, the use of projections and sub­ spaces does not stop after the general theory. They are used wherever I could figure out how to do it. Solving normal equations and using calculus (outside of maximum likelihood theory) are anathema to me. This is because I do not believe that they contribute to the understanding of linear models. I have similar feelings about the use of side conditions. Such topics are mentioned when appropriate and thenceforward avoided like the plague. On the other side of the coin, I just as strenuously reject teaching linear models with a coordinate free approach. Although Joe Eaton assures me that the issues in complicated problems freq...

Chemical Modeling of the Reactivity of Short-Lived Greenhouse Gases: A Model Inter-Comparison Prescribing a Well-Measured, Remote Troposphere

Science.gov (United States)

Prather, Michael J.; Flynn, Clare M.; Zhu, Xin; Steenrod, Stephen D.; Strode, Sarah A.; Fiore, Arlene M.; Correa, Gustavo; Murray, Lee T.; Lamarque, Jean-Francois

2018-01-01

We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating over the data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14,880 parcels along 180W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10% of parcels control 25-30% of the total reactivities), but do not fully agree on which parcels comprise the top 10%. Distinct differences in specific features occur, including the regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the 6 models tested here, 3 are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify 4, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in

Simulation of reactive geochemical transport in groundwater using a semi-analytical screening model

Science.gov (United States)

McNab, Walt W.

1997-10-01

A reactive geochemical transport model, based on a semi-analytical solution to the advective-dispersive transport equation in two dimensions, is developed as a screening tool for evaluating the impact of reactive contaminants on aquifer hydrogeochemistry. Because the model utilizes an analytical solution to the transport equation, it is less computationally intensive than models based on numerical transport schemes, is faster, and it is not subject to numerical dispersion effects. Although the assumptions used to construct the model preclude consideration of reactions between the aqueous and solid phases, thermodynamic mineral saturation indices are calculated to provide qualitative insight into such reactions. Test problems involving acid mine drainage and hydrocarbon biodegradation signatures illustrate the utility of the model in simulating essential hydrogeochemical phenomena.

Approximating chiral quark models with linear σ-models

International Nuclear Information System (INIS)

Broniowski, Wojciech; Golli, Bojan

2003-01-01

We study the approximation of chiral quark models with simpler models, obtained via gradient expansion. The resulting Lagrangian of the type of the linear σ-model contains, at the lowest level of the gradient-expanded meson action, an additional term of the form ((1)/(2))A(σ∂ μ σ+π∂ μ π) 2 . We investigate the dynamical consequences of this term and its relevance to the phenomenology of the soliton models of the nucleon. It is found that the inclusion of the new term allows for a more efficient approximation of the underlying quark theory, especially in those cases where dynamics allows for a large deviation of the chiral fields from the chiral circle, such as in quark models with non-local regulators. This is of practical importance, since the σ-models with valence quarks only are technically much easier to treat and simpler to solve than the quark models with the full-fledged Dirac sea

Multivariate statistical modelling based on generalized linear models

CERN Document Server

Fahrmeir, Ludwig

1994-01-01

This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...

Finiteness of Ricci flat supersymmetric non-linear sigma-models

International Nuclear Information System (INIS)

Alvarez-Gaume, L.; Ginsparg, P.

1985-01-01

Combining the constraints of Kaehler differential geometry with the universality of the normal coordinate expansion in the background field method, we study the ultraviolet behavior of 2-dimensional supersymmetric non-linear sigma-models with target space an arbitrary riemannian manifold M. We show that the constraint of N=2 supersymmetry requires that all counterterms to the metric beyond one-loop order are cohomologically trivial. It follows that such supersymmetric non-linear sigma-models defined on locally symmetric spaces are super-renormalizable and that N=4 models are on-shell ultraviolet finite to all orders of perturbation theory. (orig.)

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

Science.gov (United States)

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Robust Linear Models for Cis-eQTL Analysis.

Science.gov (United States)

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Practical likelihood analysis for spatial generalized linear mixed models

DEFF Research Database (Denmark)

Bonat, W. H.; Ribeiro, Paulo Justiniano

2016-01-01

We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

Large eddy simulation of n-heptane spray combustion in partially premixed combustion regime with linear eddy model

International Nuclear Information System (INIS)

Xiao, Gang; Jia, Ming; Wang, Tianyou

2016-01-01

Spray combustion of n-heptane in a constant-volume vessel under engine-relevant conditions was investigated using linear eddy model in the framework of large eddy simulation. In this numerical approach, turbulent mixing was traced by an innovative stochastic approach instead of the conventional gradient diffusion model. Chemical reaction rates were calculated with the consideration of the sub-grid scale spatial fluctuations of reactive scalars. Turbulence-chemistry interactions were represented by the separated treatments of the underlying processes including turbulent stirring, chemical reaction, and molecular diffusion. The model was validated against the experimental data of ignition delay times, chemiluminescence images, and soot images from Sandia National Laboratories. Numerical results showed that the ignition process changed from the temperature-controlled regime to the mixing-controlled regime as the initial ambient temperature increased from 800 K to 1000 K. The premixed flame and the diffusion flame coexisted, while the gross heat release rate was found to be dominated by the premixed flame. The temperature fluctuation was mainly observed around the spray jet due to the cooling effect of the fuel vaporization. The fluctuations were more significantly smoothed out by the high-temperature flame than the low-temperature flame. The mean temperature would be overpredicted if the sub-grid temperature fluctuation was neglected. - Highlights: • Turbulent mixing is traced by stochastic method instead of gradient diffusion model. • Sub-grid scale fluctuations of reactive scalars are captured. • Ignition process varies from temperature-controlled to mixing-controlled regime. • Temperature fluctuation can be smoothed out by high-temperature flame. • The heat release rate is dominated by the premixed flame.

A linear model of ductile plastic damage

International Nuclear Information System (INIS)

Lemaitre, J.

1983-01-01

A three-dimensional model of isotropic ductile plastic damage based on a continuum damage variable on the effective stress concept and on thermodynamics is derived. As shown by experiments on several metals and alloys, the model, integrated in the case of proportional loading, is linear with respect to the accumulated plastic strain and shows a large influence of stress triaxiality [fr

Sphaleron in a non-linear sigma model

International Nuclear Information System (INIS)

Sogo, Kiyoshi; Fujimoto, Yasushi.

1989-08-01

We present an exact classical saddle point solution in a non-linear sigma model. It has a topological charge 1/2 and mediates the vacuum transition. The quantum fluctuations and the transition rate are also examined. (author)

Fast and local non-linear evolution of steep wave-groups on deep water: A comparison of approximate models to fully non-linear simulations

International Nuclear Information System (INIS)

Adcock, T. A. A.; Taylor, P. H.

2016-01-01

The non-linear Schrödinger equation and its higher order extensions are routinely used for analysis of extreme ocean waves. This paper compares the evolution of individual wave-packets modelled using non-linear Schrödinger type equations with packets modelled using fully non-linear potential flow models. The modified non-linear Schrödinger Equation accurately models the relatively large scale non-linear changes to the shape of wave-groups, with a dramatic contraction of the group along the mean propagation direction and a corresponding extension of the width of the wave-crests. In addition, as extreme wave form, there is a local non-linear contraction of the wave-group around the crest which leads to a localised broadening of the wave spectrum which the bandwidth limited non-linear Schrödinger Equations struggle to capture. This limitation occurs for waves of moderate steepness and a narrow underlying spectrum

Phase behavior and reactive transport of partial melt in heterogeneous mantle model

Science.gov (United States)

Jordan, J.; Hesse, M. A.

2013-12-01

The reactive transport of partial melt is the key process that leads to the chemical and physical differentiation of terrestrial planets and smaller celestial bodies. The essential role of the lithological heterogeneities during partial melting of the mantle is increasingly recognized. How far can enriched melts propagate while interacting with the ambient mantle? Can the melt flow emanating from a fertile heterogeneity be localized through a reactive infiltration feedback in a model without exogenous factors or contrived initial conditions? A full understanding of the role of heterogeneities requires reactive melt transport models that account for the phase behavior of major elements. Previous work on reactive transport in the mantle focuses on trace element partitioning; we present the first nonlinear chromatographic analysis of reactive melt transport in systems with binary solid solution. Our analysis shows that reactive melt transport in systems with binary solid solution leads to the formation of two separate reaction fronts: a slow melting/freezing front along which enthalpy change is dominant and a fast dissolution/precipitation front along which compositional changes are dominated by an ion-exchange process over enthalpy change. An intermediate state forms between these two fronts with a bulk-rock composition and enthalpy that are not necessarily bounded by the bulk-rock composition and enthalpy of either the enriched heterogeneity or the depleted ambient mantle. The formation of this intermediate state makes it difficult to anticipate the porosity changes and hence the stability of reaction fronts. Therefore, we develop a graphical representation for the solution that allows identification of the intermediate state by inspection, for all possible bulk-rock compositions and enthalpies of the heterogeneity and the ambient mantle. We apply the analysis to the partial melting of an enriched heterogeneity. This leads to the formation of moving precipitation

Ground Motion Models for Future Linear Colliders

International Nuclear Information System (INIS)

Seryi, Andrei

2000-01-01

Optimization of the parameters of a future linear collider requires comprehensive models of ground motion. Both general models of ground motion and specific models of the particular site and local conditions are essential. Existing models are not completely adequate, either because they are too general, or because they omit important peculiarities of ground motion. The model considered in this paper is based on recent ground motion measurements performed at SLAC and at other accelerator laboratories, as well as on historical data. The issues to be studied for the models to become more predictive are also discussed

Varicella-Zoster Virus in Perth, Western Australia: Seasonality and Reactivation.

Directory of Open Access Journals (Sweden)

Igor A Korostil

Full Text Available Identification of the factors affecting reactivation of varicella-zoster virus (VZV largely remains an open question. Exposure to solar ultra violet (UV radiation is speculated to facilitate reactivation. Should the role of UV in reactivation be significant, VZV reactivation patterns would generally be expected to be synchronous with seasonal UV profiles in temperate climates.We analysed age and gender specific VZV notification time series data from Perth, Western Australia (WA. This city has more daily sunshine hours than any other major Australian city. Using the cosinor and generalized linear models, we tested these data for seasonality and correlation with UV and temperature.We established significant seasonality of varicella notifications and showed that while herpes-zoster (HZ was not seasonal it had a more stable seasonal component in males over 60 than in any other subpopulation tested. We also detected significant association between HZ notifications and UV for the entire Perth population as well as for females and males separately. In most cases, temperature proved to be a significant factor as well.Our findings suggest that UV radiation may be important for VZV reactivation, under the assumption that notification data represent an acceptably accurate qualitative measure of true VZV incidence.

Portable digital reactivity meter for power reactors

Energy Technology Data Exchange (ETDEWEB)

Steffen, G [Nuklear-Ingenieur Service G.m.b.H., Hanau (Germany, F.R.)

1977-07-01

A digital reactivity meter has been developed, which can be used for all kinds of kinetic reactivity measurements in PWR's and BWR's. The input signals may be supplied by standard neutron detectors of the reactor. The hardware configuration consists of a minicomputer with ADC and DAC, a 'Silent' terminal and a high speed paper tape reader/punch. It is easily transportable. The reactivity meter solves the inverse kinetics equations for 6 delayed neutron groups, simultaneously for up to 8 logarithmic or linear neutron flux signals. It has been successfully tested at Biblis A PWR and the KRB BWR.

Biofuel gasifier feedstock reactivity - explaining the differences and creating prediction models

Energy Technology Data Exchange (ETDEWEB)

Konttinen, J. (Jyvaeskylae Univ. (Finland)), Email: jukontti@jyu.fi; Moilanen, A. (VTT Processes, Espoo (Finland)); DeMartini, N.; Hupa, M. (AaboAkademi Univ., Turku (Finland))

2009-07-01

In this project in progress, the objective is to generate a method with reasonable cost and effort, to predict the gasification behavior of biomass fuels in a gasification reactor. The results of the project will help to understand the differences in the gasification behavior of biomass fuels. An essential hypothesis in the project is that the decrease of the catalysis properties of biomass ash will decrease biomass char gasification reactivity and thus the final carbon conversion. The project will involve TGA experiments to characterize char reactivity from 3 biomass fuels, ash characterization by fuel fractionation and SEM analysis; bench scale fluidized bed gasification for the 3 fuels; and kinetic modeling to include the change in the carbon conversion rate for different fuels as carbon gasification proceeds to completion. The constants and reactivity models will be used as part of a fluidized-bed gasification reactor model called. 'Carbon conversion predictor', in order to predict the effect of fuel ash composition on the gasification kinetics of biomass char. The University of Jyvaeskylae, Aabo Akademi University and VTT processes will work in cooperation with the private companies in Finland in the field of gasification. Also some cooperation in the USA will possibly be generated. The results of this project can be used in the design of commercial-scale biomass gasification reactors firing a variety of biomass fuels. (orig.)

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.

Evaluation of the reactive nitrogen budget of the remote atmosphere in global models using airborne measurements

Science.gov (United States)

Murray, L. T.; Strode, S. A.; Fiore, A. M.; Lamarque, J. F.; Prather, M. J.; Thompson, C. R.; Peischl, J.; Ryerson, T. B.; Allen, H.; Blake, D. R.; Crounse, J. D.; Brune, W. H.; Elkins, J. W.; Hall, S. R.; Hintsa, E. J.; Huey, L. G.; Kim, M. J.; Moore, F. L.; Ullmann, K.; Wennberg, P. O.; Wofsy, S. C.

2017-12-01

Nitrogen oxides (NOx ≡ NO + NO2) in the background atmosphere are critical precursors for the formation of tropospheric ozone and OH, thereby exerting strong influence on surface air quality, reactive greenhouse gases, and ecosystem health. The impact of NOx on atmospheric composition and climate is sensitive to the relative partitioning of reactive nitrogen between NOx and longer-lived reservoir species of the total reactive nitrogen family (NOy) such as HNO3, HNO4, PAN and organic nitrates (RONO2). Unfortunately, global chemistry-climate models (CCMs) and chemistry-transport models (CTMs) have historically disagreed in their reactive nitrogen budgets outside of polluted continental regions, and we have lacked in situ observations with which to evaluate them. Here, we compare and evaluate the NOy budget of six global models (GEOS-Chem CTM, GFDL AM3 CCM, GISS E2.1 CCM, GMI CTM, NCAR CAM CCM, and UCI CTM) using new observations of total reactive nitrogen and its member species from the NASA Atmospheric Tomography (ATom) mission. ATom has now completed two of its four planned deployments sampling the remote Pacific and Atlantic basins of both hemispheres with a comprehensive suite of measurements for constraining reactive photochemistry. All six models have simulated conditions climatologically similar to the deployments. The GMI and GEOS-Chem CTMs have in addition performed hindcast simulations using the MERRA-2 reanalysis, and have been sampled along the flight tracks. We evaluate the performance of the models relative to the observations, and identify factors contributing to their disparate behavior using known differences in model oxidation mechanisms, heterogeneous loss pathways, lightning and surface emissions, and physical loss processes.

Modelling point patterns with linear structures

DEFF Research Database (Denmark)

Møller, Jesper; Rasmussen, Jakob Gulddahl

2009-01-01

processes whose realizations contain such linear structures. Such a point process is constructed sequentially by placing one point at a time. The points are placed in such a way that new points are often placed close to previously placed points, and the points form roughly line shaped structures. We...... consider simulations of this model and compare with real data....

Modelling point patterns with linear structures

DEFF Research Database (Denmark)

Møller, Jesper; Rasmussen, Jakob Gulddahl

processes whose realizations contain such linear structures. Such a point process is constructed sequentially by placing one point at a time. The points are placed in such a way that new points are often placed close to previously placed points, and the points form roughly line shaped structures. We...... consider simulations of this model and compare with real data....

Modeling exposure–lag–response associations with distributed lag non-linear models

Science.gov (United States)

Gasparrini, Antonio

2014-01-01

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094

Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models.

Science.gov (United States)

Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme

2015-01-01

The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.

An R2 statistic for fixed effects in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver

2008-12-20

Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes.

Science.gov (United States)

Casellas, J; Bach, R

2012-06-01

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

Linear Temporal Logic-based Mission Planning

OpenAIRE

Anil Kumar; Rahul Kala

2016-01-01

In this paper, we describe the Linear Temporal Logic-based reactive motion planning. We address the problem of motion planning for mobile robots, wherein the goal specification of planning is given in complex environments. The desired task specification may consist of complex behaviors of the robot, including specifications for environment constraints, need of task optimality, obstacle avoidance, rescue specifications, surveillance specifications, safety specifications, etc. We use Linear Tem...

Universal Linear Scaling of Permeability and Time for Heterogeneous Fracture Dissolution

Science.gov (United States)

Wang, L.; Cardenas, M. B.

2017-12-01

Fractures are dynamically changing over geological time scale due to mechanical deformation and chemical reactions. However, the latter mechanism remains poorly understood with respect to the expanding fracture, which leads to a positively coupled flow and reactive transport processes, i.e., as a fracture expands, so does its permeability (k) and thus flow and reactive transport processes. To unravel this coupling, we consider a self-enhancing process that leads to fracture expansion caused by acidic fluid, i.e., CO2-saturated brine dissolving calcite fracture. We rigorously derive a theory, for the first time, showing that fracture permeability increases linearly with time [Wang and Cardenas, 2017]. To validate this theory, we resort to the direct simulation that solves the Navier-Stokes and Advection-Diffusion equations with a moving mesh according to the dynamic dissolution process in two-dimensional (2D) fractures. We find that k slowly increases first until the dissolution front breakthrough the outbound when we observe a rapid k increase, i.e., the linear time-dependence of k occurs. The theory agrees well with numerical observations across a broad range of Peclet and Damkohler numbers through homogeneous and heterogeneous 2D fractures. Moreover, the theory of linear scaling relationship between k and time matches well with experimental observations of three-dimensional (3D) fractures' dissolution. To further attest to our theory's universality for 3D heterogeneous fractures across a broad range of roughness and correlation length of aperture field, we develop a depth-averaged model that simulates the process-based reactive transport. The simulation results show that, regardless of a wide variety of dissolution patterns such as the presence of dissolution fingers and preferential dissolution paths, the linear scaling relationship between k and time holds. Our theory sheds light on predicting permeability evolution in many geological settings when the self

Estimation of group means when adjusting for covariates in generalized linear models.

Science.gov (United States)

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

Identifiability Results for Several Classes of Linear Compartment Models.

Science.gov (United States)

Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa

2015-08-01

Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.

A non-linear model of economic production processes

Science.gov (United States)

Ponzi, A.; Yasutomi, A.; Kaneko, K.

2003-06-01

We present a new two phase model of economic production processes which is a non-linear dynamical version of von Neumann's neoclassical model of production, including a market price-setting phase as well as a production phase. The rate of an economic production process is observed, for the first time, to depend on the minimum of its input supplies. This creates highly non-linear supply and demand dynamics. By numerical simulation, production networks are shown to become unstable when the ratio of different products to total processes increases. This provides some insight into observed stability of competitive capitalist economies in comparison to monopolistic economies. Capitalist economies are also shown to have low unemployment.

Effect Displays in R for Generalised Linear Models

Directory of Open Access Journals (Sweden)

John Fox

2003-07-01

Full Text Available This paper describes the implementation in R of a method for tabular or graphical display of terms in a complex generalised linear model. By complex, I mean a model that contains terms related by marginality or hierarchy, such as polynomial terms, or main effects and interactions. I call these tables or graphs effect displays. Effect displays are constructed by identifying high-order terms in a generalised linear model. Fitted values under the model are computed for each such term. The lower-order "relatives" of a high-order term (e.g., main effects marginal to an interaction are absorbed into the term, allowing the predictors appearing in the high-order term to range over their values. The values of other predictors are fixed at typical values: for example, a covariate could be fixed at its mean or median, a factor at its proportional distribution in the data, or to equal proportions in its several levels. Variations of effect displays are also described, including representation of terms higher-order to any appearing in the model.

Time space domain decomposition methods for reactive transport - Application to CO2 geological storage

International Nuclear Information System (INIS)

Haeberlein, F.

2011-01-01

Reactive transport modelling is a basic tool to model chemical reactions and flow processes in porous media. A totally reduced multi-species reactive transport model including kinetic and equilibrium reactions is presented. A structured numerical formulation is developed and different numerical approaches are proposed. Domain decomposition methods offer the possibility to split large problems into smaller subproblems that can be treated in parallel. The class of Schwarz-type domain decomposition methods that have proved to be high-performing algorithms in many fields of applications is presented with a special emphasis on the geometrical viewpoint. Numerical issues for the realisation of geometrical domain decomposition methods and transmission conditions in the context of finite volumes are discussed. We propose and validate numerically a hybrid finite volume scheme for advection-diffusion processes that is particularly well-suited for the use in a domain decomposition context. Optimised Schwarz waveform relaxation methods are studied in detail on a theoretical and numerical level for a two species coupled reactive transport system with linear and nonlinear coupling terms. Well-posedness and convergence results are developed and the influence of the coupling term on the convergence behaviour of the Schwarz algorithm is studied. Finally, we apply a Schwarz waveform relaxation method on the presented multi-species reactive transport system. (author)

H∞ /H2 model reduction through dilated linear matrix inequalities

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Stoustrup, Jakob

2012-01-01

This paper presents sufficient dilated linear matrix inequalities (LMI) conditions to the $H_{infty}$ and $H_{2}$ model reduction problem. A special structure of the auxiliary (slack) variables allows the original model of order $n$ to be reduced to an order $r=n/s$ where $n,r,s in field{N}$. Arb......This paper presents sufficient dilated linear matrix inequalities (LMI) conditions to the $H_{infty}$ and $H_{2}$ model reduction problem. A special structure of the auxiliary (slack) variables allows the original model of order $n$ to be reduced to an order $r=n/s$ where $n,r,s in field...

Optimization Research of Generation Investment Based on Linear Programming Model

Science.gov (United States)

Wu, Juan; Ge, Xueqian

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

Modeling variably saturated multispecies reactive groundwater solute transport with MODFLOW-UZF and RT3D

Science.gov (United States)

Bailey, Ryan T.; Morway, Eric D.; Niswonger, Richard G.; Gates, Timothy K.

2013-01-01

A numerical model was developed that is capable of simulating multispecies reactive solute transport in variably saturated porous media. This model consists of a modified version of the reactive transport model RT3D (Reactive Transport in 3 Dimensions) that is linked to the Unsaturated-Zone Flow (UZF1) package and MODFLOW. Referred to as UZF-RT3D, the model is tested against published analytical benchmarks as well as other published contaminant transport models, including HYDRUS-1D, VS2DT, and SUTRA, and the coupled flow and transport modeling system of CATHY and TRAN3D. Comparisons in one-dimensional, two-dimensional, and three-dimensional variably saturated systems are explored. While several test cases are included to verify the correct implementation of variably saturated transport in UZF-RT3D, other cases are included to demonstrate the usefulness of the code in terms of model run-time and handling the reaction kinetics of multiple interacting species in variably saturated subsurface systems. As UZF1 relies on a kinematic-wave approximation for unsaturated flow that neglects the diffusive terms in Richards equation, UZF-RT3D can be used for large-scale aquifer systems for which the UZF1 formulation is reasonable, that is, capillary-pressure gradients can be neglected and soil parameters can be treated as homogeneous. Decreased model run-time and the ability to include site-specific chemical species and chemical reactions make UZF-RT3D an attractive model for efficient simulation of multispecies reactive transport in variably saturated large-scale subsurface systems.

Modeling of non-linear CHP efficiency curves in distributed energy systems

DEFF Research Database (Denmark)

Milan, Christian; Stadler, Michael; Cardoso, Gonçalo

2015-01-01

Distributed energy resources gain an increased importance in commercial and industrial building design. Combined heat and power (CHP) units are considered as one of the key technologies for cost and emission reduction in buildings. In order to make optimal decisions on investment and operation...... for these technologies, detailed system models are needed. These models are often formulated as linear programming problems to keep computational costs and complexity in a reasonable range. However, CHP systems involve variations of the efficiency for large nameplate capacity ranges and in case of part load operation......, which can be even of non-linear nature. Since considering these characteristics would turn the models into non-linear problems, in most cases only constant efficiencies are assumed. This paper proposes possible solutions to address this issue. For a mixed integer linear programming problem two...

Accounting for the Decreasing Denitrification Potential of Aquifers in Travel-Time Based Reactive-Transport Models of Nitrate

Science.gov (United States)

Cirpka, O. A.; Loschko, M.; Wöhling, T.; Rudolph, D. L.

2017-12-01

Excess nitrate concentrations pose a threat to drinking-water production from groundwater in all regions of intensive agriculture worldwide. Natural organic matter, pyrite, and other reduced constituents of the aquifer matrix can be oxidized by aerobic and denitrifying bacteria, leading to self-cleaning of groundwater. Various studies have shown that the heterogeneity of both hydraulic and chemical aquifer properties influence the reactive behavior. Since the exact spatial distributions of these properties are not known, predictions on the temporal evolution of nitrate should be probabilistic. However, the computational effort of pde-based, spatially explicit multi-component reactive-transport simulations are so high that multiple model runs become impossible. Conversely, simplistic models that treat denitrification as first-order decay process miss important controls on denitrification. We have proposed a Lagrangian framework of nonlinear reactive transport, in which the electron-donor supply by the aquifer matrix is parameterized by a relative reactivity, that is the reaction rate relative to a standard reaction rate for identical solute concentrations (Loschko et al., 2016). We could show that reactive transport simplifies to solving a single ordinary dfferential equation in terms of the cumulative relative reactivity for a given combination of inflow concentrations. Simulating 3-D flow and reactive transport are computationally so inexpensive that Monte Carlo simulation become feasible. The original scheme did not consider a change of the relative reactivity over time, implying that the electron-donor pool in the matrix is infinite. We have modified the scheme to address the consumption of the reducing aquifer constituents upon the reactions. We also analyzed how a minimally complex model of aerobic respiration and denitrification could look like. With the revised scheme, we performed Monte Carlo simulations in 3-D domains, confirming that the uncertainty in

Non-linear characterisation of the physical model of an ancient masonry bridge

International Nuclear Information System (INIS)

Fragonara, L Zanotti; Ceravolo, R; Matta, E; Quattrone, A; De Stefano, A; Pecorelli, M

2012-01-01

This paper presents the non-linear investigations carried out on a scaled model of a two-span masonry arch bridge. The model has been built in order to study the effect of the central pile settlement due to riverbank erosion. Progressive damage was induced in several steps by applying increasing settlements at the central pier. For each settlement step, harmonic shaker tests were conducted under different excitation levels, this allowing for the non-linear identification of the progressively damaged system. The shaker tests have been performed at resonance with the modal frequency of the structure, which were determined from a previous linear identification. Estimated non-linearity parameters, which result from the systematic application of restoring force based identification algorithms, can corroborate models to be used in the reassessment of existing structures. The method used for non-linear identification allows monitoring the evolution of non-linear parameters or indicators which can be used in damage and safety assessment.

Study of the critical behavior of the O(N) linear and nonlinear sigma models

International Nuclear Information System (INIS)

Graziani, F.R.

1983-01-01

A study of the large N behavior of both the O(N) linear and nonlinear sigma models is presented. The purpose is to investigate the relationship between the disordered (ordered) phase of the linear and nonlinear sigma models. Utilizing operator product expansions and stability analyses, it is shown that for 2 - (lambda/sub R/(M) is the dimensionless renormalized quartic coupling and lambda* is the IR fixed point) limit of the linear sigma model which yields the nonlinear sigma model. It is also shown that stable large N linear sigma models with lambda 0) and nonlinear models are trivial. This result (i.e., triviality) is well known but only for one and two component models. Interestingly enough, the lambda< d = 4 linear sigma model remains nontrivial and tachyonic free

Linear versus non-linear supersymmetry, in general

Energy Technology Data Exchange (ETDEWEB)

Ferrara, Sergio [Theoretical Physics Department, CERN,CH-1211 Geneva 23 (Switzerland); INFN - Laboratori Nazionali di Frascati,Via Enrico Fermi 40, I-00044 Frascati (Italy); Department of Physics and Astronomy, UniversityC.L.A.,Los Angeles, CA 90095-1547 (United States); Kallosh, Renata [SITP and Department of Physics, Stanford University,Stanford, California 94305 (United States); Proeyen, Antoine Van [Institute for Theoretical Physics, Katholieke Universiteit Leuven,Celestijnenlaan 200D, B-3001 Leuven (Belgium); Wrase, Timm [Institute for Theoretical Physics, Technische Universität Wien,Wiedner Hauptstr. 8-10, A-1040 Vienna (Austria)

2016-04-12

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Linear versus non-linear supersymmetry, in general

International Nuclear Information System (INIS)

Ferrara, Sergio; Kallosh, Renata; Proeyen, Antoine Van; Wrase, Timm

2016-01-01

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

A simple reactivity feedback model accounting for radial core expansion effects in the liquid metal fast reactor

International Nuclear Information System (INIS)

Kwon, Young Min; Lee, Yong Bum; Chang, Won Pyo; Haha, Do Hee

2002-01-01

The radial core expansion due to the structure temperature rise is one of major negative reactivity insertion mechanisms in metallic fueled reactor. Thermal expansion is a result of both the laws of nature and the particular core design and it causes negative reactivity feedback by the combination of increased core volume captures and increased core surface leakage. The simple radial core expansion reactivity feedback model developed for the SSC-K code was evaluated by the code-to-code comparison analysis. From the comparison results, it can be stated that the radial core expansion reactivity feedback model employed into the SSC-K code may be reasonably accurate in the UTOP analysis

A simple reactivity feedback model accounting for radial core expansion effects in the liquid metal fast reactor

Energy Technology Data Exchange (ETDEWEB)

Kwon, Young Min; Lee, Yong Bum; Chang, Won Pyo; Haha, Do Hee [KAERI, Taejon (Korea, Republic of)

2002-10-01

The radial core expansion due to the structure temperature rise is one of major negative reactivity insertion mechanisms in metallic fueled reactor. Thermal expansion is a result of both the laws of nature and the particular core design and it causes negative reactivity feedback by the combination of increased core volume captures and increased core surface leakage. The simple radial core expansion reactivity feedback model developed for the SSC-K code was evaluated by the code-to-code comparison analysis. From the comparison results, it can be stated that the radial core expansion reactivity feedback model employed into the SSC-K code may be reasonably accurate in the UTOP analysis.

Inverse Modelling Problems in Linear Algebra Undergraduate Courses

Science.gov (United States)

Martinez-Luaces, Victor E.

2013-01-01

This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.

Science.gov (United States)

Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S

2017-06-01

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were

Available pressure amplitude of linear compressor based on phasor triangle model

Science.gov (United States)

Duan, C. X.; Jiang, X.; Zhi, X. Q.; You, X. K.; Qiu, L. M.

2017-12-01

The linear compressor for cryocoolers possess the advantages of long-life operation, high efficiency, low vibration and compact structure. It is significant to study the match mechanisms between the compressor and the cold finger, which determines the working efficiency of the cryocooler. However, the output characteristics of linear compressor are complicated since it is affected by many interacting parameters. The existing matching methods are simplified and mainly focus on the compressor efficiency and output acoustic power, while neglecting the important output parameter of pressure amplitude. In this study, a phasor triangle model basing on analyzing the forces of the piston is proposed. It can be used to predict not only the output acoustic power, the efficiency, but also the pressure amplitude of the linear compressor. Calculated results agree well with the measurement results of the experiment. By this phasor triangle model, the theoretical maximum output pressure amplitude of the linear compressor can be calculated simply based on a known charging pressure and operating frequency. Compared with the mechanical and electrical model of the linear compressor, the new model can provide an intuitionistic understanding on the match mechanism with faster computational process. The model can also explain the experimental phenomenon of the proportional relationship between the output pressure amplitude and the piston displacement in experiments. By further model analysis, such phenomenon is confirmed as an expression of the unmatched design of the compressor. The phasor triangle model may provide an alternative method for the compressor design and matching with the cold finger.

Reactive transport in a partially molten system with binary solid solution

Science.gov (United States)

Jordan, J.; Hesse, M. A.

2017-12-01

Melt extraction from the Earth's mantle through high-porosity channels is required to explain the composition of the oceanic crust. Feedbacks from reactive melt transport are thought to localize melt into a network of high-porosity channels. Recent studies invoke lithological heterogeneities in the Earth's mantle to seed the localization of partial melts. Therefore, it is necessary to understand the reaction fronts that form as melt flows across the lithological interface of a heterogeneity and the background mantle. Simplified melting models of such systems aide in the interpretation and formulation of larger scale mantle models. Motivated by the aforementioned facts, we present a chromatographic analysis of reactive melt transport across lithological boundaries, using theory for hyperbolic conservation laws. This is an extension of well-known linear trace element chromatography to the coupling of major elements and energy transport. Our analysis allows the prediction of the feedbacks that arise in reactive melt transport due to melting, freezing, dissolution and precipitation for frontal reactions. This study considers the simplified case of a rigid, partially molten porous medium with binary solid solution. As melt traverses a lithological contact-modeled as a Riemann problem-a rich set of features arise, including a reacted zone between an advancing reaction front and partial chemical preservation of the initial contact. Reactive instabilities observed in this study originate at the lithological interface rather than along a chemical gradient as in most studies of mantle dynamics. We present a regime diagram that predicts where reaction fronts become unstable, thereby allowing melt localization into high-porosity channels through reactive instabilities. After constructing the regime diagram, we test the one-dimensional hyperbolic theory against two-dimensional numerical experiments. The one-dimensional hyperbolic theory is sufficient for predicting the

The Overgeneralization of Linear Models among University Students' Mathematical Productions: A Long-Term Study

Science.gov (United States)

Esteley, Cristina B.; Villarreal, Monica E.; Alagia, Humberto R.

2010-01-01

Over the past several years, we have been exploring and researching a phenomenon that occurs among undergraduate students that we called extension of linear models to non-linear contexts or overgeneralization of linear models. This phenomenon appears when some students use linear representations in situations that are non-linear. In a first phase,…

Establishing the long-term fuel management scheme using point reactivity model

International Nuclear Information System (INIS)

Park, Yong-Soo; Kim, Jae-Hak; Lee, Young-Ouk; Song, Jae-Woong; Zee, Sung-Kyun

1994-01-01

A new approach to establish the long-term fuel management scheme is presented in this paper. The point reactivity model is used to predict the core average reactivity. An attempt to calculate batchwise power fraction is introduced through the two-dimensional nodal power algorithm based on the modified one-group diffusion equation and the number of fuel assemblies on the core periphery. Suggested is an empirical formula to estimate the radial leakage reactivity with ripe core design experience reflected. This approach predicts the cycle lengths and the discharge burnups of individual fuel batches up to an equilibrium core when the proper input data such as batch enrichment, batch size, type and content of burnable poison and reloading strategies are given. Eight benchmark calculations demonstrate that the new approach used in this study is reasonably accurate and highly efficient for the purpose of scoping calculation when compared with design code predictions. (author)

Identification of protective postexposure mycobacterial vaccine antigens using an immunosuppression-based reactivation model in the zebrafish

Directory of Open Access Journals (Sweden)

Henna Myllymäki

2018-03-01

Full Text Available Roughly one third of the human population carries a latent Mycobacterium tuberculosis infection, with a 5-10% lifetime risk of reactivation to active tuberculosis and further spreading the disease. The mechanisms leading to the reactivation of a latent Mycobacterium tuberculosis infection are insufficiently understood. Here, we used a natural fish pathogen, Mycobacterium marinum, to model the reactivation of a mycobacterial infection in the adult zebrafish (Danio rerio. A low-dose intraperitoneal injection (∼40 colony-forming units led to a latent infection, with mycobacteria found in well-organized granulomas surrounded by a thick layer of fibrous tissue. A latent infection could be reactivated by oral dexamethasone treatment, which led to disruption of the granuloma structures and dissemination of bacteria. This was associated with the depletion of lymphocytes, especially CD4+ T cells. Using this model, we verified that ethambutol is effective against an active disease but not a latent infection. In addition, we screened 15 mycobacterial antigens as postexposure DNA vaccines, of which RpfB and MMAR_4207 reduced bacterial burdens upon reactivation, as did the Ag85-ESAT-6 combination. In conclusion, the adult zebrafish-M. marinum infection model provides a feasible tool for examining the mechanisms of reactivation in mycobacterial infections, and for screening vaccine and drug candidates. This article has an associated First Person interview with the first author of the paper.

Reactivating dynamics for the susceptible-infected-susceptible model: a simple method to simulate the absorbing phase

Science.gov (United States)

Macedo-Filho, A.; Alves, G. A.; Costa Filho, R. N.; Alves, T. F. A.

2018-04-01

We investigated the susceptible-infected-susceptible model on a square lattice in the presence of a conjugated field based on recently proposed reactivating dynamics. Reactivating dynamics consists of reactivating the infection by adding one infected site, chosen randomly when the infection dies out, avoiding the dynamics being trapped in the absorbing state. We show that the reactivating dynamics can be interpreted as the usual dynamics performed in the presence of an effective conjugated field, named the reactivating field. The reactivating field scales as the inverse of the lattice number of vertices n, which vanishes at the thermodynamic limit and does not affect any scaling properties including ones related to the conjugated field.

Stress and Sleep Reactivity: A Prospective Investigation of the Stress-Diathesis Model of Insomnia

Science.gov (United States)

Drake, Christopher L.; Pillai, Vivek; Roth, Thomas

2014-01-01

Study Objectives: To prospectively assess sleep reactivity as a diathesis of insomnia, and to delineate the interaction between this diathesis and naturalistic stress in the development of insomnia among normal sleepers. Design: Longitudinal. Setting: Community-based. Participants: 2,316 adults from the Evolution of Pathways to Insomnia Cohort (EPIC) with no history of insomnia or depression (46.8 ± 13.2 y; 60% female). Interventions: None. Measurements and Results: Participants reported the number of stressful events they encountered at baseline (Time 1), as well as the level of cognitive intrusion they experienced in response to each stressor. Stressful events (OR = 1.13; P insomnia one year hence (Time 2). Intrusion mediated the effects of stressful events on risk for insomnia (P insomnia (OR = 1.78; P insomnia as a function of intrusion was significantly higher in individuals with high sleep reactivity. Trait sleep reactivity also constituted a significant risk for depression (OR = 1.67; P Insomnia at Time 2 significantly mediated this effect (P insomnia, and that it triggers insomnia by exacerbating the effects of stress-induced intrusion. Sleep reactivity is also a precipitant of depression, as mediated by insomnia. These findings support the stress-diathesis model of insomnia, while highlighting sleep reactivity as an important diathesis. Citation: Drake CL, Pillai V, Roth T. Stress and sleep reactivity: a prospective investigation of the stress-diathesis model of insomnia. SLEEP 2014;37(8):1295-1304. PMID:25083009

Free-piston engine linear generator for hybrid vehicles modeling study

Science.gov (United States)

Callahan, T. J.; Ingram, S. K.

1995-05-01

Development of a free piston engine linear generator was investigated for use as an auxiliary power unit for a hybrid electric vehicle. The main focus of the program was to develop an efficient linear generator concept to convert the piston motion directly into electrical power. Computer modeling techniques were used to evaluate five different designs for linear generators. These designs included permanent magnet generators, reluctance generators, linear DC generators, and two and three-coil induction generators. The efficiency of the linear generator was highly dependent on the design concept. The two-coil induction generator was determined to be the best design, with an efficiency of approximately 90 percent.

Neutron stars in non-linear coupling models

International Nuclear Information System (INIS)

Taurines, Andre R.; Vasconcellos, Cesar A.Z.; Malheiro, Manuel; Chiapparini, Marcelo

2001-01-01

We present a class of relativistic models for nuclear matter and neutron stars which exhibits a parameterization, through mathematical constants, of the non-linear meson-baryon couplings. For appropriate choices of the parameters, it recovers current QHD models found in the literature: Walecka, ZM and ZM3 models. We have found that the ZM3 model predicts a very small maximum neutron star mass, ∼ 0.72M s un. A strong similarity between the results of ZM-like models and those with exponential couplings is noted. Finally, we discuss the very intense scalar condensates found in the interior of neutron stars which may lead to negative effective masses. (author)

Neutron stars in non-linear coupling models

Energy Technology Data Exchange (ETDEWEB)

Taurines, Andre R.; Vasconcellos, Cesar A.Z. [Rio Grande do Sul Univ., Porto Alegre, RS (Brazil); Malheiro, Manuel [Universidade Federal Fluminense, Niteroi, RJ (Brazil); Chiapparini, Marcelo [Universidade do Estado, Rio de Janeiro, RJ (Brazil)

2001-07-01

We present a class of relativistic models for nuclear matter and neutron stars which exhibits a parameterization, through mathematical constants, of the non-linear meson-baryon couplings. For appropriate choices of the parameters, it recovers current QHD models found in the literature: Walecka, ZM and ZM3 models. We have found that the ZM3 model predicts a very small maximum neutron star mass, {approx} 0.72M{sub s}un. A strong similarity between the results of ZM-like models and those with exponential couplings is noted. Finally, we discuss the very intense scalar condensates found in the interior of neutron stars which may lead to negative effective masses. (author)

Neutronic characteristics of linear-assembly breed-and-burn reactors

International Nuclear Information System (INIS)

Petroski, Robert; Forget, Benoit; Forsberg, Charles

2012-01-01

Highlights: ► Simple models used to characterize general behavior of linear-assembly B and B reactors. ► Diffusion theory model developed to explain axial distributions, height vs. reactivity. ► Neutron excess concept reformulated to include linear-assembly B and B reactors. ► Designed model of B and B reactor started using melt-refined B and B reactor used fuel. ► Computed doubling time of fuel cycle requiring no chemical separations. - Abstract: Linear-assembly breed-and-burn (B and B) reactors are B and B reactors that use axially connected assemblies similar to conventional LWR or fast reactor fuel assemblies. Methods for analyzing linear-assembly B and B reactors and their fuel cycles are developed and applied. General neutronic characteristics of linear-assembly B and B reactors are analyzed, including the effects that burnup, shuffling sequence, and radial and axial size have on equilibrium-cycle k-effective. The mechanisms that give rise to a highly peaked axial burnup distribution are explained, and a method for predicting peak burnup vs. k-effective based on infinite-medium depletion calculations is developed. Next, the neutron excess concept from previous studies of B and B reactors is extended to apply to linear-assembly B and B reactors, which allows the amount of starter fuel needed to establish a given equilibrium cycle to be calculated. Several example applications of the neutron excess formulation are given. First, an example model of a linear-assembly B and B reactor is analyzed to find the neutron excess cost of an equilibrium cycle. Second, simple one-dimensional models are used to predict the neutron excess value obtainable from different starter fuel configurations. Finally, these ideas are applied to design a fuel cycle consisting of linear-assembly B and B reactors and fuel recycling via a melt refining process. The neutron excess concept is used to design an appropriate starter fuel configuration made from melt refined fuel, which

A comparison of linear tyre models for analysing shimmy

NARCIS (Netherlands)

Besselink, I.J.M.; Maas, J.W.L.H.; Nijmeijer, H.

2011-01-01

A comparison is made between three linear, dynamic tyre models using low speed step responses and yaw oscillation tests. The match with the measurements improves with increasing complexity of the tyre model. Application of the different tyre models to a two degree of freedom trailing arm suspension

S-AMP for non-linear observation models

DEFF Research Database (Denmark)

Cakmak, Burak; Winther, Ole; Fleury, Bernard H.

2015-01-01

Recently we presented the S-AMP approach, an extension of approximate message passing (AMP), to be able to handle general invariant matrix ensembles. In this contribution we extend S-AMP to non-linear observation models. We obtain generalized AMP (GAMP) as the special case when the measurement...

Diagnostics for Linear Models With Functional Responses

OpenAIRE

Xu, Hongquan; Shen, Qing

2005-01-01

Linear models where the response is a function and the predictors are vectors are useful in analyzing data from designed experiments and other situations with functional observations. Residual analysis and diagnostics are considered for such models. Studentized residuals are defined and their properties are studied. Chi-square quantile-quantile plots are proposed to check the assumption of Gaussian error process and outliers. Jackknife residuals and an associated test are proposed to det...

New classical r-matrices from integrable non-linear sigma-models

International Nuclear Information System (INIS)

Laartz, J.; Bordemann, M.; Forger, M.; Schaper, U.

1993-01-01

Non-linear sigma models on Riemannian symmetric spaces constitute the most general class of classical non-linear sigma models which are known to be integrable. Using the current algebra structure of these models their canonical structure is analyzed and it is shown that their non-ultralocal fundamental Poisson bracket relation is governed by a field dependent non antisymmetric r-matrix obeying a dynamical Yang Baxter equation. The fundamental Poisson bracket relations and the r-matrix are derived explicitly and a new kind of algebra is found that is supposed to replace the classical Yang Baxter algebra governing the canonical structure of ultralocal models. (Author) 9 refs

Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations

DEFF Research Database (Denmark)

Tornøe, Christoffer Wenzel; Agersø, Henrik; Madsen, Henrik

2004-01-01

The standard software for non-linear mixed-effect analysis of pharmacokinetic/phar-macodynamic (PK/PD) data is NONMEM while the non-linear mixed-effects package NLME is an alternative as tong as the models are fairly simple. We present the nlmeODE package which combines the ordinary differential...... equation (ODE) solver package odesolve and the non-Linear mixed effects package NLME thereby enabling the analysis of complicated systems of ODEs by non-linear mixed-effects modelling. The pharmacokinetics of the anti-asthmatic drug theophylline is used to illustrate the applicability of the nlme...

Matrix algebra for linear models

CERN Document Server

Gruber, Marvin H J

2013-01-01

Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. Matrix Algebra for Linear Models offers readers a unique, unified view of matrix analysis theory (where and when necessary), methods, and their applications. Written f

A gauge model describing N relativistic particles bound by linear forces

International Nuclear Information System (INIS)

Filippov, A.T.

1988-01-01

A relativistic model of N particles bound by linear forces is obtained by applying the gauging procedure to the linear canonical symmteries of a simple (rudimentary) nonrelativistic N-particle Lagrangian extended to relativistic phase space. The new (gauged) Lagrangian is formally Poincare invariant, the Hamiltonian is a linear combination of first-class constraints which are closed with respect to Pisson brackets and generate the localized canonical symmteries. The gauge potentials appear as the Lagrange multipliers of the constraints. Gauge fixing and quantization of the model are also briefly discussed. 11 refs

Specificity of the Linear Array HPV Genotyping Test for detecting human papillomavirus genotype 52 (HPV-52)

OpenAIRE

Kocjan, Boštjan; Poljak, Mario; Oštrbenk, Anja

2015-01-01

Introduction: HPV-52 is one of the most frequent human papillomavirus (HPV) genotypes causing significant cervical pathology. The most widely used HPV genotyping assay, the Roche Linear Array HPV Genotyping Test (Linear Array), is unable to identify HPV- 52 status in samples containing HPV-33, HPV-35, and/or HPV-58. Methods: Linear Array HPV-52 analytical specificity was established by testing 100 specimens reactive with the Linear Array HPV- 33/35/52/58 cross-reactive probe, but not with the...

Mathematical modelling in engineering: A proposal to introduce linear algebra concepts

Directory of Open Access Journals (Sweden)

Andrea Dorila Cárcamo

2016-03-01

Full Text Available The modern dynamic world requires that basic science courses for engineering, including linear algebra, emphasize the development of mathematical abilities primarily associated with modelling and interpreting, which aren´t limited only to calculus abilities. Considering this, an instructional design was elaborated based on mathematic modelling and emerging heuristic models for the construction of specific linear algebra concepts:  span and spanning set. This was applied to first year engineering students. Results suggest that this type of instructional design contributes to the construction of these mathematical concepts and can also favour first year engineering students understanding of key linear algebra concepts and potentiate the development of higher order skills.

Non-linear models for the detection of impaired cerebral blood flow autoregulation.

Science.gov (United States)

Chacón, Max; Jara, José Luis; Miranda, Rodrigo; Katsogridakis, Emmanuel; Panerai, Ronney B

2018-01-01

The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxide and air. Non-linear models with BP as input and CBF velocity (CBFV) as output, were implemented with support vector machines (SVM) using separate recordings for learning and validation. Dynamic SVM implementations used either moving average or autoregressive structures. The efficiency of dynamic CA was estimated from the model's derived CBFV response to a step change in BP as an autoregulation index for both linear and non-linear models. Non-linear models with recurrences (autoregressive) showed the best results, with CA indexes of 5.9 ± 1.5 in normocapnia, and 2.5 ± 1.2 for hypercapnia with an area under the receiver-operator curve of 0.955. The high performance achieved by non-linear SVM models to detect deterioration of dynamic CA should encourage further assessment of its applicability to clinical conditions where CA might be impaired.

Analysis of baseline, average, and longitudinally measured blood pressure data using linear mixed models.

Science.gov (United States)

Hossain, Ahmed; Beyene, Joseph

2014-01-01

This article compares baseline, average, and longitudinal data analysis methods for identifying genetic variants in genome-wide association study using the Genetic Analysis Workshop 18 data. We apply methods that include (a) linear mixed models with baseline measures, (b) random intercept linear mixed models with mean measures outcome, and (c) random intercept linear mixed models with longitudinal measurements. In the linear mixed models, covariates are included as fixed effects, whereas relatedness among individuals is incorporated as the variance-covariance structure of the random effect for the individuals. The overall strategy of applying linear mixed models decorrelate the data is based on Aulchenko et al.'s GRAMMAR. By analyzing systolic and diastolic blood pressure, which are used separately as outcomes, we compare the 3 methods in identifying a known genetic variant that is associated with blood pressure from chromosome 3 and simulated phenotype data. We also analyze the real phenotype data to illustrate the methods. We conclude that the linear mixed model with longitudinal measurements of diastolic blood pressure is the most accurate at identifying the known single-nucleotide polymorphism among the methods, but linear mixed models with baseline measures perform best with systolic blood pressure as the outcome.

Sex Differences in Adolescent Depression: Stress Exposure and Reactivity Models

Science.gov (United States)

Hankin, Benjamin L.; Mermelstein, Robin; Roesch, Linda

2007-01-01

Stress exposure and reactivity models were examined as explanations for why girls exhibit greater levels of depressive symptoms than boys. In a multiwave, longitudinal design, adolescents' depressive symptoms, alcohol usage, and occurrence of stressors were assessed at baseline, 6, and 12 months later (N=538; 54.5% female; ages 13-18, average…

Linear models for joint association and linkage QTL mapping

Directory of Open Access Journals (Sweden)

Fernando Rohan L

2009-09-01

Full Text Available Abstract Background Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure. Results We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission average of the substitution effects of founders' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided. Conclusion The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward.

A non-linear dissipative model of magnetism

Czech Academy of Sciences Publication Activity Database

Durand, P.; Paidarová, Ivana

2010-01-01

Roč. 89, č. 6 (2010), s. 67004 ISSN 1286-4854 R&D Projects: GA AV ČR IAA100400501 Institutional research plan: CEZ:AV0Z40400503 Keywords : non-linear dissipative model of magnetism * thermodynamics * physical chemistry Subject RIV: CF - Physical ; Theoretical Chemistry http://epljournal.edpsciences.org/

Modelling and measurement of a moving magnet linear compressor performance

International Nuclear Information System (INIS)

Liang, Kun; Stone, Richard; Davies, Gareth; Dadd, Mike; Bailey, Paul

2014-01-01

A novel moving magnet linear compressor with clearance seals and flexure bearings has been designed and constructed. It is suitable for a refrigeration system with a compact heat exchanger, such as would be needed for CPU cooling. The performance of the compressor has been experimentally evaluated with nitrogen and a mathematical model has been developed to evaluate the performance of the linear compressor. The results from the compressor model and the measurements have been compared in terms of cylinder pressure, the ‘P–V’ loop, stroke, mass flow rate and shaft power. The cylinder pressure was not measured directly but was derived from the compressor dynamics and the motor magnetic force characteristics. The comparisons indicate that the compressor model is well validated and can be used to study the performance of this type of compressor, to help with design optimization and the identification of key parameters affecting the system transients. The electrical and thermodynamic losses were also investigated, particularly for the design point (stroke of 13 mm and pressure ratio of 3.0), since a full understanding of these can lead to an increase in compressor efficiency. - Highlights: • Model predictions of the performance of a novel moving magnet linear compressor. • Prototype linear compressor performance measurements using nitrogen. • Reconstruction of P–V loops using a model of the dynamics and electromagnetics. • Close agreement between the model and measurements for the P–V loops. • The design point motor efficiency was 74%, with potential improvements identified

A New Approach to Optimal Allocation of Reactive Power Ancillary Service in Distribution Systems in the Presence of Distributed Energy Resources

Directory of Open Access Journals (Sweden)

Abouzar Samimi

2015-11-01

Full Text Available One of the most important Distribution System Operators (DSO schemes addresses the Volt/Var control (VVC problem. Developing a cost-based reactive power dispatch model for distribution systems, in which the reactive powers are appropriately priced, can motivate Distributed Energy Resources (DERs to participate actively in VVC. In this paper, new reactive power cost models for DERs, including synchronous machine-based DGs and wind turbines (WTs, are formulated based on their capability curves. To address VVC in the context of competitive electricity markets in distribution systems, first, in a day-ahead active power market, the initial active power dispatch of generation units is estimated considering environmental and economic aspects. Based on the results of the initial active power dispatch, the proposed VVC model is executed to optimally allocate reactive power support among all providers. Another novelty of this paper lies in the pricing scheme that rewards transformers and capacitors for tap and step changing, respectively, while incorporating the reactive power dispatch model. A Benders decomposition algorithm is employed as a solution method to solve the proposed reactive power dispatch, which is a mixed integer non-linear programming (MINLP problem. Finally, a typical 22-bus distribution network is used to verify the efficiency of the proposed method.

Prediction of minimum temperatures in an alpine region by linear and non-linear post-processing of meteorological models

Directory of Open Access Journals (Sweden)

R. Barbiero

2007-05-01

Full Text Available Model Output Statistics (MOS refers to a method of post-processing the direct outputs of numerical weather prediction (NWP models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511–L60 and LAMI-3. Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself.

A Linear Viscoelastic Model Calibration of Sylgard 184.

Energy Technology Data Exchange (ETDEWEB)

Long, Kevin Nicholas; Brown, Judith Alice

2017-04-01

We calibrate a linear thermoviscoelastic model for solid Sylgard 184 (90-10 formulation), a lightly cross-linked, highly flexible isotropic elastomer for use both in Sierra / Solid Mechanics via the Universal Polymer Model as well as in Sierra / Structural Dynamics (Salinas) for use as an isotropic viscoelastic material. Material inputs for the calibration in both codes are provided. The frequency domain master curve of oscillatory shear was obtained from a report from Los Alamos National Laboratory (LANL). However, because the form of that data is different from the constitutive models in Sierra, we also present the mapping of the LANL data onto Sandia’s constitutive models. Finally, blind predictions of cyclic tension and compression out to moderate strains of 40 and 20% respectively are compared with Sandia’s legacy cure schedule material. Although the strain rate of the data is unknown, the linear thermoviscoelastic model accurately predicts the experiments out to moderate strains for the slower strain rates, which is consistent with the expectation that quasistatic test procedures were likely followed. This good agreement comes despite the different cure schedules between the Sandia and LANL data.

Linearization of the interaction principle: Analytic Jacobians in the 'Radiant' model

International Nuclear Information System (INIS)

Spurr, R.J.D.; Christi, M.J.

2007-01-01

In this paper we present a new linearization of the Radiant radiative transfer model. Radiant uses discrete ordinates for solving the radiative transfer equation in a multiply-scattering anisotropic medium with solar and thermal sources, but employs the adding method (interaction principle) for the stacking of reflection and transmission matrices in a multilayer atmosphere. For the linearization, we show that the entire radiation field is analytically differentiable with respect to any surface or atmospheric parameter for which we require Jacobians (derivatives of the radiance field). Derivatives of the discrete ordinate solutions are based on existing methods developed for the LIDORT radiative transfer models. Linearization of the interaction principle is completely new and constitutes the major theme of the paper. We discuss the application of the Radiant model and its linearization in the Level 2 algorithm for the retrieval of columns of carbon dioxide as the main target of the Orbiting Carbon Observatory (OCO) mission

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

Science.gov (United States)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Linear accelerator modeling: development and application

International Nuclear Information System (INIS)

Jameson, R.A.; Jule, W.D.

1977-01-01

Most of the parameters of a modern linear accelerator can be selected by simulating the desired machine characteristics in a computer code and observing how the parameters affect the beam dynamics. The code PARMILA is used at LAMPF for the low-energy portion of linacs. Collections of particles can be traced with a free choice of input distributions in six-dimensional phase space. Random errors are often included in order to study the tolerances which should be imposed during manufacture or in operation. An outline is given of the modifications made to the model, the results of experiments which indicate the validity of the model, and the use of the model to optimize the longitudinal tuning of the Alvarez linac

Modification of the finite element heat and mass transfer code (FEHMN) to model multicomponent reactive transport

International Nuclear Information System (INIS)

Viswanathan, H.S.

1995-01-01

The finite element code FEHMN is a three-dimensional finite element heat and mass transport simulator that can handle complex stratigraphy and nonlinear processes such as vadose zone flow, heat flow and solute transport. Scientists at LANL have been developed hydrologic flow and transport models of the Yucca Mountain site using FEHMN. Previous FEHMN simulations have used an equivalent K d model to model solute transport. In this thesis, FEHMN is modified making it possible to simulate the transport of a species with a rigorous chemical model. Including the rigorous chemical equations into FEHMN simulations should provide for more representative transport models for highly reactive chemical species. A fully kinetic formulation is chosen for the FEHMN reactive transport model. Several methods are available to computationally implement a fully kinetic formulation. Different numerical algorithms are investigated in order to optimize computational efficiency and memory requirements of the reactive transport model. The best algorithm of those investigated is then incorporated into FEHMN. The algorithm chosen requires for the user to place strongly coupled species into groups which are then solved for simultaneously using FEHMN. The complete reactive transport model is verified over a wide variety of problems and is shown to be working properly. The simulations demonstrate that gas flow and carbonate chemistry can significantly affect 14 C transport at Yucca Mountain. The simulations also provide that the new capabilities of FEHMN can be used to refine and buttress already existing Yucca Mountain radionuclide transport studies

Control Rod Driveline Reactivity Feedback Model for Liquid Metal Reactors

International Nuclear Information System (INIS)

Kwon, Young-Min; Jeong, Hae-Yong; Chang, Won-Pyo; Cho, Chung-Ho; Lee, Yong-Bum

2008-01-01

The thermal expansion of the control rod drivelines (CRDL) is one important passive mitigator under all unprotected accident conditions in the metal and oxide cores. When the CRDL are washed by hot sodium in the coolant outlet plenum, the CRDL thermally expands and causes the control rods to be inserted further down into the active core region, providing a negative reactivity feedback. Since the control rods are attached to the top of the vessel head and the core attaches to the bottom of the reactor vessel (RV), the expansion of the vessel wall as it heats will either lower the core or raise the control rods supports. This contrary thermal expansion of the reactor vessel wall pulls the control rods out of the core somewhat, providing a positive reactivity feedback. However this is not a safety factor early in a transient because its time constant is relatively large. The total elongated length is calculated by subtracting the vessel expansion from the CRDL expansion to determine the net control rod expansion into the core. The system-wide safety analysis code SSC-K includes the CRDL/RV reactivity feedback model in which control rod and vessel expansions are calculated using single-nod temperatures for the vessel and CRDL masses. The KALIMER design has the upper internal structures (UIS) in which the CRDLs are positioned outside the structure where they are exposed to the mixed sodium temperature exiting the core. A new method to determine the CRDL expansion is suggested. Two dimensional hot pool thermal hydraulic model (HP2D) originally developed for the analysis of the stratification phenomena in the hot pool is utilized for a detailed heat transfer between the CRDL mass and the hot pool coolant. However, the reactor vessel wall temperature is still calculated by a simple lumped model

RETRANS, Reactivity Transients in LWR

International Nuclear Information System (INIS)

Kamelander, G.

1989-01-01

1 - Description of program or function: RETRANS is appropriate to calculate power excursions in light water reactors initiated by reactivity insertions due to withdrawal of control elements. As in the code TWIGL, the neutron physics model is based on the time-dependent two-group neutron diffusion equations. The equation of state of the coolant is approximated by a table built into the code. RETRANS solves the heat conduction equation and calculates the heat transfer coefficient for representative fuel rods at each time-step. 2 - Method of solution: The time-dependent neutron diffusion equations are modified by an exponential transformation and solved by means of a finite difference method. There is an option accelerating the inner iterations of the difference scheme by a coarse-mesh re-balancing method. The heat balance equations of the thermo- hydraulic model are discretized and converted into a tri-diagonal system of linear equations which is solved recursively. 3 - Restrictions on the complexity of the problem: r-z-geometry, one- phase-flow

Calculation of reactivity using a finite impulse response filter

Energy Technology Data Exchange (ETDEWEB)

Suescun Diaz, Daniel [COPPE/UFRJ, Programa de Engenharia Nuclear, Caixa Postal 68509, CEP 21941-914, RJ (Brazil); Senra Martinez, Aquilino [COPPE/UFRJ, Programa de Engenharia Nuclear, Caixa Postal 68509, CEP 21941-914, RJ (Brazil)], E-mail: aquilino@lmp.ufrj.br; Carvalho Da Silva, Fernando [COPPE/UFRJ, Programa de Engenharia Nuclear, Caixa Postal 68509, CEP 21941-914, RJ (Brazil)

2008-03-15

A new formulation is presented in this paper to solve the inverse kinetics equation. This method is based on the Laplace transform of the point kinetics equations, resulting in an expression equivalent to the inverse kinetics equation as a function of the power history. Reactivity can be written in terms of the summation of convolution with response to impulse, characteristic of a linear system. For its digital form the Z-transform is used, which is the discrete version of the Laplace transform. This new method of reactivity calculation has very special features, amongst which it can be pointed out that the linear part is characterized by a filter named finite impulse response (FIR). The FIR filter will always be, stable and non-varying in time, and, apart from this, it can be implemented in the non-recursive form. This type of implementation does not require feedback, allowing the calculation of reactivity in a continuous way.

The reasoned/reactive model: A new approach to examining eating decisions among female college dieters and nondieters.

Science.gov (United States)

Ruhl, Holly; Holub, Shayla C; Dolan, Elaine A

2016-12-01

Female college students are prone to unhealthy eating patterns that can impact long-term health. This study examined female students' healthy and unhealthy eating behaviors with three decision-making models. Specifically, the theory of reasoned action, prototype/willingness model, and new reasoned/reactive model were compared to determine how reasoned (logical) and reactive (impulsive) factors relate to dietary decisions. Females (N=583, M age =20.89years) completed measures on reasoned cognitions about foods (attitudes, subjective norms, nutrition knowledge, intentions to eat foods), reactive cognitions about foods (prototypes, affect, willingness to eat foods), dieting, and food consumption. Structural equation modeling (SEM) revealed the new reasoned/reactive model to be the preeminent model for examining eating behaviors. This model showed that attitudes were related to intentions and willingness to eat healthy and unhealthy foods. Affect was related to willingness to eat healthy and unhealthy foods, whereas nutrition knowledge was related to intentions and willingness to eat healthy foods only. Intentions and willingness were related to healthy and unhealthy food consumption. Dieting status played a moderating role in the model and revealed mean-level differences between dieters and nondieters. This study highlights the importance of specific factors in relation to female students' eating decisions and unveils a comprehensive model for examining health behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimal difference-based estimation for partially linear models

KAUST Repository

Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun

2017-01-01

Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.

Optimal difference-based estimation for partially linear models

KAUST Repository

Zhou, Yuejin

2017-12-16

Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.

The minimal linear σ model for the Goldstone Higgs

International Nuclear Information System (INIS)

Feruglio, F.; Gavela, M.B.; Kanshin, K.; Machado, P.A.N.; Rigolin, S.; Saa, S.

2016-01-01

In the context of the minimal SO(5) linear σ-model, a complete renormalizable Lagrangian -including gauge bosons and fermions- is considered, with the symmetry softly broken to SO(4). The scalar sector describes both the electroweak Higgs doublet and the singlet σ. Varying the σ mass would allow to sweep from the regime of perturbative ultraviolet completion to the non-linear one assumed in models in which the Higgs particle is a low-energy remnant of some strong dynamics. We analyze the phenomenological implications and constraints from precision observables and LHC data. Furthermore, we derive the d≤6 effective Lagrangian in the limit of heavy exotic fermions.

FASTREACT – An efficient numerical framework for the solution of reactive transport problems

International Nuclear Information System (INIS)

Trinchero, Paolo; Molinero, Jorge; Román-Ross, Gabriela; Berglund, Sten; Selroos, Jan-Olof

2014-01-01

Highlights: • We present a tool for the efficient solution of reactive transport problems. • The tool is used to simulate radionuclide transport in a two-dimensional medium. • The results are successfully compared with those obtained using an Eulerian approach. • A large-scale application example is also solved. • The results show that the proposed tool can efficiently solve large-scale models. - Abstract: In the framework of safety assessment studies for geological disposal, large scale reactive transport models are powerful inter-disciplinary tools aiming at supporting regulatory decision making as well as providing input to repository engineering activities. Important aspects of these kinds of models are their often very large temporal and spatial modelling scales and the need to integrate different non-linear processes (e.g., mineral dissolution and precipitation, adsorption and desorption, microbial reactions and redox transformations). It turns out that these types of models may be computationally highly demanding. In this work, we present a Lagrangian-based framework, denoted as FASTREACT, that aims at solving multi-component-reactive transport problems with a computationally efficient approach allowing complex modelling problems to be solved in large spatial and temporal scales. The tool has been applied to simulate radionuclide migration in a synthetic heterogeneous transmissivity field and the results have been successfully compared with those obtained using a standard Eulerian approach. Finally, the same geochemical model has been coupled to an ensemble of realistic three-dimensional transport pathways to simulate the migration of a set of radionuclides from a hypothetical repository for spent nuclear fuel to the surface. The results of this modelling exercise, which includes key processes such as the exchange of mass between the conductive fractures and the matrix, show that FASTREACT can efficiently solve large-scale reactive transport models

Reactivity of lignin and lignin models towards UV-assisted peroxide

International Nuclear Information System (INIS)

Sun, Y.P.; Wallis, A.F.A.; Nguyen, K.L.

1997-01-01

The comparative reactivities of a series of guaiacyl and syringyl lignin model compounds and their methylated analogues towards alkaline peroxide and UV-alkaline peroxide were investigated. The overall reaction was followed by monitoring the reduction of the substrate as a function of time, and in every case, the reaction showed pseudo-first-order kinetics. The reaction rates of most lignin models having identical sidechains with alkaline peroxide and with UV-alkaline peroxide were in the order syringyl guaiacyl 3,4,5-trimethoxyphenyl veratryl. Thus phenols react faster than their methyl ethers, and an extra ortho methoxyl group promotes the reaction. Lignin models possessing electron-donating sidechains had generally higher reaction rates than those with electron-withdrawing sidechains. The reaction rates of the series of benzoic acids were 2-4 times higher at pH 11 than at pH 5. UV-peroxide degradation of a eucalypt kraft lignin was faster than that of a pine kraft lignin, and degradation was 1.4-1.6 times faster at pH 11 than at pH 5. The data are consistent with the formation of higher amounts of reactive radicals under alkaline conditions, and aromatic rings with greater electronegativities promoting reactions with the radicals

High-resolution mapping of linear antibody epitopes using ultrahigh-density peptide microarrays

DEFF Research Database (Denmark)

Buus, Søren; Rockberg, Johan; Forsström, Björn

2012-01-01

Antibodies empower numerous important scientific, clinical, diagnostic, and industrial applications. Ideally, the epitope(s) targeted by an antibody should be identified and characterized, thereby establishing antibody reactivity, highlighting possible cross-reactivities, and perhaps even warning...... against unwanted (e.g. autoimmune) reactivities. Antibodies target proteins as either conformational or linear epitopes. The latter are typically probed with peptides, but the cost of peptide screening programs tends to prohibit comprehensive specificity analysis. To perform high-throughput, high......-resolution mapping of linear antibody epitopes, we have used ultrahigh-density peptide microarrays generating several hundred thousand different peptides per array. Using exhaustive length and substitution analysis, we have successfully examined the specificity of a panel of polyclonal antibodies raised against...

Robust estimation for partially linear models with large-dimensional covariates.

Science.gov (United States)

Zhu, LiPing; Li, RunZe; Cui, HengJian

2013-10-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.

Optimization for decision making linear and quadratic models

CERN Document Server

Murty, Katta G

2010-01-01

While maintaining the rigorous linear programming instruction required, Murty's new book is unique in its focus on developing modeling skills to support valid decision-making for complex real world problems, and includes solutions to brand new algorithms.

A note on probabilistic models over strings: the linear algebra approach.

Science.gov (United States)

Bouchard-Côté, Alexandre

2013-12-01

Probabilistic models over strings have played a key role in developing methods that take into consideration indels as phylogenetically informative events. There is an extensive literature on using automata and transducers on phylogenies to do inference on these probabilistic models, in which an important theoretical question is the complexity of computing the normalization of a class of string-valued graphical models. This question has been investigated using tools from combinatorics, dynamic programming, and graph theory, and has practical applications in Bayesian phylogenetics. In this work, we revisit this theoretical question from a different point of view, based on linear algebra. The main contribution is a set of results based on this linear algebra view that facilitate the analysis and design of inference algorithms on string-valued graphical models. As an illustration, we use this method to give a new elementary proof of a known result on the complexity of inference on the "TKF91" model, a well-known probabilistic model over strings. Compared to previous work, our proving method is easier to extend to other models, since it relies on a novel weak condition, triangular transducers, which is easy to establish in practice. The linear algebra view provides a concise way of describing transducer algorithms and their compositions, opens the possibility of transferring fast linear algebra libraries (for example, based on GPUs), as well as low rank matrix approximation methods, to string-valued inference problems.

Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.

Science.gov (United States)

Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko

2016-03-01

In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models.

Science.gov (United States)

Pozo, Carlos; Marín-Sanguino, Alberto; Alves, Rui; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Sorribas, Albert

2011-08-25

Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Directory of Open Access Journals (Sweden)

Sorribas Albert

2011-08-01

Full Text Available Abstract Background Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

Science.gov (United States)

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Thermal chemical-mechanical reactive flow model of shock initiation in solid explosives

International Nuclear Information System (INIS)

Nicholls, A.L. III; Tarver, C.M.

1998-01-01

The three dimensional Arbitrary Lagrange Eulerian hydrodynamic computer code ALE3D with fully coupled thermal-chemical-mechanical material models provides the framework for the development of a physically realistic model of shock initiation and detonation of solid explosives. The processes of hot spot formation during shock compression, subsequent ignition of reaction or failure to react, growth of reaction in individual hot spots, and coalescence of reacting hot spots during the transition to detonation can now be modeled using Arrhenius chemical kinetic rate laws and heat transfer to propagate the reactive flow. This paper discusses the growth rates of reacting hot spots in HMX and TATB and their coalescence during shock to detonation transition. Hot spot deflagration rates are found to be fast enough to consume explosive particles less than 10 mm in diameter during typical shock duration times, but larger particles must fragment and create more reactive surface area in order to be rapidly consumed

Non-linear sigma model on the fuzzy supersphere

International Nuclear Information System (INIS)

Kurkcuoglu, Seckin

2004-01-01

In this note we develop fuzzy versions of the supersymmetric non-linear sigma model on the supersphere S (2,2) . In hep-th/0212133 Bott projectors have been used to obtain the fuzzy C P 1 model. Our approach utilizes the use of supersymmetric extensions of these projectors. Here we obtain these (super)-projectors and quantize them in a fashion similar to the one given in hep-th/0212133. We discuss the interpretation of the resulting model as a finite dimensional matrix model. (author)

Linear and Nonlinear Career Models: Metaphors, Paradigms, and Ideologies.

Science.gov (United States)

Buzzanell, Patrice M.; Goldzwig, Steven R.

1991-01-01

Examines the linear or bureaucratic career models (dominant in career research, metaphors, paradigms, and ideologies) which maintain career myths of flexibility and individualized routes to success in organizations incapable of offering such versatility. Describes nonlinear career models which offer suggestive metaphors for re-visioning careers…

MAGDM linear-programming models with distinct uncertain preference structures.

Science.gov (United States)

Xu, Zeshui S; Chen, Jian

2008-10-01

Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

Linear approximation model network and its formation via ...

Indian Academy of Sciences (India)

niques, an alternative `linear approximation model' (LAM) network approach is .... network is LPV, existing LTI theory is difficult to apply (Kailath 1980). ..... Beck J V, Arnold K J 1977 Parameter estimation in engineering and science (New York: ...

Nonlinearity measure and internal model control based linearization in anti-windup design

Energy Technology Data Exchange (ETDEWEB)

Perev, Kamen [Systems and Control Department, Technical University of Sofia, 8 Cl. Ohridski Blvd., 1756 Sofia (Bulgaria)

2013-12-18

This paper considers the problem of internal model control based linearization in anti-windup design. The nonlinearity measure concept is used for quantifying the control system degree of nonlinearity. The linearizing effect of a modified internal model control structure is presented by comparing the nonlinearity measures of the open-loop and closed-loop systems. It is shown that the linearization properties are improved by increasing the control system local feedback gain. However, it is emphasized that at the same time the stability of the system deteriorates. The conflicting goals of stability and linearization are resolved by solving the design problem in different frequency ranges.

Dynamic generalized linear models for monitoring endemic diseases

DEFF Research Database (Denmark)

Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq

2016-01-01

The objective was to use a Dynamic Generalized Linear Model (DGLM) based on abinomial distribution with a linear trend, for monitoring the PRRS (Porcine Reproductive and Respiratory Syndrome sero-prevalence in Danish swine herds. The DGLM was described and its performance for monitoring control...... and eradication programmes based on changes in PRRS sero-prevalence was explored. Results showed a declining trend in PRRS sero-prevalence between 2007 and 2014 suggesting that Danish herds are slowly eradicating PRRS. The simulation study demonstrated the flexibility of DGLMs in adapting to changes intrends...... in sero-prevalence. Based on this, it was possible to detect variations in the growth model component. This study is a proof-of-concept, demonstrating the use of DGLMs for monitoring endemic diseases. In addition, the principles stated might be useful in general research on monitoring and surveillance...

Ajuste de modelos estocásticos lineares e não-lineares para a descrição do perfil longitudinal de árvores Fitting linear and nonlinear stochastic models to describe longitudinal tree profile

Directory of Open Access Journals (Sweden)

Leonardo Machado Pires

2007-10-01

Full Text Available Os modelos polinomiais são mais difundidos no meio florestal brasileiro na descrição do perfil de árvores devido à sua facilidade de ajuste e precisão. O mesmo não ocorre com os modelos não-lineares, os quais possuem maior dificuldade de ajuste. Dentre os modelos não-lineares clássicos, na descrição do perfil, podem-se citar o de Gompertz, o Logístico e o de Weibull. Portanto, este estudo visou comparar os modelos lineares e não lineares para a descrição do perfil de árvores. As medidas de comparação foram o coeficiente de determinação (R², o erro-padrão residual (s yx, o coeficiente de determinação corrigido (R²ajustado, o gráfico dos resíduos e a facilidade de ajuste. Os resultados ressaltaram que, dentre os modelos não-lineares, o que obteve melhor desempenho, de forma geral, foi o modelo Logístico, apesar de o modelo de Gompertz ser melhor em termos de erro-padrão residual. Nos modelos lineares, o polinômio proposto por Pires & Calegario foi superior aos demais. Ao comparar os modelos não-lineares com os lineares, o modelo Logístico foi melhor em razão, principalmente, do fato de o comportamento dos dados ser não-linear, à baixa correlação entre os parâmetros e à fácil interpretação deles, facilitando a convergência e o ajuste.Polynomial models are most commonly used in Brazilian forestry for taper modeling due to its straightforwardly fitting and precision. The use of nonlinear regression classic models, like Gompertz, Logistic and Weibull, is not very common in Brazil. Therefore, this study aimed to verify the best nonlinear and linear models, and among these the best model to describe the longitudinal tree profile. The comparison measures were: R², syx, R²adjusted, residual graphics and fitting convergence. The results pointed out that among the non-linear models the best behavior, in general, was given by the Logistic model, although the Gompertz model was superior compared with the Weibull

Digital reactivity meter

International Nuclear Information System (INIS)

Copie, M.; Valantic, B.

1978-01-01

Digital reactivity meters (DRM) are mostly used as measuring instruments, e.g. for calibration of control rods, and there are only a few cases of their incorporation into the control systems of the reactors. To move in this direction there is more development work needed. First of all, fast algorithms are needed for inverse kinetics equations to relieve the computer for more important tasks of reactor model solving in real time. The next problem, currently under investigation, is the incorporation of the reactor thermal-hydraulic model into the DRM so that it can be used in the power range. Such an extension of DHM allows presentation not only of the instantaneous reactivity of the system, but also the inserted reactivity can be estimated from the temperature reactivity feed-backs. One of the applications of this concept is the anomalous digital reactivity monitor (ADRN) as part of the reactor protection system. As a solution of the first problem, a fast algorithm for solving the inverse kinetics equations has been implemented in the off-line program RODCAL on CDC 1700 computer and tested for its accuracy by performing different control rod calibrations on the reactor TRIGA

A non-linear model of information seeking behaviour

Directory of Open Access Journals (Sweden)

Allen E. Foster

2005-01-01

Full Text Available The results of a qualitative, naturalistic, study of information seeking behaviour are reported in this paper. The study applied the methods recommended by Lincoln and Guba for maximising credibility, transferability, dependability, and confirmability in data collection and analysis. Sampling combined purposive and snowball methods, and led to a final sample of 45 inter-disciplinary researchers from the University of Sheffield. In-depth semi-structured interviews were used to elicit detailed examples of information seeking. Coding of interview transcripts took place in multiple iterations over time and used Atlas-ti software to support the process. The results of the study are represented in a non-linear Model of Information Seeking Behaviour. The model describes three core processes (Opening, Orientation, and Consolidation and three levels of contextual interaction (Internal Context, External Context, and Cognitive Approach, each composed of several individual activities and attributes. The interactivity and shifts described by the model show information seeking to be non-linear, dynamic, holistic, and flowing. The paper concludes by describing the whole model of behaviours as analogous to an artist's palette, in which activities remain available throughout information seeking. A summary of key implications of the model and directions for further research are included.

Non-Linear Transmission Line (NLTL) Microwave Source Lecture Notes the United States Particle Accelerator School

Energy Technology Data Exchange (ETDEWEB)

Russell, Steven J. [Los Alamos National Laboratory; Carlsten, Bruce E. [Los Alamos National Laboratory

2012-06-26

We will quickly go through the history of the non-linear transmission lines (NLTLs). We will describe how they work, how they are modeled and how they are designed. Note that the field of high power, NLTL microwave sources is still under development, so this is just a snap shot of their current state. Topics discussed are: (1) Introduction to solitons and the KdV equation; (2) The lumped element non-linear transmission line; (3) Solution of the KdV equation; (4) Non-linear transmission lines at microwave frequencies; (5) Numerical methods for NLTL analysis; (6) Unipolar versus bipolar input; (7) High power NLTL pioneers; (8) Resistive versus reactive load; (9) Non-lineaer dielectrics; and (10) Effect of losses.

A quantitative analysis of instabilities in the linear chiral sigma model

International Nuclear Information System (INIS)

Nemes, M.C.; Nielsen, M.; Oliveira, M.M. de; Providencia, J. da

1990-08-01

We present a method to construct a complete set of stationary states corresponding to small amplitude motion which naturally includes the continuum solution. The energy wheighted sum rule (EWSR) is shown to provide for a quantitative criterium on the importance of instabilities which is known to occur in nonasymptotically free theories. Out results for the linear σ model showed be valid for a large class of models. A unified description of baryon and meson properties in terms of the linear σ model is also given. (author)

Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility

International Nuclear Information System (INIS)

Heydari, Somayeh; Siddiqui, Afzal

2010-01-01

Energy prices are often highly volatile with unexpected spikes. Capturing these sudden spikes may lead to more informed decision-making in energy investments, such as valuing gas-fired power plants, than ignoring them. In this paper, non-linear regime-switching models and models with mean-reverting stochastic volatility are compared with ordinary linear models. The study is performed using UK electricity and natural gas daily spot prices and suggests that with the aim of valuing a gas-fired power plant with and without operational flexibility, non-linear models with stochastic volatility, specifically for logarithms of electricity prices, provide better out-of-sample forecasts than both linear models and regime-switching models.

Linear mixed models a practical guide using statistical software

CERN Document Server

West, Brady T; Galecki, Andrzej T

2014-01-01

Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...

Application of the simplex method of linear programming model to ...

African Journals Online (AJOL)

This work discussed how the simplex method of linear programming could be used to maximize the profit of any business firm using Saclux Paint Company as a case study. It equally elucidated the effect variation in the optimal result obtained from linear programming model, will have on any given firm. It was demonstrated ...

Electron Model of Linear-Field FFAG

CERN Document Server

Koscielniak, Shane R

2005-01-01

A fixed-field alternating-gradient accelerator (FFAG) that employs only linear-field elements ushers in a new regime in accelerator design and dynamics. The linear-field machine has the ability to compact an unprecedented range in momenta within a small component aperture. With a tune variation which results from the natural chromaticity, the beam crosses many strong, uncorrec-table, betatron resonances during acceleration. Further, relativistic particles in this machine exhibit a quasi-parabolic time-of-flight that cannot be addressed with a fixed-frequency rf system. This leads to a new concept of bucketless acceleration within a rotation manifold. With a large energy jump per cell, there is possibly strong synchro-betatron coupling. A few-MeV electron model has been proposed to demonstrate the feasibility of these untested acceleration features and to investigate them at length under a wide range of operating conditions. This paper presents a lattice optimized for a 1.3 GHz rf, initial technology choices f...

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.

Effect of linear and non-linear blade modelling techniques on simulated fatigue and extreme loads using Bladed

Science.gov (United States)

Beardsell, Alec; Collier, William; Han, Tao

2016-09-01

There is a trend in the wind industry towards ever larger and more flexible turbine blades. Blade tip deflections in modern blades now commonly exceed 10% of blade length. Historically, the dynamic response of wind turbine blades has been analysed using linear models of blade deflection which include the assumption of small deflections. For modern flexible blades, this assumption is becoming less valid. In order to continue to simulate dynamic turbine performance accurately, routine use of non-linear models of blade deflection may be required. This can be achieved by representing the blade as a connected series of individual flexible linear bodies - referred to in this paper as the multi-part approach. In this paper, Bladed is used to compare load predictions using single-part and multi-part blade models for several turbines. The study examines the impact on fatigue and extreme loads and blade deflection through reduced sets of load calculations based on IEC 61400-1 ed. 3. Damage equivalent load changes of up to 16% and extreme load changes of up to 29% are observed at some turbine load locations. It is found that there is no general pattern in the loading differences observed between single-part and multi-part blade models. Rather, changes in fatigue and extreme loads with a multi-part blade model depend on the characteristics of the individual turbine and blade. Key underlying causes of damage equivalent load change are identified as differences in edgewise- torsional coupling between the multi-part and single-part models, and increased edgewise rotor mode damping in the multi-part model. Similarly, a causal link is identified between torsional blade dynamics and changes in ultimate load results.

A linear solvation energy relationship study for the reactivity of 2-substituted cyclohex-1-enecarboxylic and 2-substituted benzoic acids with diazodiphenylmethane in aprotic and protic solvents

Directory of Open Access Journals (Sweden)

JASMINA B. NIKOLIC

2007-12-01

Full Text Available The rate constants for the reaction of 2-substituted cyclohex-1-enylcarboxylic acids and the corresponding 2-substituted benzoic acids with diazodiphenyl methane were determined in various aprotic solvents at 30 ºC. In order to explain the kinetic results through solvent effects, the second order rate constants of the reaction of the examined acids were correlated using the Kamlet–Taft solvatechromic equation. The correlations of the kinetic data were carried out by means of multiple linear regression analysis and the solvent effects on the reaction rates were analyzed in terms of the contributions of the initial and transition state. The signs of the equation coefficients support the proposed reaction mechanism. The quantitative relationship between the molecular structure and the chemical reactivity is discussed, as well as the effect of geometry on the reactivity of the examined molecules.

The low-energy constants of the extended linear sigma model

Energy Technology Data Exchange (ETDEWEB)

Divotgey, Florian; Giacosa, Francesco; Kovacs, Peter; Rischke, Dirk H. [Institut fuer Theoretische Physik, Goethe-Universitaet Frankfurt am Main (Germany)

2016-07-01

The low-energy dynamics of Quantum Chromodynamics (QCD) is fully determined by the interactions of the (pseudo-) Nambu-Goldstone bosons of spontaneous chiral symmetry breaking, i.e., for two quark flavors, the pions. Pion dynamics is described by the low-energy effective theory of QCD, chiral perturbation theory (ChPT), which is based on the nonlinear realization of chiral symmetry. An alternative description is provided by the Linear Sigma Model, where chiral symmetry is linearly realized. An extended version of this model, the so-called extended Linear Sigma Model (eLSM) was recently developed which incorporates all J{sup P}=0{sup ±}, 1{sup ±} anti qq mesons up to 2 GeV in mass. A fit of the coupling constants of this model to experimentally measured masses and decay widths has a surprisingly good quality. In this talk, it is demonstrated that the low-energy limit of the eLSM, obtained by integrating out all fields which are heavier than the pions, assumes the same form as ChPT. Moreover, the low-energy constants (LECs) of the eLSM agree with those of ChPT.

Non Linear Modelling and Control of Hydraulic Actuators

Directory of Open Access Journals (Sweden)

B. Šulc

2002-01-01

Full Text Available This paper deals with non-linear modelling and control of a differential hydraulic actuator. The nonlinear state space equations are derived from basic physical laws. They are more powerful than the transfer function in the case of linear models, and they allow the application of an object oriented approach in simulation programs. The effects of all friction forces (static, Coulomb and viscous have been modelled, and many phenomena that are usually neglected are taken into account, e.g., the static term of friction, the leakage between the two chambers and external space. Proportional Differential (PD and Fuzzy Logic Controllers (FLC have been applied in order to make a comparison by means of simulation. Simulation is performed using Matlab/Simulink, and some of the results are compared graphically. FLC is tuned in a such way that it produces a constant control signal close to its maximum (or minimum, where possible. In the case of PD control the occurrence of peaks cannot be avoided. These peaks produce a very high velocity that oversteps the allowed values.

Artificial Neural Network versus Linear Models Forecasting Doha Stock Market

Science.gov (United States)

Yousif, Adil; Elfaki, Faiz

2017-12-01

The purpose of this study is to determine the instability of Doha stock market and develop forecasting models. Linear time series models are used and compared with a nonlinear Artificial Neural Network (ANN) namely Multilayer Perceptron (MLP) Technique. It aims to establish the best useful model based on daily and monthly data which are collected from Qatar exchange for the period starting from January 2007 to January 2015. Proposed models are for the general index of Qatar stock exchange and also for the usages in other several sectors. With the help of these models, Doha stock market index and other various sectors were predicted. The study was conducted by using various time series techniques to study and analyze data trend in producing appropriate results. After applying several models, such as: Quadratic trend model, double exponential smoothing model, and ARIMA, it was concluded that ARIMA (2,2) was the most suitable linear model for the daily general index. However, ANN model was found to be more accurate than time series models.

Modelling reactive transport in a phosphogypsum dump, Venezia, Italia

Science.gov (United States)

Calcara, Massimo; Borgia, Andrea; Cattaneo, Laura; Bartolo, Sergio; Clemente, Gianni; Glauco Amoroso, Carlo; Lo Re, Fabio; Tozzato, Elena

2013-04-01

We develop a reactive-transport porous media flow model for a phosphogypsum dump located on the intertidal deposits of the Venetian Lagoon: 1. we construct a complex conceptual and geologic model from field data using the GMS™ graphical user interface; 2. the geological model is mapped onto a rectangular MODFLOW grid; 3. using the TMT2 FORTRAN90 code we translate this grid into the MESH, INCON and GENER input files for the TOUGH2 series of codes; 4. we run TOUGH-REACT to model flow and reactive transport in the dump and the sediments below it. The model includes 3 different dump materials (phosphogypsum, bituminous and hazardous wastes) with the pores saturated by specific fluids. The sediments below the dump are formed by an intertidal sequence of calcareous sands and silts, in addition to clays and organic deposits, all of which are initially saturated with lagoon salty waters. The recharge rain-water dilutes the dump fluids. In turn, the percolates from the dump react with the underlying sediments and the sea water that saturates them. Simulation results have been compared with chemical sampled analyses. In fact, in spite of the simplicity of our model we are able to show how the pH becomes neutral at a short distance below the dump, a fact observed during aquifer monitoring. The spatial and temporal evolution of dissolution and precipitation reactions occur in our model much alike reality. Mobility of some elements, such as divalent iron, are reduced by specific and concurrent conditions of pH from near-neutrality to moderately high values and positive redox potential; opposite conditions favour mobility of potentially toxic metals such as Cr, As Cd and Pb. Vertical movement are predominant. Trend should be therefore heavily influenced by pH and Eh values. If conditions are favourable to mobility, concentration of these substances in the bottom strata could be high. However, simulation suggest that the sediments tend to reduce the transport potential of

Unification of three linear models for the transient visual system

NARCIS (Netherlands)

Brinker, den A.C.

1989-01-01

Three different linear filters are considered as a model describing the experimentally determined triphasic impulse responses of discs. These impulse responses arc associated with the transient visual system. Each model reveals a different feature of the system. Unification of the models is

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

New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

Science.gov (United States)

Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

2017-06-21

We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

A Detailed Analytical Study of Non-Linear Semiconductor Device Modelling

Directory of Open Access Journals (Sweden)

Umesh Kumar

1995-01-01

junction diode have been developed. The results of computer simulated examples have been presented in each case. The non-linear lumped model for Gunn is a unified model as it describes the diffusion effects as the-domain traves from cathode to anode. An additional feature of this model is that it describes the domain extinction and nucleation phenomena in Gunn dioder with the help of a simple timing circuit. The non-linear lumped model for SCR is general and is valid under any mode of operation in any circuit environment. The memristive circuit model for p-n junction diodes is capable of simulating realistically the diode’s dynamic behavior under reverse, forward and sinusiodal operating modes. The model uses memristor, the charge-controlled resistor to mimic various second-order effects due to conductivity modulation. It is found that both storage time and fall time of the diode can be accurately predicted.

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

Science.gov (United States)

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Separation-induced boundary layer transition: Modeling with a non-linear eddy-viscosity model coupled with the laminar kinetic energy equation

International Nuclear Information System (INIS)

Vlahostergios, Z.; Yakinthos, K.; Goulas, A.

2009-01-01

We present an effort to model the separation-induced transition on a flat plate with a semi-circular leading edge, using a cubic non-linear eddy-viscosity model combined with the laminar kinetic energy. A non-linear model, compared to a linear one, has the advantage to resolve the anisotropic behavior of the Reynolds-stresses in the near-wall region and it provides a more accurate expression for the generation of turbulence in the transport equation of the turbulence kinetic energy. Although in its original formulation the model is not able to accurately predict the separation-induced transition, the inclusion of the laminar kinetic energy increases its accuracy. The adoption of the laminar kinetic energy by the non-linear model is presented in detail, together with some additional modifications required for the adaption of the laminar kinetic energy into the basic concepts of the non-linear eddy-viscosity model. The computational results using the proposed combined model are shown together with the ones obtained using an isotropic linear eddy-viscosity model, which adopts also the laminar kinetic energy concept and in comparison with the existing experimental data.

Modelling non-linear effects of dark energy

Science.gov (United States)

Bose, Benjamin; Baldi, Marco; Pourtsidou, Alkistis

2018-04-01

We investigate the capabilities of perturbation theory in capturing non-linear effects of dark energy. We test constant and evolving w models, as well as models involving momentum exchange between dark energy and dark matter. Specifically, we compare perturbative predictions at 1-loop level against N-body results for four non-standard equations of state as well as varying degrees of momentum exchange between dark energy and dark matter. The interaction is modelled phenomenologically using a time dependent drag term in the Euler equation. We make comparisons at the level of the matter power spectrum and the redshift space monopole and quadrupole. The multipoles are modelled using the Taruya, Nishimichi and Saito (TNS) redshift space spectrum. We find perturbation theory does very well in capturing non-linear effects coming from dark sector interaction. We isolate and quantify the 1-loop contribution coming from the interaction and from the non-standard equation of state. We find the interaction parameter ξ amplifies scale dependent signatures in the range of scales considered. Non-standard equations of state also give scale dependent signatures within this same regime. In redshift space the match with N-body is improved at smaller scales by the addition of the TNS free parameter σv. To quantify the importance of modelling the interaction, we create mock data sets for varying values of ξ using perturbation theory. This data is given errors typical of Stage IV surveys. We then perform a likelihood analysis using the first two multipoles on these sets and a ξ=0 modelling, ignoring the interaction. We find the fiducial growth parameter f is generally recovered even for very large values of ξ both at z=0.5 and z=1. The ξ=0 modelling is most biased in its estimation of f for the phantom w=‑1.1 case.

Generalized linear mixed models modern concepts, methods and applications

CERN Document Server

Stroup, Walter W

2012-01-01

PART I The Big PictureModeling BasicsWhat Is a Model?Two Model Forms: Model Equation and Probability DistributionTypes of Model EffectsWriting Models in Matrix FormSummary: Essential Elements for a Complete Statement of the ModelDesign MattersIntroductory Ideas for Translating Design and Objectives into ModelsDescribing ""Data Architecture"" to Facilitate Model SpecificationFrom Plot Plan to Linear PredictorDistribution MattersMore Complex Example: Multiple Factors with Different Units of ReplicationSetting the StageGoals for Inference with Models: OverviewBasic Tools of InferenceIssue I: Data

Wavefront Sensing for WFIRST with a Linear Optical Model

Science.gov (United States)

Jurling, Alden S.; Content, David A.

2012-01-01

In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.

Application of semi-empirical modeling and non-linear regression to unfolding fast neutron spectra from integral reaction rate data

International Nuclear Information System (INIS)

Harker, Y.D.

1976-01-01

A semi-empirical analytical expression representing a fast reactor neutron spectrum has been developed. This expression was used in a non-linear regression computer routine to obtain from measured multiple foil integral reaction data the neutron spectrum inside the Coupled Fast Reactivity Measurement Facility. In this application six parameters in the analytical expression for neutron spectrum were adjusted in the non-linear fitting process to maximize consistency between calculated and measured integral reaction rates for a set of 15 dosimetry detector foils. In two-thirds of the observations the calculated integral agreed with its respective measured value to within the experimental standard deviation, and in all but one case agreement within two standard deviations was obtained. Based on this quality of fit the estimated 70 to 75 percent confidence intervals for the derived spectrum are 10 to 20 percent for the energy range 100 eV to 1 MeV, 10 to 50 percent for 1 MeV to 10 MeV and 50 to 90 percent for 10 MeV to 18 MeV. The analytical model has demonstrated a flexibility to describe salient features of neutron spectra of the fast reactor type. The use of regression analysis with this model has produced a stable method to derive neutron spectra from a limited amount of integral data

Heterotic non-linear sigma models with anti-de Sitter target spaces

International Nuclear Information System (INIS)

Michalogiorgakis, Georgios; Gubser, Steven S.

2006-01-01

We calculate the beta function of non-linear sigma models with S D+1 and AdS D+1 target spaces in a 1/D expansion up to order 1/D 2 and to all orders in α ' . This beta function encodes partial information about the spacetime effective action for the heterotic string to all orders in α ' . We argue that a zero of the beta function, corresponding to a worldsheet CFT with AdS D+1 target space, arises from competition between the one-loop and higher-loop terms, similarly to the bosonic and supersymmetric cases studied previously in [J.J. Friess, S.S. Gubser, Non-linear sigma models with anti-de Sitter target spaces, Nucl. Phys. B 750 (2006) 111-141]. Various critical exponents of the non-linear sigma model are calculated, and checks of the calculation are presented

Non Linear signa models probing the string structure

International Nuclear Information System (INIS)

Abdalla, E.

1987-01-01

The introduction of a term depending on the extrinsic curvature to the string action, and related non linear sigma models defined on a symmetric space SO(D)/SO(2) x SO(d-2) is descussed . Coupling to fermions are also treated. (author) [pt

Weighted functional linear regression models for gene-based association analysis.

Science.gov (United States)

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

Distinguishing Environment and System in Coloured Petri Net Models of Reactive Systems

DEFF Research Database (Denmark)

Tjell, Simon

2007-01-01

This paper introduces and formally defines the environment-and-system-partitioned property for behavioral models of reactive systems expressed in the formal modeling language Coloured Petri Net. The purpose of the formalization is to make it possible to automatically validate any CPN model...... with respect to this property based on structural analysis. A model has the environment-and-system-partitioned property if it is based on a clear division between environment and system. This division is important in many model-driven approaches to software development such as model-based testing and automated...

REDUCING UNCERTAINTIES IN MODEL PREDICTIONS VIA HISTORY MATCHING OF CO2 MIGRATION AND REACTIVE TRANSPORT MODELING OF CO2 FATE AT THE SLEIPNER PROJECT

Energy Technology Data Exchange (ETDEWEB)

Zhu, Chen

2015-03-31

An important question for the Carbon Capture, Storage, and Utility program is “can we adequately predict the CO2 plume migration?” For tracking CO2 plume development, the Sleipner project in the Norwegian North Sea provides more time-lapse seismic monitoring data than any other sites, but significant uncertainties still exist for some of the reservoir parameters. In Part I, we assessed model uncertainties by applying two multi-phase compositional simulators to the Sleipner Benchmark model for the uppermost layer (Layer 9) of the Utsira Sand and calibrated our model against the time-lapsed seismic monitoring data for the site from 1999 to 2010. Approximate match with the observed plume was achieved by introducing lateral permeability anisotropy, adding CH4 into the CO2 stream, and adjusting the reservoir temperatures. Model-predicted gas saturation, CO2 accumulation thickness, and CO2 solubility in brine—none were used as calibration metrics—were all comparable with the interpretations of the seismic data in the literature. In Part II & III, we evaluated the uncertainties of predicted long-term CO2 fate up to 10,000 years, due to uncertain reaction kinetics. Under four scenarios of the kinetic rate laws, the temporal and spatial evolution of CO2 partitioning into the four trapping mechanisms (hydrodynamic/structural, solubility, residual/capillary, and mineral) was simulated with ToughReact, taking into account the CO2-brine-rock reactions and the multi-phase reactive flow and mass transport. Modeling results show that different rate laws for mineral dissolution and precipitation reactions resulted in different predicted amounts of trapped CO2 by carbonate minerals, with scenarios of the conventional linear rate law for feldspar dissolution having twice as much mineral trapping (21% of the injected CO2) as scenarios with a Burch-type or Alekseyev et al.–type rate law for feldspar dissolution (11%). So far, most reactive transport modeling (RTM) studies for

Optical linear algebra processors - Noise and error-source modeling

Science.gov (United States)

Casasent, D.; Ghosh, A.

1985-01-01

The modeling of system and component noise and error sources in optical linear algebra processors (OLAPs) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.

Optical linear algebra processors: noise and error-source modeling.

Science.gov (United States)

Casasent, D; Ghosh, A

1985-06-01

The modeling of system and component noise and error sources in optical linear algebra processors (OLAP's) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.

OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

Science.gov (United States)

Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

2012-01-01

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation

Energy Technology Data Exchange (ETDEWEB)

Wu, Y.; Ajo-Franklin, J.B.; Spycher, N.; Hubbard, S.S.; Zhang, G.; Williams, K.H.; Taylor, J.; Fujita, Y.; Smith, R.

2011-07-15

Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH{sub 4}{sup

Risk evaluations of aging phenomena: The linear aging reliability model and its extensions

International Nuclear Information System (INIS)

Vesely, W.E.; Wolford, A.J.

1988-01-01

A model for component failure rates due to aging mechanisms is developed from basic phenomenological considerations. In the treatment, the occurrences of deterioration are modeled as following a Poisson process. The severity of damage is allowed to have any distribution, however the damage is assumed to accumulate independently. Finally, the failure rate is modeled as being proportional to the accumulated damage. Using this treatment, the linear aging failure rate model is obtained. The applicability of the linear aging model to various mechanisms is discussed. Extensions of the model to cover nonlinear and dependent aging phenomena are also described. The implementability of the linear aging model is demonstrated by applying it to the aging data collected in the U.S. NRC Nuclear Plant Aging Research (NPAR) Program. (orig./HP)

Using Quartile-Quartile Lines as Linear Models

Science.gov (United States)

Gordon, Sheldon P.

2015-01-01

This article introduces the notion of the quartile-quartile line as an alternative to the regression line and the median-median line to produce a linear model based on a set of data. It is based on using the first and third quartiles of a set of (x, y) data. Dynamic spreadsheets are used as exploratory tools to compare the different approaches and…

Modification of the finite element heat and mass transfer code (FEHM) to model multicomponent reactive transport

International Nuclear Information System (INIS)

Viswanathan, H.S.

1996-08-01

The finite element code FEHMN, developed by scientists at Los Alamos National Laboratory (LANL), is a three-dimensional finite element heat and mass transport simulator that can handle complex stratigraphy and nonlinear processes such as vadose zone flow, heat flow and solute transport. Scientists at LANL have been developing hydrologic flow and transport models of the Yucca Mountain site using FEHMN. Previous FEHMN simulations have used an equivalent Kd model to model solute transport. In this thesis, FEHMN is modified making it possible to simulate the transport of a species with a rigorous chemical model. Including the rigorous chemical equations into FEHMN simulations should provide for more representative transport models for highly reactive chemical species. A fully kinetic formulation is chosen for the FEHMN reactive transport model. Several methods are available to computationally implement a fully kinetic formulation. Different numerical algorithms are investigated in order to optimize computational efficiency and memory requirements of the reactive transport model. The best algorithm of those investigated is then incorporated into FEHMN. The algorithm chosen requires for the user to place strongly coupled species into groups which are then solved for simultaneously using FEHMN. The complete reactive transport model is verified over a wide variety of problems and is shown to be working properly. The new chemical capabilities of FEHMN are illustrated by using Los Alamos National Laboratory's site scale model of Yucca Mountain to model two-dimensional, vadose zone 14 C transport. The simulations demonstrate that gas flow and carbonate chemistry can significantly affect 14 C transport at Yucca Mountain. The simulations also prove that the new capabilities of FEHMN can be used to refine and buttress already existing Yucca Mountain radionuclide transport studies

Modelization of reactive transport: application to the dedolomitization (Institut del Ciencies de la Tierr, CSIC, Barcelona (ES))

International Nuclear Information System (INIS)

Ayora, C.; Taberner, C.; Samper, J.

1994-01-01

The replacement of dolomite with calcite (dedolomization) has been analyzed by means of two numerical models of reactive transport. The results of successive calculations under different scenarios have been compared with the observations made on the dedolomites developed on the Triassic strata from Prades (Tarragona, Spain). The model based on the local equilibrium assumption for water-rock interaction does not predict the development of the porosity associated to the replacement. The model based on kinetic laws for mineral dissolution and precipitation does predict the observed proportions of calcite, dolomite and porosity. The result of modeling under kinetic laws is sensitive to parameters such as the flow velocity, the chemical composition of the recharge water and the reactive surface of the minerals. The replacement and associated porosity is only formed for infiltration flows higher than 100 mm/year. The water has a neutral to slightly alkaline pH, far from equilibrium with carbonates and the atmosphere. The calcium concentrations must be one order of magnitude higher the average of surficial waters, probably due to sulfate dissolution. The reactive surface of dolomite has been estimated from a simple geometric model of fractures, whereas that of calcite has been inferred from calculations based on nucleation and crystal growth theory. The reactive surface of calcite appears to be several orders of magnitude lower than that of dolomite, in agreement with what is required for reactive transport calculations to generate porosity. The dedolomization and associated porosity takes place in the first meter of aquifers, whereas downstream the replacement vanishes and does not create porosity

Real-Time Reactive Power Distribution in Microgrids by Dynamic Programing

DEFF Research Database (Denmark)

Levron, Yoash; Beck, Yuval; Katzir, Liran

2017-01-01

In this paper a new real-time optimization method for reactive power distribution in microgrids is proposed. The method enables location of a globally optimal distribution of reactive power under normal operating conditions. The method exploits the typical compact structure of microgrids to obtain...... combination of reactive powers, by means of dynamic programming. Since every single step involves a one-dimensional problem, the complexity of the solution is only linear with the number of clusters, and as a result, a globally optimal solution may be obtained in real time. The paper includes the results...

Technical note: A linear model for predicting δ13 Cprotein.

Science.gov (United States)

Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M

2015-08-01

Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2)  = 0.86, P analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.

Comparison of the SASSYS/SAS4A radial core expansion reactivity feedback model and the empirical correlation for FFTF

International Nuclear Information System (INIS)

Wigeland, R.A.

1987-01-01

The present emphasis on inherent safety for LMR designs has resulted in a need to represent the various reactivity feedback mechanisms as accurately as possible. The dominant negative reactivity feedback has been found to result from radial expansion of the core for most postulated ATWS events. For this reason, a more detailed model for calculating the reactivity feedback from radial core expansion has been recently developed for use with the SASSYS/SAS4A Code System. The purpose of this summary is to present an extension to the model so that it is more suitable for handling a core restraint design as used in FFTF, and to compare the SASSYS/SAS4A results using this model to the empirical correlation presently being used to account for radial core expansion reactivity feedback to FFTF

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DEFF Research Database (Denmark)

Ding, Tao; Li, Cheng; Huang, Can

2018-01-01

–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

The Predictive Effect of Big Five Factor Model on Social Reactivity ...

African Journals Online (AJOL)

The study tested a model of providing a predictive explanation of Big Five Factor on social reactivity among secondary school adolescents of Cross River State, Nigeria. A sample of 200 students randomly selected across 12 public secondary schools in the State participated in the study (120 male and 80 female). Data ...

Increased airway reactivity in a neonatal mouse model of Continuous Positive Airway Pressure (CPAP)

Science.gov (United States)

Mayer, Catherine A.; Martin, Richard J.; MacFarlane, Peter M.

2015-01-01

Background Continuous positive airway pressure (CPAP) is a primary form of respiratory support used in the intensive care of preterm infants, but its long-term effects on airway (AW) function are unknown. Methods We developed a neonatal mouse model of CPAP treatment to determine whether it modifies later AW reactivity. Un-anesthetized spontaneously breathing mice were fitted with a mask to deliver CPAP (6cmH2O, 3hrs/day) for 7 consecutive days starting at postnatal day 1. Airway reactivity to methacholine was assessed using the in vitro living lung slice preparation. Results One week of CPAP increased AW responsiveness to methacholine in male, but not female mice, compared to untreated control animals. The AW hyper-reactivity of male mice persisted for 2 weeks (at P21) after CPAP treatment ended. 4 days of CPAP, however, did not significantly increase AW reactivity. Females also exhibited AW hyper-reactivity at P21, suggesting a delayed response to early (7 days) CPAP treatment. The effects of 7 days of CPAP on hyper-reactivity to methacholine were unique to smaller AWs whereas larger ones were relatively unaffected. Conclusion These data may be important to our understanding of the potential long-term consequences of neonatal CPAP therapy used in the intensive care of preterm infants. PMID:25950451

Generalized linear longitudinal mixed models with linear covariance structure and multiplicative random effects

DEFF Research Database (Denmark)

Holst, René; Jørgensen, Bent

2015-01-01

The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains...... a marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids...... the multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish....