Transport coefficient computation based on input/output reduced order models

Science.gov (United States)

Hurst, Joshua L.

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

Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

Science.gov (United States)

Qi, D.; Majda, A.

2017-12-01

A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with

Robust simulation of buckled structures using reduced order modeling

International Nuclear Information System (INIS)

Wiebe, R.; Perez, R.A.; Spottswood, S.M.

2016-01-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties. (paper)

Robust simulation of buckled structures using reduced order modeling

Science.gov (United States)

Wiebe, R.; Perez, R. A.; Spottswood, S. M.

2016-09-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.

AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS

Energy Technology Data Exchange (ETDEWEB)

Mandelli, D.; Alfonsi, A.; Talbot, P.; Wang, C.; Maljovec, D.; Smith, C.; Rabiti, C.; Cogliati, J.

2016-10-01

The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, the overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).

Reduced-Order Computational Model for Low-Frequency Dynamics of Automobiles

Directory of Open Access Journals (Sweden)

A. Arnoux

2013-01-01

Full Text Available A reduced-order model is constructed to predict, for the low-frequency range, the dynamical responses in the stiff parts of an automobile constituted of stiff and flexible parts. The vehicle has then many elastic modes in this range due to the presence of many flexible parts and equipment. A nonusual reduced-order model is introduced. The family of the elastic modes is not used and is replaced by an adapted vector basis of the admissible space of global displacements. Such a construction requires a decomposition of the domain of the structure in subdomains in order to control the spatial wave length of the global displacements. The fast marching method is used to carry out the subdomain decomposition. A probabilistic model of uncertainties is introduced. The parameters controlling the level of uncertainties are estimated solving a statistical inverse problem. The methodology is validated with a large computational model of an automobile.

Vortex network community based reduced-order force model

Science.gov (United States)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko

2017-11-01

We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).

A novel condition for stable nonlinear sampled-data models using higher-order discretized approximations with zero dynamics.

Science.gov (United States)

Zeng, Cheng; Liang, Shan; Xiang, Shuwen

2017-05-01

Continuous-time systems are usually modelled by the form of ordinary differential equations arising from physical laws. However, the use of these models in practice and utilizing, analyzing or transmitting these data from such systems must first invariably be discretized. More importantly, for digital control of a continuous-time nonlinear system, a good sampled-data model is required. This paper investigates the new consistency condition which is weaker than the previous similar results presented. Moreover, given the stability of the high-order approximate model with stable zero dynamics, the novel condition presented stabilizes the exact sampled-data model of the nonlinear system for sufficiently small sampling periods. An insightful interpretation of the obtained results can be made in terms of the stable sampling zero dynamics, and the new consistency condition is surprisingly associated with the relative degree of the nonlinear continuous-time system. Our controller design, based on the higher-order approximate discretized model, extends the existing methods which mainly deal with the Euler approximation. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Identification of the reduced order models of a BWR reactor

International Nuclear Information System (INIS)

Hernandez S, A.

2004-01-01

The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)

Linear and nonlinear stability analysis in BWRs applying a reduced order model

Energy Technology Data Exchange (ETDEWEB)

Olvera G, O. A.; Espinosa P, G.; Prieto G, A., E-mail: omar_olverag@hotmail.com [Universidad Autonoma Metropolitana, Unidad Iztapalapa, San Rafael Atlixco No. 186, Col. Vicentina, 09340 Ciudad de Mexico (Mexico)

2016-09-15

Boiling Water Reactor (BWR) stability studies are generally conducted through nonlinear reduced order models (Rom) employing various techniques such as bifurcation analysis and time domain numerical integration. One of those models used for these studies is the March-Leuba Rom. Such model represents qualitatively the dynamic behavior of a BWR through a one-point reactor kinetics, a one node representation of the heat transfer process in fuel, and a two node representation of the channel Thermal hydraulics to account for the void reactivity feedback. Here, we study the effect of this higher order model on the overall stability of the BWR. The change in the stability boundaries is determined by evaluating the eigenvalues of the Jacobian matrix. The nonlinear model is also integrated numerically to show that in the nonlinear region, the system evolves to stable limit cycles when operating close to the stability boundary. We also applied a new technique based on the Empirical Mode Decomposition (Emd) to estimate a parameter linked with stability in a BWR. This instability parameter is not exactly the classical Decay Ratio (Dr), but it will be linked with it. The proposed method allows decomposing the analyzed signal in different levels or mono-component functions known as intrinsic mode functions (Imf). One or more of these different modes can be associated to the instability problem in BWRs. By tracking the instantaneous frequencies (calculated through Hilbert Huang Transform (HHT) and the autocorrelation function (Acf) of the Imf linked to instability. The estimation of the proposed parameter can be achieved. The current methodology was validated with simulated signals of the studied model. (Author)

Linear and nonlinear stability analysis in BWRs applying a reduced order model

International Nuclear Information System (INIS)

Olvera G, O. A.; Espinosa P, G.; Prieto G, A.

2016-09-01

Boiling Water Reactor (BWR) stability studies are generally conducted through nonlinear reduced order models (Rom) employing various techniques such as bifurcation analysis and time domain numerical integration. One of those models used for these studies is the March-Leuba Rom. Such model represents qualitatively the dynamic behavior of a BWR through a one-point reactor kinetics, a one node representation of the heat transfer process in fuel, and a two node representation of the channel Thermal hydraulics to account for the void reactivity feedback. Here, we study the effect of this higher order model on the overall stability of the BWR. The change in the stability boundaries is determined by evaluating the eigenvalues of the Jacobian matrix. The nonlinear model is also integrated numerically to show that in the nonlinear region, the system evolves to stable limit cycles when operating close to the stability boundary. We also applied a new technique based on the Empirical Mode Decomposition (Emd) to estimate a parameter linked with stability in a BWR. This instability parameter is not exactly the classical Decay Ratio (Dr), but it will be linked with it. The proposed method allows decomposing the analyzed signal in different levels or mono-component functions known as intrinsic mode functions (Imf). One or more of these different modes can be associated to the instability problem in BWRs. By tracking the instantaneous frequencies (calculated through Hilbert Huang Transform (HHT) and the autocorrelation function (Acf) of the Imf linked to instability. The estimation of the proposed parameter can be achieved. The current methodology was validated with simulated signals of the studied model. (Author)

Development of Boundary Condition Independent Reduced Order Thermal Models using Proper Orthogonal Decomposition

Science.gov (United States)

Raghupathy, Arun; Ghia, Karman; Ghia, Urmila

2008-11-01

Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.

A Reduced Order Model to Predict Transient Flows around Straight Bladed Vertical Axis Wind Turbines

Directory of Open Access Journals (Sweden)

Soledad Le Clainche

2018-03-01

Full Text Available We develop a reduced order model to represent the complex flow behaviour around vertical axis wind turbines. First, we simulate vertical axis turbines using an accurate high order discontinuous Galerkin–Fourier Navier–Stokes Large Eddy Simulation solver with sliding meshes and extract flow snapshots in time. Subsequently, we construct a reduced order model based on a high order dynamic mode decomposition approach that selects modes based on flow frequency. We show that only a few modes are necessary to reconstruct the flow behaviour of the original simulation, even for blades rotating in turbulent regimes. Furthermore, we prove that an accurate reduced order model can be constructed using snapshots that do not sample one entire turbine rotation (but only a fraction of it, which reduces the cost of generating the reduced order model. Additionally, we compare the reduced order model based on the high order Navier–Stokes solver to fast 2D simulations (using a Reynolds Averaged Navier–Stokes turbulent model to illustrate the good performance of the proposed methodology.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

Science.gov (United States)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Reduced order dynamic model for polysaccharides molecule attached to an atomic force microscope

International Nuclear Information System (INIS)

Tang Deman; Li Aiqin; Attar, Peter; Dowell, Earl H.

2004-01-01

A dynamic analysis and numerical simulation has been conducted of a polysaccharides molecular structure (a ten (10) single-α-D-glucose molecule chain) connected to a moving atomic force microscope (AFM). Sinusoidal base excitation of the AFM cantilevered beam is considered. First a linearized perturbation model is constructed for the complex polysaccharides molecular structure. Then reduced order (dynamic) models based upon a proper orthogonal decomposition (POD) technique are constructed using global modes for both the linearized perturbation model and for the full nonlinear model. The agreement between the original and reduced order models (ROM/POD) is very good even when only a few global modes are included in the ROM for either the linear case or for the nonlinear case. The computational advantage of the reduced order model is clear from the results presented

Reduced Order Modeling for Prediction and Control of Large-Scale Systems.

Energy Technology Data Exchange (ETDEWEB)

Kalashnikova, Irina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Mathematics; Arunajatesan, Srinivasan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Aerosciences Dept.; Barone, Matthew Franklin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Aerosciences Dept.; van Bloemen Waanders, Bart Gustaaf [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Uncertainty Quantification and Optimization Dept.; Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Component Science and Mechanics Dept.

2014-05-01

This report describes work performed from June 2012 through May 2014 as a part of a Sandia Early Career Laboratory Directed Research and Development (LDRD) project led by the first author. The objective of the project is to investigate methods for building stable and efficient proper orthogonal decomposition (POD)/Galerkin reduced order models (ROMs): models derived from a sequence of high-fidelity simulations but having a much lower computational cost. Since they are, by construction, small and fast, ROMs can enable real-time simulations of complex systems for onthe- spot analysis, control and decision-making in the presence of uncertainty. Of particular interest to Sandia is the use of ROMs for the quantification of the compressible captive-carry environment, simulated for the design and qualification of nuclear weapons systems. It is an unfortunate reality that many ROM techniques are computationally intractable or lack an a priori stability guarantee for compressible flows. For this reason, this LDRD project focuses on the development of techniques for building provably stable projection-based ROMs. Model reduction approaches based on continuous as well as discrete projection are considered. In the first part of this report, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is developed. The key idea is to apply a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. It is shown that, for many PDE systems including the linearized compressible Euler and linearized compressible Navier-Stokes equations, the desired transformation is induced by a special inner product, termed the “symmetry inner product”. Attention is then turned to nonlinear conservation laws. A new transformation and corresponding energy-based inner product for the full nonlinear compressible Navier

Reduced-order modeling of piezoelectric energy harvesters with nonlinear circuits under complex conditions

Science.gov (United States)

Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong

2018-04-01

A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.

Vascular stents: Coupling full 3-D with reduced-order structural models

International Nuclear Information System (INIS)

Avdeev, I; Shams, M

2010-01-01

Self-expanding nitinol stents are used to treat peripheral arterial disease. The peripheral arteries are subjected to a combination of mechanical forces such as compression, torsion, bending, and contraction. Most commercially available peripheral self-expanding stents are composed of a series of sub-millimeter V-shaped struts, which are laser-cut from a nitinol tube and surface-treated for better fatigue performance. The numerical stent models must accurately predict location and distribution of local stresses and strains caused by large arterial deformations. Full 3-D finite element non-linear analysis of an entire stent is computationally expensive to the point of being prohibitive, especially for longer stents. Reduced-order models based on beam or shell elements are fairly accurate in capturing global deformations, but are not very helpful in predicting stent failure. We propose a mixed approach that combines the full 3-D model and reduced-order models. Several global-local, full 3-D/reduced-order finite element models of a peripheral self-expanding stent were validated and compared with experimental data. The kinematic constraint method used to couple various elements together was found to be very efficient and easily applicable to commercial FEA codes. The proposed mixed models can be used to accurately predict stent failure based on realistic (patient-specific), non-linear kinematic behavior of peripheral arteries.

Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit

International Nuclear Information System (INIS)

Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua J.; Talbot, Paul W.; Rinaldi, Ivan; Maljovec, Dan; Wang, Bei; Pascucci, Valerio; Zhao, Haihua

2015-01-01

The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.

Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit

Energy Technology Data Exchange (ETDEWEB)

Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cogliati, Joshua J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talbot, Paul W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rinaldi, Ivan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Maljovec, Dan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Bei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pascucci, Valerio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-09-01

The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters

Energy Technology Data Exchange (ETDEWEB)

Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California Santa-Barbara; Bullo, Francesco [University of California Santa-Barbara; Dhople, Sairaj V. [University of Minnesota

2017-08-21

Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.

An Online Method for Interpolating Linear Parametric Reduced-Order Models

KAUST Repository

Amsallem, David; Farhat, Charbel

2011-01-01

A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Science.gov (United States)

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Directory of Open Access Journals (Sweden)

Zhong Yi Wan

Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more

Identification of reduced-order model for an aeroelastic system from flutter test data

Directory of Open Access Journals (Sweden)

Wei Tang

2017-02-01

Full Text Available Recently, flutter active control using linear parameter varying (LPV framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by synthesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI models by using system identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering technique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.

Jacobian projection reduced-order models for dynamic systems with contact nonlinearities

Science.gov (United States)

Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.

2018-02-01

In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.

Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network

Science.gov (United States)

Yao, Weigang; Liou, Meng-Sing

2012-01-01

The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis

Reduced order ARMA spectral estimation of ocean waves

Digital Repository Service at National Institute of Oceanography (India)

Mandal, S.; Witz, J.A.; Lyons, G.J.

. After selecting the initial model order based on the Akaike Information Criterion method, a novel model order reduction technique is applied to obtain the final reduced order ARMA model. First estimates of the higher order autoregressive coefficients... of the reduced order ARMA model is obtained. The moving average part is determined based on partial fraction and recursive methods. The above system identification models and model order reduction technique are shown here to be successfully applied...

Bilinear reduced order approximate model of parabolic distributed solar collectors

KAUST Repository

Elmetennani, Shahrazed

2015-07-01

This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low dimensional bilinear state representation, enables the reproduction of the heat transfer dynamics along the collector tube for system analysis. Moreover, presented as a reduced order bilinear state space model, the well established control theory for this class of systems can be applied. The approximation efficiency has been proven by several simulation tests, which have been performed considering parameters of the Acurex field with real external working conditions. Model accuracy has been evaluated by comparison to the analytical solution of the hyperbolic distributed model and its semi discretized approximation highlighting the benefits of using the proposed numerical scheme. Furthermore, model sensitivity to the different parameters of the gaussian interpolation has been studied.

State reduced order models for the modelling of the thermal behavior of buildings

Energy Technology Data Exchange (ETDEWEB)

Menezo, Christophe; Bouia, Hassan; Roux, Jean-Jacques; Depecker, Patrick [Institute National de Sciences Appliquees de Lyon, Villeurbanne Cedex, (France). Centre de Thermique de Lyon (CETHIL). Equipe Thermique du Batiment]. E-mail: menezo@insa-cethil-etb.insa-lyon.fr; bouia@insa-cethil-etb.insa-lyon.fr; roux@insa-cethil-etb.insa-lyon.fr; depecker@insa-cethil-etb.insa-lyon.fr

2000-07-01

This work is devoted to the field of building physics and related to the reduction of heat conduction models. The aim is to enlarge the model libraries of heat and mass transfer codes through limiting the considerable dimensions reached by the numerical systems during the modelling process of a multizone building. We show that the balanced realization technique, specifically adapted to the coupling of reduced order models with the other thermal phenomena, turns out to be very efficient. (author)

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

Science.gov (United States)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

Reduced order modeling in topology optimization of vibroacoustic problems

DEFF Research Database (Denmark)

Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas

2017-01-01

complex 3D parts. The optimization process can therefore become highly time consuming due to the need to solve a large system of equations at each iteration. Projection-based parametric Model Order Reduction (pMOR) methods have successfully been applied for reducing the computational cost of material......There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...

Fast prediction and evaluation of eccentric inspirals using reduced-order models

Science.gov (United States)

Barta, Dániel; Vasúth, Mátyás

2018-06-01

A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.

Reduced order methods for modeling and computational reduction

CERN Document Server

Rozza, Gianluigi

2014-01-01

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.  Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...

Probabilistic error bounds for reduced order modeling

Energy Technology Data Exchange (ETDEWEB)

Abdo, M.G.; Wang, C.; Abdel-Khalik, H.S., E-mail: abdo@purdue.edu, E-mail: wang1730@purdue.edu, E-mail: abdelkhalik@purdue.edu [Purdue Univ., School of Nuclear Engineering, West Lafayette, IN (United States)

2015-07-01

Reduced order modeling has proven to be an effective tool when repeated execution of reactor analysis codes is required. ROM operates on the assumption that the intrinsic dimensionality of the associated reactor physics models is sufficiently small when compared to the nominal dimensionality of the input and output data streams. By employing a truncation technique with roots in linear algebra matrix decomposition theory, ROM effectively discards all components of the input and output data that have negligible impact on reactor attributes of interest. This manuscript introduces a mathematical approach to quantify the errors resulting from the discarded ROM components. As supported by numerical experiments, the introduced analysis proves that the contribution of the discarded components could be upper-bounded with an overwhelmingly high probability. The reverse of this statement implies that the ROM algorithm can self-adapt to determine the level of the reduction needed such that the maximum resulting reduction error is below a given tolerance limit that is set by the user. (author)

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters: Preprint

Energy Technology Data Exchange (ETDEWEB)

Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California, Santa Barbara; Bullo, Francesco [University of California, Santa Barbara; Dhople, Sairaj [University of Minnesota

2017-08-31

Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. That is, we show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.

REDUCED ISOTROPIC CRYSTAL MODEL WITH RESPECT TO THE FOURTH-ORDER ELASTIC MODULI

Directory of Open Access Journals (Sweden)

O. Burlayenko

2018-04-01

Full Text Available Using a reduced isotropic crystal model the relationship between the fourth-order elastic moduli of an isotropic medium and the independent components of the fourth-order elastic moduli tensor of real crystals of various crystal systems is found. To calculate the coefficients of these relations, computer algebra systems Redberry and Mathematica for working with high order tensors in the symbolic and explicit form were used, in light of the overly complex computation. In an isotropic medium, there are four independent fourth order elastic moduli. This is due to the presence of four invariants for an eighth-rank tensor in the three-dimensional space, that has symmetries over the pairs of indices. As an example, the moduli of elasticity of an isotropic medium corresponding to certain crystals of cubic system are given (LiF, NaCl, MgO, CaF2. From the obtained results it can be seen that the reduced isotropic crystal model can be most effectively applied to high-symmetry crystal systems.

Reduced order models, inertial manifolds, and global bifurcations: searching instability boundaries in nuclear power systems

International Nuclear Information System (INIS)

Suarez Antola, R.

2011-01-01

is obtained. Analytical formulae are derived for the frequency of oscillation and the parameters that determine the stability of the steady states, including sub- and supercritical oincar?-Andronov- Hopf (AH) bifurcations. A Bautin's bifurcation scenario seems possible on the power-flow plane: near the boundary of stability, a region where stable steady states are surrounded by unstable limit cycles surrounded at their turn by stable limit cycles. The qualitative analytical results are compared with recent digital simulations and applications of semi-analytical bifurcation theory done with reduced order models of BWR.

Simulation of local instabilities with the use of reduced order models

International Nuclear Information System (INIS)

Dykin, V.; Demaziere, C.; Lange, C.; Hennig, D.

2011-01-01

The development of an advanced reduced order model (ROM) with four heated channels, taking into account local, regional and core-wide oscillations, is described. The ROM contains three sub-models: a neutron-kinetic model (describing neutron transport), a thermal- hydraulic model (describing the coolant flow) and a heat transfer model (describing heat transfer between the fuel and the coolant). All these three models are coupled to each other, using two feedback mechanisms: void feedback and doppler feedback. Each of the sub-models is described by a set of reduced ordinary differential equations, derived from the corresponding time space-dependent partial differential equations by using different types of approximations and mathematical techniques. All three models were developed from past ROMs and, subsequently, were modified in order to fit the purpose of our investigations. One of the novelties of the present ROM is that it takes into account the effect of the first three neutronic modes, namely the fundamental, the first and the second azimuthal modes, as well as the effect of local oscillations on these modes. In order to have a proper representation of both azimuthal modes, a four heated channel ROM was developed. Another modification, compared to earlier work, is the determination of the coupling reactivity coefficients for both void fraction and fuel temperature, which were calculated explicitly by evaluating cross-section perturbations with the help of the SIMULATE-3 and the CORESIM codes. The ROM was thereafter applied to a channel instability event that occurred at the Swedish Forsmark-1 BWR in 1996/1997. The time signals for each of the modes were generated from the ROM and compared with the measurements, performed at the plant. Some qualitative comparison between the ROM and the measurements was made. The results could bear some significance in understanding the instability event and its coupling mechanism to core-wide oscillations. (author)

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

Science.gov (United States)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

Extreme learning machine for reduced order modeling of turbulent geophysical flows

Science.gov (United States)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Reduced-Order Models for Load Management in the Power Grid

Science.gov (United States)

Alizadeh, Mahnoosh

In recent years, considerable research efforts have been directed towards designing control schemes that can leverage the inherent flexibility of electricity demand that is not tapped into in today's electricity markets. It is expected that these control schemes will be carried out by for-profit entities referred to as aggregators that operate at the edge of the power grid network. While the aggregator control problem is receiving much attention, more high-level questions of how these aggregators should plan their market participation, interact with the main grid and with each other, remain rather understudied. Answering these questions requires a large-scale model for the aggregate flexibility that can be harnessed from the a population of customers, particularly for residences and small businesses. The contribution of this thesis towards this goal is divided into three parts: In Chapter 3, a reduced-order model for a large population of heterogeneous appliances is provided by clustering load profiles that share similar degrees of freedom together. The use of such reduced-order model for system planning and optimal market decision making requires a foresighted approximation of the number of appliances that will join each cluster. Thus, Chapter 4 provides a systematic framework to generate such forecasts for the case of Electric Vehicles, based on real-world battery charging data. While these two chapters set aside the economic side that is naturally involved with participation in demand response programs and mainly focus on the control problem, Chapter 5 is dedicated to the study of optimal pricing mechanisms in order to recruit heterogeneous customers in a demand response program in which an aggregator can directly manage their appliances' load under their specified preferences. Prices are proportional to the wholesale market savings that can result from each recruitment event.

Reduced-Order Modeling of Unsteady Aerodynamics Across Multiple Mach Regimes

Science.gov (United States)

2013-01-01

elastic deformation, has been the subject of intensive study and has been treated in a number of textbooks , including Refs. 9–11, as well as review...simulations, which can be quite computationally-intensive. Reduced-order models (ROMs) o er a solution to these competing demands of accuracy and e ciency...regimes, from subsonic to hypersonic ight. The correction factor term allows the ROM to be accurate over a range of vehicle elastic modal deformation

A new first-order turbulence mixing model for the stable atmospheric boundary-layer: development and testing in large-eddy and single column models

Science.gov (United States)

Huang, J.; Bou-Zeid, E.; Golaz, J.

2011-12-01

Parameterization of the stably-stratified atmospheric boundary-layer is of crucial importance to different aspects of numerical weather prediction at regional scales and climate modeling at global scales, such as land-surface temperature forecasts, fog and frost prediction, and polar climate. It is well-known that most operational climate models require excessive turbulence mixing of the stable boundary-layer to prevent decoupling of the atmospheric component from the land component under strong stability, but the performance of such a model is unlikely to be satisfactory under weakly and moderately stable conditions. In this study we develop and test a general turbulence mixing model of the stable boundary-layer which works under different stabilities and for steady as well as unsteady conditions. A-priori large-eddy simulation (LES) tests are presented to motivate and verify the new parameterization. Subsequently, an assessment of this model using the GFDL single-column model (SCM) is performed. Idealized test cases including continuously varying stability, as well as stability discontinuity, are used to test the new SCM against LES results. A good match of mean and flux profiles is found when the new parameterization is used, while other traditional first-order turbulence models using the concept of stability function perform poorly. SCM spatial resolution is also found to have little impact on the performance of the new turbulence closure, but temporal resolution is important and a numerical stability criterion based on the model time step is presented.

Modal-based reduced-order model of BWR out-of phase instabilities

International Nuclear Information System (INIS)

Turso, J.A.; Edwards, R.M.; March-Leuba, J.

1995-01-01

For the past 40 yr, reduced-order modeling of boiling water reactor (BWR) dynamic behavior has been accomplished by several researchers. These models have been primarily concerned with providing insight into the so-called corewide neutron flux oscillation, where the power at each radial location in the core oscillates in unison. This is generally considered to be an illustration of the fundamental neutronic mode excited by the core thermal hydraulics. The time dependence of the fundamental mode is typically described by the point-kinetics equations, with one or more delayed-neutron groups. Thermal-hydraulic excitation of the first azimuthal harmonic mode, the so-called out-of-phase (OOP) instability, has been observed in operating BWRs. The temporal behavior of a low-order model of this phenomenon can be characterized using the modal point-kinetics formulation developed in this paper

Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations

Science.gov (United States)

Bang, Youngsuk

Reduced order modeling (ROM) has been recognized as an indispensable approach when the engineering analysis requires many executions of high fidelity simulation codes. Examples of such engineering analyses in nuclear reactor core calculations, representing the focus of this dissertation, include the functionalization of the homogenized few-group cross-sections in terms of the various core conditions, e.g. burn-up, fuel enrichment, temperature, etc. This is done via assembly calculations which are executed many times to generate the required functionalization for use in the downstream core calculations. Other examples are sensitivity analysis used to determine important core attribute variations due to input parameter variations, and uncertainty quantification employed to estimate core attribute uncertainties originating from input parameter uncertainties. ROM constructs a surrogate model with quantifiable accuracy which can replace the original code for subsequent engineering analysis calculations. This is achieved by reducing the effective dimensionality of the input parameter, the state variable, or the output response spaces, by projection onto the so-called active subspaces. Confining the variations to the active subspace allows one to construct an ROM model of reduced complexity which can be solved more efficiently. This dissertation introduces a new algorithm to render reduction with the reduction errors bounded based on a user-defined error tolerance which represents the main challenge of existing ROM techniques. Bounding the error is the key to ensuring that the constructed ROM models are robust for all possible applications. Providing such error bounds represents one of the algorithmic contributions of this dissertation to the ROM state-of-the-art. Recognizing that ROM techniques have been developed to render reduction at different levels, e.g. the input parameter space, the state space, and the response space, this dissertation offers a set of novel

Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations

Science.gov (United States)

Mitry, Mina

Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.

Empirical Reduced-Order Modeling for Boundary Feedback Flow Control

Directory of Open Access Journals (Sweden)

Seddik M. Djouadi

2008-01-01

Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.

Package Equivalent Reactor Networks as Reduced Order Models for Use with CAPE-OPEN Compliant Simulation

Energy Technology Data Exchange (ETDEWEB)

Meeks, E.; Chou, C. -P.; Garratt, T.

2013-03-31

Engineering simulations of coal gasifiers are typically performed using computational fluid dynamics (CFD) software, where a 3-D representation of the gasifier equipment is used to model the fluid flow in the gasifier and source terms from the coal gasification process are captured using discrete-phase model source terms. Simulations using this approach can be very time consuming, making it difficult to imbed such models into overall system simulations for plant design and optimization. For such system-level designs, process flowsheet software is typically used, such as Aspen Plus® [1], where each component where each component is modeled using a reduced-order model. For advanced power-generation systems, such as integrated gasifier/gas-turbine combined-cycle systems (IGCC), the critical components determining overall process efficiency and emissions are usually the gasifier and combustor. Providing more accurate and more computationally efficient reduced-order models for these components, then, enables much more effective plant-level design optimization and design for control. Based on the CHEMKIN-PRO and ENERGICO software, we have developed an automated methodology for generating an advanced form of reduced-order model for gasifiers and combustors. The reducedorder model offers representation of key unit operations in flowsheet simulations, while allowing simulation that is fast enough to be used in iterative flowsheet calculations. Using high-fidelity fluiddynamics models as input, Reaction Design’s ENERGICO® [2] software can automatically extract equivalent reactor networks (ERNs) from a CFD solution. For the advanced reduced-order concept, we introduce into the ERN a much more detailed kinetics model than can be included practically in the CFD simulation. The state-of-the-art chemistry solver technology within CHEMKIN-PRO allows that to be accomplished while still maintaining a very fast model turn-around time. In this way, the ERN becomes the basis for

Sparsity enabled cluster reduced-order models for control

Science.gov (United States)

Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

2018-01-01

Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

Frequency-domain reduced order models for gravitational waves from aligned-spin compact binaries

International Nuclear Information System (INIS)

Pürrer, Michael

2014-01-01

Black-hole binary coalescences are one of the most promising sources for the first detection of gravitational waves. Fast and accurate theoretical models of the gravitational radiation emitted from these coalescences are highly important for the detection and extraction of physical parameters. Spinning effective-one-body models for binaries with aligned-spins have been shown to be highly faithful, but are slow to generate and thus have not yet been used for parameter estimation (PE) studies. I provide a frequency-domain singular value decomposition-based surrogate reduced order model that is thousands of times faster for typical system masses and has a faithfulness mismatch of better than ∼0.1% with the original SEOBNRv1 model for advanced LIGO detectors. This model enables PE studies up to signal-to-noise ratios (SNRs) of 20 and even up to 50 for total masses below 50 M ⊙ . This paper discusses various choices for approximations and interpolation over the parameter space that can be made for reduced order models of spinning compact binaries, provides a detailed discussion of errors arising in the construction and assesses the fidelity of such models. (paper)

Reduced-order modelling of wind turbines

NARCIS (Netherlands)

Elkington, K.; Slootweg, J.G.; Ghandhari, M.; Kling, W.L.; Ackermann, T.

2012-01-01

In this chapter power system dynamics simulation(PSDS) isused to study the dynamics of large-scale power systems. It is necessary to incorporate models of wind turbine generating systems into PSDS software packages in order to analyse the impact of high wind power penetration on electrical power

Disturbance estimation of nuclear power plant by using reduced-order model

International Nuclear Information System (INIS)

Tashima, Shin-ichi; Wakabayashi, Jiro

1983-01-01

An estimation method is proposed of multiplex disturbances which occur in a nuclear power plant. The method is composed of two parts: (i) the identification of a simplified model of multi-input and multi-output to describe the related system response, and (ii) the design of a Kalman filter to estimate the multiplex disturbance. Concerning the simplified model, several observed signals are firstly selected as output variables which can well represent the system response caused by the disturbances. A reduced-order model is utilized for designing the disturbance estimator. This is based on the following two considerations. The first is that the disturbance is assumed to be of a quasistatic nature. The other is based on the intuition that there exist a few dominant modes between the disturbances and the selected observed signals and that most of the non-dominant modes which remain may not affect the accuracy of the disturbance estimator. The reduced-order model is furtherly transformed to a single-output model using a linear combination of the output signals, where the standard procedure of the structural identification is evaded. The parameters of the model thus transformed are calculated by the generalized least square method. As for the multiplex disturbance estimator, the Kalman filtering method is applied by compromising the following three items : (a) quick response to disturbance, (b) reduction of estimation error in the presence of observation noises, and (c) the elimination of cross-interference between the disturbances to the plant and the estimates from the Kalman filter. The effectiveness of the proposed method is verified through some computer experiments using a BWR plant simulator. (author)

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

Science.gov (United States)

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

Reduced order models inertial manifold and global bifurcations: searching instability boundaries in nuclear power systems

International Nuclear Information System (INIS)

Suarez Antola, R.

2009-01-01

In the framework of an analytic or numerical model of a BWR power plant, this could imply first to find an suitable approximation to the solution manifold of the differential equations describing the stability behaviour of this nonlinear system, and then a classification of the different solution types concerning their relation with the operational safety of the power plant, by distributing the different solution types in relation with the exclusion region of the power-flow map. Then the goal is to obtain the best attainable qualitative and quantitative global picture of plant dynamics. To do this, the construction and the analysis of the so called reduced order models (Rom) seems a necessary step. A reduced order model results after the full system of coupled nonlinear partial differential equations of the plant is reduced to a system of coupled nonlinear ordinary differential equations

Reducing the transfer of radioiodine to milk in cows by adding stable iodine to the forage

International Nuclear Information System (INIS)

Kiefer, P.; Voigt, G.

1999-05-01

The publication reports the activities for the study and explains the measured results achieved. The usefulness of stable iodine administration to cows for reducing radioiodine transfer to the milk is explained. It was found that enhanced stable radioiodine doses have an effect on the iodine metabolism of dairy cows that has to be taken into account. Initially, a literature study was carried out, which then served as a basis for defining subsequent study objectives and experiments. The evaluation of the results yields information about the effects of stable iodine on the radioiodine transfer, as well as the metabolic pathways of iodine in dairy cows. In order to achieve a clear transfer reducing effect (by a factor of 2), doses of 1g/d have to be fed to a cow. This dose will lead to a stable iodine concentration in the milk of about 10 mg/kg. The WHO recommends a daily maximum dose of 0.5 mg of stable iodine in order to safely prevent adverse health effects in man. Ingestion of more than 2 mg/d may induce in man thyroid disorders and other metabolic disorders. In some countries, the reference level for dairy milk accepted is 0.5 mg of iodine/kg of milk. (orig./CB) [de

Reduced order model of draft tube flow

International Nuclear Information System (INIS)

Rudolf, P; Štefan, D

2014-01-01

Swirling flow with compact coherent structures is very good candidate for proper orthogonal decomposition (POD), i.e. for decomposition into eigenmodes, which are the cornerstones of the flow field. Present paper focuses on POD of steady flows, which correspond to different operating points of Francis turbine draft tube flow. Set of eigenmodes is built using a limited number of snapshots from computational simulations. Resulting reduced order model (ROM) describes whole operating range of the draft tube. ROM enables to interpolate in between the operating points exploiting the knowledge about significance of particular eigenmodes and thus reconstruct the velocity field in any operating point within the given range. Practical example, which employs axisymmetric simulations of the draft tube flow, illustrates accuracy of ROM in regions without vortex breakdown together with need for higher resolution of the snapshot database close to location of sudden flow changes (e.g. vortex breakdown). ROM based on POD interpolation is very suitable tool for insight into flow physics of the draft tube flows (especially energy transfers in between different operating points), for supply of data for subsequent stability analysis or as an initialization database for advanced flow simulations

Class of unconditionally stable second-order implicit schemes for hyperbolic and parabolic equations

International Nuclear Information System (INIS)

Lui, H.C.

The linearized Burgers equation is considered as a model u/sub t/ tau/sub x/ = bu/sub xx/, where the subscripts t and x denote the derivatives of the function u with respect to time t and space x; a and b are constants (b greater than or equal to 0). Numerical schemes for solving the equation are described that are second-order accurate, unconditionally stable, and dissipative of higher order. (U.S.)

High-Order Entropy Stable Formulations for Computational Fluid Dynamics

Science.gov (United States)

Carpenter, Mark H.; Fisher, Travis C.

2013-01-01

A systematic approach is presented for developing entropy stable (SS) formulations of any order for the Navier-Stokes equations. These SS formulations discretely conserve mass, momentum, energy and satisfy a mathematical entropy inequality. They are valid for smooth as well as discontinuous flows provided sufficient dissipation is added at shocks and discontinuities. Entropy stable formulations exist for all diagonal norm, summation-by-parts (SBP) operators, including all centered finite-difference operators, Legendre collocation finite-element operators, and certain finite-volume operators. Examples are presented using various entropy stable formulations that demonstrate the current state-of-the-art of these schemes.

A Fuel-Sensitive Reduced-Order Model (ROM) for Piston Engine Scaling Analysis

Science.gov (United States)

2017-09-29

of high Reynolds number nonreacting and reacting JP-8 sprays in a constant pressure flow vessel with a detailed chemistry approach . J Energy Resour...for rapid grid generation applied to in-cylinder diesel engine simulations. Society of Automotive Engineers ; 2007 Apr. SAE Technical Paper No.: 2007...ARL-TR-8172 ● Sep 2017 US Army Research Laboratory A Fuel-Sensitive Reduced-Order Model (ROM) for Piston Engine Scaling Analysis

A Modified AH-FDTD Unconditionally Stable Method Based on High-Order Algorithm

Directory of Open Access Journals (Sweden)

Zheng Pan

2017-01-01

Full Text Available The unconditionally stable method, Associated-Hermite FDTD, has attracted more and more attentions in computational electromagnetic for its time-frequency compact property. Because of the fewer orders of AH basis needed in signal reconstruction, the computational efficiency can be improved further. In order to further improve the accuracy of the traditional AH-FDTD, a high-order algorithm is introduced. Using this method, the dispersion error induced by the space grid can be reduced, which makes it possible to set coarser grid. The simulation results show that, on the condition of coarse grid, the waveforms obtained from the proposed method are matched well with the analytic result, and the accuracy of the proposed method is higher than the traditional AH-FDTD. And the efficiency of the proposed method is higher than the traditional FDTD method in analysing 2D waveguide problems with fine-structure.

Cluster-based Reduced-order Modelling of Flow in the Wake of a Seal-vibrissa-shaped Cylinder

Science.gov (United States)

Wei, Zheng; Li, Qiliang; Yang, Zhigang; Xia, Chao; Shanghai Automotive Wind Tunnel Center Team

2017-11-01

The flow around a seal-vibrissa-shaped cylinder is numerically calculated using large eddy simulation (LES) at the Reynolds number of 20000, along with a smooth and a twisted cylinder for comparison. The mean drag coefficient of the seal-vibrissa-shaped cylinder is lower than that of the smooth and twisted cylinders, respectively. The fluctuating lift coefficient of the seal-vibrissa-shaped cylinder shows a substantial decrease compared with the smooth cylinder. The seal-vibrissa-shaped surface leads to more stable wake, longer vortex formation length, higher base pressure and three-dimensional separation. In addition, cluster-based reduced-order modelling (CROM) is performed to analyze phase-dependent variations of the wake flow, which discloses the complex unsteady behavior in different cross sections. Meanwhile, two flow regimes, anti-phased and in-phase-dominated vortex shedding, generated by the twisted cylinder and the seal-vibrissa-shaped cylinder are distinguished and extracted, their interrelationship are evaluated, and the question how forces are affected is answered. Supported by the National Key Research and Development Program of China (2016YFB1200503-04) and the Shanghai Automotive Wind Tunnel Technical Service Platform (16DZ2290400).

High-Order Entropy Stable Finite Difference Schemes for Nonlinear Conservation Laws: Finite Domains

Science.gov (United States)

Fisher, Travis C.; Carpenter, Mark H.

2013-01-01

Developing stable and robust high-order finite difference schemes requires mathematical formalism and appropriate methods of analysis. In this work, nonlinear entropy stability is used to derive provably stable high-order finite difference methods with formal boundary closures for conservation laws. Particular emphasis is placed on the entropy stability of the compressible Navier-Stokes equations. A newly derived entropy stable weighted essentially non-oscillatory finite difference method is used to simulate problems with shocks and a conservative, entropy stable, narrow-stencil finite difference approach is used to approximate viscous terms.

Computational design of patterned interfaces using reduced order models

International Nuclear Information System (INIS)

Vattre, A.J.; Abdolrahim, N.; Kolluri, K.; Demkowicz, M.J.

2014-01-01

Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit dislocation patterns by tailoring interface crystallography and composition. Our approach relies on a novel method for predicting the internal structure of interfaces: rather than obtaining it from resource-intensive atomistic simulations, we compute it using an efficient reduced order model based on anisotropic elasticity theory. Moreover, our strategy incorporates interface synthesis as a constraint on the design process. As an illustration, we apply our approach to the design of interfaces with rapid, 1-D point defect diffusion. Patterned interfaces may be integrated into the microstructure of composite materials, markedly improving performance. (authors)

Control-oriented reduced order modeling of dipteran flapping flight

Science.gov (United States)

Faruque, Imraan

Flying insects achieve flight stabilization and control in a manner that requires only small, specialized neural structures to perform the essential components of sensing and feedback, achieving unparalleled levels of robust aerobatic flight on limited computational resources. An engineering mechanism to replicate these control strategies could provide a dramatic increase in the mobility of small scale aerial robotics, but a formal investigation has not yet yielded tools that both quantitatively and intuitively explain flapping wing flight as an "input-output" relationship. This work uses experimental and simulated measurements of insect flight to create reduced order flight dynamics models. The framework presented here creates models that are relevant for the study of control properties. The work begins with automated measurement of insect wing motions in free flight, which are then used to calculate flight forces via an empirically-derived aerodynamics model. When paired with rigid body dynamics and experimentally measured state feedback, both the bare airframe and closed loop systems may be analyzed using frequency domain system identification. Flight dynamics models describing maneuvering about hover and cruise conditions are presented for example fruit flies (Drosophila melanogaster) and blowflies (Calliphorids). The results show that biologically measured feedback paths are appropriate for flight stabilization and sexual dimorphism is only a minor factor in flight dynamics. A method of ranking kinematic control inputs to maximize maneuverability is also presented, showing that the volume of reachable configurations in state space can be dramatically increased due to appropriate choice of kinematic inputs.

Support-Vector-Machine-Based Reduced-Order Model for Limit Cycle Oscillation Prediction of Nonlinear Aeroelastic System

Directory of Open Access Journals (Sweden)

Gang Chen

2012-01-01

Full Text Available It is not easy for the system identification-based reduced-order model (ROM and even eigenmode based reduced-order model to predict the limit cycle oscillation generated by the nonlinear unsteady aerodynamics. Most of these traditional ROMs are sensitive to the flow parameter variation. In order to deal with this problem, a support vector machine- (SVM- based ROM was investigated and the general construction framework was proposed. The two-DOF aeroelastic system for the NACA 64A010 airfoil in transonic flow was then demonstrated for the new SVM-based ROM. The simulation results show that the new ROM can capture the LCO behavior of the nonlinear aeroelastic system with good accuracy and high efficiency. The robustness and computational efficiency of the SVM-based ROM would provide a promising tool for real-time flight simulation including nonlinear aeroelastic effects.

Nonlinear Parameter-Varying AeroServoElastic Reduced Order Model for Aerostructural Sensing and Control, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The overall goal of the project is to develop reliable reduced order modeling technologies to automatically generate nonlinear, parameter-varying (PV),...

Nonlinear Parameter-Varying AeroServoElastic Reduced Order Model for Aerostructural Sensing and Control, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The overall goal of the project is to develop reliable reduced order modeling technologies to automatically generate parameter-varying (PV), aeroservoelastic (ASE)...

An extended Kalman filter approach to non-stationary Bayesian estimation of reduced-order vocal fold model parameters.

Science.gov (United States)

Hadwin, Paul J; Peterson, Sean D

2017-04-01

The Bayesian framework for parameter inference provides a basis from which subject-specific reduced-order vocal fold models can be generated. Previously, it has been shown that a particle filter technique is capable of producing estimates and associated credibility intervals of time-varying reduced-order vocal fold model parameters. However, the particle filter approach is difficult to implement and has a high computational cost, which can be barriers to clinical adoption. This work presents an alternative estimation strategy based upon Kalman filtering aimed at reducing the computational cost of subject-specific model development. The robustness of this approach to Gaussian and non-Gaussian noise is discussed. The extended Kalman filter (EKF) approach is found to perform very well in comparison with the particle filter technique at dramatically lower computational cost. Based upon the test cases explored, the EKF is comparable in terms of accuracy to the particle filter technique when greater than 6000 particles are employed; if less particles are employed, the EKF actually performs better. For comparable levels of accuracy, the solution time is reduced by 2 orders of magnitude when employing the EKF. By virtue of the approximations used in the EKF, however, the credibility intervals tend to be slightly underpredicted.

Static aeroelastic analysis including geometric nonlinearities based on reduced order model

Directory of Open Access Journals (Sweden)

Changchuan Xie

2017-04-01

Full Text Available This paper describes a method proposed for modeling large deflection of aircraft in nonlinear aeroelastic analysis by developing reduced order model (ROM. The method is applied for solving the static aeroelastic and static aeroelastic trim problems of flexible aircraft containing geometric nonlinearities; meanwhile, the non-planar effects of aerodynamics and follower force effect have been considered. ROMs are computational inexpensive mathematical representations compared to traditional nonlinear finite element method (FEM especially in aeroelastic solutions. The approach for structure modeling presented here is on the basis of combined modal/finite element (MFE method that characterizes the stiffness nonlinearities and we apply that structure modeling method as ROM to aeroelastic analysis. Moreover, the non-planar aerodynamic force is computed by the non-planar vortex lattice method (VLM. Structure and aerodynamics can be coupled with the surface spline method. The results show that both of the static aeroelastic analysis and trim analysis of aircraft based on structure ROM can achieve a good agreement compared to analysis based on the FEM and experimental result.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

Science.gov (United States)

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

A Reduced-Order Model for Evaluating the Dynamic Response of Multilayer Plates to Impulsive Loads

Science.gov (United States)

2016-04-12

A REDUCED-ORDER MODEL FOR EVALUATING THE DYNAMIC RESPONSE OF MULTILAYER PLATES TO IMPULSIVE LOADS Weiran Jiang, Alyssa Bennett, Nickolas...innovative multilayer materials or structures to optimize the dynamic performance as a mechanism to absorb and spread energy from an impulsive load...models. • Optimizing the structural weight and levels of protection of the multilayer plates with a good combination of materials. Technical Approach 2016

Generalized Reduced Order Modeling of Aeroservoelastic Systems

Science.gov (United States)

Gariffo, James Michael

Transonic aeroelastic and aeroservoelastic (ASE) modeling presents a significant technical and computational challenge. Flow fields with a mixture of subsonic and supersonic flow, as well as moving shock waves, can only be captured through high-fidelity CFD analysis. With modern computing power, it is realtively straightforward to determine the flutter boundary for a single structural configuration at a single flight condition, but problems of larger scope remain quite costly. Some such problems include characterizing a vehicle's flutter boundary over its full flight envelope, optimizing its structural weight subject to aeroelastic constraints, and designing control laws for flutter suppression. For all of these applications, reduced-order models (ROMs) offer substantial computational savings. ROM techniques in general have existed for decades, and the methodology presented in this dissertation builds on successful previous techniques to create a powerful new scheme for modeling aeroelastic systems, and predicting and interpolating their transonic flutter boundaries. In this method, linear ASE state-space models are constructed from modal structural and actuator models coupled to state-space models of the linearized aerodynamic forces through feedback loops. Flutter predictions can be made from these models through simple eigenvalue analysis of their state-transition matrices for an appropriate set of dynamic pressures. Moreover, this analysis returns the frequency and damping trend of every aeroelastic branch. In contrast, determining the critical dynamic pressure by direct time-marching CFD requires a separate run for every dynamic pressure being analyzed simply to obtain the trend for the critical branch. The present ROM methodology also includes a new model interpolation technique that greatly enhances the benefits of these ROMs. This enables predictions of the dynamic behavior of the system for flight conditions where CFD analysis has not been explicitly

A Reduced-order NLTE Kinetic Model for Radiating Plasmas of Outer Envelopes of Stellar Atmospheres

Energy Technology Data Exchange (ETDEWEB)

Munafò, Alessandro [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 206A Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States); Mansour, Nagi N. [NASA Ames Research Center, Moffett Field, 94035 CA (United States); Panesi, Marco, E-mail: munafo@illinois.edu, E-mail: nagi.n.mansour@nasa.gov, E-mail: m.panesi@illinois.edu [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 306 Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States)

2017-04-01

The present work proposes a self-consistent reduced-order NLTE kinetic model for radiating plasmas found in the outer layers of stellar atmospheres. A detailed collisional-radiative kinetic mechanism is constructed by leveraging the most up-to-date set of ab initio and experimental data available in the literature. This constitutes the starting point for the derivation of a reduced-order model, obtained by lumping the bound energy states into groups. In order to determine the needed thermo-physical group properties, uniform and Maxwell–Boltzmann energy distributions are used to reconstruct the energy population of each group. Finally, the reduced set of governing equations for the material gas and the radiation field is obtained based on the moment method. Applications consider the steady flow across a shock wave in partially ionized hydrogen. The results clearly demonstrate that adopting a Maxwell–Boltzmann grouping allows, on the one hand, for a substantial reduction of the number of unknowns and, on the other, to maintain accuracy for both gas and radiation quantities. Also, it is observed that, when neglecting line radiation, the use of two groups already leads to a very accurate resolution of the photo-ionization precursor, internal relaxation, and radiative cooling regions. The inclusion of line radiation requires adopting just one additional group to account for optically thin losses in the α , β , and γ lines of the Balmer and Paschen series. This trend has been observed for a wide range of shock wave velocities.

Reduced-Order Modeling of 3D Rayleigh-Benard Turbulent Convection

Science.gov (United States)

Hassanzadeh, Pedram; Grover, Piyush; Nabi, Saleh

2017-11-01

Accurate Reduced-Order Models (ROMs) of turbulent geophysical flows have broad applications in science and engineering; for example, to study the climate system or to perform real-time flow control/optimization in energy systems. Here we focus on 3D Rayleigh-Benard turbulent convection at the Rayleigh number of 106 as a prototype for turbulent geophysical flows, which are dominantly buoyancy driven. The purpose of the study is to evaluate and improve the performance of different model reduction techniques using this setting. One-dimensional ROMs for horizontally averaged temperature are calculated using several methods. Specifically, the Linear Response Function (LRF) of the system is calculated from a large DNS dataset using Dynamic Mode Decomposition (DMD) and Fluctuation-Dissipation Theorem (FDT). The LRF is also calculated using the Green's function method of Hassanzadeh and Kuang (2016, J. Atmos. Sci.), which is based on using numerous forced DNS runs. The performance of these LRFs in estimating the system's response to weak external forcings or controlling the time-mean flow are compared and contrasted. The spectral properties of the LRFs and the scaling of the accuracy with the length of the dataset (for the data-driven methods) are also discussed.

A model for a stable coronal loop

International Nuclear Information System (INIS)

Hoven, G.V.; Chiuderi, C.; Giachetti, R.

1977-01-01

We present here a new plasma-physics model of a stable active-region arch which corresponds to the structure observed in the EUV. Pressure gradients are seen, so that the equilibrium magnetic field must depart from the force-free form valid in the surrounding corona. We take advantage of the data and of the approximate cylindrical symmetry to develop a modified form of the commonly assumed sheared-spiral structure. The dynamic MHD behavior of this new pressure/field model is then evaluated by the Newcomb criterion, taken from controlled-fusion physics, and the results show short-wavelength stability in a specific parameter range. Thus we demonstrate the possibility, for pressure profiles with widths of the order of the magnetic-field scale, that such arches can persist for reasonable periods. Finally, the spatial proportions and magnetic fields of a characteristic stable coronal loop are described

A reduced order aerothermodynamic modeling framework for hypersonic vehicles based on surrogate and POD

OpenAIRE

Chen Xin; Liu Li; Long Teng; Yue Zhenjiang

2015-01-01

Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, computation fluid dynamics (CFD) and experimental investigation, a reduced order modeling (ROM) framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design ...

A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring [PowerPoint

Energy Technology Data Exchange (ETDEWEB)

Roettgen, Dan [Wisc; Seeger, Benjamin [Stuttgart; Tai, Wei Che [Washington; Baek, Seunghun [Michigan; Dossogne, Tilan [Liege; Allen, Matthew S [Wisc; Kuether, Robert J.; Brake, Matthew Robert; Mayes, Randall L.

2016-01-01

Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.

Energy stable and high-order-accurate finite difference methods on staggered grids

Science.gov (United States)

O'Reilly, Ossian; Lundquist, Tomas; Dunham, Eric M.; Nordström, Jan

2017-10-01

For wave propagation over distances of many wavelengths, high-order finite difference methods on staggered grids are widely used due to their excellent dispersion properties. However, the enforcement of boundary conditions in a stable manner and treatment of interface problems with discontinuous coefficients usually pose many challenges. In this work, we construct a provably stable and high-order-accurate finite difference method on staggered grids that can be applied to a broad class of boundary and interface problems. The staggered grid difference operators are in summation-by-parts form and when combined with a weak enforcement of the boundary conditions, lead to an energy stable method on multiblock grids. The general applicability of the method is demonstrated by simulating an explosive acoustic source, generating waves reflecting against a free surface and material discontinuity.

Reduced Order Models for Dynamic Behavior of Elastomer Damping Devices

Science.gov (United States)

Morin, B.; Legay, A.; Deü, J.-F.

2016-09-01

In the context of passive damping, various mechanical systems from the space industry use elastomer components (shock absorbers, silent blocks, flexible joints...). The material of these devices has frequency, temperature and amplitude dependent characteristics. The associated numerical models, using viscoelastic and hyperelastic constitutive behaviour, may become computationally too expensive during a design process. The aim of this work is to propose efficient reduced viscoelastic models of rubber devices. The first step is to choose an accurate material model that represent the viscoelasticity. The second step is to reduce the rubber device finite element model to a super-element that keeps the frequency dependence. This reduced model is first built by taking into account the fact that the device's interfaces are much more rigid than the rubber core. To make use of this difference, kinematical constraints enforce the rigid body motion of these interfaces reducing the rubber device model to twelve dofs only on the interfaces (three rotations and three translations per face). Then, the superelement is built by using a component mode synthesis method. As an application, the dynamic behavior of a structure supported by four hourglass shaped rubber devices under harmonic loads is analysed to show the efficiency of the proposed approach.

Linear Parameter Varying Versus Linear Time Invariant Reduced Order Controller Design of Turboprop Aircraft Dynamics

Directory of Open Access Journals (Sweden)

Widowati

2012-07-01

Full Text Available The applicability of parameter varying reduced order controllers to aircraft model is proposed. The generalization of the balanced singular perturbation method of linear time invariant (LTI system is used to reduce the order of linear parameter varying (LPV system. Based on the reduced order model the low-order LPV controller is designed by using synthesis technique. The performance of the reduced order controller is examined by applying it to lateral-directional control of aircraft model having 20th order. Furthermore, the time responses of the closed loop system with reduced order LPV controllers and reduced order LTI controller is compared. From the simulation results, the 8th order LPV controller can maintain stability and to provide the same level of closed-loop systems performance as the full-order LPV controller. It is different with the reduced-order LTI controller that cannot maintain stability and performance for all allowable parameter trajectories.

Nonlinear dynamics of an electrically actuated imperfect microbeam resonator: Experimental investigation and reduced-order modeling

KAUST Repository

Ruzziconi, Laura

2013-06-10

We present a study of the dynamic behavior of a microelectromechanical systems (MEMS) device consisting of an imperfect clamped-clamped microbeam subjected to electrostatic and electrodynamic actuation. Our objective is to develop a theoretical analysis, which is able to describe and predict all the main relevant aspects of the experimental response. Extensive experimental investigation is conducted, where the main imperfections coming from microfabrication are detected, the first four experimental natural frequencies are identified and the nonlinear dynamics are explored at increasing values of electrodynamic excitation, in a neighborhood of the first symmetric resonance. Several backward and forward frequency sweeps are acquired. The nonlinear behavior is highlighted, which includes ranges of multistability, where the nonresonant and the resonant branch coexist, and intervals where superharmonic resonances are clearly visible. Numerical simulations are performed. Initially, two single mode reduced-order models are considered. One is generated via the Galerkin technique, and the other one via the combined use of the Ritz method and the Padé approximation. Both of them are able to provide a satisfactory agreement with the experimental data. This occurs not only at low values of electrodynamic excitation, but also at higher ones. Their computational efficiency is discussed in detail, since this is an essential aspect for systematic local and global simulations. Finally, the theoretical analysis is further improved and a two-degree-of-freedom reduced-order model is developed, which is also capable of capturing the measured second symmetric superharmonic resonance. Despite the apparent simplicity, it is shown that all the proposed reduced-order models are able to describe the experimental complex nonlinear dynamics of the device accurately and properly, which validates the proposed theoretical approach. © 2013 IOP Publishing Ltd.

Progress Report on SAM Reduced-Order Model Development for Thermal Stratification and Mixing during Reactor Transients

Energy Technology Data Exchange (ETDEWEB)

Hu, R. [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-09-01

This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.

SUN-RAH: a nucleoelectric BWR university simulator based in reduced order models

International Nuclear Information System (INIS)

Morales S, J.B.; Lopez R, A.; Sanchez B, A.; Sanchez S, R.; Hernandez S, A.

2003-01-01

The development of a simulator that allows to represent the dynamics of a nucleo electric central, with nuclear reactor of the BWR type, using reduced order models is presented. These models present the characteristics defined by the dominant poles of the system (1) and most of those premature operation transitories in a power station can be reproduced with considerable fidelity if the models are identified with data of plant or references of a code of better estimate like RAMONA, TRAC (2) or RELAP. The models of the simulator are developments or own simplifications starting from the physical laws and retaining the main terms. This work describes the objective of the project and the general specifications of the University student of Nucleo electric simulator with Boiling Water Reactor type (SUN-RAH) as well as the finished parts that fundamentally are the nuclear reactor, the one of steam supply (NSSS), the plant balance (BOP), the main controllers of the plant and the implemented graphic interfaces. The pendent goals as well as the future developments and applications of SUN-RAH are described. (Author)

Tapered composite likelihood for spatial max-stable models

KAUST Repository

Sang, Huiyan

2014-05-01

Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.

Tapered composite likelihood for spatial max-stable models

KAUST Repository

Sang, Huiyan; Genton, Marc G.

2014-01-01

Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.

Bayesian Modeling of Air Pollution Extremes Using Nested Multivariate Max-Stable Processes

KAUST Repository

Vettori, Sabrina; Huser, Raphaë l; Genton, Marc G.

2018-01-01

Capturing the potentially strong dependence among the peak concentrations of multiple air pollutants across a spatial region is crucial for assessing the related public health risks. In order to investigate the multivariate spatial dependence properties of air pollution extremes, we introduce a new class of multivariate max-stable processes. Our proposed model admits a hierarchical tree-based formulation, in which the data are conditionally independent given some latent nested $\\alpha$-stable random factors. The hierarchical structure facilitates Bayesian inference and offers a convenient and interpretable characterization. We fit this nested multivariate max-stable model to the maxima of air pollution concentrations and temperatures recorded at a number of sites in the Los Angeles area, showing that the proposed model succeeds in capturing their complex tail dependence structure.

Bayesian Modeling of Air Pollution Extremes Using Nested Multivariate Max-Stable Processes

KAUST Repository

Vettori, Sabrina

2018-03-18

Capturing the potentially strong dependence among the peak concentrations of multiple air pollutants across a spatial region is crucial for assessing the related public health risks. In order to investigate the multivariate spatial dependence properties of air pollution extremes, we introduce a new class of multivariate max-stable processes. Our proposed model admits a hierarchical tree-based formulation, in which the data are conditionally independent given some latent nested $\\\\alpha$-stable random factors. The hierarchical structure facilitates Bayesian inference and offers a convenient and interpretable characterization. We fit this nested multivariate max-stable model to the maxima of air pollution concentrations and temperatures recorded at a number of sites in the Los Angeles area, showing that the proposed model succeeds in capturing their complex tail dependence structure.

A reduced-order, single-bubble cavitation model with applications to therapeutic ultrasound.

Science.gov (United States)

Kreider, Wayne; Crum, Lawrence A; Bailey, Michael R; Sapozhnikov, Oleg A

2011-11-01

Cavitation often occurs in therapeutic applications of medical ultrasound such as shock-wave lithotripsy (SWL) and high-intensity focused ultrasound (HIFU). Because cavitation bubbles can affect an intended treatment, it is important to understand the dynamics of bubbles in this context. The relevant context includes very high acoustic pressures and frequencies as well as elevated temperatures. Relative to much of the prior research on cavitation and bubble dynamics, such conditions are unique. To address the relevant physics, a reduced-order model of a single, spherical bubble is proposed that incorporates phase change at the liquid-gas interface as well as heat and mass transport in both phases. Based on the energy lost during the inertial collapse and rebound of a millimeter-sized bubble, experimental observations were used to tune and test model predictions. In addition, benchmarks from the published literature were used to assess various aspects of model performance. Benchmark comparisons demonstrate that the model captures the basic physics of phase change and diffusive transport, while it is quantitatively sensitive to specific model assumptions and implementation details. Given its performance and numerical stability, the model can be used to explore bubble behaviors across a broad parameter space relevant to therapeutic ultrasound.

High-order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.

2015-01-01

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

High-order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano

2015-09-29

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

Post-accident action for radiation protection: Reducing the transfer of radioiodine to milk in cows by adding stable iodine to the forage

International Nuclear Information System (INIS)

Kiefer, P.; Voigt, G.

1999-01-01

The publication summarizes the activities for the study and reports the measured results achieved. The usefulness of stable iodine administration to cows for reducing the radioiodine transfer to the milk is explained. It was found that enhanced stable radioiodine doses have an effect on the metabolism of dairy cows that has to be taken into account. Initially, a literature study was carried out, which then served as a basis for defining subsequent studies and experiments. The evaluation of the results yields information about the effects of stable iodine on the radioiodine transfer as well as the metabolic pathways of iodine in dairy cows. In order to achieve a clear transfer-reducing effect (by a factor of 2), doses of 1g/d have to be administered to a cow. This dose will lead to a stable iodine concentration in the milk of about 10 mg/kg. The WHO recommends a daily maximum of 0.5 mg of stable iodine in order to safely prevent adverse health effects in man. Ingestion of more than 2 mg/d may induce in man thyroid disorders and other metabolic disorders. In some countries, the reference level for dairy milk accepted is 0.5 mg of iodine/kg of milk. (orig./CB) [de

A Reduced-Order Controller Considering High-Order Modal Information of High-Rise Buildings for AMD Control System with Time-Delay

Directory of Open Access Journals (Sweden)

Zuo-Hua Li

2017-01-01

Full Text Available Time-delays of control force calculation, data acquisition, and actuator response will degrade the performance of Active Mass Damper (AMD control systems. To reduce the influence, model reduction method is used to deal with the original controlled structure. However, during the procedure, the related hierarchy information of small eigenvalues will be directly discorded. As a result, the reduced-order model ignores the information of high-order mode, which will reduce the design accuracy of an AMD control system. In this paper, a new reduced-order controller based on the improved Balanced Truncation (BT method is designed to reduce the calculation time and to retain the abandoned high-order modal information. It includes high-order natural frequency, damping ratio, and vibration modal information of the original structure. Then, a control gain design method based on Guaranteed Cost Control (GCC algorithm is presented to eliminate the adverse effects of data acquisition and actuator response time-delays in the design process of the reduced-order controller. To verify its effectiveness, the proposed methodology is applied to a numerical example of a ten-storey frame and an experiment of a single-span four-storey steel frame. Both numerical and experimental results demonstrate that the reduced-order controller with GCC algorithm has an excellent control effect; meanwhile it can compensate time-delays effectively.

Multivariable robust adaptive controller using reduced-order model

Directory of Open Access Journals (Sweden)

Wei Wang

1990-04-01

Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.

A stable higher order space time Galerkin marching-on-in-time scheme

KAUST Repository

Pray, Andrew J.

2013-07-01

We present a method for the stable solution of time-domain integral equations. The method uses a technique developed in [1] to accurately evaluate matrix elements. As opposed to existing stabilization schemes, the method presented uses higher order basis functions in time to improve the accuracy of the solver. The method is validated by showing convergence in temporal basis function order, time step size, and geometric discretization order. © 2013 IEEE.

Bilinear reduced order approximate model of parabolic distributed solar collectors

KAUST Repository

Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem

2015-01-01

This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low

A reduced-order vortex model of three-dimensional unsteady non-linear aerodynamics

Science.gov (United States)

Eldredge, Jeff D.

2014-11-01

Rapid, large-amplitude maneuvers of low aspect ratio wings are inherent to biologically-inspired flight. These give rise to unsteady phenomena associated with the interactions among the coherent structures shed from wing edges. The objective of this work is to distill these phenomena into a low-order physics-based dynamical model. The model is based on interconnected vortex loops, composed of linear segments between a small number of vertices. Thus, the dynamics of the fluid are reduced to tracking the evolution of the vertices, whose motions are determined from the velocity field induced by the loops and wing motion. The feature that distinguishes this method from previous treatments is that the vortex loops, analogous to point vortices in our two-dimensional model, have time-varying strength. That is, the flux of vorticity from the wing is concentrated in the constituent segments. Chains of interconnected loops can be shed from any edge of the wing. The evolution equation for the loop vertices is based on the impulse matching principle developed in previous work. We demonstrate the model in various maneuvers, including impulse starts of low aspect ratio wings, oscillatory pitching, etc., and compare with experimental results and high-fidelity simulations where applicable. This work was supported by AFOSR under Award FA9550-11-1-0098.

Reduced-order model based active disturbance rejection control of hydraulic servo system with singular value perturbation theory.

Science.gov (United States)

Wang, Chengwen; Quan, Long; Zhang, Shijie; Meng, Hongjun; Lan, Yuan

2017-03-01

Hydraulic servomechanism is the typical mechanical/hydraulic double-dynamics coupling system with the high stiffness control and mismatched uncertainties input problems, which hinder direct applications of many advanced control approaches in the hydraulic servo fields. In this paper, by introducing the singular value perturbation theory, the original double-dynamics coupling model of the hydraulic servomechanism was reduced to a integral chain system. So that, the popular ADRC (active disturbance rejection control) technology could be directly applied to the reduced system. In addition, the high stiffness control and mismatched uncertainties input problems are avoided. The validity of the simplified model is analyzed and proven theoretically. The standard linear ADRC algorithm is then developed based on the obtained reduced-order model. Extensive comparative co-simulations and experiments are carried out to illustrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Identification of the reduced order models of a BWR reactor; Identificacion de modelos de orden reducido de un reactor BWR

Energy Technology Data Exchange (ETDEWEB)

Hernandez S, A. [UNAM, Laboratorio de Analisis de Ingenieria de Reactores Nucleares, DEPFI, Campus Morelos, en IMTA Jiutepec, Morelos (Mexico)]. e-mail: augusto@correo.unam.mx

2004-07-01

The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)

On the POD based reduced order modeling of high Reynolds flows

Science.gov (United States)

Behzad, Fariduddin; Helenbrook, Brian; Ahmadi, Goodarz

2012-11-01

Reduced-order modeling (ROM) of a high Reynolds fluid flow using the proper orthogonal decomposition (POD) was studied. Particular attention was given to incompressible, unsteady flow over a two-dimensional NACA0015 airfoil. The Reynolds number is 105 and the angle of attacked of the airfoil is 12°. For DNS solution, hp-finite element method is employed to drive flow samples from which the POD modes are extracted. Particular attention is paid on two issues. First, the stability of POD-ROM resimulation of the turbulent flow is studied. High Reynolds flow contains a lot of fluctuating modes. So, to reach a certain amount of error, more POD modes are needed and the effect of truncation of POD modes is more important. Second, the role of convergence rate on the results of POD. Due to complexity of the flow, convergence of the governing equations is more difficult and the influences of weak convergence appear in the results of POD-ROM. For each issue, the capability of the POD-ROM is assessed in terms of predictions quality of times upon which the POD model was derived. The results are compared with DNS solution and the accuracy and efficiency of different cases are evaluated.

Development of a Reduced-Order Model for Reacting Gas-Solids Flow using Proper Orthogonal Decomposition

Energy Technology Data Exchange (ETDEWEB)

McDaniel, Dwayne [Florida International Univ., Miami, FL (United States); Dulikravich, George [Florida International Univ., Miami, FL (United States); Cizmas, Paul [Florida International Univ., Miami, FL (United States)

2017-11-27

This report summarizes the objectives, tasks and accomplishments made during the three year duration of this research project. The report presents the results obtained by applying advanced computational techniques to develop reduced-order models (ROMs) in the case of reacting multiphase flows based on high fidelity numerical simulation of gas-solids flow structures in risers and vertical columns obtained by the Multiphase Flow with Interphase eXchanges (MFIX) software. The research includes a numerical investigation of reacting and non-reacting gas-solids flow systems and computational analysis that will involve model development to accelerate the scale-up process for the design of fluidization systems by providing accurate solutions that match the full-scale models. The computational work contributes to the development of a methodology for obtaining ROMs that is applicable to the system of gas-solid flows. Finally, the validity of the developed ROMs is evaluated by comparing the results against those obtained using the MFIX code. Additionally, the robustness of existing POD-based ROMs for multiphase flows is improved by avoiding non-physical solutions of the gas void fraction and ensuring that the reduced kinetics models used for reactive flows in fluidized beds are thermodynamically consistent.

A Reduced Order Model for the Design of Oxy-Coal Combustion Systems

Directory of Open Access Journals (Sweden)

Steven L. Rowan

2015-01-01

Full Text Available Oxy-coal combustion is one of the more promising technologies currently under development for addressing the issues associated with greenhouse gas emissions from coal-fired power plants. Oxy-coal combustion involves combusting the coal fuel in mixtures of pure oxygen and recycled flue gas (RFG consisting of mainly carbon dioxide (CO2. As a consequence, many researchers and power plant designers have turned to CFD simulations for the study and design of new oxy-coal combustion power plants, as well as refitting existing air-coal combustion facilities to oxy-coal combustion operations. While CFD is a powerful tool that can provide a vast amount of information, the simulations themselves can be quite expensive in terms of computational resources and time investment. As a remedy, a reduced order model (ROM for oxy-coal combustion has been developed to supplement the CFD simulations. With this model, it is possible to quickly estimate the average outlet temperature of combustion flue gases given a known set of mass flow rates of fuel and oxidant entering the power plant boiler as well as determine the required reactor inlet mass flow rates for a desired outlet temperature. Several cases have been examined with this model. The results compare quite favorably to full CFD simulation results.

Concurrent hyperthermia estimation schemes based on extended Kalman filtering and reduced-order modelling.

Science.gov (United States)

Potocki, J K; Tharp, H S

1993-01-01

The success of treating cancerous tissue with heat depends on the temperature elevation, the amount of tissue elevated to that temperature, and the length of time that the tissue temperature is elevated. In clinical situations the temperature of most of the treated tissue volume is unknown, because only a small number of temperature sensors can be inserted into the tissue. A state space model based on a finite difference approximation of the bioheat transfer equation (BHTE) is developed for identification purposes. A full-order extended Kalman filter (EKF) is designed to estimate both the unknown blood perfusion parameters and the temperature at unmeasured locations. Two reduced-order estimators are designed as computationally less intensive alternatives to the full-order EKF. Simulation results show that the success of the estimation scheme depends strongly on the number and location of the temperature sensors. Superior results occur when a temperature sensor exists in each unknown blood perfusion zone, and the number of sensors is at least as large as the number of unknown perfusion zones. Unacceptable results occur when there are more unknown perfusion parameters than temperature sensors, or when the sensors are placed in locations that do not sample the unknown perfusion information.

A stable higher order space time Galerkin marching-on-in-time scheme

KAUST Repository

Pray, Andrew J.; Shanker, Balasubramaniam; Bagci, Hakan

2013-01-01

We present a method for the stable solution of time-domain integral equations. The method uses a technique developed in [1] to accurately evaluate matrix elements. As opposed to existing stabilization schemes, the method presented uses higher order

Reduced-order LPV model of flexible wind turbines from high fidelity aeroelastic codes

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Sønderby, Ivan Bergquist; Hansen, Morten Hartvig

2013-01-01

of high-order linear time invariant (LTI) models. Firstly, the high-order LTI models are locally approximated using modal and balanced truncation and residualization. Then, an appropriate coordinate transformation is applied to allow interpolation of the model matrices between points on the parameter...

A non-linear reduced order methodology applicable to boiling water reactor stability analysis

International Nuclear Information System (INIS)

Prill, Dennis Paul

2013-01-01

Thermal-hydraulic coupling between power, flow rate and density, intensified by neutronics feedback are the main drivers of boiling water reactor (BWR) stability behavior. High-power low-flow conditions in connection with unfavorable power distributions can lead the BWR system into unstable regions where power oscillations can be triggered. This important threat to operational safety requires careful analysis for proper understanding. Analyzing an exhaustive parameter space of the non-linear BWR system becomes feasible with methodologies based on reduced order models (ROMs), saving computational cost and improving the physical understanding. Presently within reactor dynamics, no general and automatic prediction of high-dimensional ROMs based on detailed BWR models are available. In this thesis a systematic self-contained model order reduction (MOR) technique is derived which is applicable for several classes of dynamical problems, and in particular to BWRs of any degree of details. Expert knowledge can be given by operational, experimental or numerical transient data and is transfered into an optimal basis function representation. The methodology is mostly automated and provides the framework for the reduction of various different systems of any level of complexity. Only little effort is necessary to attain a reduced version within this self-written code which is based on coupling of sophisticated commercial software. The methodology reduces a complex system in a grid-free manner to a small system able to capture even non-linear dynamics. It is based on an optimal choice of basis functions given by the so-called proper orthogonal decomposition (POD). Required steps to achieve reliable and numerical stable ROM are given by a distinct calibration road-map. In validation and verification steps, a wide spectrum of representative test examples is systematically studied regarding a later BWR application. The first example is non-linear and has a dispersive character

Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

Science.gov (United States)

Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang

2016-09-01

Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.

A stabilized MFE reduced-order extrapolation model based on POD for the 2D unsteady conduction-convection problem.

Science.gov (United States)

Xia, Hong; Luo, Zhendong

2017-01-01

In this study, we devote ourselves to establishing a stabilized mixed finite element (MFE) reduced-order extrapolation (SMFEROE) model holding seldom unknowns for the two-dimensional (2D) unsteady conduction-convection problem via the proper orthogonal decomposition (POD) technique, analyzing the existence and uniqueness and the stability as well as the convergence of the SMFEROE solutions and validating the correctness and dependability of the SMFEROE model by means of numerical simulations.

An energy-stable time-integrator for phase-field models

KAUST Repository

Vignal, Philippe

2016-12-27

We introduce a provably energy-stable time-integration method for general classes of phase-field models with polynomial potentials. We demonstrate how Taylor series expansions of the nonlinear terms present in the partial differential equations of these models can lead to expressions that guarantee energy-stability implicitly, which are second-order accurate in time. The spatial discretization relies on a mixed finite element formulation and isogeometric analysis. We also propose an adaptive time-stepping discretization that relies on a first-order backward approximation to give an error-estimator. This error estimator is accurate, robust, and does not require the computation of extra solutions to estimate the error. This methodology can be applied to any second-order accurate time-integration scheme. We present numerical examples in two and three spatial dimensions, which confirm the stability and robustness of the method. The implementation of the numerical schemes is done in PetIGA, a high-performance isogeometric analysis framework.

An energy-stable time-integrator for phase-field models

KAUST Repository

Vignal, Philippe; Collier, N.; Dalcin, Lisandro; Brown, D.L.; Calo, V.M.

2016-01-01

We introduce a provably energy-stable time-integration method for general classes of phase-field models with polynomial potentials. We demonstrate how Taylor series expansions of the nonlinear terms present in the partial differential equations of these models can lead to expressions that guarantee energy-stability implicitly, which are second-order accurate in time. The spatial discretization relies on a mixed finite element formulation and isogeometric analysis. We also propose an adaptive time-stepping discretization that relies on a first-order backward approximation to give an error-estimator. This error estimator is accurate, robust, and does not require the computation of extra solutions to estimate the error. This methodology can be applied to any second-order accurate time-integration scheme. We present numerical examples in two and three spatial dimensions, which confirm the stability and robustness of the method. The implementation of the numerical schemes is done in PetIGA, a high-performance isogeometric analysis framework.

Preparation and characterization of stable aqueous higher-order fullerenes

International Nuclear Information System (INIS)

Aich, Nirupam; Flora, Joseph R V; Saleh, Navid B

2012-01-01

Stable aqueous suspensions of nC 60 and individual higher fullerenes, i.e. C 70 , C 76 and C 84 , are prepared by a calorimetric modification of a commonly used liquid–liquid extraction technique. The energy requirement for synthesis of higher fullerenes has been guided by molecular-scale interaction energy calculations. Solubilized fullerenes show crystalline behavior by exhibiting lattice fringes in high resolution transmission electron microscopy images. The fullerene colloidal suspensions thus prepared are stable with a narrow distribution of cluster radii (42.7 ± 0.8 nm, 46.0 ± 14.0 nm, 60 ± 3.2 nm and 56.3 ± 1.1 nm for nC 60 , nC 70 , nC 76 and nC 84 , respectively) as measured by time-resolved dynamic light scattering. The ζ-potential values for all fullerene samples showed negative surface potentials with similar magnitude ( − 38.6 ± 5.8 mV, − 39.1 ± 4.2 mV, − 38.9 ± 5.8 mV and − 41.7 ± 5.1 mV for nC 60 , nC 70 , nC 76 and nC 84 , respectively), which provide electrostatic stability to the colloidal clusters. This energy-based modified solubilization technique to produce stable aqueous fullerenes will likely aid in future studies focusing on better applicability, determination of colloidal properties, and understanding of environmental fate, transport and toxicity of higher-order fullerenes. (paper)

Experimental evidence and modelling of drought induced alternative stable soil moisture states

Science.gov (United States)

Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget

2017-04-01

The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?

A stabilized MFE reduced-order extrapolation model based on POD for the 2D unsteady conduction-convection problem

Directory of Open Access Journals (Sweden)

Hong Xia

2017-05-01

Full Text Available Abstract In this study, we devote ourselves to establishing a stabilized mixed finite element (MFE reduced-order extrapolation (SMFEROE model holding seldom unknowns for the two-dimensional (2D unsteady conduction-convection problem via the proper orthogonal decomposition (POD technique, analyzing the existence and uniqueness and the stability as well as the convergence of the SMFEROE solutions and validating the correctness and dependability of the SMFEROE model by means of numerical simulations.

On the effect of deterministic terms on the bias in stable AR models

NARCIS (Netherlands)

van Giersbergen, N.P.A.

2004-01-01

This paper compares the first-order bias approximation for the autoregressive (AR) coefficients in stable AR models in the presence of deterministic terms. It is shown that the bias due to inclusion of an intercept and trend is twice as large as the bias due to an intercept. For the AR(1) model, the

High Performance Reduced Order Models for Wind Turbines with Full-Scale Converters Applied on Grid Interconnection Studies

DEFF Research Database (Denmark)

Pereira, Heverton A.; F. Cupertino, Allan; Teodorescu, Remus

2014-01-01

Wind power has achieved technological evolution, and Grid Code (GC) requirements forced wind industry consolidation in the last three decades. However, more studies are necessary to understand how the dynamics inherent in this energy source interact with the power system. Traditional energy...... of Absolute Error (NIAE). Models are analyzed during wind speed variations and balanced voltage dip. During faults, WPPs must be able to supply reactive power to the grid, and this characteristic is analyzed. Using the proposed performance index, it is possible to conclude if a reduced order model is suitable...

A fourth order spline collocation approach for a business cycle model

Science.gov (United States)

Sayfy, A.; Khoury, S.; Ibdah, H.

2013-10-01

A collocation approach, based on a fourth order cubic B-splines is presented for the numerical solution of a Kaleckian business cycle model formulated by a nonlinear delay differential equation. The equation is approximated and the nonlinearity is handled by employing an iterative scheme arising from Newton's method. It is shown that the model exhibits a conditionally dynamical stable cycle. The fourth-order rate of convergence of the scheme is verified numerically for different special cases.

A Truly Second-Order and Unconditionally Stable Thermal Lattice Boltzmann Method

Directory of Open Access Journals (Sweden)

Zhen Chen

2017-03-01

Full Text Available An unconditionally stable thermal lattice Boltzmann method (USTLBM is proposed in this paper for simulating incompressible thermal flows. In USTLBM, solutions to the macroscopic governing equations that are recovered from lattice Boltzmann equation (LBE through Chapman–Enskog (C-E expansion analysis are resolved in a predictor–corrector scheme and reconstructed within lattice Boltzmann framework. The development of USTLBM is inspired by the recently proposed simplified thermal lattice Boltzmann method (STLBM. Comparing with STLBM which can only achieve the first-order of accuracy in time, the present USTLBM ensures the second-order of accuracy both in space and in time. Meanwhile, all merits of STLBM are maintained by USTLBM. Specifically, USTLBM directly updates macroscopic variables rather than distribution functions, which greatly saves virtual memories and facilitates implementation of physical boundary conditions. Through von Neumann stability analysis, it can be theoretically proven that USTLBM is unconditionally stable. It is also shown in numerical tests that, comparing to STLBM, lower numerical error can be expected in USTLBM at the same mesh resolution. Four typical numerical examples are presented to demonstrate the robustness of USTLBM and its flexibility on non-uniform and body-fitted meshes.

Reduced-order model for inertial locomotion of a slender swimmer

Science.gov (United States)

Mahalinkam, Raksha; Gong, Felicity; Khair, Aditya S.

2018-04-01

The inertial locomotion of an elongated model swimmer in a Newtonian fluid is quantified, wherein self-propulsion is achieved via steady tangential surface treadmilling. The swimmer has a length 2 l and a circular cross section of longitudinal profile a R (z ) , where a is the characteristic width of the cross section, R (z ) is a dimensionless shape function, and z is a dimensionless coordinate, normalized by l , along the centerline of the body. It is assumed that the swimmer is slender, ɛ =a /l ≪1 . Hence, we utilize slender-body theory to analyze the Navier-Stokes equations that describe the flow around the swimmer. Therefrom, we compute an asymptotic approximation to the swimming speed, U , as U /us=1 -β [V (Re ) -1/2 ∫-11z lnR (z ) d z ] /ln(1 /ɛ ) +O [1 /ln2(1 /ɛ ) ], where us is the characteristic speed of the surface treadmilling, Re is the Reynolds number based on the body length, and β is a dimensionless parameter that differentiates between "pusher" (propelled from the rear, β 0 ) -type swimmers. The function V (Re ) increases monotonically with increasing Re ; hence, fluid inertia causes an increase (decrease) in the swimming speed of a pusher (puller). Next, we demonstrate that the power expenditure of the swimmer increases monotonically with increasing Re . Further, the power expenditures of a puller and pusher with the same value of |β | are equal. Therefore, pushers are superior in inertial locomotion as compared to pullers, in that they achieve a faster swimming speed for the same power expended. Finally, it is demonstrated that the flow structure predicted from our reduced-order model is consistent with that from direct numerical simulation of swimmers at intermediate Re .

A Fault Detection Filtering for Networked Control Systems Based on Balanced Reduced-Order

Directory of Open Access Journals (Sweden)

Da-Meng Dai

2015-01-01

Full Text Available Due to the probability of the packet dropout in the networked control systems, a balanced reduced-order fault detection filter is proposed. In this paper, we first analyze the packet dropout effects in the networked control systems. Then, in order to obtain a robust fault detector for the packet dropout, we use the balanced structure to construct a reduced-order model for residual dynamics. Simulation results are provided to testify the proposed method.

Stable cycling in discrete-time genetic models.

OpenAIRE

Hastings, A

1981-01-01

Examples of stable cycling are discussed for two-locus, two-allele, deterministic, discrete-time models with constant fitnesses. The cases that cycle were found by using numerical techniques to search for stable Hopf bifurcations. One consequence of the results is that apparent cases of directional selection may be due to stable cycling.

Stable cycling in discrete-time genetic models.

Science.gov (United States)

Hastings, A

1981-11-01

Examples of stable cycling are discussed for two-locus, two-allele, deterministic, discrete-time models with constant fitnesses. The cases that cycle were found by using numerical techniques to search for stable Hopf bifurcations. One consequence of the results is that apparent cases of directional selection may be due to stable cycling.

Highly polarized light from stable ordered magnetic fields in GRB 120308A.

Science.gov (United States)

Mundell, C G; Kopač, D; Arnold, D M; Steele, I A; Gomboc, A; Kobayashi, S; Harrison, R M; Smith, R J; Guidorzi, C; Virgili, F J; Melandri, A; Japelj, J

2013-12-05

After the initial burst of γ-rays that defines a γ-ray burst (GRB), expanding ejecta collide with the circumburst medium and begin to decelerate at the onset of the afterglow, during which a forward shock travels outwards and a reverse shock propagates backwards into the oncoming collimated flow, or 'jet'. Light from the reverse shock should be highly polarized if the jet's magnetic field is globally ordered and advected from the central engine, with a position angle that is predicted to remain stable in magnetized baryonic jet models or vary randomly with time if the field is produced locally by plasma or magnetohydrodynamic instabilities. Degrees of linear polarization of P ≈ 10 per cent in the optical band have previously been detected in the early afterglow, but the lack of temporal measurements prevented definitive tests of competing jet models. Hours to days after the γ-ray burst, polarization levels are low (P < 4 per cent), when emission from the shocked ambient medium dominates. Here we report the detection of P =28(+4)(-4) per cent in the immediate afterglow of Swift γ-ray burst GRB 120308A, four minutes after its discovery in the γ-ray band, decreasing to P = 16(+5)(-4) per cent over the subsequent ten minutes. The polarization position angle remains stable, changing by no more than 15 degrees over this time, with a possible trend suggesting gradual rotation and ruling out plasma or magnetohydrodynamic instabilities. Instead, the polarization properties show that GRBs contain magnetized baryonic jets with large-scale uniform fields that can survive long after the initial explosion.

A Reduced Order, One Dimensional Model of Joint Response

Energy Technology Data Exchange (ETDEWEB)

DOHNER,JEFFREY L.

2000-11-06

As a joint is loaded, the tangent stiffness of the joint reduces due to slip at interfaces. This stiffness reduction continues until the direction of the applied load is reversed or the total interface slips. Total interface slippage in joints is called macro-slip. For joints not undergoing macro-slip, when load reversal occurs the tangent stiffness immediately rebounds to its maximum value. This occurs due to stiction effects at the interface. Thus, for periodic loads, a softening and rebound hardening cycle is produced which defines a hysteretic, energy absorbing trajectory. For many jointed sub-structures, this hysteretic trajectory can be approximated using simple polynomial representations. This allows for complex joint substructures to be represented using simple non-linear models. In this paper a simple one dimensional model is discussed.

Reduced-order modeling (ROM) for simulation and optimization powerful algorithms as key enablers for scientific computing

CERN Document Server

Milde, Anja; Volkwein, Stefan

2018-01-01

This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike. .

Asymptotically stable fourth-order accurate schemes for the diffusion equation on complex shapes

International Nuclear Information System (INIS)

Abarbanel, S.; Ditkowski, A.

1997-01-01

An algorithm which solves the multidimensional diffusion equation on complex shapes to fourth-order accuracy and is asymptotically stable in time is presented. This bounded-error result is achieved by constructing, on a rectangular grid, a differentiation matrix whose symmetric part is negative definite. The differentiation matrix accounts for the Dirichlet boundary condition by imposing penalty-like terms. Numerical examples in 2-D show that the method is effective even where standard schemes, stable by traditional definitions, fail. The ability of the paradigm to be applied to arbitrary geometric domains is an important feature of the algorithm. 5 refs., 14 figs

Multiscale Reduced Order Modeling of Complex Multi-Bay Structures

Science.gov (United States)

2013-07-01

fuselage panel studied in [28], see Fig. 2 for a picture of the actual hardware taken from [28]. The finite element model of the 9-bay panel, shown in...discussed. Two alternatives to reduce the computational time for the solution of these problems are explored. iii A mi familia ...results at P=0.98-1.82 lb/in, P=1.4-2.6 lb/in. The baseline solution P=1.4-2.6 lb/in has a 46 mean value of 2 lb/in and it is actually very close to

Tempered stable distributions stochastic models for multiscale processes

CERN Document Server

Grabchak, Michael

2015-01-01

This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions.  A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.

Fabrication of highly ordered nanoporous alumina films by stable high-field anodization

International Nuclear Information System (INIS)

Li Yanbo; Zheng Maojun; Ma Li; Shen Wenzhong

2006-01-01

Stable high-field anodization (1500-4000 A m -2 ) for the fabrication of highly ordered porous anodic alumina films has been realized in a H 3 PO 4 -H 2 O-C 2 H 5 OH system. By maintaining the self-ordering voltage and adjusting the anodizing current density, high-quality self-ordered alumina films with a controllable inter-pore distance over a large range are achieved. The high anodizing current densities lead to high-speed film growth (4-10 μm min -1 ). The inter-pore distance is not solely dependent on the anodizing voltage, but is also influenced by the anodizing current density. This approach is simple and cost-effective, and is of great value for applications in diverse areas of nanotechnology

Reduced-order computational model in nonlinear structural dynamics for structures having numerous local elastic modes in the low-frequency range. Application to fuel assemblies

International Nuclear Information System (INIS)

Batou, A.; Soize, C.; Brie, N.

2013-01-01

Highlights: • A ROM of a nonlinear dynamical structure is built with a global displacements basis. • The reduced order model of fuel assemblies is accurate and of very small size. • The shocks between grids of a row of seven fuel assemblies are computed. -- Abstract: We are interested in the construction of a reduced-order computational model for nonlinear complex dynamical structures which are characterized by the presence of numerous local elastic modes in the low-frequency band. This high modal density makes the use of the classical modal analysis method not suitable. Therefore the reduced-order computational model is constructed using a basis of a space of global displacements, which is constructed a priori and which allows the nonlinear dynamical response of the structure observed on the stiff part to be predicted with a good accuracy. The methodology is applied to a complex industrial structure which is made up of a row of seven fuel assemblies with possibility of collisions between grids and which is submitted to a seismic loading

Reduced-order computational model in nonlinear structural dynamics for structures having numerous local elastic modes in the low-frequency range. Application to fuel assemblies

Energy Technology Data Exchange (ETDEWEB)

Batou, A., E-mail: anas.batou@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee (France); Soize, C., E-mail: christian.soize@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee (France); Brie, N., E-mail: nicolas.brie@edf.fr [EDF R and D, Département AMA, 1 avenue du général De Gaulle, 92140 Clamart (France)

2013-09-15

Highlights: • A ROM of a nonlinear dynamical structure is built with a global displacements basis. • The reduced order model of fuel assemblies is accurate and of very small size. • The shocks between grids of a row of seven fuel assemblies are computed. -- Abstract: We are interested in the construction of a reduced-order computational model for nonlinear complex dynamical structures which are characterized by the presence of numerous local elastic modes in the low-frequency band. This high modal density makes the use of the classical modal analysis method not suitable. Therefore the reduced-order computational model is constructed using a basis of a space of global displacements, which is constructed a priori and which allows the nonlinear dynamical response of the structure observed on the stiff part to be predicted with a good accuracy. The methodology is applied to a complex industrial structure which is made up of a row of seven fuel assemblies with possibility of collisions between grids and which is submitted to a seismic loading.

Supplementary Material for: High-Order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.

2016-01-01

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of points is a very challenging problem and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

An Efficient Reduced-Order Model for the Nonlinear Dynamics of Carbon Nanotubes

KAUST Repository

Xu, Tiantian

2014-08-17

Because of the inherent nonlinearities involving the behavior of CNTs when excited by electrostatic forces, modeling and simulating their behavior is challenging. The complicated form of the electrostatic force describing the interaction of their cylindrical shape, forming upper electrodes, to lower electrodes poises serious computational challenges. This presents an obstacle against applying and using several nonlinear dynamics tools that typically used to analyze the behavior of complicated nonlinear systems, such as shooting, continuation, and integrity analysis techniques. This works presents an attempt to resolve this issue. We present an investigation of the nonlinear dynamics of carbon nanotubes when actuated by large electrostatic forces. We study expanding the complicated form of the electrostatic force into enough number of terms of the Taylor series. We plot and compare the expanded form of the electrostatic force to the exact form and found that at least twenty terms are needed to capture accurately the strong nonlinear form of the force over the full range of motion. Then, we utilize this form along with an Euler–Bernoulli beam model to study the static and dynamic behavior of CNTs. The geometric nonlinearity and the nonlinear electrostatic force are considered. An efficient reduced-order model (ROM) based on the Galerkin method is developed and utilized to simulate the static and dynamic responses of the CNTs. We found that the use of the new expanded form of the electrostatic force enables avoiding the cumbersome evaluation of the spatial integrals involving the electrostatic force during the modal projection procedure in the Galerkin method, which needs to be done at every time step. Hence, the new method proves to be much more efficient computationally.

Non-intrusive reduced order modeling of nonlinear problems using neural networks

Science.gov (United States)

Hesthaven, J. S.; Ubbiali, S.

2018-06-01

We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs), particularly multi-layer perceptrons (MLPs), to accurately approximate the coefficients of the reduced model. The search for the optimal number of neurons and the minimum amount of training samples to avoid overfitting is carried out in the offline phase through an automatic routine, relying upon a joint use of the Latin hypercube sampling (LHS) and the Levenberg-Marquardt (LM) training algorithm. This guarantees a complete offline-online decoupling, leading to an efficient RB method - referred to as POD-NN - suitable also for general nonlinear problems with a non-affine parametric dependence. Numerical studies are presented for the nonlinear Poisson equation and for driven cavity viscous flows, modeled through the steady incompressible Navier-Stokes equations. Both physical and geometrical parametrizations are considered. Several results confirm the accuracy of the POD-NN method and show the substantial speed-up enabled at the online stage as compared to a traditional RB strategy.

A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

Science.gov (United States)

Mohan, Arvind; Gaitonde, Datta

2017-11-01

Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

Science.gov (United States)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

Science.gov (United States)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

A parametric model order reduction technique for poroelastic finite element models.

Science.gov (United States)

Lappano, Ettore; Polanz, Markus; Desmet, Wim; Mundo, Domenico

2017-10-01

This research presents a parametric model order reduction approach for vibro-acoustic problems in the frequency domain of systems containing poroelastic materials (PEM). The method is applied to the Finite Element (FE) discretization of the weak u-p integral formulation based on the Biot-Allard theory and makes use of reduced basis (RB) methods typically employed for parametric problems. The parametric reduction is obtained rewriting the Biot-Allard FE equations for poroelastic materials using an affine representation of the frequency (therefore allowing for RB methods) and projecting the frequency-dependent PEM system on a global reduced order basis generated with the proper orthogonal decomposition instead of standard modal approaches. This has proven to be better suited to describe the nonlinear frequency dependence and the strong coupling introduced by damping. The methodology presented is tested on two three-dimensional systems: in the first experiment, the surface impedance of a PEM layer sample is calculated and compared with results of the literature; in the second, the reduced order model of a multilayer system coupled to an air cavity is assessed and the results are compared to those of the reference FE model.

Higher-order Skyrme hair of black holes

Science.gov (United States)

Gudnason, Sven Bjarke; Nitta, Muneto

2018-05-01

Higher-order derivative terms are considered as replacement for the Skyrme term in an Einstein-Skyrme-like model in order to pinpoint which properties are necessary for a black hole to possess stable static scalar hair. We find two new models able to support stable black hole hair in the limit of the Skyrme term being turned off. They contain 8 and 12 derivatives, respectively, and are roughly the Skyrme-term squared and the so-called BPS-Skyrme-term squared. In the twelfth-order model we find that the lower branches, which are normally unstable, become stable in the limit where the Skyrme term is turned off. We check this claim with a linear stability analysis. Finally, we find for a certain range of the gravitational coupling and horizon radius, that the twelfth-order model contains 4 solutions as opposed to 2. More surprisingly, the lowest part of the would-be unstable branch turns out to be the stable one of the 4 solutions.

A new approach to establish both stable and metastable phase equilibria for fcc ordered/disordered phase transition: application to the Al–Ni and Ni–Si systems

International Nuclear Information System (INIS)

Yuan Xiaoming; Zhang Lijun; Du Yong; Xiong Wei; Tang Ying; Wang Aijun; Liu Shuhong

2012-01-01

Both two-sublattice (2SL) and four-sublattice (4SL) models in the framework of the compound energy formalism can be used to describe the fcc ordered/disordered transitions. When transferring the parameters of 2SL disregarding the metastable ordered states into those of 4SL, inconsistence in either stable or metastable phase diagrams could appear, as detected in both Al–Ni and Ni–Si systems. To avoid such a kind of drawback, this behavior was analyzed and investigated in the Ni–Si and Al–Ni systems with the aid of first–principle calculations. Furthermore, a new approach considering both the stable and metastable fcc ordered phase equilibria deduced from the first–principles calculations was proposed to perform a reliable thermodynamic modeling for the fcc ordered/disordered transition. The Ni–Si system was then thermodynamically assessed using the presently proposed approach. The good agreement between the calculation and experiments demonstrates the reliability of the proposed approach. It is expected that the approach is valid for other systems showing complex ordered/disordered transitions. - Highlights: ► We discuss the drawbacks of order/disorder modeling in the Ni–Si and Al–Ni systems. ► We perform ab initio calculation of thermodynamic properties in the Ni–Si system. ► A CALPHAD–type approach is proposed to model the fcc ordered/disordered transition. ► The Ni–Si system was thermodynamically assessed using the new approach.

Dynamic Flight Simulation Utilizing High Fidelity CFD-Based Nonlinear Reduced Order Model, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The overall technical objective of the Phase I effort is to develop a nonlinear aeroelastic solver utilizing the FUN3D generated nonlinear aerodynamic Reduced Order...

Fast temperature optimization of multi-source hyperthermia applicators with reduced-order modeling of 'virtual sources'

International Nuclear Information System (INIS)

Cheng, K-S; Stakhursky, Vadim; Craciunescu, Oana I; Stauffer, Paul; Dewhirst, Mark; Das, Shiva K

2008-01-01

The goal of this work is to build the foundation for facilitating real-time magnetic resonance image guided patient treatment for heating systems with a large number of physical sources (e.g. antennas). Achieving this goal requires knowledge of how the temperature distribution will be affected by changing each source individually, which requires time expenditure on the order of the square of the number of sources. To reduce computation time, we propose a model reduction approach that combines a smaller number of predefined source configurations (fewer than the number of actual sources) that are most likely to heat tumor. The source configurations consist of magnitude and phase source excitation values for each actual source and may be computed from a CT scan based plan or a simplified generic model of the corresponding patient anatomy. Each pre-calculated source configuration is considered a 'virtual source'. We assume that the actual best source settings can be represented effectively as weighted combinations of the virtual sources. In the context of optimization, each source configuration is treated equivalently to one physical source. This model reduction approach is tested on a patient upper-leg tumor model (with and without temperature-dependent perfusion), heated using a 140 MHz ten-antenna cylindrical mini-annular phased array. Numerical simulations demonstrate that using only a few pre-defined source configurations can achieve temperature distributions that are comparable to those from full optimizations using all physical sources. The method yields close to optimal temperature distributions when using source configurations determined from a simplified model of the tumor, even when tumor position is erroneously assumed to be ∼2.0 cm away from the actual position as often happens in practical clinical application of pre-treatment planning. The method also appears to be robust under conditions of changing, nonlinear, temperature-dependent perfusion. The

Modelling stable atmospheric boundary layers over snow

NARCIS (Netherlands)

Sterk, H.A.M.

2015-01-01

Thesis entitled:

Modelling Stable Atmospheric Boundary Layers over Snow

H.A.M. Sterk

Wageningen, 29th of April, 2015

Summary

The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs

Sliding Mode Control of Diesel Engine Air-path System With Dual-loop EGR and VGT Based on the Reduced-order Model

Directory of Open Access Journals (Sweden)

Kim Sooyoung

2016-01-01

Full Text Available This paper presents the design of a model-based controller for the diesel engine air-path system. The controller is implemented based on a reduced order model consisting of only pressure and power dynamics with practical concerns. To deal with the model uncertainties effectively, a sliding mode controller, which is robust to model uncertainties, is proposed for the air-path system. The control performance of the proposed control scheme is verified through simulation with the valid plant model of a 6,000cc heavy duty diesel engine.

Investigation of the density wave oscillation in ocean motions with reduced order models

International Nuclear Information System (INIS)

Yan, B.H.; Li, R.

2018-01-01

Highlights: •The parameter about the degree of instability is defined. •The results are in satisfactory agreement with experimental results. •The effect of ocean motions on DWO is analyzed quantitatively. •The results are of good universality and generality. -- Abstract: The two phase flow instability is an important phenomenon in nuclear power and thermal systems. In the research and design of small modular reactor, the effect of ocean motions on the two phase flow instability should be evaluated. In this work, the density wave oscillation in a uniformly heated channel in ocean motions is investigated with reduced order model by transforming the partial differential equations to ordinary differential equations. This kind of frequency domain method is complementary to the time domain analysis with system codes, not as alternatives. The parameter about the degree of instability is defined for the quantitative analysis of two phase flow instability. The results are in satisfactory agreement with experimental results. The effect of ocean motions on density wave oscillation in a uniformly heated channel is analyzed quantitatively. The parametric study is also carried out.

A reduced-order representation of the Schrödinger equation

Directory of Open Access Journals (Sweden)

Ming-C. Cheng

2016-09-01

Full Text Available A reduced-order-based representation of the Schrödinger equation is investigated for electron wave functions in semiconductor nanostructures. In this representation, the Schrödinger equation is projected onto an eigenspace described by a small number of basis functions that are generated from the proper orthogonal decomposition (POD. The approach substantially reduces the numerical degrees of freedom (DOF’s needed to numerically solve the Schrödinger equation for the wave functions and eigenstate energies in a quantum structure and offers an accurate solution as detailed as the direct numerical simulation of the Schrödinger equation. To develop such an approach, numerical data accounting for parametric variations of the system are used to perform decomposition in order to generate the POD eigenvalues and eigenvectors for the system. This approach is applied to develop POD models for single and multiple quantum well structure. Errors resulting from the approach are examined in detail associated with the selected numerical DOF’s of the POD model and quality of data used for generation of the POD eigenvalues and basis functions. This study investigates the fundamental concepts of the POD approach to the Schrödinger equation and paves a way toward developing an efficient modeling methodology for large-scale multi-block simulation of quantum nanostructures.

A 3D Fractional-Order Chaotic System with Only One Stable Equilibrium and Controlling Chaos

Directory of Open Access Journals (Sweden)

Shiyun Shen

2017-01-01

Full Text Available One 3D fractional-order chaotic system with only one locally asymptotically stable equilibrium is reported. To verify the chaoticity, the maximum Lyapunov exponent (MAXLE with respect to the fractional-order and chaotic attractors are obtained by numerical calculation for this system. Furthermore, by linear scalar controller consisting of a single state variable, one control scheme for stabilization of the 3D fractional-order chaotic system is suggested. The numerical simulations show the feasibility of the control scheme.

Development of a Reduced-Order Three-Dimensional Flow Model for Thermal Mixing and Stratification Simulation during Reactor Transients

Energy Technology Data Exchange (ETDEWEB)

Hu, Rui

2017-09-03

Mixing, thermal-stratification, and mass transport phenomena in large pools or enclosures play major roles for the safety of reactor systems. Depending on the fidelity requirement and computational resources, various modeling methods, from the 0-D perfect mixing model to 3-D Computational Fluid Dynamics (CFD) models, are available. Each is associated with its own advantages and shortcomings. It is very desirable to develop an advanced and efficient thermal mixing and stratification modeling capability embedded in a modern system analysis code to improve the accuracy of reactor safety analyses and to reduce modeling uncertainties. An advanced system analysis tool, SAM, is being developed at Argonne National Laboratory for advanced non-LWR reactor safety analysis. While SAM is being developed as a system-level modeling and simulation tool, a reduced-order three-dimensional module is under development to model the multi-dimensional flow and thermal mixing and stratification in large enclosures of reactor systems. This paper provides an overview of the three-dimensional finite element flow model in SAM, including the governing equations, stabilization scheme, and solution methods. Additionally, several verification and validation tests are presented, including lid-driven cavity flow, natural convection inside a cavity, laminar flow in a channel of parallel plates. Based on the comparisons with the analytical solutions and experimental results, it is demonstrated that the developed 3-D fluid model can perform very well for a wide range of flow problems.

Linear stability analysis of flow instabilities with a nodalized reduced order model in heated channel

International Nuclear Information System (INIS)

Paul, Subhanker; Singh, Suneet

2015-01-01

The prime objective of the presented work is to develop a Nodalized Reduced Order Model (NROM) to carry linear stability analysis of flow instabilities in a two-phase flow system. The model is developed by dividing the single phase and two-phase region of a uniformly heated channel into N number of nodes followed by time dependent spatial linear approximations for single phase enthalpy and two-phase quality between the consecutive nodes. Moving boundary scheme has been adopted in the model, where all the node boundaries vary with time due to the variation of boiling boundary inside the heated channel. Using a state space approach, the instability thresholds are delineated by stability maps plotted in parameter planes of phase change number (N pch ) and subcooling number (N sub ). The prime feature of the present model is that, though the model equations are simpler due to presence of linear-linear approximations for single phase enthalpy and two-phase quality, yet the results are in good agreement with the existing models (Karve [33]; Dokhane [34]) where the model equations run for several pages and experimental data (Solberg [41]). Unlike the existing ROMs, different two-phase friction factor multiplier correlations have been incorporated in the model. The applicability of various two-phase friction factor multipliers and their effects on stability behaviour have been depicted by carrying a comparative study. It is also observed that the Friedel model for friction factor calculations produces the most accurate results with respect to the available experimental data. (authors)

Model order reduction techniques with applications in finite element analysis

CERN Document Server

Qu, Zu-Qing

2004-01-01

Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardware, simulations are often extremely computationally intensive and time-consuming when full-blown models are under consideration. The need to reduce the computational cost involved when dealing with high-order/many-degree-of-freedom models can be offset by adroit computation. In this light, model-reduction methods have become a major goal of simulation and modeling research. Model reduction can also ameliorate problems in the correlation of widely used finite-element analyses and test analysis models produced by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work in dynamic condensation techniques: - Compares the effectiveness of static, exact, dynamic, SEREP and iterative-dynamic condensation techniques in producing valid reduced-order mo...

Stable and high order accurate difference methods for the elastic wave equation in discontinuous media

KAUST Repository

Duru, Kenneth

2014-12-01

© 2014 Elsevier Inc. In this paper, we develop a stable and systematic procedure for numerical treatment of elastic waves in discontinuous and layered media. We consider both planar and curved interfaces where media parameters are allowed to be discontinuous. The key feature is the highly accurate and provably stable treatment of interfaces where media discontinuities arise. We discretize in space using high order accurate finite difference schemes that satisfy the summation by parts rule. Conditions at layer interfaces are imposed weakly using penalties. By deriving lower bounds of the penalty strength and constructing discrete energy estimates we prove time stability. We present numerical experiments in two space dimensions to illustrate the usefulness of the proposed method for simulations involving typical interface phenomena in elastic materials. The numerical experiments verify high order accuracy and time stability.

On reducibility and ergodicity of population projection matrix models

DEFF Research Database (Denmark)

Stott, Iain; Townley, Stuart; Carslake, David

2010-01-01

from all stages to all other stages) and therefore ergodic (whatever initial stage structure is used in the population projection, it will always exhibit the same stable asymptotic growth rate). 2. Evaluation of 652 PPM models for 171 species from the literature suggests that 24·7% of PPM models...... structure used in the population projection). In our sample of published PPMs, 15·6% are non-ergodic. 3. This presents a problem: reducible–ergodic models often defy biological rationale in their description of the life cycle but may or may not prove problematic for analysis as they often behave similarly...... of reducibility in published PPMs, with significant implications for the predictive power of such models in many cases. We suggest that as a general rule, reducibility of PPM models should be avoided. However, we provide a guide to the pertinent analysis of reducible matrix models, largely based upon whether...

Stable and high order accurate difference methods for the elastic wave equation in discontinuous media

KAUST Repository

Duru, Kenneth; Virta, Kristoffer

2014-01-01

to be discontinuous. The key feature is the highly accurate and provably stable treatment of interfaces where media discontinuities arise. We discretize in space using high order accurate finite difference schemes that satisfy the summation by parts rule. Conditions

Stable Galerkin versus equal-order Galerkin least-squares elements for the stokes flow problem

International Nuclear Information System (INIS)

Franca, L.P.; Frey, S.L.; Sampaio, R.

1989-11-01

Numerical experiments are performed for the stokes flow problem employing a stable Galerkin method and a Galerkin/Least-squares method with equal-order elements. Error estimates for the methods tested herein are reviewed. The numerical results presented attest the good stability properties of all methods examined herein. (A.C.A.S.) [pt

Experimental verifications of a structural damage identification technique using reduced order finite-element model

Science.gov (United States)

Li, Rui; Zhou, Li; Yang, Jann N.

2010-04-01

An objective of the structural health monitoring system is to identify the state of the structure and to detect the damage when it occurs. Analysis techniques for the damage identification of structures, based on vibration data measured from sensors, have received considerable attention. Recently, a new damage tracking technique, referred to as the adaptive quadratic sum-square error (AQSSE) technique, has been proposed, and simulation studies demonstrated that the AQSSE technique is quite effective in identifying structural damages. In this paper, the adaptive quadratic sumsquare error (AQSSE) along with the reduced-order finite-element method is proposed to identify the damages of complex structures. Experimental tests were conducted to verify the capability of the proposed damage detection approach. A series of experimental tests were performed using a scaled cantilever beam subject to the white noise and sinusoidal excitations. The capability of the proposed reduced-order finite-element based adaptive quadratic sum-square error (AQSSE) method in detecting the structural damage is demonstrated by the experimental results.

CFD simulations and reduced order modeling of a refrigerator compartment including radiation effects

International Nuclear Information System (INIS)

Bayer, Ozgur; Oskay, Ruknettin; Paksoy, Akin; Aradag, Selin

2013-01-01

Highlights: ► Free convection in a refrigerator is simulated including radiation effects. ► Heat rates are affected drastically when radiation effects are considered. ► 95% of the flow energy can be represented by using one spatial POD mode. - Abstract: Considering the engineering problem of natural convection in domestic refrigerator applications, this study aims to simulate the fluid flow and temperature distribution in a single commercial refrigerator compartment by using the experimentally determined temperature values as the specified constant wall temperature boundary conditions. The free convection in refrigerator applications is evaluated as a three-dimensional (3D), turbulent, transient and coupled non-linear flow problem. Radiation heat transfer mode is also included in the analysis. According to the results, taking radiation effects into consideration does not change the temperature distribution inside the refrigerator significantly; however the heat rates are affected drastically. The flow inside the compartment is further analyzed with a reduced order modeling method called Proper Orthogonal Decomposition (POD) and the energy contents of several spatial and temporal modes that exist in the flow are examined. The results show that approximately 95% of all the flow energy can be represented by only using one spatial mode

Reduced order modeling and parameter identification of a building energy system model through an optimization routine

International Nuclear Information System (INIS)

Harish, V.S.K.V.; Kumar, Arun

2016-01-01

Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.

Multi-Zone hybrid model for failure detection of the stable ventilation systems

DEFF Research Database (Denmark)

Gholami, Mehdi; Schiøler, Henrik; Soltani, Mohsen

2010-01-01

In this paper, a conceptual multi-zone model for climate control of a live stock building is elaborated. The main challenge of this research is to estimate the parameters of a nonlinear hybrid model. A recursive estimation algorithm, the Extended Kalman Filter (EKF) is implemented for estimation....... Since the EKF is sensitive to the initial guess, in the following the estimation process is split up into simple parts and approximate parameters are found with a non recursive least squares method in order to provide good initial values. Results based on experiments from a real life stable facility...

Flapping Wings of an Inclined Stroke Angle: Experiments and Reduced-Order Models in Dual Aerial/Aquatic Flight

Science.gov (United States)

Izraelevitz, Jacob; Triantafyllou, Michael

2016-11-01

Flapping wings in nature demonstrate a large force actuation envelope, with capabilities beyond the limits of static airfoil section coefficients. Puffins, guillemots, and other auks particularly showcase this mechanism, as they are able to both generate both enough thrust to swim and lift to fly, using the same wing, by changing the wing motion trajectory. The wing trajectory is therefore an additional design criterion to be optimized along with traditional aircraft parameters, and could possibly enable dual aerial/aquatic flight. We showcase finite aspect-ratio flapping wing experiments, dynamic similarity arguments, and reduced-order models for predicting the performance of flapping wings that carry out complex motion trajectories.

A Model Describing Stable Coherent Synchrotron Radiation in Storage Rings

International Nuclear Information System (INIS)

Sannibale, F.

2004-01-01

We present a model describing high power stable broadband coherent synchrotron radiation (CSR) in the terahertz frequency region in an electron storage ring. The model includes distortion of bunch shape from the synchrotron radiation (SR), which enhances higher frequency coherent emission, and limits to stable emission due to an instability excited by the SR wakefield. It gives a quantitative explanation of several features of the recent observations of CSR at the BESSY II storage ring. We also use this model to optimize the performance of a source for stable CSR emission

A model describing stable coherent synchrotron radiation in storage rings

International Nuclear Information System (INIS)

Sannibale, F.; Byrd, J.M.; Loftsdottir, A.; Venturini, M.; Abo-Bakr, M.; Feikes, J.; Holldack, K.; Kuske, P.; Wuestefeld, G.; Huebers, H.-W.; Warnock, R.

2004-01-01

We present a model describing high power stable broadband coherent synchrotron radiation (CSR) in the terahertz frequency region in an electron storage ring. The model includes distortion of bunch shape from the synchrotron radiation (SR), which enhances higher frequency coherent emission, and limits to stable emission due to an instability excited by the SR wakefield. It gives a quantitative explanation of several features of the recent observations of CSR at the BESSY II storage ring. We also use this model to optimize the performance of a source for stable CSR emission

Model-order reduction of lumped parameter systems via fractional calculus

Science.gov (United States)

Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio

2018-04-01

This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang; Youssef, Marzouk; Willcox, Karen

2014-01-01

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce

Lattice Boltzmann flow simulations with applications of reduced order modeling techniques

KAUST Repository

Brown, Donald

2014-01-01

With the recent interest in shale gas, an understanding of the flow mechanisms at the pore scale and beyond is necessary, which has attracted a lot of interest from both industry and academia. One of the suggested algorithms to help understand flow in such reservoirs is the Lattice Boltzmann Method (LBM). The primary advantage of LBM is its ability to approximate complicated geometries with simple algorithmic modificatoins. In this work, we use LBM to simulate the flow in a porous medium. More specifically, we use LBM to simulate a Brinkman type flow. The Brinkman law allows us to integrate fast free-flow and slow-flow porous regions. However, due to the many scales involved and complex heterogeneities of the rock microstructure, the simulation times can be long, even with the speed advantage of using an explicit time stepping method. The problem is two-fold, the computational grid must be able to resolve all scales and the calculation requires a steady state solution implying a large number of timesteps. To help reduce the computational complexity and total simulation times, we use model reduction techniques to reduce the dimension of the system. In this approach, we are able to describe the dynamics of the flow by using a lower dimensional subspace. In this work, we utilize the Proper Orthogonal Decomposition (POD) technique, to compute the dominant modes of the flow and project the solution onto them (a lower dimensional subspace) to arrive at an approximation of the full system at a lowered computational cost. We present a few proof-of-concept examples of the flow field and the corresponding reduced model flow field.

A reduced order aerothermodynamic modeling framework for hypersonic vehicles based on surrogate and POD

Directory of Open Access Journals (Sweden)

Chen Xin

2015-10-01

Full Text Available Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, computation fluid dynamics (CFD and experimental investigation, a reduced order modeling (ROM framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design is developed. Both proper orthogonal decomposition (POD and surrogate are considered and compared to construct ROMs. Two surrogate approaches named Kriging and optimized radial basis function (ORBF are utilized to construct ROMs. Furthermore, an enhanced algorithm of fast maximin Latin hypercube design is proposed, which proves to be helpful to improve the precisions of ROMs. Test results for the three-dimensional aerothermodynamic over a hypersonic surface indicate that: the ROMs precision based on Kriging is better than that by ORBF, ROMs based on Kriging are marginally more accurate than ROMs based on POD-Kriging. In a word, the ROM framework for hypersonic aerothermodynamics has good precision and efficiency.

A stable high-order perturbation of surfaces method for numerical simulation of diffraction problems in triply layered media

Energy Technology Data Exchange (ETDEWEB)

Hong, Youngjoon, E-mail: hongy@uic.edu; Nicholls, David P., E-mail: davidn@uic.edu

2017-02-01

The accurate numerical simulation of linear waves interacting with periodic layered media is a crucial capability in engineering applications. In this contribution we study the stable and high-order accurate numerical simulation of the interaction of linear, time-harmonic waves with a periodic, triply layered medium with irregular interfaces. In contrast with volumetric approaches, High-Order Perturbation of Surfaces (HOPS) algorithms are inexpensive interfacial methods which rapidly and recursively estimate scattering returns by perturbation of the interface shape. In comparison with Boundary Integral/Element Methods, the stable HOPS algorithm we describe here does not require specialized quadrature rules, periodization strategies, or the solution of dense non-symmetric positive definite linear systems. In addition, the algorithm is provably stable as opposed to other classical HOPS approaches. With numerical experiments we show the remarkable efficiency, fidelity, and accuracy one can achieve with an implementation of this algorithm.

A Stable-Matching-Based User Linking Method with User Preference Order

Directory of Open Access Journals (Sweden)

Xuzhong Wang

2017-01-01

Full Text Available With the development of social networks, more and more users choose to use multiple accounts from different networks to meet their needs. Linking a particular user’s multiple accounts not only can improve user’s experience of the net-services such as recommender system, but also plays a significant role in network security. However, multiple accounts of the same user are often not directly linked to each other, and further, the privacy policy provided by the service provider makes it harder to find accounts for a particular user. In this paper, we propose a stable-matching-based method with user preference order for the problem of low accuracy of user linking in cross-media sparse data. Different from the traditional way which just calculates the similarity of accounts, we take full account of the mutual influence among multiple accounts by regarding different networks as bilateral (multilateral market and user linking as a stable matching problem in such a market. Based on the combination of Game-Theoretic Machine Learning and Pairwise, a novel user linking method has been proposed. The experiment shows that our method has a 21.6% improvement in accuracy compared with the traditional linking method and a further increase of about 7.8% after adding the prior knowledge.

Stochastic reduced-order model for an automotive vehicle in presence of numerous local elastic modes in the low-frequency range

OpenAIRE

Arnoux , A.; Batou , Anas; Soize , Christian; Gagliardini , L.

2012-01-01

International audience; This paper is devoted to the construction of a stochastic reduced-order model for dynamical structures having a high modal density in the low-frequency range, such as an automotive vehicle. This type of structure is characterized by the fact that it exhibits, in the low-frequency range, not only the classical global elastic modes but also numerous local elastic modes which cannot easily be separated from the global elastic modes. An approach has recently been proposed ...

Classification of stable solutions for non-homogeneous higher-order elliptic PDEs

Directory of Open Access Journals (Sweden)

Abdellaziz Harrabi

2017-04-01

Full Text Available Abstract Under some assumptions on the nonlinearity f, we will study the nonexistence of nontrivial stable solutions or solutions which are stable outside a compact set of R n $\\mathbb {R}^{n}$ for the following semilinear higher-order problem: ( − Δ k u = f ( u in  R n , $$\\begin{aligned} (-\\Delta^{k} u= f(u \\quad \\mbox{in }\\mathbb {R}^{n}, \\end{aligned}$$ with k = 1 , 2 , 3 , 4 $k=1,2,3,4$ . The main methods used are the integral estimates and the Pohozaev identity. Many classes of nonlinearity will be considered; even the sign-changing nonlinearity, which has an adequate subcritical growth at zero as for example f ( u = − m u + λ | u | θ − 1 u − μ | u | p − 1 u $f(u= -m u +\\lambda|u|^{\\theta-1}u-\\mu |u|^{p-1}u$ , where m ≥ 0 $m\\geq0$ , λ > 0 $\\lambda>0$ , μ > 0 $\\mu>0$ , p , θ > 1 $p, \\theta>1$ . More precisely, we shall revise the nonexistence theorem of Berestycki and Lions (Arch. Ration. Mech. Anal. 82:313-345, 1983 in the class of smooth finite Morse index solutions as the well known work of Bahri and Lions (Commun. Pure Appl. Math. 45:1205-1215, 1992. Also, the case when f ( u u $f(uu$ is a nonnegative function will be studied under a large subcritical growth assumption at zero, for example f ( u = | u | θ − 1 u ( 1 + | u | q $f(u=|u|^{\\theta-1}u(1 + |u|^{q}$ or f ( u = | u | θ − 1 u e | u | q $f(u= |u|^{\\theta-1}u e^{|u|^{q}}$ , θ > 1 $\\theta>1$ and q > 0 $q>0$ . Extensions to solutions which are merely stable are discussed in the case of supercritical growth with k = 1 $k=1$ .

Stable CSR in storage rings: A model

International Nuclear Information System (INIS)

Sannibale, Fernando; Byrd, John M.; Loftsdottir, Agusta; Venturini, Marco; Abo-Bakr, Michael; Feikes, Jorge; Holldack, Karsten; Kuske, Peter; Wustefeld, Godehart; Hubers, Heinz-Willerm; Warnock, Robert

2005-01-01

A comprehensive historical view of the work done on coherent synchrotron radiation (CSR) in storage rings is given in reference [1]. Here we want just to point out that even if the issue of CSR in storage rings was already discussed over 50 years ago, it is only recently that a considerable number of observations have been reported. In fact, intense bursts of coherent synchrotron radiation with a stochastic character were measured in the terahertz frequency range, at several synchrotron light source storage rings [2-8]. It has been shown [8-11], that this bursting emission of CSR is associated with a single bunch instability, usually referred as microbunching instability (MBI), driven by the fields of the synchrotron radiation emitted by the bunch itself. Of remarkably different characteristics was the CSR emission observed at BESSY II in Berlin, when the storage ring was tuned into a special low momentum compaction mode [12, 13]. In fact, the emitted radiation was not the quasi-random bursting observed in the other machines, but a powerful and stable flux of broadband CSR in the terahertz range. This was an important result, because it experimentally demonstrated the concrete possibility of constructing a stable broadband source with extremely high power in the terahertz region. Since the publication of the first successful experiment using the ring as a CSR source [14], BESSY II has regular scheduled user s shifts dedicated to CSR experiments. At the present time, several other laboratories are investigating the possibility of a CSR mode of operation [15-17] and a design for a new ring optimized for CSR is at an advanced stage [18]. In what follows, we describe a model that first accounts for the BESSY II observations and then indicates that the special case of BESSY II is actually quite general and typical when relativistic electron storage rings are tuned for short bunches. The model provides a scheme for predicting and optimizing the performance of ring

Stable CSR in Storage Rings: A Model

International Nuclear Information System (INIS)

Sannibale, F.

2005-01-01

A comprehensive historical view of the work done on coherent synchrotron radiation (CSR) in storage rings is given in reference [1]. Here we want just to point out that even if the issue of CSR in storage rings was already discussed over 50 years ago, it is only recently that a considerable number of observations have been reported. In fact, intense bursts of coherent synchrotron radiation with a stochastic character were measured in the terahertz frequency range, at several synchrotron light source storage rings [2-8]. It has been shown [8-11], that this bursting emission of CSR is associated with a single bunch instability, usually referred as microbunching instability (MBI), driven by the fields of the synchrotron radiation emitted by the bunch itself. Of remarkably different characteristics was the CSR emission observed at BESSY II in Berlin, when the storage ring was tuned into a special low momentum compaction mode [12, 13]. In fact, the emitted radiation was not the quasi-random bursting observed in the other machines, but a powerful and stable flux of broadband CSR in the terahertz range. This was an important result, because it experimentally demonstrated the concrete possibility of constructing a stable broadband source with extremely high power in the terahertz region. Since the publication of the first successful experiment using the ring as a CSR source [14], BESSY II has regular scheduled user's shifts dedicated to CSR experiments. At the present time, several other laboratories are investigating the possibility of a CSR mode of operation [15-17] and a design for a new ring optimized for CSR is at an advanced stage [18]. In what follows, we describe a model that first accounts for the BESSY II observations and then indicates that the special case of BESSY II is actually quite general and typical when relativistic electron storage rings are tuned for short bunches. The model provides a scheme for predicting and optimizing the performance of ring

Stable lattice Boltzmann model for Maxwell equations in media

Science.gov (United States)

Hauser, A.; Verhey, J. L.

2017-12-01

The present work shows a method for stable simulations via the lattice Boltzmann (LB) model for electromagnetic waves (EM) transiting homogeneous media. LB models for such media were already presented in the literature, but they suffer from numerical instability when the media transitions are sharp. We use one of these models in the limit of pure vacuum derived from Liu and Yan [Appl. Math. Model. 38, 1710 (2014), 10.1016/j.apm.2013.09.009] and apply an extension that treats the effects of polarization and magnetization separately. We show simulations of simple examples in which EM waves travel into media to quantify error scaling, stability, accuracy, and time scaling. For conductive media, we use the Strang splitting and check the simulations accuracy at the example of the skin effect. Like pure EM propagation, the error for the static limits, which are constructed with a current density added in a first-order scheme, can be less than 1 % . The presented method is an easily implemented alternative for the stabilization of simulation for EM waves propagating in spatially complex structured media properties and arbitrary transitions.

Synchronization in reduced-order of chaotic systems via control approaches based on high-order sliding-mode observer

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, A. [Electrical Engineering Doctoral Program, Mechanical and Electrical Engineering Faculty, Autonomous University of Nuevo Leon, 66450 San Nicolas de los Garza, N.L. (Mexico)], E-mail: angelrdz@gmail.com; De Leon, J. [Electrical Engineering Doctoral Program, Mechanical and Electrical Engineering Faculty, Autonomous University of Nuevo Leon, 66450 San Nicolas de los Garza, N.L. (Mexico)], E-mail: drjleon@gmail.com; Fridman, L. [Department of Control, Division of Electrical Engineering, Engineering Faculty, National Autonomous University of Mexico, 04510 Mexico City (Mexico)], E-mail: lfridman@servidor.unam.mx

2009-12-15

The reduced-order synchronization problem of two chaotic systems (master-slave) with different dimension and relative degree is considered. A control scheme based on a high-order sliding-mode observer-identifier and a feedback state controller is proposed, where the trajectories of slave can be synchronized with a canonical projection of the master. Thus, the reduced-order synchronization is achieved in spite of master/slave mismatches. Simulation results are provided in order to illustrate the performance of the proposed synchronization scheme.

Synchronization in reduced-order of chaotic systems via control approaches based on high-order sliding-mode observer

International Nuclear Information System (INIS)

Rodriguez, A.; De Leon, J.; Fridman, L.

2009-01-01

The reduced-order synchronization problem of two chaotic systems (master-slave) with different dimension and relative degree is considered. A control scheme based on a high-order sliding-mode observer-identifier and a feedback state controller is proposed, where the trajectories of slave can be synchronized with a canonical projection of the master. Thus, the reduced-order synchronization is achieved in spite of master/slave mismatches. Simulation results are provided in order to illustrate the performance of the proposed synchronization scheme.

Reducing equifinality using isotopes in a process-based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

Science.gov (United States)

Ford, William I.; Fox, James F.; Pollock, Erik

2017-08-01

The fate of bioavailable nitrogen species transported through agricultural landscapes remains highly uncertain given complexities of measuring fluxes impacting the fluvial N cycle. We present and test a new numerical model named Technology for Removable Annual Nitrogen in Streams For Ecosystem Restoration (TRANSFER), which aims to reduce model uncertainty due to erroneous parameterization, i.e., equifinality, in stream nitrogen cycle assessment and quantify the significance of transient and permanent removal pathways. TRANSFER couples nitrogen elemental and stable isotope mass-balance equations with existing hydrologic, hydraulic, sediment transport, algal biomass, and sediment organic matter mass-balance subroutines and a robust GLUE-like uncertainty analysis. We test the model in an agriculturally impacted, third-order stream reach located in the Bluegrass Region of Central Kentucky. Results of the multiobjective model evaluation for the model application highlight the ability of sediment nitrogen fingerprints including elemental concentrations and stable N isotope signatures to reduce equifinality of the stream N model. Advancements in the numerical simulations allow for illumination of the significance of algal sloughing fluxes for the first time in relation to denitrification. Broadly, model estimates suggest that denitrification is slightly greater than algal N sloughing (10.7% and 6.3% of dissolved N load on average), highlighting the potential for overestimation of denitrification by 37%. We highlight the significance of the transient N pool given the potential for the N store to be regenerated to the water column in downstream reaches, leading to harmful and nuisance algal bloom development.

Structure of acid-stable carmine.

Science.gov (United States)

Sugimoto, Naoki; Kawasaki, Yoko; Sato, Kyoko; Aoki, Hiromitsu; Ichi, Takahito; Koda, Takatoshi; Yamazaki, Takeshi; Maitani, Tamio

2002-02-01

Acid-stable carmine has recently been distributed in the U.S. market because of its good acid stability, but it is not permitted in Japan. We analyzed and determined the structure of the major pigment in acid-stable carmine, in order to establish an analytical method for it. Carminic acid was transformed into a different type of pigment, named acid-stable carmine, through amination when heated in ammonia solution. The features of the structure were clarified using a model compound, purpurin, in which the orientation of hydroxyl groups on the A ring of the anthraquinone skeleton is the same as that of carminic acid. By spectroscopic means and the synthesis of acid-stable carmine and purpurin derivatives, the structure of the major pigment in acid-stable carmine was established as 4-aminocarminic acid, a novel compound.

Investigating Uranium Mobility Using Stable Isotope Partitioning of 238U/235U and a Reactive Transport Model

Science.gov (United States)

Bizjack, M.; Johnson, T. M.; Druhan, J. L.; Shiel, A. E.

2015-12-01

We report a numerical reactive transport model which explicitly incorporates the effectively stable isotopes of uranium (U) and the factors that influence their partitioning in bioactive systems. The model reproduces trends observed in U isotope ratios and concentration measurements from a field experiment, thereby improving interpretations of U isotope ratios as a tracer for U reactive transport. A major factor contributing to U storage and transport is its redox state, which is commonly influenced by the availability of organic carbon to support metal-reducing microbial communities. Both laboratory and field experiments have demonstrated that biogenic reduction of U(VI) fractionates the stable isotope ratio 238U/235U, producing an isotopically heavy solid U(IV) product. It has also been shown that other common reactive transport processes involving U do not fractionate isotopes to a consistently measurable level, which suggests the capacity to quantify the extent of bioreduction occurring in groundwater containing U using 238U/235U ratios. A recent study of a U bioremediation experiment at the Rifle IFRC site (Colorado, USA) applied Rayleigh distillation models to quantify U stable isotope fractionation observed during acetate amendment. The application of these simplified models were fit to the observations only by invoking a "memory-effect," or a constant source of low-concentration, unfractionated U(VI). In order to more accurately interpret the measured U isotope ratios, we present a multi-component reactive transport model using the CrunchTope software. This approach is capable of quantifying the cycling and partitioning of individual U isotopes through a realistic network of transport and reaction pathways including reduction, oxidation, and microbial growth. The model incorporates physical heterogeneity of the aquifer sediments through zones of decreased permeability, which replicate the observed bromide tracer, major ion chemistry, U concentration, and U

Reduced-order aeroelastic model for limit-cycle oscillations in vortex-dominated unsteady airfoil flows

Science.gov (United States)

Suresh Babu, Arun Vishnu; Ramesh, Kiran; Gopalarathnam, Ashok

2017-11-01

In previous research, Ramesh et al. (JFM,2014) developed a low-order discrete vortex method for modeling unsteady airfoil flows with intermittent leading edge vortex (LEV) shedding using a leading edge suction parameter (LESP). LEV shedding is initiated using discrete vortices (DVs) whenever the Leading Edge Suction Parameter (LESP) exceeds a critical value. In subsequent research, the method was successfully employed by Ramesh et al. (JFS, 2015) to predict aeroelastic limit-cycle oscillations in airfoil flows dominated by intermittent LEV shedding. When applied to flows that require large number of time steps, the computational cost increases due to the increasing vortex count. In this research, we apply an amalgamation strategy to actively control the DV count, and thereby reduce simulation time. A pair each of LEVs and TEVs are amalgamated at every time step. The ideal pairs for amalgamation are identified based on the requirement that the flowfield in the vicinity of the airfoil is least affected (Spalart, 1988). Instead of placing the amalgamated vortex at the centroid, we place it at an optimal location to ensure that the leading-edge suction and the airfoil bound circulation are conserved. Results of the initial study are promising.

Simplified Predictive Models for CO₂ Sequestration Performance Assessment: Research Topical Report on Task #4 - Reduced-Order Method (ROM) Based Models

Energy Technology Data Exchange (ETDEWEB)

Mishra, Srikanta; Jin, Larry; He, Jincong; Durlofsky, Louis

2015-06-30

Reduced-order models provide a means for greatly accelerating the detailed simulations that will be required to manage CO₂ storage operations. In this work, we investigate the use of one such method, POD-TPWL, which has previously been shown to be effective in oil reservoir simulation problems. This method combines trajectory piecewise linearization (TPWL), in which the solution to a new (test) problem is represented through a linearization around the solution to a previously-simulated (training) problem, with proper orthogonal decomposition (POD), which enables solution states to be expressed in terms of a relatively small number of parameters. We describe the application of POD-TPWL for CO₂-water systems simulated using a compositional procedure. Stanford’s Automatic Differentiation-based General Purpose Research Simulator (AD-GPRS) performs the full-order training simulations and provides the output (derivative matrices and system states) required by the POD-TPWL method. A new POD-TPWL capability introduced in this work is the use of horizontal injection wells that operate under rate (rather than bottom-hole pressure) control. Simulation results are presented for CO₂ injection into a synthetic aquifer and into a simplified model of the Mount Simon formation. Test cases involve the use of time-varying well controls that differ from those used in training runs. Results of reasonable accuracy are consistently achieved for relevant well quantities. Runtime speedups of around a factor of 370 relative to full- order AD-GPRS simulations are achieved, though the preprocessing needed for POD-TPWL model construction corresponds to the computational requirements for about 2.3 full-order simulation runs. A preliminary treatment for POD-TPWL modeling in which test cases differ from training runs in terms of geological parameters (rather than well controls) is also presented. Results in this case involve only small differences between

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang

2014-01-06

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.

Reduced-order modellin for high-pressure transient flow of hydrogen-natural gas mixture

Science.gov (United States)

Agaie, Baba G.; Khan, Ilyas; Alshomrani, Ali Saleh; Alqahtani, Aisha M.

2017-05-01

In this paper the transient flow of hydrogen compressed-natural gas (HCNG) mixture which is also referred to as hydrogen-natural gas mixture in a pipeline is numerically computed using the reduced-order modelling technique. The study on transient conditions is important because the pipeline flows are normally in the unsteady state due to the sudden opening and closure of control valves, but most of the existing studies only analyse the flow in the steady-state conditions. The mathematical model consists in a set of non-linear conservation forms of partial differential equations. The objective of this paper is to improve the accuracy in the prediction of the HCNG transient flow parameters using the Reduced-Order Modelling (ROM). The ROM technique has been successfully used in single-gas and aerodynamic flow problems, the gas mixture has not been done using the ROM. The study is based on the velocity change created by the operation of the valves upstream and downstream the pipeline. Results on the flow characteristics, namely the pressure, density, celerity and mass flux are based on variations of the mixing ratio and valve reaction and actuation time; the ROM computational time cost advantage are also presented.

Application of Reduced Order Transonic Aerodynamic Influence Coefficient Matrix for Design Optimization

Science.gov (United States)

Pak, Chan-gi; Li, Wesley W.

2009-01-01

Supporting the Aeronautics Research Mission Directorate guidelines, the National Aeronautics and Space Administration [NASA] Dryden Flight Research Center is developing a multidisciplinary design, analysis, and optimization [MDAO] tool. This tool will leverage existing tools and practices, and allow the easy integration and adoption of new state-of-the-art software. Today s modern aircraft designs in transonic speed are a challenging task due to the computation time required for the unsteady aeroelastic analysis using a Computational Fluid Dynamics [CFD] code. Design approaches in this speed regime are mainly based on the manual trial and error. Because of the time required for unsteady CFD computations in time-domain, this will considerably slow down the whole design process. These analyses are usually performed repeatedly to optimize the final design. As a result, there is considerable motivation to be able to perform aeroelastic calculations more quickly and inexpensively. This paper will describe the development of unsteady transonic aeroelastic design methodology for design optimization using reduced modeling method and unsteady aerodynamic approximation. The method requires the unsteady transonic aerodynamics be represented in the frequency or Laplace domain. Dynamically linear assumption is used for creating Aerodynamic Influence Coefficient [AIC] matrices in transonic speed regime. Unsteady CFD computations are needed for the important columns of an AIC matrix which corresponded to the primary modes for the flutter. Order reduction techniques, such as Guyan reduction and improved reduction system, are used to reduce the size of problem transonic flutter can be found by the classic methods, such as Rational function approximation, p-k, p, root-locus etc. Such a methodology could be incorporated into MDAO tool for design optimization at a reasonable computational cost. The proposed technique is verified using the Aerostructures Test Wing 2 actually designed

A model of the transverse modes of stable and unstable porro-prism resonators using symmetry considerations

Science.gov (United States)

Burger, Liesl; Forbes, Andrew

2007-09-01

A simple model of a Porro prism laser resonator has been found to correctly predict the formation of the "petal" mode patterns typical of these resonators. A geometrical analysis of the petals suggests that these petals are the lowest-order modes of this type of resonator. Further use of the model reveals the formation of more complex beam patterns, and the nature of these patterns is investigated. Also, the output of stable and unstable resonator modes is presented.

Index-aware model order reduction : LTI DAEs in electric networks

NARCIS (Netherlands)

Banagaaya, N.; Schilders, W.H.A.; Ali, G.; Tischendorf, C.

2014-01-01

Purpose Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues. Design/methodology/approach Most methods first do an index reduction before reducing a

Reduced-Order Direct Numerical Simulation of Solute Transport in Porous Media

Science.gov (United States)

Mehmani, Yashar; Tchelepi, Hamdi

2017-11-01

Pore-scale models are an important tool for analyzing fluid dynamics in porous materials (e.g., rocks, soils, fuel cells). Current direct numerical simulation (DNS) techniques, while very accurate, are computationally prohibitive for sample sizes that are statistically representative of the porous structure. Reduced-order approaches such as pore-network models (PNM) aim to approximate the pore-space geometry and physics to remedy this problem. Predictions from current techniques, however, have not always been successful. This work focuses on single-phase transport of a passive solute under advection-dominated regimes and delineates the minimum set of approximations that consistently produce accurate PNM predictions. Novel network extraction (discretization) and particle simulation techniques are developed and compared to high-fidelity DNS simulations for a wide range of micromodel heterogeneities and a single sphere pack. Moreover, common modeling assumptions in the literature are analyzed and shown that they can lead to first-order errors under advection-dominated regimes. This work has implications for optimizing material design and operations in manufactured (electrodes) and natural (rocks) porous media pertaining to energy systems. This work was supported by the Stanford University Petroleum Research Institute for Reservoir Simulation (SUPRI-B).

A Compact Unconditionally Stable Method for Time-Domain Maxwell's Equations

Directory of Open Access Journals (Sweden)

Zhuo Su

2013-01-01

Full Text Available Higher order unconditionally stable methods are effective ways for simulating field behaviors of electromagnetic problems since they are free of Courant-Friedrich-Levy conditions. The development of accurate schemes with less computational expenditure is desirable. A compact fourth-order split-step unconditionally-stable finite-difference time-domain method (C4OSS-FDTD is proposed in this paper. This method is based on a four-step splitting form in time which is constructed by symmetric operator and uniform splitting. The introduction of spatial compact operator can further improve its performance. Analyses of stability and numerical dispersion are carried out. Compared with noncompact counterpart, the proposed method has reduced computational expenditure while keeping the same level of accuracy. Comparisons with other compact unconditionally-stable methods are provided. Numerical dispersion and anisotropy errors are shown to be lower than those of previous compact unconditionally-stable methods.

Stable-label intravenous glucose tolerance test minimal model

International Nuclear Information System (INIS)

Avogaro, A.; Bristow, J.D.; Bier, D.M.; Cobelli, C.; Toffolo, G.

1989-01-01

The minimal model approach to estimating insulin sensitivity (Sl) and glucose effectiveness in promoting its own disposition at basal insulin (SG) is a powerful tool that has been underutilized given its potential applications. In part, this has been due to its inability to separate insulin and glucose effects on peripheral uptake from their effects on hepatic glucose inflow. Prior enhancements, with radiotracer labeling of the dosage, permit this separation but are unsuitable for use in pregnancy and childhood. In this study, we labeled the intravenous glucose tolerance test (IVGTT) dosage with [6,6- 2 H 2 ]glucose, [2- 2 H]glucose, or both stable isotopically labeled glucose tracers and modeled glucose kinetics in six postabsorptive, nonobese adults. As previously found with the radiotracer model, the tracer-estimated S*l derived from the stable-label IVGTT was greater than Sl in each case except one, and the tracer-estimated SG* was less than SG in each instance. More importantly, however, the stable-label IVGTT estimated each parameter with an average precision of +/- 5% (range 3-9%) compared to average precisions of +/- 74% (range 7-309%) for SG and +/- 22% (range 3-72%) for Sl. In addition, because of the different metabolic fates of the two deuterated tracers, there were minor differences in basal insulin-derived measures of glucose effectiveness, but these differences were negligible for parameters describing insulin-stimulated processes. In conclusion, the stable-label IVGTT is a simple, highly precise means of assessing insulin sensitivity and glucose effectiveness at basal insulin that can be used to measure these parameters in individuals of all ages, including children and pregnant women

Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

DEFF Research Database (Denmark)

Giacobello, Daniele; Christensen, Mads Græsbøll; Jensen, Tobias Lindstrøm

2014-01-01

In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate...... saturations when this is used to synthesize speech. In this paper, we introduce two new methods to obtain intrinsically stable predictors with the 1-norm minimization. The first method is based on constraining the roots of the predictor to lie within the unit circle by reducing the numerical range...... based linear prediction for modeling and coding of speech....

Low-order aeroelastic models of wind turbines for controller design

DEFF Research Database (Denmark)

Sønderby, Ivan Bergquist

Wind turbine controllers are used to optimize the performance of wind turbines such as to reduce power variations and fatigue and extreme loads on wind turbine components. Accurate tuning and design of modern controllers must be done using low-order models that accurately captures the aeroelastic...... response of the wind turbine. The purpose of this thesis is to investigate the necessary model complexity required in aeroelastic models used for controller design and to analyze and propose methods to design low-order aeroelastic wind turbine models that are suited for model-based control design....... The thesis contains a characterization of the dynamics that influence the open-loop aeroelastic frequency response of a modern wind turbine, based on a high-order aeroelastic wind turbine model. One main finding is that the transfer function from collective pitch to generator speed is affected by two low...

Extremely Stable Polypyrrole Achieved via Molecular Ordering for Highly Flexible Supercapacitors.

Science.gov (United States)

Huang, Yan; Zhu, Minshen; Pei, Zengxia; Huang, Yang; Geng, Huiyuan; Zhi, Chunyi

2016-01-27

The cycling stability of flexible supercapacitors with conducting polymers as electrodes is limited by the structural breakdown arising from repetitive counterion flow during charging/discharging. Supercapacitors made of facilely electropolymerized polypyrrole (e-PPy) have ultrahigh capacitance retentions of more than 97, 91, and 86% after 15000, 50000, and 100000 charging/discharging cycles, respectively, and can sustain more than 230000 charging/discharging cycles with still approximately half of the initial capacitance retained. To the best of our knowledge, such excellent long-term cycling stability was never reported. The fully controllable electropolymerization shows superiority in molecular ordering, favoring uniform stress distribution and charge transfer. Being left at ambient conditions for even 8 months, e-PPy supercapacitors completely retain the good electrochemical performance. The extremely stable supercapacitors with excellent flexibility and scalability hold considerable promise for the commerical application of flexible and wearable electronics.

Fabrication and characterization of stable superhydrophobic surface with good friction-reducing performance on Al foil

Energy Technology Data Exchange (ETDEWEB)

Li, Peipei [Key Laboratory of Ministry of Education for Special Functional Materials, Henan University, Kaifeng 475004 (China); Chen, Xinhua, E-mail: xuc0374@hotmail.com [College of Chemistry and Chemical Engineering, Xuchang University, Xuchang 461000 (China); Yang, Guangbin; Yu, Laigui [Key Laboratory of Ministry of Education for Special Functional Materials, Henan University, Kaifeng 475004 (China); Zhang, Pingyu, E-mail: pingyu@henu.edu.cn [Key Laboratory of Ministry of Education for Special Functional Materials, Henan University, Kaifeng 475004 (China)

2014-05-01

Graphical abstract: A lotus-leaf-like hierarchical structure was successfully created on Al foil by a facile three-step solution–immersion method. As-obtained etched-immersed Al/STA rough surface contains interconnected convex–concave micro-structure and uniformly distributed nano-sheets that endow the surface with excellent superhydrophobicity (WCA: 164.2°; WSA: below 5°). Besides, the as-prepared etched-immersed Al/STA superhydrophobic surface on Al foil exhibits good friction-reducing ability and stable superhydrophobicity. - Highlights: • A stable superhydrophobic surface was created on aluminum foil by a facile three-step solution–immersion method. • A lotus-leaf-like hierarchical structure consists of interconnected convex–concave micro-structure and uniformly distributed nano-sheets has been constructed on the aluminum surface. • The superhydrophobic surfaces on aluminum substrate showing effective friction-reducing performance and self-cleaning ability. - Abstract: A lotus-leaf-like hierarchical structure with superhydrophobicity was created on Al foil by a facile three-step solution–immersion method involving etching in hydrochloric acid solution and immersing in hot water as well as surface-modification by stearic acid (denoted as STA). As-prepared etched-immersed Al/STA rough surface was characterized by means of scanning electron microscopy and X-ray photoelectron spectroscopy. Moreover, the water contact angles and water sliding angles of as-prepared etched-immersed Al/STA rough surface were measured, and the friction-reducing performance and self-cleaning ability of the as-prepared surface were also evaluated. Results indicate that the etched-immersed Al/STA rough surface consists of interconnected convex–concave micro-structure and uniformly distributed nano-sheets. Besides, it exhibits stable superhydrophobicity and good friction-reducing ability. Namely, it has a contact angle of water as high as 164.2° and a water sliding

Fabrication and characterization of stable superhydrophobic surface with good friction-reducing performance on Al foil

International Nuclear Information System (INIS)

Li, Peipei; Chen, Xinhua; Yang, Guangbin; Yu, Laigui; Zhang, Pingyu

2014-01-01

Graphical abstract: A lotus-leaf-like hierarchical structure was successfully created on Al foil by a facile three-step solution–immersion method. As-obtained etched-immersed Al/STA rough surface contains interconnected convex–concave micro-structure and uniformly distributed nano-sheets that endow the surface with excellent superhydrophobicity (WCA: 164.2°; WSA: below 5°). Besides, the as-prepared etched-immersed Al/STA superhydrophobic surface on Al foil exhibits good friction-reducing ability and stable superhydrophobicity. - Highlights: • A stable superhydrophobic surface was created on aluminum foil by a facile three-step solution–immersion method. • A lotus-leaf-like hierarchical structure consists of interconnected convex–concave micro-structure and uniformly distributed nano-sheets has been constructed on the aluminum surface. • The superhydrophobic surfaces on aluminum substrate showing effective friction-reducing performance and self-cleaning ability. - Abstract: A lotus-leaf-like hierarchical structure with superhydrophobicity was created on Al foil by a facile three-step solution–immersion method involving etching in hydrochloric acid solution and immersing in hot water as well as surface-modification by stearic acid (denoted as STA). As-prepared etched-immersed Al/STA rough surface was characterized by means of scanning electron microscopy and X-ray photoelectron spectroscopy. Moreover, the water contact angles and water sliding angles of as-prepared etched-immersed Al/STA rough surface were measured, and the friction-reducing performance and self-cleaning ability of the as-prepared surface were also evaluated. Results indicate that the etched-immersed Al/STA rough surface consists of interconnected convex–concave micro-structure and uniformly distributed nano-sheets. Besides, it exhibits stable superhydrophobicity and good friction-reducing ability. Namely, it has a contact angle of water as high as 164.2° and a water sliding

Low-order dynamical system model of a fully developed turbulent channel flow

Science.gov (United States)

Hamilton, Nicholas; Tutkun, Murat; Cal, Raúl Bayoán

2017-06-01

A reduced order model of a turbulent channel flow is composed from a direct numerical simulation database hosted at the Johns Hopkins University. Snapshot proper orthogonal decomposition (POD) is used to identify the Hilbert space from which the reduced order model is obtained, as the POD basis is defined to capture the optimal energy content by mode. The reduced order model is defined by coupling the evolution of the dynamic POD mode coefficients through their respective time derivative with a least-squares polynomial fit of terms up to third order. Parameters coupling the dynamics of the POD basis are defined in analog to those produced in the classical Galerkin projection. The resulting low-order dynamical system is tested for a range of basis modes demonstrating that the non-linear mode interactions do not lead to a monotonic decrease in error propagation. A basis of five POD modes accounts for 50% of the integrated turbulence kinetic energy but captures only the largest features of the turbulence in the channel flow and is not able to reflect the anticipated flow dynamics. Using five modes, the low-order model is unable to accurately reproduce Reynolds stresses, and the root-mean-square error of the predicted stresses is as great as 30%. Increasing the basis to 28 modes accounts for 90% of the kinetic energy and adds intermediate scales to the dynamical system. The difference between the time derivatives of the random coefficients associated with individual modes and their least-squares fit is amplified in the numerical integration leading to unstable long-time solutions. Periodic recalibration of the dynamical system is undertaken by limiting the integration time to the range of the sampled data and offering the dynamical system new initial conditions. Renewed initial conditions are found by pushing the mode coefficients in the end of the integration time toward a known point along the original trajectories identified through a least-squares projection. Under

Femtosecond single-beam direct laser poling of stable and efficient second-order nonlinear optical properties in glass

International Nuclear Information System (INIS)

Papon, G.; Marquestaut, N.; Royon, A.; Canioni, L.; Petit, Y.; Dussauze, M.; Rodriguez, V.; Cardinal, T.

2014-01-01

We depict a new approach for the localized creation in three dimensions (3D) of a highly demanded nonlinear optical function for integrated optics, namely second harmonic generation. We report on the nonlinear optical characteristics induced by single-beam femtosecond direct laser writing in a tailored silver-containing phosphate glass. The original spatial distribution of the nonlinear pattern, composed of four lines after one single laser writing translation, is observed and modeled with success, demonstrating the electric field induced origin of the second harmonic generation. These efficient second-order nonlinear structures (with χ eff (2)  ∼ 0.6 pm V −1 ) with sub-micron scale are impressively stable under thermal constraint up to glass transition temperature, which makes them very promising for new photonic applications, especially when 3D nonlinear architectures are desired

Trimming a hazard logic tree with a new model-order-reduction technique

Science.gov (United States)

Porter, Keith; Field, Edward; Milner, Kevin R

2017-01-01

The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.

Near-optimal order-reduced control for A/C (air-conditioning) system of EVs (electric vehicles)

International Nuclear Information System (INIS)

Chiu, Chien-Chin; Tsai, Nan-Chyuan; Lin, Chun-Chi

2014-01-01

This work is aimed to investigate the regulation problem for thermal comfortableness and propose control strategies for cabin environment of EVs (electric vehicles) by constructing a reduced-scale A/C (air-conditioning) system which mainly consists of two modules: ECB (environmental control box) and AHU (air-handling unit). Temperature and humidity in the ECB can be regulated by AHU via cooling, heating, mixing air streams and adjusting speed of fans. To synthesize the near-optimal controllers, the mathematical model for the system thermodynamics is developed by employing the equivalent lumped heat capacity approach, energy/mass conservation principle and the heat transfer theories. In addition, from the clustering pattern of system eigenvalues, the thermodynamics of the interested system can evidently be characterized by two-time-scale property. That is, the studied system can be decoupled into two subsystems, slow mode and fast mode, by singular perturbation technique. As to the optimal control strategies for EVs, by taking thermal comfortableness, humidity and energy consumption all into account, a series of optimal controllers is synthesized on the base of the order-reduced thermodynamic model. The feedback control loop for the experimental test rig is examined and realized by the aid of the control system development kit dSPACE DS1104 and the commercial software MATLAB/Simulink. To sum up, the intensive computer simulations and experimental results verify that the performance of the near-optimal order-reduced control law is almost as superior as that of standard LQR (Linear-Quadratic Regulator). - Highlights: • A reduced-scale test rig for A/C (air-conditioning) system to imitate the temperature/humidity of cabin in EV (electric vehicle) is constructed. • The non-linear thermodynamic model of A/C system can be decoupled by singular perturbation technique. • The temperature/humidity in cabin is regulated to the desired values by proposed optimal

Reduced order modeling, statistical analysis and system identification for a bladed rotor with geometric mistuning

Science.gov (United States)

Vishwakarma, Vinod

Modified Modal Domain Analysis (MMDA) is a novel method for the development of a reduced-order model (ROM) of a bladed rotor. This method utilizes proper orthogonal decomposition (POD) of Coordinate Measurement Machine (CMM) data of blades' geometries and sector analyses using ANSYS. For the first time ROM of a geometrically mistuned industrial scale rotor (Transonic rotor) with large size of Finite Element (FE) model is generated using MMDA. Two methods for estimating mass and stiffness mistuning matrices are used a) exact computation from sector FE analysis, b) estimates based on POD mistuning parameters. Modal characteristics such as mistuned natural frequencies, mode shapes and forced harmonic response are obtained from ROM for various cases, and results are compared with full rotor ANSYS analysis and other ROM methods such as Subset of Nominal Modes (SNM) and Fundamental Model of Mistuning (FMM). Accuracy of MMDA ROM is demonstrated with variations in number of POD features and geometric mistuning parameters. It is shown for the aforementioned case b) that the high accuracy of ROM studied in previous work with Academic rotor does not directly translate to the Transonic rotor. Reasons for such mismatch in results are investigated and attributed to higher mistuning in Transonic rotor. Alternate solutions such as estimation of sensitivities via least squares, and interpolation of mass and stiffness matrices on manifolds are developed, and their results are discussed. Statistics such as mean and standard deviations of forced harmonic response peak amplitude are obtained from random permutations, and are shown to have similar results as those of Monte Carlo simulations. These statistics are obtained and compared for 3 degree of freedom (DOF) lumped parameter model (LPM) of rotor, Academic rotor and Transonic rotor. A state -- estimator based on MMDA ROM and Kalman filter is also developed for offline or online estimation of harmonic forcing function from

Entropy stable high order discontinuous Galerkin methods for ideal compressible MHD on structured meshes

Science.gov (United States)

Liu, Yong; Shu, Chi-Wang; Zhang, Mengping

2018-02-01

We present a discontinuous Galerkin (DG) scheme with suitable quadrature rules [15] for ideal compressible magnetohydrodynamic (MHD) equations on structural meshes. The semi-discrete scheme is analyzed to be entropy stable by using the symmetrizable version of the equations as introduced by Godunov [32], the entropy stable DG framework with suitable quadrature rules [15], the entropy conservative flux in [14] inside each cell and the entropy dissipative approximate Godunov type numerical flux at cell interfaces to make the scheme entropy stable. The main difficulty in the generalization of the results in [15] is the appearance of the non-conservative "source terms" added in the modified MHD model introduced by Godunov [32], which do not exist in the general hyperbolic system studied in [15]. Special care must be taken to discretize these "source terms" adequately so that the resulting DG scheme satisfies entropy stability. Total variation diminishing / bounded (TVD/TVB) limiters and bound-preserving limiters are applied to control spurious oscillations. We demonstrate the accuracy and robustness of this new scheme on standard MHD examples.

Adaptive parametric model order reduction technique for optimization of vibro-acoustic models: Application to hearing aid design

Science.gov (United States)

Creixell-Mediante, Ester; Jensen, Jakob S.; Naets, Frank; Brunskog, Jonas; Larsen, Martin

2018-06-01

Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we present an adaptive pMOR technique where the construction of the projection basis is embedded in the optimization process and requires fewer full system analyses, while the accuracy of the reduced system is monitored by a cheap error indicator. The performance of the proposed method is evaluated for a 4-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system.

Reduced Order Modeling Methods for Turbomachinery Design

Science.gov (United States)

2009-03-01

and Ma- terials Conference, May 2006. [45] A. Gelman , J. B. Carlin, H. S. Stern, and D. B. Rubin, Bayesian Data Analysis. New York, NY: Chapman I& Hall...Macian- Juan , and R. Chawla, “A statistical methodology for quantif ca- tion of uncertainty in best estimate code physical models,” Annals of Nuclear En

A Reduced-Order Successive Linear Estimator for Geostatistical Inversion and its Application in Hydraulic Tomography

Science.gov (United States)

Zha, Yuanyuan; Yeh, Tian-Chyi J.; Illman, Walter A.; Zeng, Wenzhi; Zhang, Yonggen; Sun, Fangqiang; Shi, Liangsheng

2018-03-01

Hydraulic tomography (HT) is a recently developed technology for characterizing high-resolution, site-specific heterogeneity using hydraulic data (nd) from a series of cross-hole pumping tests. To properly account for the subsurface heterogeneity and to flexibly incorporate additional information, geostatistical inverse models, which permit a large number of spatially correlated unknowns (ny), are frequently used to interpret the collected data. However, the memory storage requirements for the covariance of the unknowns (ny × ny) in these models are prodigious for large-scale 3-D problems. Moreover, the sensitivity evaluation is often computationally intensive using traditional difference method (ny forward runs). Although employment of the adjoint method can reduce the cost to nd forward runs, the adjoint model requires intrusive coding effort. In order to resolve these issues, this paper presents a Reduced-Order Successive Linear Estimator (ROSLE) for analyzing HT data. This new estimator approximates the covariance of the unknowns using Karhunen-Loeve Expansion (KLE) truncated to nkl order, and it calculates the directional sensitivities (in the directions of nkl eigenvectors) to form the covariance and cross-covariance used in the Successive Linear Estimator (SLE). In addition, the covariance of unknowns is updated every iteration by updating the eigenvalues and eigenfunctions. The computational advantages of the proposed algorithm are demonstrated through numerical experiments and a 3-D transient HT analysis of data from a highly heterogeneous field site.

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

Science.gov (United States)

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-05-01

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

Low order physical models of vertical axis wind turbines

Science.gov (United States)

Craig, Anna; Dabiri, John; Koseff, Jeffrey

2016-11-01

In order to examine the ability of low-order physical models of vertical axis wind turbines to accurately reproduce key flow characteristics, experiments were conducted on rotating turbine models, rotating solid cylinders, and stationary porous flat plates (of both uniform and non-uniform porosities). From examination of the patterns of mean flow, the wake turbulence spectra, and several quantitative metrics, it was concluded that the rotating cylinders represent a reasonably accurate analog for the rotating turbines. In contrast, from examination of the patterns of mean flow, it was found that the porous flat plates represent only a limited analog for rotating turbines (for the parameters examined). These findings have implications for both laboratory experiments and numerical simulations, which have previously used analogous low order models in order to reduce experimental/computational costs. NSF GRF and SGF to A.C; ONR N000141211047 and the Gordon and Betty Moore Foundation Grant GBMF2645 to J.D.; and the Bob and Norma Street Environmental Fluid Mechanics Laboratory at Stanford University.

Reduced-Order Dynamic Modeling, Fouling Detection, and Optimal Control of Solar-Powered Direct Contact Membrane Distillation

KAUST Repository

Karam, Ayman M.

2016-12-01

Membrane Distillation (MD) is an emerging sustainable desalination technique. While MD has many advantages and can be powered by solar thermal energy, its main drawback is the low water production rate. However, the MD process has not been fully optimized in terms of its manipulated and controlled variables. This is largely due to the lack of adequate dynamic models to study and simulate the process. In addition, MD is prone to membrane fouling, which is a fault that degrades the performance of the MD process. This work has three contributions to address these challenges. First, we derive a mathematical model of Direct Contact Membrane Distillation (DCMD), which is the building block for the next parts. Then, the proposed model is extended to account for membrane fouling and an observer-based fouling detection method is developed. Finally, various control strategies are implemented to optimize the performance of the DCMD solar-powered process. In part one, a reduced-order dynamic model of DCMD is developed based on lumped capacitance method and electrical analogy to thermal systems. The result is an electrical equivalent thermal network to the DCMD process, which is modeled by a system of nonlinear differential algebraic equations (DAEs). This model predicts the water-vapor flux and the temperature distribution along the module length. Experimental data is collected to validate the steady-state and dynamic responses of the proposed model, with great agreement demonstrated in both. The second part proposes an extension of the model to account for membrane fouling. An adaptive observer for DAE systems is developed and convergence proof is presented. A method for membrane fouling detection is then proposed based on adaptive observers. Simulation results demonstrate the performance of the membrane fouling detection method. Finally, an optimization problem is formulated to maximize the process efficiency of a solar-powered DCMD. The adapted method is known as Extremum

Nonlinear thermal reduced model for Microwave Circuit Analysis

OpenAIRE

Chang, Christophe; Sommet, Raphael; Quéré, Raymond; Dueme, Ph.

2004-01-01

With the constant increase of transistor power density, electro thermal modeling is becoming a necessity for accurate prediction of device electrical performances. For this reason, this paper deals with a methodology to obtain a precise nonlinear thermal model based on Model Order Reduction of a three dimensional thermal Finite Element (FE) description. This reduced thermal model is based on the Ritz vector approach which ensure the steady state solution in every case. An equi...

An implicit second order numerical method for two-fluid models

International Nuclear Information System (INIS)

Toumi, I.

1995-01-01

We present an implicit upwind numerical method for a six equation two-fluid model based on a linearized Riemann solver. The construction of this approximate Riemann solver uses an extension of Roe's scheme. Extension to second order accurate method is achieved using a piecewise linear approximation of the solution and a slope limiter method. For advancing in time, a linearized implicit integrating step is used. In practice this new numerical method has proved to be stable and capable of generating accurate non-oscillating solutions for two-phase flow calculations. The scheme was applied both to shock tube problems and to standard tests for two-fluid codes. (author)

Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

Directory of Open Access Journals (Sweden)

Xin Lu

2018-03-01

Full Text Available In recent years, the fractional order model has been employed to state of charge (SOC estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation. The experimental results showed that the proposed iterative method can quickly estimate the SOC by several iterations while maintaining high estimation accuracy.

Reduced-order modeling with sparse polynomial chaos expansion and dimension reduction for evaluating the impact of CO2 and brine leakage on groundwater

Science.gov (United States)

Liu, Y.; Zheng, L.; Pau, G. S. H.

2016-12-01

A careful assessment of the risk associated with geologic CO2 storage is critical to the deployment of large-scale storage projects. While numerical modeling is an indispensable tool for risk assessment, there has been increasing need in considering and addressing uncertainties in the numerical models. However, uncertainty analyses have been significantly hindered by the computational complexity of the model. As a remedy, reduced-order models (ROM), which serve as computationally efficient surrogates for high-fidelity models (HFM), have been employed. The ROM is constructed at the expense of an initial set of HFM simulations, and afterwards can be relied upon to predict the model output values at minimal cost. The ROM presented here is part of National Risk Assessment Program (NRAP) and intends to predict the water quality change in groundwater in response to hypothetical CO2 and brine leakage. The HFM based on which the ROM is derived is a multiphase flow and reactive transport model, with 3-D heterogeneous flow field and complex chemical reactions including aqueous complexation, mineral dissolution/precipitation, adsorption/desorption via surface complexation and cation exchange. Reduced-order modeling techniques based on polynomial basis expansion, such as polynomial chaos expansion (PCE), are widely used in the literature. However, the accuracy of such ROMs can be affected by the sparse structure of the coefficients of the expansion. Failing to identify vanishing polynomial coefficients introduces unnecessary sampling errors, the accumulation of which deteriorates the accuracy of the ROMs. To address this issue, we treat the PCE as a sparse Bayesian learning (SBL) problem, and the sparsity is obtained by detecting and including only the non-zero PCE coefficients one at a time by iteratively selecting the most contributing coefficients. The computational complexity due to predicting the entire 3-D concentration fields is further mitigated by a dimension

Generalized modeling of the fractional-order memcapacitor and its character analysis

Science.gov (United States)

Guo, Zhang; Si, Gangquan; Diao, Lijie; Jia, Lixin; Zhang, Yanbin

2018-06-01

Memcapacitor is a new type of memory device generalized from the memristor. This paper proposes a generalized fractional-order memcapacitor model by introducing the fractional calculus into the model. The generalized formulas are studied and the two fractional-order parameter α, β are introduced where α mostly affects the fractional calculus value of charge q within the generalized Ohm's law and β generalizes the state equation which simulates the physical mechanism of a memcapacitor into the fractional sense. This model will be reduced to the conventional memcapacitor as α = 1 , β = 0 and to the conventional memristor as α = 0 , β = 1 . Then the numerical analysis of the fractional-order memcapacitor is studied. And the characteristics and output behaviors of the fractional-order memcapacitor applied with sinusoidal charge are derived. The analysis results have shown that there are four basic v - q and v - i curve patterns when the fractional order α, β respectively equal to 0 or 1, moreover all v - q and v - i curves of the other fractional-order models are transition curves between the four basic patterns.

Efficient response spectrum analysis of a reactor using Model Order Reduction

International Nuclear Information System (INIS)

Oh, Jin Ho; Choi, Jin Bok; Ryu, Jeong Soo

2012-01-01

A response spectrum analysis (RSA) has been widely used to evaluate the structural integrity of various structural components in the nuclear industry. However, solving the large and complex structural systems numerically using the RSA requires a considerable amount of computational resources and time. To overcome this problem, this paper proposes the RSA based on the model order reduction (MOR) technique achieved by applying a projection from a higher order to a lower order space using Krylov subspaces generated by the Arnoldi algorithm. The dynamic characteristics of the final reduced system are almost identical with those of the full system by matching the moments of the reduced system with those of the full system up to the required nth order. It is remarkably efficient in terms of computation time and does not require a global system. Numerical examples demonstrate that the proposed method saves computational costs effectively, and provides a reduced system framework that predicts the accurate responses of a global system

An order insertion scheduling model of logistics service supply chain considering capacity and time factors.

Science.gov (United States)

Liu, Weihua; Yang, Yi; Wang, Shuqing; Liu, Yang

2014-01-01

Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.

Modelling of the flow of stable air over a complex region

CSIR Research Space (South Africa)

Scholtz, MT

1976-01-01

Full Text Available The flow of stable air over a general region of complex topography and non-uniform surface temperature has been investigated. In order to gain further understanding of the motion of surface air, it was necessary to study the vertical structure...

Parametric reduced models for the nonlinear Schrödinger equation.

Science.gov (United States)

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

A reduced-order adaptive neuro-fuzzy inference system model as a software sensor for rapid estimation of five-day biochemical oxygen demand

Science.gov (United States)

Noori, Roohollah; Safavi, Salman; Nateghi Shahrokni, Seyyed Afshin

2013-07-01

The five-day biochemical oxygen demand (BOD5) is one of the key parameters in water quality management. In this study, a novel approach, i.e., reduced-order adaptive neuro-fuzzy inference system (ROANFIS) model was developed for rapid estimation of BOD5. In addition, an uncertainty analysis of adaptive neuro-fuzzy inference system (ANFIS) and ROANFIS models was carried out based on Monte-Carlo simulation. Accuracy analysis of ANFIS and ROANFIS models based on both developed discrepancy ratio and threshold statistics revealed that the selected ROANFIS model was superior. Pearson correlation coefficient (R) and root mean square error for the best fitted ROANFIS model were 0.96 and 7.12, respectively. Furthermore, uncertainty analysis of the developed models indicated that the selected ROANFIS had less uncertainty than the ANFIS model and accurately forecasted BOD5 in the Sefidrood River Basin. Besides, the uncertainty analysis also showed that bracketed predictions by 95% confidence bound and d-factor in the testing steps for the selected ROANFIS model were 94% and 0.83, respectively.

New Designs of Reduced-Order Observer-Based Controllers for Singularly Perturbed Linear Systems

Directory of Open Access Journals (Sweden)

Heonjong Yoo

2017-01-01

Full Text Available The slow and fast reduced-order observers and reduced-order observer-based controllers are designed by using the two-stage feedback design technique for slow and fast subsystems. The new designs produce an arbitrary order of accuracy, while the previously known designs produce the accuracy of O(ϵ only where ϵ is a small singular perturbation parameter. Several cases of reduced-order observer designs are considered depending on the measured state space variables: only all slow variables are measured, only all fast variables are measured, and some combinations of the slow and fast variables are measured. Since the two-stage methods have been used to overcome the numerical ill-conditioning problem for Cases (III–(V, they have similar procedures. The numerical ill-conditioning problem is avoided so that independent feedback controllers can be applied to each subsystem. The design allows complete time-scale separation for both the reduced-order observer and controller through the complete and exact decomposition into slow and fast time scales. This method reduces both offline and online computations.

Chaotic and stable perturbed maps: 2-cycles and spatial models

Science.gov (United States)

Braverman, E.; Haroutunian, J.

2010-06-01

As the growth rate parameter increases in the Ricker, logistic and some other maps, the models exhibit an irreversible period doubling route to chaos. If a constant positive perturbation is introduced, then the Ricker model (but not the classical logistic map) experiences period doubling reversals; the break of chaos finally gives birth to a stable two-cycle. We outline the maps which demonstrate a similar behavior and also study relevant discrete spatial models where the value in each cell at the next step is defined only by the values at the cell and its nearest neighbors. The stable 2-cycle in a scalar map does not necessarily imply 2-cyclic-type behavior in each cell for the spatial generalization of the map.

A review of available countermeasures to reduce radioiodine transfer to milk. With special regard to the use of stable iodine

International Nuclear Information System (INIS)

Howard, B.

1993-03-01

Contamination of milk by 131 I constitutes an important potential component of the collective dose to the population after a nuclear accident, and a relatively large dose saving can be gained by applying suitable countermeasures. Stable iodine prophylaxis is recommended for humans to prevent or reduce by the thyroid of inhaled radioiodine but controls on food are more appropriate to reduce radioiodine intakes from ingestion. Therefore it is important to have effective, practical countermeasures available to prevent radioiodine contamination of milk. This review evaluates currently available countermeasures which can be used to reduce radioiodine contamination of milk. In particular, it critically assesses available data on the effectiveness of stable iodine administration. The simplest and most effective countermeasure is to provide dairy animals with uncontaminated feed, this countermeasure has the added advantage that it will be effective for other radionuclides which may be present in the fallout. Alternatively, another effective response is to process the milk into storable dairy products for an appropriate length of time to allow for physical decay. The use of additives given to ruminants to reduce radioiodine in milk should be viewed as an alternative countermeasure which could be effective, but would not be the preferred option. However, it should be considered, particularly if difficulties are anticipated with the first two options. Stable iodine administration is a practical, and feasible option which has the potential to reduce radioiodine levels in milk, by at most a factor of three and the radiation dose to the animals thyroid. However, the stable iodine supplementation at low doses, and after the ingestion of radioiodine, may lead to increases in radioiodine levels in milk. Similarly, if ruminants are already receiving high iodine intakes, stable iodine is unlikely to be effective. Currently available data is inadequate to recommend a suitable dose

An algebraic method for constructing stable and consistent autoregressive filters

International Nuclear Information System (INIS)

Harlim, John; Hong, Hoon; Robbins, Jacob L.

2015-01-01

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides a discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern

Reduced cost mission design using surrogate models

Science.gov (United States)

Feldhacker, Juliana D.; Jones, Brandon A.; Doostan, Alireza; Hampton, Jerrad

2016-01-01

This paper uses surrogate models to reduce the computational cost associated with spacecraft mission design in three-body dynamical systems. Sampling-based least squares regression is used to project the system response onto a set of orthogonal bases, providing a representation of the ΔV required for rendezvous as a reduced-order surrogate model. Models are presented for mid-field rendezvous of spacecraft in orbits in the Earth-Moon circular restricted three-body problem, including a halo orbit about the Earth-Moon L2 libration point (EML-2) and a distant retrograde orbit (DRO) about the Moon. In each case, the initial position of the spacecraft, the time of flight, and the separation between the chaser and the target vehicles are all considered as design inputs. The results show that sample sizes on the order of 102 are sufficient to produce accurate surrogates, with RMS errors reaching 0.2 m/s for the halo orbit and falling below 0.01 m/s for the DRO. A single function call to the resulting surrogate is up to two orders of magnitude faster than computing the same solution using full fidelity propagators. The expansion coefficients solved for in the surrogates are then used to conduct a global sensitivity analysis of the ΔV on each of the input parameters, which identifies the separation between the spacecraft as the primary contributor to the ΔV cost. Finally, the models are demonstrated to be useful for cheap evaluation of the cost function in constrained optimization problems seeking to minimize the ΔV required for rendezvous. These surrogate models show significant advantages for mission design in three-body systems, in terms of both computational cost and capabilities, over traditional Monte Carlo methods.

Second-order sliding mode controller with model reference adaptation for automatic train operation

Science.gov (United States)

Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

2017-11-01

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

A MODEL FOR PRODUCING STABLE, BROADBAND TERAHERTZ COHERENT SYNCHROTRON RADIATION IN STORAGE RINGS

International Nuclear Information System (INIS)

Sannibale, Fernando; Byrd, John M.; Loftsdottir, Agusta; Martin, MichaelC.; Venturini, Marco

2003-01-01

We present a model for producing stable broadband coherent synchrotron radiation (CSR) in the terahertz frequency region in an electron storage ring. The model includes distortion of bunch shape from the synchrotron radiation (SR), enhancing higher frequency coherent emission and limits to stable emission due to a microbunching instability excited by the SR. We use this model to optimize the performance of a source for CSR emission

Sexual antagonism and meiotic drive cause stable linkage disequilibrium and favour reduced recombination on the X chromosome.

Science.gov (United States)

Rydzewski, W T; Carioscia, S A; Liévano, G; Lynch, V D; Patten, M M

2016-06-01

Sexual antagonism and meiotic drive are sex-specific evolutionary forces with the potential to shape genomic architecture. Previous theory has found that pairing two sexually antagonistic loci or combining sexual antagonism with meiotic drive at linked autosomal loci augments genetic variation, produces stable linkage disequilibrium (LD) and favours reduced recombination. However, the influence of these two forces has not been examined on the X chromosome, which is thought to be enriched for sexual antagonism and meiotic drive. We investigate the evolution of the X chromosome under both sexual antagonism and meiotic drive with two models: in one, both loci experience sexual antagonism; in the other, we pair a meiotic drive locus with a sexually antagonistic locus. We find that LD arises between the two loci in both models, even when the two loci freely recombine in females and that driving haplotypes will be enriched for male-beneficial alleles, further skewing sex ratios in these populations. We introduce a new measure of LD, Dz', which accounts for population allele frequencies and is appropriate for instances where these are sex specific. Both models demonstrate that natural selection favours modifiers that reduce the recombination rate. These results inform observed patterns of congealment found on driving X chromosomes and have implications for patterns of natural variation and the evolution of recombination rates on the X chromosome. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Construction of second order accurate monotone and stable residual distribution schemes for unsteady flow problems

International Nuclear Information System (INIS)

Abgrall, Remi; Mezine, Mohamed

2003-01-01

The aim of this paper is to construct upwind residual distribution schemes for the time accurate solution of hyperbolic conservation laws. To do so, we evaluate a space-time fluctuation based on a space-time approximation of the solution and develop new residual distribution schemes which are extensions of classical steady upwind residual distribution schemes. This method has been applied to the solution of scalar advection equation and to the solution of the compressible Euler equations both in two space dimensions. The first version of the scheme is shown to be, at least in its first order version, unconditionally energy stable and possibly conditionally monotonicity preserving. Using an idea of Csik et al. [Space-time residual distribution schemes for hyperbolic conservation laws, 15th AIAA Computational Fluid Dynamics Conference, Anahein, CA, USA, AIAA 2001-2617, June 2001], we modify the formulation to end up with a scheme that is unconditionally energy stable and unconditionally monotonicity preserving. Several numerical examples are shown to demonstrate the stability and accuracy of the method

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

Science.gov (United States)

Ballabrera-Poy, Joaquim; Busalacchi, Antonio J.; Murtugudde, Ragu

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N. In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions I up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Time-Frequency Analysis Using Warped-Based High-Order Phase Modeling

Directory of Open Access Journals (Sweden)

Ioana Cornel

2005-01-01

Full Text Available The high-order ambiguity function (HAF was introduced for the estimation of polynomial-phase signals (PPS embedded in noise. Since the HAF is a nonlinear operator, it suffers from noise-masking effects and from the appearance of undesired cross-terms when multicomponents PPS are analyzed. In order to improve the performances of the HAF, the multi-lag HAF concept was proposed. Based on this approach, several advanced methods (e.g., product high-order ambiguity function (PHAF have been recently proposed. Nevertheless, performances of these new methods are affected by the error propagation effect which drastically limits the order of the polynomial approximation. This phenomenon acts especially when a high-order polynomial modeling is needed: representation of the digital modulation signals or the acoustic transient signals. This effect is caused by the technique used for polynomial order reduction, common for existing approaches: signal multiplication with the complex conjugated exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We will prove that this method reduces considerably the effect of error propagation. Namely, with this order reduction method, the estimation error at a given order will depend only on the performances of the estimation method.

Ordering dynamics of microscopic models with nonconserved order parameter of continuous symmetry

DEFF Research Database (Denmark)

Zhang, Z.; Mouritsen, Ole G.; Zuckermann, Martin J.

1993-01-01

crystals. For both models, which have a nonconserved order parameter, it is found that the linear scale, R(t), of the evolving order, following quenches to below the transition temperature, grows at late times in an effectively algebraic fashion, R(t)∼tn, with exponent values which are strongly temperature......Numerical Monte Carlo temperature-quenching experiments have been performed on two three-dimensional classical lattice models with continuous ordering symmetry: the Lebwohl-Lasher model [Phys. Rev. A 6, 426 (1972)] and the ferromagnetic isotropic Heisenberg model. Both models describe a transition...... from a disordered phase to an orientationally ordered phase of continuous symmetry. The Lebwohl-Lasher model accounts for the orientational ordering properties of the nematic-isotropic transition in liquid crystals and the Heisenberg model for the ferromagnetic-paramagnetic transition in magnetic...

Observation of ferromagnetic ordering in a stable α -Co (OH) 2 phase grown on a Mo S2 surface

Science.gov (United States)

Debnath, Anup; Bhattacharya, Shatabda; Saha, Shyamal K.

2017-12-01

Because of the potential application of Co (OH) 2 in a magnetic cooling system as a result of its superior magnetocaloric effect many people have investigated magnetic properties of Co (OH) 2 . Unfortunately, most of the works have been carried out on the β -Co (OH) 2 phase due to the fact that the α -Co (OH) 2 phase is very unstable and continuously transformed into the stable β -Co (OH) 2 phase. However, in the present work, using a Mo S2 sheet as a two-dimensional template, we have been able to synthesize a stable α -Co (OH) 2 phase in addition to a β -Co (OH) 2 phase by varying the layer thickness. It is seen that for thinner samples the β phase, while for thicker samples α phase, is grown on the Mo S2 surface. Magnetic measurements are carried out for the samples over the temperature range from 2 to 300 K and it is seen that for the β phase, ferromagnetic ordering with fairly large coercivity (1271 Oe) at 2 K is obtained instead of the usual antiferromagnetism. The most interesting result is the observation of ferromagnetic ordering with a transition temperature (Curie temperature) more than 100 K in the α -Co (OH) 2 phase. Complete saturation in the hysteresis curve under application of very low field having coercivity of ˜162 Oe at 2 K and 60 Oe at 50 K is obtained. A thin stable α -Co (OH) 2 phase grown on Mo S2 surface with very soft ferromagnetic ordering will be very useful as the core material in electromagnets.

Design of four-point SENB specimens with stable crack growth

DEFF Research Database (Denmark)

Jørgensen, Jeppe Bjørn; Kildegaard, Casper; Sørensen, Bent F.

2018-01-01

A four-point single-edge-notch-beam (SENB) test specimen loaded in displacement control (fixed grip) is proposed for studying crack deflection at bi-material interfaces. In order to ensure stable crack growth, a novel analytical model of the four-point SENB specimen in fixed grip is derived...... and compared with numerical models. Model results show that the specimen should be short and thick, and the start-crack length should be deep for the crack to propagate stable towards the bi-material interface. Observations from experimental tests of four-point SENB specimens with different start-crack lengths...

Assessment of reduced-order unscented Kalman filter for parameter identification in 1-dimensional blood flow models using experimental data.

Science.gov (United States)

Caiazzo, A; Caforio, Federica; Montecinos, Gino; Muller, Lucas O; Blanco, Pablo J; Toro, Eluterio F

2016-10-25

This work presents a detailed investigation of a parameter estimation approach on the basis of the reduced-order unscented Kalman filter (ROUKF) in the context of 1-dimensional blood flow models. In particular, the main aims of this study are (1) to investigate the effects of using real measurements versus synthetic data for the estimation procedure (i.e., numerical results of the same in silico model, perturbed with noise) and (2) to identify potential difficulties and limitations of the approach in clinically realistic applications to assess the applicability of the filter to such setups. For these purposes, the present numerical study is based on a recently published in vitro model of the arterial network, for which experimental flow and pressure measurements are available at few selected locations. To mimic clinically relevant situations, we focus on the estimation of terminal resistances and arterial wall parameters related to vessel mechanics (Young's modulus and wall thickness) using few experimental observations (at most a single pressure or flow measurement per vessel). In all cases, we first perform a theoretical identifiability analysis on the basis of the generalized sensitivity function, comparing then the results owith the ROUKF, using either synthetic or experimental data, to results obtained using reference parameters and to available measurements. Copyright © 2016 John Wiley & Sons, Ltd.

Modelling the artic stable boundary layer and its coupling to the surface

NARCIS (Netherlands)

Steeneveld, G.J.; Wiel, van de B.J.H.; Holtslag, A.A.M.

2006-01-01

The impact of coupling the atmosphere to the surface energy balance is examined for the stable boundary layer, as an extension of the first GABLS (GEWEX Atmospheric Boundary-Layer Study) one-dimensional model intercomparison. This coupling is of major importance for the stable boundary-layer

Application of aggregation techniques for model order reduction of nuclear plants for operator guidance systems

International Nuclear Information System (INIS)

Zwingelstein, G.C.

1980-12-01

After a short description of a disturbance analysis system for nuclear plant based on real time dynamic modelling and simulation, a scheme for generating aggregated reduced models of high order systems is presented. This method allows the choice of dominant dynamic modes and its efficiency is illustrated for the case of a 29th order nuclear plant model

COMBINING SOURCES IN STABLE ISOTOPE MIXING MODELS: ALTERNATIVE METHODS

Science.gov (United States)

Stable isotope mixing models are often used to quantify source contributions to a mixture. Examples include pollution source identification; trophic web studies; analysis of water sources for soils, plants, or water bodies; and many others. A common problem is having too many s...

A reduced fidelity model for the rotary chemical looping combustion reactor

International Nuclear Information System (INIS)

Iloeje, Chukwunwike O.; Zhao, Zhenlong; Ghoniem, Ahmed F.

2017-01-01

Highlights: • Methodology for developing a reduced fidelity rotary CLC reactor model is presented. • The reduced model determines optimal reactor configuration that meets design and operating requirements. • A 4-order of magnitude reduction in computational cost is achieved with good prediction accuracy. • Sensitivity studies demonstrate importance of accurate kinetic parameters for reactor optimization. - Abstract: The rotary chemical looping combustion reactor has great potential for efficient integration with CO_2 capture-enabled energy conversion systems. In earlier studies, we described a one-dimensional rotary reactor model, and used it to demonstrate the feasibility of continuous reactor operation. Though this detailed model provides a high resolution representation of the rotary reactor performance, it is too computationally expensive for studies that require multiple model evaluations. Specifically, it is not ideal for system-level studies where the reactor is a single component in an energy conversion system. In this study, we present a reduced fidelity model (RFM) of the rotary reactor that reduces computational cost and determines an optimal combination of variables that satisfy reactor design requirements. Simulation results for copper, nickel and iron-based oxygen carriers show a four-order of magnitude reduction in simulation time, and reasonable prediction accuracy. Deviations from the detailed reference model predictions range from 3% to 20%, depending on oxygen carrier type and operating conditions. This study also demonstrates how the reduced model can be modified to deal with both optimization and design oriented problems. A parametric study using the reduced model is then applied to analyze the sensitivity of the optimal reactor design to changes in selected operating and kinetic parameters. These studies show that temperature and activation energy have a greater impact on optimal geometry than parameters like pressure or feed fuel

HIGHLY-ACCURATE MODEL ORDER REDUCTION TECHNIQUE ON A DISCRETE DOMAIN

Directory of Open Access Journals (Sweden)

L. D. Ribeiro

2015-09-01

Full Text Available AbstractIn this work, we present a highly-accurate technique of model order reduction applied to staged processes. The proposed method reduces the dimension of the original system based on null values of moment-weighted sums of heat and mass balance residuals on real stages. To compute these sums of weighted residuals, a discrete form of Gauss-Lobatto quadrature was developed, allowing a high degree of accuracy in these calculations. The locations where the residuals are cancelled vary with time and operating conditions, characterizing a desirable adaptive nature of this technique. Balances related to upstream and downstream devices (such as condenser, reboiler, and feed tray of a distillation column are considered as boundary conditions of the corresponding difference-differential equations system. The chosen number of moments is the dimension of the reduced model being much lower than the dimension of the complete model and does not depend on the size of the original model. Scaling of the discrete independent variable related with the stages was crucial for the computational implementation of the proposed method, avoiding accumulation of round-off errors present even in low-degree polynomial approximations in the original discrete variable. Dynamical simulations of distillation columns were carried out to check the performance of the proposed model order reduction technique. The obtained results show the superiority of the proposed procedure in comparison with the orthogonal collocation method.

Governor Design for a Hydropower Plant with an Upstream Surge Tank by GA-Based Fuzzy Reduced-Order Sliding Mode

Directory of Open Access Journals (Sweden)

Chang Xu

2015-11-01

Full Text Available This paper investigates governor design by reduced-order sliding mode for a hydropower plant with an upstream surge tank. The governing system is made up of a tunnel, a surge tank, a penstock, a wicket gate and servomechanism, a governor, a hydro-turbine and a grid. Concerning the components of the governing system, their mathematic models are established. Then, these models are interconnected to simulate the governing system. From the viewpoint of state space in modern control theory, the governing system is partially observed, which challenges the governor design. By introducing an additional state variable, the control method of reduced-order sliding mode is proposed, where the governor design is based on a reduced-order governing system. Since the governor is applied to the original governing system, the system stability is analyzed by means of the small gain theorem. An genetic algorithm is employed to search a group of parameters of the predefined sliding surface, and a fuzzy inference system is utilized to decrease the chattering problem. Some numerical simulations are illustrated to verify the feasibility and robustness of the control method.

BWR stability using a reducing dynamical model

International Nuclear Information System (INIS)

Ballestrin Bolea, J. M.; Blazquez Martinez, J. B.

1990-01-01

BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)

Self-similar anomalous diffusion and Levy-stable laws

International Nuclear Information System (INIS)

Uchaikin, Vladimir V

2003-01-01

Stochastic principles for constructing the process of anomalous diffusion are considered, and corresponding models of random processes are reviewed. The self-similarity and the independent-increments principles are used to extend the notion of diffusion process to the class of Levy-stable processes. Replacing the independent-increments principle with the renewal principle allows us to take the next step in generalizing the notion of diffusion, which results in fractional-order partial space-time differential equations of diffusion. Fundamental solutions to these equations are represented in terms of stable laws, and their relationship to the fractality and memory of the medium is discussed. A new class of distributions, called fractional stable distributions, is introduced. (reviews of topical problems)

Finite difference schemes for second order systems describing black holes

International Nuclear Information System (INIS)

Motamed, Mohammad; Kreiss, H-O.; Babiuc, M.; Winicour, J.; Szilagyi, B.

2006-01-01

In the harmonic description of general relativity, the principal part of Einstein's equations reduces to 10 curved space wave equations for the components of the space-time metric. We present theorems regarding the stability of several evolution-boundary algorithms for such equations when treated in second order differential form. The theorems apply to a model black hole space-time consisting of a spacelike inner boundary excising the singularity, a timelike outer boundary and a horizon in between. These algorithms are implemented as stable, convergent numerical codes and their performance is compared in a 2-dimensional excision problem

Stable explicit coupling of the Yee scheme with a linear current model in fluctuating magnetized plasmas

International Nuclear Information System (INIS)

Silva, Filipe da; Pinto, Martin Campos; Després, Bruno; Heuraux, Stéphane

2015-01-01

This work analyzes the stability of the Yee scheme for non-stationary Maxwell's equations coupled with a linear current model with density fluctuations. We show that the usual procedure may yield unstable scheme for physical situations that correspond to strongly magnetized plasmas in X-mode (TE) polarization. We propose to use first order clustered discretization of the vectorial product that gives back a stable coupling. We validate the schemes on some test cases representative of direct numerical simulations of X-mode in a magnetic fusion plasma including turbulence

Geospatial modeling of plant stable isotope ratios - the development of isoscapes

Science.gov (United States)

West, J. B.; Ehleringer, J. R.; Hurley, J. M.; Cerling, T. E.

2007-12-01

Large-scale spatial variation in stable isotope ratios can yield critical insights into the spatio-temporal dynamics of biogeochemical cycles, animal movements, and shifts in climate, as well as anthropogenic activities such as commerce, resource utilization, and forensic investigation. Interpreting these signals requires that we understand and model the variation. We report progress in our development of plant stable isotope ratio landscapes (isoscapes). Our approach utilizes a GIS, gridded datasets, a range of modeling approaches, and spatially distributed observations. We synthesize findings from four studies to illustrate the general utility of the approach, its ability to represent observed spatio-temporal variability in plant stable isotope ratios, and also outline some specific areas of uncertainty. We also address two basic, but critical questions central to our ability to model plant stable isotope ratios using this approach: 1. Do the continuous precipitation isotope ratio grids represent reasonable proxies for plant source water?, and 2. Do continuous climate grids (as is or modified) represent a reasonable proxy for the climate experienced by plants? Plant components modeled include leaf water, grape water (extracted from wine), bulk leaf material ( Cannabis sativa; marijuana), and seed oil ( Ricinus communis; castor bean). Our approaches to modeling the isotope ratios of these components varied from highly sophisticated process models to simple one-step fractionation models to regression approaches. The leaf water isosocapes were produced using steady-state models of enrichment and continuous grids of annual average precipitation isotope ratios and climate. These were compared to other modeling efforts, as well as a relatively sparse, but geographically distributed dataset from the literature. The latitudinal distributions and global averages compared favorably to other modeling efforts and the observational data compared well to model predictions

Compact state-space models for complex superconducting radio-frequency structures based on model order reduction and concatenation methods

International Nuclear Information System (INIS)

Flisgen, Thomas

2015-01-01

The modeling of large chains of superconducting cavities with couplers is a challenging task in computational electrical engineering. The direct numerical treatment of these structures can easily lead to problems with more than ten million degrees of freedom. Problems of this complexity are typically solved with the help of parallel programs running on supercomputing infrastructures. However, these infrastructures are expensive to purchase, to operate, and to maintain. The aim of this thesis is to introduce and to validate an approach which allows for modeling large structures on a standard workstation. The novel technique is called State-Space Concatenations and is based on the decomposition of the complete structure into individual segments. The radio-frequency properties of the generated segments are described by a set of state-space equations which either emerge from analytical considerations or from numerical discretization schemes. The model order of these equations is reduced using dedicated model order reduction techniques. In a final step, the reduced-order state-space models of the segments are concatenated in accordance with the topology of the complete structure. The concatenation is based on algebraic continuity constraints of electric and magnetic fields on the decomposition planes and results in a compact state-space system of the complete radio-frequency structure. Compared to the original problem, the number of degrees of freedom is drastically reduced, i.e. a problem with more than ten million degrees of freedom can be reduced on a standard workstation to a problem with less than one thousand degrees of freedom. The final state-space system allows for determining frequency-domain transfer functions, field distributions, resonances, and quality factors of the complete structure in a convenient manner. This thesis presents the theory of the state-space concatenation approach and discusses several validation and application examples. The examples

Reducing turnaround time for laboratory test results does not improve retention of stable HIV-infected adults on POV program: experience from Uganda.

Science.gov (United States)

Maselle, Edna; Muhanguzi, Asaph; Muhumuza, Simon; Nansubuga, Jeniffer; Nawavvu, Cecilia; Namusobya, Jeniffer; Kamya, Moses R; Semitala, Fred C

2014-01-01

HIV/ AIDS clinics in resource limited settings (RLS) face increasing numbers of patients and workforce shortage [1, 2]. To address these challenges, efficient models of care like pharmacy only visits (POV) and nurse only visits (NOV) are recommended [3]. The Makerere University Joint AIDS Program (MJAP), a PEPFAR funded program providing care to over 42,000 HIV infected adults has implemented the POV model since 2009. In this model, stable patients on antiretroviral therapy (ART) with adherence to ART >95% and Karnofsky score >90% are reviewed by a doctor every four months but visit pharmacy for ART re-fills every two months. A study conducted in August 2011 showed low retention on the POV program with symptomatic diseases, pending CD4 count, complete blood count results, and poor adherence to ART as the major reasons for the non-retention in the POV program. To improve retention on POV, the TAT (Turnaround Time) for laboratory results (the main reason for non-retention in the previous study) was reduced from one month to one week. In August 2012, the study was repeated to assess the effect of reducing TAT on improving retention one year after patients were placed on POV. A cohort analysis of data from patients in August 2011 and in August 2012 on POV was done. We compared retention of POV before and after reducing the TAT for laboratory results. Retention on POV was 12.0% (95% CI 9.50-14.7) among 619 patients in 2011, (70% Females), mean age was 33 years, Standard Deviation (SD) 8.5 compared to 11.1% (95% CI 9.15-13.4) among 888 patients (70% Females), mean age 38.3 years, SD 8.9 in 2012 (p=0.59). The main reasons for non-retention on the POV program in 2012 were poor adherence to ART (23%) and missed clinic appointments (14%). Reducing TAT for laboratory test results did not improve retention of stable HIV-infected adults on POV in our clinic. Strategies for improving adherence to ART and keeping clinic appointments need to be employed to balance workload and

Implementation of a reduced order Kalman filter to assimilate ocean color data into a coupled physical-biochemical model of the North Aegean Sea.

Science.gov (United States)

Kalaroni, Sofia; Tsiaras, Kostas; Economou-Amilli, Athena; Petihakis, George; Politikos, Dimitrios; Triantafyllou, George

2013-04-01

Within the framework of the European project OPEC (Operational Ecology), a data assimilation system was implemented to describe chlorophyll-a concentrations of the North Aegean, as well the impact on the European anchovy (Engraulis encrasicolus) biomass distribution provided by a bioenergetics model, related to the density of three low trophic level functional groups of zooplankton (heterotrophic flagellates, microzooplankton and mesozooplankton). The three-dimensional hydrodynamic-biogeochemical model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The assimilation scheme is based on the Singular Evolutive Extended Kalman (SEEK) filter and its variant that uses a fixed correction base (SFEK). For the initialization, SEEK filter uses a reduced order error covariance matrix provided by the dominant Empirical Orthogonal Functions (EOF) of model. The assimilation experiments were performed for year 2003 using SeaWiFS chlorophyll-a data during which the physical model uses the atmospheric forcing obtained from the regional climate model HIRHAM5. The assimilation system is validated by assessing the relevance of the system in fitting the data, the impact of the assimilation on non-observed biochemical parameters and the overall quality of the forecasts.

Reduced Order Fractional Fourier Transform A New Variant to Fractional Signal Processing Definition and Properties

OpenAIRE

Kumar, Sanjay

2018-01-01

In this paper, a new variant to fractional signal processing is proposed known as the Reduced Order Fractional Fourier Transform. Various properties satisfied by its transformation kernel is derived. The properties associated with the proposed Reduced Order Fractional Fourier Transform like shift, modulation, time-frequency shift property are also derived and it is shown mathematically that when the rotation angle of Reduced Order Fractional Fourier Transform approaches 90 degrees, the propos...

Partially ordered models

NARCIS (Netherlands)

Fernandez, R.; Deveaux, V.

2010-01-01

We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).

Reduced-cost second-order algebraic-diagrammatic construction method for excitation energies and transition moments

Science.gov (United States)

Mester, Dávid; Nagy, Péter R.; Kállay, Mihály

2018-03-01

A reduced-cost implementation of the second-order algebraic-diagrammatic construction [ADC(2)] method is presented. We introduce approximations by restricting virtual natural orbitals and natural auxiliary functions, which results, on average, in more than an order of magnitude speedup compared to conventional, density-fitting ADC(2) algorithms. The present scheme is the successor of our previous approach [D. Mester, P. R. Nagy, and M. Kállay, J. Chem. Phys. 146, 194102 (2017)], which has been successfully applied to obtain singlet excitation energies with the linear-response second-order coupled-cluster singles and doubles model. Here we report further methodological improvements and the extension of the method to compute singlet and triplet ADC(2) excitation energies and transition moments. The various approximations are carefully benchmarked, and conservative truncation thresholds are selected which guarantee errors much smaller than the intrinsic error of the ADC(2) method. Using the canonical values as reference, we find that the mean absolute error for both singlet and triplet ADC(2) excitation energies is 0.02 eV, while that for oscillator strengths is 0.001 a.u. The rigorous cutoff parameters together with the significantly reduced operation count and storage requirements allow us to obtain accurate ADC(2) excitation energies and transition properties using triple-ζ basis sets for systems of up to one hundred atoms.

Estimation in the positive stable shared frailty Cox proportional hazards model

DEFF Research Database (Denmark)

Martinussen, Torben; Pipper, Christian Bressen

2005-01-01

model in situations where the correlated survival data show a decreasing association with time. In this paper, we devise a likelihood based estimation procedure for the positive stable shared frailty Cox model, which is expected to obtain high efficiency. The proposed estimator is provided with large...

Data mining of Ti-Al semi-empirical parameters for developing reduced order models

Energy Technology Data Exchange (ETDEWEB)

Broderick, Scott R [Department of Materials Science and Engineering and Institute for Combinatorial Discovery, Iowa State University, Ames, IA 50011 (United States); Aourag, Hafid [Department of Physics, University Abou Bakr Belkaid, Tlemcen 13000 (Algeria); Rajan, Krishna [Department of Materials Science and Engineering and Institute for Combinatorial Discovery, Iowa State University, Ames, IA 50011 (United States)

2011-05-15

A focus of materials design is determining the minimum amount of information necessary to fully describe a system, thus reducing the number of empirical results required and simplifying the data analysis. Screening descriptors calculated through a semi-empirical model, we demonstrate how an informatics-based analysis can be used to address this issue with no prior assumptions. We have developed a unique approach for identifying the minimum number of descriptors necessary to capture all the information of a system. Using Ti-Al alloys of varying compositions and crystal chemistries as the test bed, 5 of the 21 original descriptors from electronic structure calculations are found to capture all the information from the calculation, thereby reducing the structure-chemistry-property search space. Additionally, by combining electronic structure calculations with data mining, we classify the systems by chemistries and structures, based on the electronic structure inputs, and thereby rank the impact of change in chemistry and crystal structure on the electronic structure. -- Research Highlights: {yields} We developed an informatics-based methodology to minimize the necessary information. {yields} We applied this methodology to descriptors from semi-empirical calculations. {yields} We developed a validation approach for maintaining information from screening. {yields} We classified intermetallics and identified patterns of composition and structure.

Data mining of Ti-Al semi-empirical parameters for developing reduced order models

International Nuclear Information System (INIS)

Broderick, Scott R.; Aourag, Hafid; Rajan, Krishna

2011-01-01

A focus of materials design is determining the minimum amount of information necessary to fully describe a system, thus reducing the number of empirical results required and simplifying the data analysis. Screening descriptors calculated through a semi-empirical model, we demonstrate how an informatics-based analysis can be used to address this issue with no prior assumptions. We have developed a unique approach for identifying the minimum number of descriptors necessary to capture all the information of a system. Using Ti-Al alloys of varying compositions and crystal chemistries as the test bed, 5 of the 21 original descriptors from electronic structure calculations are found to capture all the information from the calculation, thereby reducing the structure-chemistry-property search space. Additionally, by combining electronic structure calculations with data mining, we classify the systems by chemistries and structures, based on the electronic structure inputs, and thereby rank the impact of change in chemistry and crystal structure on the electronic structure. -- Research Highlights: → We developed an informatics-based methodology to minimize the necessary information. → We applied this methodology to descriptors from semi-empirical calculations. → We developed a validation approach for maintaining information from screening. → We classified intermetallics and identified patterns of composition and structure.

Split degenerate states and stable p+ip phases from holography

Energy Technology Data Exchange (ETDEWEB)

Nie, Zhang-Yu; Zeng, Hui [Kunming University of Science and Technology, Kunming (China); Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing (China); Pan, Qiyuan [Hunan Normal Univ., Key Lab. of Low Dimensional Quantum Structures and Quantum Control of Ministry of Education, and Synergetic Innovation Center for Quantum Effects and Applications, Dept. of Physics, Changsha (China); Zeng, Hua-Bi [Yangzhou University, College of Physics Science and Technology, Yangzhou, Jiangsu (China); National Central University, Department of Physics, Chungli (China)

2017-02-15

In this paper, we investigate the p+ip superfluid phases in the complex vector field holographic p-wave model. We find that in the probe limit, the p+ip phase and the p-wave phase are equally stable, hence the p and ip orders can be mixed with an arbitrary ratio to form more general p+λip phases, which are also equally stable with the p-wave and p+ip phases. As a result, the system possesses a degenerate thermal state in the superfluid region. We further study the case on considering the back-reaction on the metric, and we find that the degenerate ground states will be separated into p-wave and p+ip phases, and the p-wave phase is more stable. Finally, due to the different critical temperature of the zeroth order phase transitions from p-wave and p+ip phases to the normal phase, there is a temperature region where the p+ip phase exists but the p-wave phase does not. In this region we find the stable holographic p+ip phase for the first time. (orig.)

A physiological skeletal model for radionuclide and stable element biokinetics in children and adults

International Nuclear Information System (INIS)

Richardson, R.B.

2010-01-01

A physiological skeletal model (PSM) is described that represents the skeletal uptake, retention and clearance of both bone-surface-seeking and bone-volume-seeking radionuclides and stable elements. A key objective of the PSM is to model the higher skeletal growth and bone turnover in infants and children (compared to adults) in order to to account for their greater uptake and cancer risk from bone-seeking contaminants such as lead and plutonium. The PSM is a compartmental model that allows for the incorporation of organic and inorganic material in the bone volume via quiescent bone surfaces, forming bone surfaces and the lacuno-canaliculi system. The model uniquely incorporates a tertiary phase of mineralization via bone fluids. The PSM's structural concepts and biokinetic parameters - such as realistic mass transfers, organ and tissue masses, and bone remodelling half times - are selected mainly on the basis of physiological and anatomical criteria. For brevity, model parameter values or evaluated for adults only. The PSM is an improvement on existing skeletal models that are based more on compartment structures and pathways that rendered good fits to biokinetic data rather than on being anatomically and physiologically accurate. (author)

Reducing the first-order Doppler shift in a Sagnac interferometer

NARCIS (Netherlands)

Hannemann, S.; Salumbides, E.J.; Ubachs, W.M.G.

2007-01-01

We demonstrate a technique to reduce first-order Doppler shifts in crossed atomic/molecular and laser beam setups by aligning two counterpropagating laser beams as part of a Sagnac interferometer. Interference fringes on the exit port of the interferometer reveal minute deviations from perfect

Bartlett correction in the stable AR(1) model with intercept and trend

NARCIS (Netherlands)

van Giersbergen, N.P.A.

2004-01-01

The Bartlett correction is derived for testing hypotheses about the autoregressive parameter ρ in the stable: (i) AR(1) model; (ii) AR(1) model with intercept; (iii) AR(1) model with intercept and linear trend. The correction is found explicitly as a function of ρ. In the models with deterministic

Search for stable mutli-charged particles with the ATLAS experiment

CERN Document Server

Zimmermann, S

2013-01-01

A search for stable massive particles with electric charges of $|q|=2e$ to $|q|=6e$ is performed with the ATLAS detector at the LHC. A dataset of 4.4$\\, \\text{fb}^{-1}$ is searched for highly ionization muon signatures. No deviation from the standard model expectations is observed and 95% CL upper cross section limits on the order of $\\mathcal{O}(0.01 - 0.1\\, \\text{pb})$ are set. This result represents the first limit on the production cross section of stable massive particles with charges $|q|=2e$ to $|q|=5e$ published by the ATLAS collaboration and improves a previous limit on particles with $|q|=6e$ by two orders of magnitude.

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

Science.gov (United States)

Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-05-01

Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Finding Non-Zero Stable Fixed Points of the Weighted Kuramoto model is NP-hard

OpenAIRE

Taylor, Richard

2015-01-01

The Kuramoto model when considered over the full space of phase angles [$0,2\\pi$) can have multiple stable fixed points which form basins of attraction in the solution space. In this paper we illustrate the fundamentally complex relationship between the network topology and the solution space by showing that determining the possibility of multiple stable fixed points from the network topology is NP-hard for the weighted Kuramoto Model. In the case of the unweighted model this problem is shown...

On the locally stable states of the Sherrington-Kirkpatrick model

International Nuclear Information System (INIS)

Parga, N.; Parisi, G.

1985-07-01

By using a steepest descent algorithm we calculate the attraction basin of locally stable states of the Sherrington-Kirkpatrick model of spin glasses. Looking for correlations among these states we show the existence of clusters of spins and construct a cluster Hamiltonian. (author)

Nonlinear behavior of multiple-helicity resistive interchange modes near marginally stable states

International Nuclear Information System (INIS)

Sugama, Hideo; Nakajima, Noriyoshi; Wakatani, Masahiro.

1991-05-01

Nonlinear behavior of resistive interchange modes near marginally stable states is theoretically studied under the multiple-helicity condition. Reduced fluid equations in the sheared slab configuration are used in order to treat a local transport problem. With the use of the invariance property of local reduced fluid model equations under a transformation between the modes with different rational surfaces, weakly nonlinear theories for single-helicity modes by Hamaguchi and Nakajima are extended to the multiple-helicity case and applied to the resistive interchange modes. We derive the nonlinear amplitude equations of the multiple-helicity modes, from which the convective transport in the saturated state is obtained. It is shown how the convective transport is enhanced by nonlinear interaction between modes with different rational surfaces compared with the single-helicity case. We confirm that theoretical results are in good agreement with direct numerical simulations. (author)

BWR stability using a reduced dynamical model

International Nuclear Information System (INIS)

Ballestrin Bolea, J.M.; Blazquez, J.B.

1990-01-01

BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical struct-ure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations in non-linear. Simple parametric calculat-ion of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author). 7 refs

A Robust Computational Technique for Model Order Reduction of Two-Time-Scale Discrete Systems via Genetic Algorithms

Directory of Open Access Journals (Sweden)

Othman M. K. Alsmadi

2015-01-01

Full Text Available A robust computational technique for model order reduction (MOR of multi-time-scale discrete systems (single input single output (SISO and multi-input multioutput (MIMO is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.

On the solution of high order stable time integration methods

Czech Academy of Sciences Publication Activity Database

Axelsson, Owe; Blaheta, Radim; Sysala, Stanislav; Ahmad, B.

2013-01-01

Roč. 108, č. 1 (2013), s. 1-22 ISSN 1687-2770 Institutional support: RVO:68145535 Keywords : evolution equations * preconditioners for quadratic matrix polynomials * a stiffly stable time integration method Subject RIV: BA - General Mathematics Impact factor: 0.836, year: 2013 http://www.boundaryvalueproblems.com/content/2013/1/108

Application of the MOVE algorithm for the identification of reduced order models of a core of a BWR type reactor

International Nuclear Information System (INIS)

Victoria R, M.A.; Morales S, J.B.

2005-01-01

Presently work is applied the modified algorithm of the ellipsoid of optimal volume (MOVE) to a reduced order model of 5 differential equations of the core of a boiling water reactor (BWR) with the purpose of estimating the parameters that model the dynamics. The viability is analyzed of carrying out an analysis that calculates the global dynamic parameters that determine the stability of the system and the uncertainty of the estimate. The modified algorithm of the ellipsoid of optimal volume (MOVE), is a method applied to the parametric identification of systems, in particular to the estimate of groups of parameters (PSE for their initials in English). It is looked for to obtain the ellipsoid of smaller volume that guarantees to contain the real value of the parameters of the model. The PSE MOVE is a recursive identification method that can manage the sign of noise and to ponder it, the ellipsoid represents an advantage due to its easy mathematical handling in the computer, the results that surrender are very useful for the design of Robust Control since to smaller volume of the ellipsoid, better is in general the performance of the system to control. The comparison with other methods presented in the literature to estimate the reason of decline (DR) of a BWR is presented. (Author)

Fractional-order in a macroeconomic dynamic model

Science.gov (United States)

David, S. A.; Quintino, D. D.; Soliani, J.

2013-10-01

In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

Higher Order, Hybrid BEM/FEM Methods Applied to Antenna Modeling

Science.gov (United States)

Fink, P. W.; Wilton, D. R.; Dobbins, J. A.

2002-01-01

In this presentation, the authors address topics relevant to higher order modeling using hybrid BEM/FEM formulations. The first of these is the limitation on convergence rates imposed by geometric modeling errors in the analysis of scattering by a dielectric sphere. The second topic is the application of an Incomplete LU Threshold (ILUT) preconditioner to solve the linear system resulting from the BEM/FEM formulation. The final tOpic is the application of the higher order BEM/FEM formulation to antenna modeling problems. The authors have previously presented work on the benefits of higher order modeling. To achieve these benefits, special attention is required in the integration of singular and near-singular terms arising in the surface integral equation. Several methods for handling these terms have been presented. It is also well known that achieving he high rates of convergence afforded by higher order bases may als'o require the employment of higher order geometry models. A number of publications have described the use of quadratic elements to model curved surfaces. The authors have shown in an EFIE formulation, applied to scattering by a PEC .sphere, that quadratic order elements may be insufficient to prevent the domination of modeling errors. In fact, on a PEC sphere with radius r = 0.58 Lambda(sub 0), a quartic order geometry representation was required to obtain a convergence benefi.t from quadratic bases when compared to the convergence rate achieved with linear bases. Initial trials indicate that, for a dielectric sphere of the same radius, - requirements on the geometry model are not as severe as for the PEC sphere. The authors will present convergence results for higher order bases as a function of the geometry model order in the hybrid BEM/FEM formulation applied to dielectric spheres. It is well known that the system matrix resulting from the hybrid BEM/FEM formulation is ill -conditioned. For many real applications, a good preconditioner is required

Nuclear-coupled thermal-hydraulic nonlinear stability analysis using a novel BWR reduced order model. Pt. 1. The effects of using drift flux versus homogeneous equilibrium models

International Nuclear Information System (INIS)

Dokhane, A.; Henning, D.; Chawla, R.; Rizwan-Uddin

2003-01-01

BWR stability analysis at PSI, as at other research centres, is usually carried out employing complex system codes. However, these do not allow a detailed investigation of the complete manifold of all possible solutions of the associated nonlinear differential equation set. A novel analytical, reduced order model for BWR stability has been developed at PSI, in several successive steps. In the first step, the thermal-hydraulic model was used for studying the thermal-hydraulic instabilities. A study was then conducted of the one-channel nuclear-coupled thermal-hydraulic dynamics in a BWR by adding a simple point kinetic model for neutron kinetics and a model for the fuel heat conduction dynamics. In this paper, a two-channel nuclear-coupled thermal-hydraulic model is introduced to simulate the out-of phase oscillations in a BWR. This model comprises three parts: spatial mode neutron kinetics with the fundamental and fist azimuthal modes; fuel heat conduction dynamics; and thermal-hydraulics model. This present model is an extension of the Karve et al. model i.e., a drift flux model is used instead of the homogeneous equilibrium model for two-phase flow, and lambda modes are used instead of the omega modes for the neutron kinetics. This two-channel model is employed in stability and bifurcation analyses, carried out using the bifurcation code BIFDD. The stability boundary (SB) and the nature of the Poincare-Andronov-Hopf bifurcation (PAF-B) are determined and visualized in a suitable two-dimensional parameter/state space. A comparative study of the homogeneous equilibrium model (HEM) and the drift flux model (DFM) is carried out to investigate the effects of the DFM parameters the void distribution parameter C 0 and the drift velocity V gi -on the SB, the nature of PAH bifurcation, and on the type of oscillation mode (in-phase or out-of-phase). (author)

Modeling hemoglobin at optical frequency using the unconditionally stable fundamental ADI-FDTD method.

Science.gov (United States)

Heh, Ding Yu; Tan, Eng Leong

2011-04-12

This paper presents the modeling of hemoglobin at optical frequency (250 nm - 1000 nm) using the unconditionally stable fundamental alternating-direction-implicit finite-difference time-domain (FADI-FDTD) method. An accurate model based on complex conjugate pole-residue pairs is proposed to model the complex permittivity of hemoglobin at optical frequency. Two hemoglobin concentrations at 15 g/dL and 33 g/dL are considered. The model is then incorporated into the FADI-FDTD method for solving electromagnetic problems involving interaction of light with hemoglobin. The computation of transmission and reflection coefficients of a half space hemoglobin medium using the FADI-FDTD validates the accuracy of our model and method. The specific absorption rate (SAR) distribution of human capillary at optical frequency is also shown. While maintaining accuracy, the unconditionally stable FADI-FDTD method exhibits high efficiency in modeling hemoglobin.

On the Entropy Based Associative Memory Model with Higher-Order Correlations

Directory of Open Access Journals (Sweden)

Masahiro Nakagawa

2010-01-01

Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.

Intact Rapid Facial Mimicry as well as Generally Reduced Mimic Responses in Stable Schizophrenia Patients

Science.gov (United States)

Chechko, Natalya; Pagel, Alena; Otte, Ellen; Koch, Iring; Habel, Ute

2016-01-01

Spontaneous emotional expressions (rapid facial mimicry) perform both emotional and social functions. In the current study, we sought to test whether there were deficits in automatic mimic responses to emotional facial expressions in patients (15 of them) with stable schizophrenia compared to 15 controls. In a perception-action interference paradigm (the Simon task; first experiment), and in the context of a dual-task paradigm (second experiment), the task-relevant stimulus feature was the gender of a face, which, however, displayed a smiling or frowning expression (task-irrelevant stimulus feature). We measured the electromyographical activity in the corrugator supercilii and zygomaticus major muscle regions in response to either compatible or incompatible stimuli (i.e., when the required response did or did not correspond to the depicted facial expression). The compatibility effect based on interactions between the implicit processing of a task-irrelevant emotional facial expression and the conscious production of an emotional facial expression did not differ between the groups. In stable patients (in spite of a reduced mimic reaction), we observed an intact capacity to respond spontaneously to facial emotional stimuli. PMID:27303335

Stable Superstring Relics and Ultrahigh Energy Cosmic Rays

CERN Document Server

Coriano, Claudio; Plumacher, Michael; Coriano, Claudio; Faraggi, Alon E.; Plumacher, Michael

2001-01-01

One of the most intriguing experimental results of recent years is the observation of Ultrahigh Energy Cosmic Rays (UHECRs) above the GZK cutoff. Plausible candidates for the UHECR primaries are the decay products of a meta--stable matter state with mass of order O(10^{12-15 GeV}), which simultaneously is a good cold dark matter candidate. We study possible meta-stable matter states that arise from Wilson line breaking of GUT symmetries in semi-realistic heterotic string models. In the models that we study the exotic matter states can be classified according to patterns of SO(10) symmetry breaking. We show that cryptons, which are states that carry fractional electric charge $\\pm1/2$, and are confined by a hidden gauge group cannot produce viable dark matter. This is due to the fact that, in addition to the lightest neutral bound state, cryptons give rise to meta-stable charged bound states. However, these states may still account for the UHECR events. We argue that the uniton, which is an exotic Standard Mod...

Magnetic order and Kondo effect in the Anderson-lattice model

International Nuclear Information System (INIS)

Bernhard, B.H.; Aguiar, C.; Kogoutiouk, I.; Coqblin, B.

2007-01-01

The Anderson-lattice model has been extensively developed to account for the properties of many anomalous rare-earth compounds and in particular for the competition between the Kondo effect and an antiferromagnetic (AF) phase in a cubic lattice. Here we apply the higher-order decoupling of the equations of motion for the Green Functions (GF) introduced in [H.G. Luo, S.J. Wang, Phys. Rev. B 62 (2000) 1485]. We obtain an improved description of the phase diagram, where the AF phase subsists in a smaller range of the model parameters. As higher-order GF are included in the chain of equations, we are able to calculate directly the local spin-flip correlation function † ↓ d † ↑ f ↑ d ↓ >. As a further improvement to the previous approximation of [B.H. Bernhard, C. Aguiar, B. Coqblin, Physica B 378-380 (2006) 712], we obtain a reduced range of existence for the AF phase for the symmetric half-filled case and then we discuss the competition between the AF order and the Kondo effect as a function of the band filling

Stable isotope reactive transport modeling in water-rock interactions during CO2 injection

Science.gov (United States)

Hidalgo, Juan J.; Lagneau, Vincent; Agrinier, Pierre

2010-05-01

Stable isotopes can be of great usefulness in the characterization and monitoring of CO2 sequestration sites. Stable isotopes can be used to track the migration of the CO2 plume and identify leakage sources. Moreover, they provide unique information about the chemical reactions that take place on the CO2-water-rock system. However, there is a lack of appropriate tools that help modelers to incorporate stable isotope information into the flow and transport models used in CO2 sequestration problems. In this work, we present a numerical tool for modeling the transport of stable isotopes in groundwater reactive systems. The code is an extension of the groundwater single-phase flow and reactive transport code HYTEC [2]. HYTEC's transport module was modified to include element isotopes as separate species. This way, it is able to track isotope composition of the system by computing the mixing between the background water and the injected solution accounting for the dependency of diffusion on the isotope mass. The chemical module and database have been expanded to included isotopic exchange with minerals and the isotope fractionation associated with chemical reactions and mineral dissolution or precipitation. The performance of the code is illustrated through a series of column synthetic models. The code is also used to model the aqueous phase CO2 injection test carried out at the Lamont-Doherty Earth Observatory site (Palisades, New York, USA) [1]. References [1] N. Assayag, J. Matter, M. Ader, D. Goldberg, and P. Agrinier. Water-rock interactions during a CO2 injection field-test: Implications on host rock dissolution and alteration effects. Chemical Geology, 265(1-2):227-235, July 2009. [2] Jan van der Lee, Laurent De Windt, Vincent Lagneau, and Patrick Goblet. Module-oriented modeling of reactive transport with HYTEC. Computers & Geosciences, 29(3):265-275, April 2003.

Electrochemical state and internal variables estimation using a reduced-order physics-based model of a lithium-ion cell and an extended Kalman filter

Energy Technology Data Exchange (ETDEWEB)

Stetzel, KD; Aldrich, LL; Trimboli, MS; Plett, GL

2015-03-15

This paper addresses the problem of estimating the present value of electrochemical internal variables in a lithium-ion cell in real time, using readily available measurements of cell voltage, current, and temperature. The variables that can be estimated include any desired set of reaction flux and solid and electrolyte potentials and concentrations at any set of one-dimensional spatial locations, in addition to more standard quantities such as state of charge. The method uses an extended Kalman filter along with a one-dimensional physics-based reduced-order model of cell dynamics. Simulations show excellent and robust predictions having dependable error bounds for most internal variables. (C) 2014 Elsevier B.V. All rights reserved.

Stable Boundary Layer Issues

OpenAIRE

Steeneveld, G.J.

2012-01-01

Understanding and prediction of the stable atmospheric boundary layer is a challenging task. Many physical processes are relevant in the stable boundary layer, i.e. turbulence, radiation, land surface coupling, orographic turbulent and gravity wave drag, and land surface heterogeneity. The development of robust stable boundary layer parameterizations for use in NWP and climate models is hampered by the multiplicity of processes and their unknown interactions. As a result, these models suffer ...

Local Search Approaches in Stable Matching Problems

Directory of Open Access Journals (Sweden)

Toby Walsh

2013-10-01

Full Text Available The stable marriage (SM problem has a wide variety of practical applications, ranging from matching resident doctors to hospitals, to matching students to schools or, more generally, to any two-sided market. In the classical formulation, n men and n women express their preferences (via a strict total order over the members of the other sex. Solving an SM problem means finding a stable marriage where stability is an envy-free notion: no man and woman who are not married to each other would both prefer each other to their partners or to being single. We consider both the classical stable marriage problem and one of its useful variations (denoted SMTI (Stable Marriage with Ties and Incomplete lists where the men and women express their preferences in the form of an incomplete preference list with ties over a subset of the members of the other sex. Matchings are permitted only with people who appear in these preference lists, and we try to find a stable matching that marries as many people as possible. Whilst the SM problem is polynomial to solve, the SMTI problem is NP-hard. We propose to tackle both problems via a local search approach, which exploits properties of the problems to reduce the size of the neighborhood and to make local moves efficiently. We empirically evaluate our algorithm for SM problems by measuring its runtime behavior and its ability to sample the lattice of all possible stable marriages. We evaluate our algorithm for SMTI problems in terms of both its runtime behavior and its ability to find a maximum cardinality stable marriage. Experimental results suggest that for SM problems, the number of steps of our algorithm grows only as O(n log(n, and that it samples very well the set of all stable marriages. It is thus a fair and efficient approach to generate stable marriages. Furthermore, our approach for SMTI problems is able to solve large problems, quickly returning stable matchings of large and often optimal size, despite the

Formulation of a reduced order model of the climatic system by combining classical simulation methods with artificial intelligence techniques

Science.gov (United States)

Bounceur, Nabila; Crucifix, Michel

2010-05-01

The climate is a multivariable dynamic complex system, governed by equations which are strongly nonlinear. The space-time modes of climatic variability extend on a very broad scale and constitute a major difficulty to represent this variability over long time-scales. It is generally decided to separate the dynamics of the slow components (ice sheets, carbon cycle, deep oceans) which have a time scale of about thousand of years and more, from those of the fast components (atmosphere, mixed layer, earth and ice surface) for which the time scale is for about some years. In this framework, the time-evolution of the slow components depends on the statistics of the fast components, and the latter are controlled by the slow components and the external forcing particularly astronomical ones characterised by the variation of the orbital parameters: Obliquity, precession and eccentricity. The statistics of the fast components of the climate could in principle be estimated with a general circulation model of the atmosphere and ocean. However, the demand on computing resources would be far too excessive. Given the complexity of the climatic system, the great number of dynamic equations which govern it and its degree of nonlinearity we are interested in the statistical reduction rather than an analytical one. The order reduction problem is equivalent to approximator construction. We will focus on neural networks because they constitute very powerful estimators in presence of non-linearity. The training of this network would be done using the output of the climate model of intermediate complexity "LoveClim" developed and available in the Institute of Astronomy and Geophysics G.Lemaître in Belgium as a first step of statistical reduction. The output of the model are first reduced using different methods of reduction order going from linear ones as principal component analysis (PCA) and empirical orthogonal functions (EOF) to non linear ones as Non Linear Principal component

An Optimally Stable and Accurate Second-Order SSP Runge-Kutta IMEX Scheme for Atmospheric Applications

Science.gov (United States)

Rokhzadi, Arman; Mohammadian, Abdolmajid; Charron, Martin

2018-01-01

The objective of this paper is to develop an optimized implicit-explicit (IMEX) Runge-Kutta scheme for atmospheric applications focusing on stability and accuracy. Following the common terminology, the proposed method is called IMEX-SSP2(2,3,2), as it has second-order accuracy and is composed of diagonally implicit two-stage and explicit three-stage parts. This scheme enjoys the Strong Stability Preserving (SSP) property for both parts. This new scheme is applied to nonhydrostatic compressible Boussinesq equations in two different arrangements, including (i) semiimplicit and (ii) Horizontally Explicit-Vertically Implicit (HEVI) forms. The new scheme preserves the SSP property for larger regions of absolute monotonicity compared to the well-studied scheme in the same class. In addition, numerical tests confirm that the IMEX-SSP2(2,3,2) improves the maximum stable time step as well as the level of accuracy and computational cost compared to other schemes in the same class. It is demonstrated that the A-stability property as well as satisfying "second-stage order" and stiffly accurate conditions lead the proposed scheme to better performance than existing schemes for the applications examined herein.

Multi-Criteria Model for Determining Order Size

Directory of Open Access Journals (Sweden)

Katarzyna Jakowska-Suwalska

2013-01-01

Full Text Available A multi-criteria model for determining the order size for materials used in production has been presented. It was assumed that the consumption rate of each material is a random variable with a known probability distribution. Using such a model, in which the purchase cost of materials ordered is limited, three criteria were considered: order size, probability of a lack of materials in the production process, and deviations in the order size from the consumption rate in past periods. Based on an example, it has been shown how to use the model to determine the order sizes for polyurethane adhesive and wood in a hard-coal mine. (original abstract

Computation of External Quality Factors for RF Structures by Means of Model Order Reduction and a Perturbation Approach

CERN Document Server

Flisgen, Thomas; van Rienen, Ursula

2016-01-01

External quality factors are significant quantities to describe losses via waveguide ports in radio frequency resonators. The current contribution presents a novel approach to determine external quality factors by means of a two-step procedure: First, a state-space model for the lossless radio frequency structure is generated and its model order is reduced. Subsequently, a perturbation method is applied on the reduced model so that external losses are accounted for. The advantage of this approach results from the fact that the challenges in dealing with lossy systems are shifted to the reduced order model. This significantly saves computational costs. The present paper provides a short overview on existing methods to compute external quality factors. Then, the novel approach is introduced and validated in terms of accuracy and computational time by means of commercial software.

Feasibility of self-correcting quantum memory and thermal stability of topological order

International Nuclear Information System (INIS)

Yoshida, Beni

2011-01-01

Recently, it has become apparent that the thermal stability of topologically ordered systems at finite temperature, as discussed in condensed matter physics, can be studied by addressing the feasibility of self-correcting quantum memory, as discussed in quantum information science. Here, with this correspondence in mind, we propose a model of quantum codes that may cover a large class of physically realizable quantum memory. The model is supported by a certain class of gapped spin Hamiltonians, called stabilizer Hamiltonians, with translation symmetries and a small number of ground states that does not grow with the system size. We show that the model does not work as self-correcting quantum memory due to a certain topological constraint on geometric shapes of its logical operators. This quantum coding theoretical result implies that systems covered or approximated by the model cannot have thermally stable topological order, meaning that systems cannot be stable against both thermal fluctuations and local perturbations simultaneously in two and three spatial dimensions. - Highlights: → We define a class of physically realizable quantum codes. → We determine their coding and physical properties completely. → We establish the connection between topological order and self-correcting memory. → We find they do not work as self-correcting quantum memory. → We find they do not have thermally stable topological order.

Unconditionally energy stable numerical schemes for phase-field vesicle membrane model

Science.gov (United States)

Guillén-González, F.; Tierra, G.

2018-02-01

Numerical schemes to simulate the deformation of vesicles membranes via minimizing the bending energy have been widely studied in recent times due to its connection with many biological motivated problems. In this work we propose a new unconditionally energy stable numerical scheme for a vesicle membrane model that satisfies exactly the conservation of volume constraint and penalizes the surface area constraint. Moreover, we extend these ideas to present an unconditionally energy stable splitting scheme decoupling the interaction of the vesicle with a surrounding fluid. Finally, the well behavior of the proposed schemes are illustrated through several computational experiments.

The use of stable isotopes as minerals tracers in human nutrition research

International Nuclear Information System (INIS)

Sajet, A. S.

2007-01-01

The idea of using stable isotopes as tracers in metabolic studies of vital systems started when it was noted that stable isotopes have the ability to unite with biomolecules.The article aims to review the methods used to measure quantities of tracer in doses given to donors orally or via intravenous injection, determinants of detection and their estimation as well as the use of mass spectrometer and other devices to measure different stable isotopes. In fact, the use of stable isotopes in nutrition research is an essential technique in order to understand many of the processes related to minerals absorption and the human body composition of water, fat and bones, transportation of food components within the body and estimation of the ages of red blood cells. It is possible to use the secretion of stable isotopes taken by injection to determine the paths of excretion or estimate self-retaining material by the intestine. The stable isotope technology helps to know the mechanics of minerals absorption and excretion in the body. It was possible to find out metabolic reactions of metals using mathematical models based on the measurement of tracers amount in biological fluids in order to know the absorbance situation of metals in the body.

Temperature and Humidity Control in Livestock Stables

DEFF Research Database (Denmark)

Hansen, Michael; Andersen, Palle; Nielsen, Kirsten M.

2010-01-01

The paper describes temperature and humidity control of a livestock stable. It is important to have a correct air flow pattern in the livestock stable in order to achieve proper temperature and humidity control as well as to avoid draught. In the investigated livestock stable the air flow...

Self-esteem Is Mostly Stable Across Young Adulthood: Evidence from Latent STARTS Models.

Science.gov (United States)

Wagner, Jenny; Lüdtke, Oliver; Trautwein, Ulrich

2016-08-01

How stable is self-esteem? This long-standing debate has led to different conclusions across different areas of psychology. Longitudinal data and up-to-date statistical models have recently indicated that self-esteem has stable and autoregressive trait-like components and state-like components. We applied latent STARTS models with the goal of replicating previous findings in a longitudinal sample of young adults (N = 4,532; Mage  = 19.60, SD = 0.85; 55% female). In addition, we applied multigroup models to extend previous findings on different patterns of stability for men versus women and for people with high versus low levels of depressive symptoms. We found evidence for the general pattern of a major proportion of stable and autoregressive trait variance and a smaller yet substantial amount of state variance in self-esteem across 10 years. Furthermore, multigroup models suggested substantial differences in the variance components: Females showed more state variability than males. Individuals with higher levels of depressive symptoms showed more state and less autoregressive trait variance in self-esteem. Results are discussed with respect to the ongoing trait-state debate and possible implications of the group differences that we found in the stability of self-esteem. © 2015 Wiley Periodicals, Inc.

Numerically stable, scalable formulas for parallel and online computation of higher-order multivariate central moments with arbitrary weights

Energy Technology Data Exchange (ETDEWEB)

Pebay, Philippe [Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Terriberry, Timothy B. [Xiph.Org Foundation, Arlington, VA (United States); Kolla, Hemanth [Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Bennett, Janine [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)

2016-03-29

Formulas for incremental or parallel computation of second order central moments have long been known, and recent extensions of these formulas to univariate and multivariate moments of arbitrary order have been developed. Formulas such as these, are of key importance in scenarios where incremental results are required and in parallel and distributed systems where communication costs are high. We survey these recent results, and improve them with arbitrary-order, numerically stable one-pass formulas which we further extend with weighted and compound variants. We also develop a generalized correction factor for standard two-pass algorithms that enables the maintenance of accuracy over nearly the full representable range of the input, avoiding the need for extended-precision arithmetic. We then empirically examine algorithm correctness for pairwise update formulas up to order four as well as condition number and relative error bounds for eight different central moment formulas, each up to degree six, to address the trade-offs between numerical accuracy and speed of the various algorithms. Finally, we demonstrate the use of the most elaborate among the above mentioned formulas, with the utilization of the compound moments for a practical large-scale scientific application.

SECOND ORDER LEAST SQUARE ESTIMATION ON ARCH(1 MODEL WITH BOX-COX TRANSFORMED DEPENDENT VARIABLE

Directory of Open Access Journals (Sweden)

Herni Utami

2014-03-01

Full Text Available Box-Cox transformation is often used to reduce heterogeneity and to achieve a symmetric distribution of response variable. In this paper, we estimate the parameters of Box-Cox transformed ARCH(1 model using second-order leastsquare method and then we study the consistency and asymptotic normality for second-order least square (SLS estimators. The SLS estimation was introduced byWang (2003, 2004 to estimate the parameters of nonlinear regression models with independent and identically distributed errors

Model selection criteria : how to evaluate order restrictions

NARCIS (Netherlands)

Kuiper, R.M.

2012-01-01

Researchers often have ideas about the ordering of model parameters. They frequently have one or more theories about the ordering of the group means, in analysis of variance (ANOVA) models, or about the ordering of coefficients corresponding to the predictors, in regression models.A researcher might

A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics

Science.gov (United States)

Kerfriden, P.; Goury, O.; Rabczuk, T.; Bordas, S.P.A.

2013-01-01

We propose in this paper a reduced order modelling technique based on domain partitioning for parametric problems of fracture. We show that coupling domain decomposition and projection-based model order reduction permits to focus the numerical effort where it is most needed: around the zones where damage propagates. No a priori knowledge of the damage pattern is required, the extraction of the corresponding spatial regions being based solely on algebra. The efficiency of the proposed approach is demonstrated numerically with an example relevant to engineering fracture. PMID:23750055

Reduced 123I-BMIPP uptake implies decreased myocardial flow reserve in patients with chronic stable angina.

Science.gov (United States)

Kageyama, Hiroyuki; Morita, Koichi; Katoh, Chietsugu; Tsukamoto, Takahiro; Noriyasu, Kazuyuki; Mabuchi, Megumi; Naya, Masanao; Kawai, Yuko; Tamaki, Nagara

2006-01-01

Long-chain fatty acid (LCFA) is the main energy source for normal myocardium at rest, but in ischemic myocardium, the main energy substrate shifts from LCFA to glucose. 123I-BMIPP is a radiolabeled LCFA analog. In chronic stable angina without previous infarction, we suppose that reduced 123I-BMIPP uptake is related to the substrate shift in myocardium with decreased myocardial flow reserve (MFR). The purpose of this study was to relate 123I-BMIPP uptake to rest myocardial blood flow (MBF), hyperemic MBF, and MFR assessed with 15O-water positron emission tomography (PET). We enrolled 21 patients with chronic stable angina without previous infarction, all of whom underwent 123I-BMIPP single-photon emission computed tomography (SPECT) and 15O-water PET. The left ventricle was divided into 13 segments. In each segment, rest MBF and hyperemic MBF were measured by PET. 123I-BMIPP uptake was evaluated as follows: score 0=normal, 1=slightly decreased uptake, 2=moderately decreased uptake, 3=severely decreased uptake, and 4=complete defect. 123I-BMIPP uptake was compared with rest MBF, hyperemic MBF, and MFR. The numbers of segments with 123I-BMIPP scores 0, 1, 2, 3, and 4 were 178, 40, 25, 24, and 0, respectively. The rest MBFs for scores 0, 1, 2, and 3 were 0.93+/-0.25, 0.86+/-0.21, 0.97+/-0.30, and 0.99+/-0.37 ml/min/g, respectively. The hyperemic MBFs for scores 0, 1, 2, and 3 were 2.76+/-1.29, 1.84+/-0.74, 1.37+/-0.39, and 1.08+/-0.40 ml/min/g, respectively. The MFRs for scores 0, 1, 2, and 3 were 3.01+/-1.38, 2.20+/-0.95, 1.44+/-0.22, and 1.10+/-0.26, respectively. As 123I-BMIPP uptake declined, hyperemic MBF and MFR decreased. In chronic stable angina without previous infarction, reduced 123I-BMIPP uptake implies decreased MFR.

Reduced 123I-BMIPP uptake implies decreased myocardial flow reserve in patients with chronic stable angina

International Nuclear Information System (INIS)

Kageyama, Hiroyuki; Morita, Koichi; Katoh, Chietsugu; Mabuchi, Megumi; Tamaki, Nagara; Tsukamoto, Takahiro; Noriyasu, Kazuyuki; Naya, Masanao; Kawai, Yuko

2006-01-01

Long-chain fatty acid (LCFA) is the main energy source for normal myocardium at rest, but in ischemic myocardium, the main energy substrate shifts from LCFA to glucose. 123 I-BMIPP is a radiolabeled LCFA analog. In chronic stable angina without previous infarction, we suppose that reduced 123 I-BMIPP uptake is related to the substrate shift in myocardium with decreased myocardial flow reserve (MFR). The purpose of this study was to relate 123 I-BMIPP uptake to rest myocardial blood flow (MBF), hyperemic MBF, and MFR assessed with 15 O-water positron emission tomography (PET). We enrolled 21 patients with chronic stable angina without previous infarction, all of whom underwent 123 I-BMIPP single-photon emission computed tomography (SPECT) and 15 O-water PET. The left ventricle was divided into 13 segments. In each segment, rest MBF and hyperemic MBF were measured by PET. 123 I-BMIPP uptake was evaluated as follows: score 0=normal, 1=slightly decreased uptake, 2=moderately decreased uptake, 3=severely decreased uptake, and 4=complete defect. 123 I-BMIPP uptake was compared with rest MBF, hyperemic MBF, and MFR. The numbers of segments with 123 I-BMIPP scores 0, 1, 2, 3, and 4 were 178, 40, 25, 24, and 0, respectively. The rest MBFs for scores 0, 1, 2, and 3 were 0.93±0.25, 0.86±0.21, 0.97±0.30, and 0.99±0.37 ml/min/g, respectively. The hyperemic MBFs for scores 0, 1, 2, and 3 were 2.76±1.29, 1.84±0.74, 1.37±0.39, and 1.08±0.40 ml/min/g, respectively. The MFRs for scores 0, 1, 2, and 3 were 3.01±1.38, 2.20±0.95, 1.44±0.22, and 1.10±0.26, respectively. As 123 I-BMIPP uptake declined, hyperemic MBF and MFR decreased. In chronic stable angina without previous infarction, reduced 123 I-BMIPP uptake implies decreased MFR. (orig.)

Study Tranport Barrier Formation using Bi- Stable Sandpile Model

International Nuclear Information System (INIS)

Kitpitak, B.; Kanjanaput, W.; Poolyarat, N.; Picha, R; Onjun, T.

2014-01-01

The formation of plasma transport barrier in Tokamak is an important issue for achieving high energy confinement and sufficient fusion performance. The simulation using in this experiment simulates cycles of dropping grains in a sandpile with two stable and two unstable slope regimes which share the same characteristic as the formation of pedestal and there are several parameters used, including stable boundaries, grains in a toppling, relax process iterations per cycle, grains in a drop and number of drops per cycle. By using this simulation, the effects of the relaxation times and number of trooping grain (the number of collapsing grain in the relaxation process) can be investigated. It is found in the simulations that the pedestal region can be observed only when the number of deposited grain exceeds a critical value which is related to number of relaxation times and number of allowed trooping grain. In another words, the pedestal formation occurs when the particle deposition rate is higher than the average diffusion rate. In addition, altering amount of trooping grain can lead to remarkable effects on slope and height of the profiles. In order to achieve better energy confinement, further study of formation of plasma transport barrier is needed.

Derivation of reduced model for control system design using Chebyshev techniques

International Nuclear Information System (INIS)

Bistritz, Y.

1978-07-01

New methods are developed for reduced-order modelling of high-order, linear, time-invariant systems characterized by a transfer function. The first method is based on manipulating two Chebyshev polynomial series, one representing the frequency characteristics of the high-order system and the other representing the approximating low-order model. The proposed method can be viewed as generalizing the classical Pade approximation problem, with Chebyshev polynomial series being over a desired frequency interval instead of a power series about a single frequency point. The second method is based on approximating the high-order transfer function in terms of best Chebyshev approximation on a desired domain in the complex plane. An algorithm to find for a complex function best Chebyshev rational approximations in the complex plane is suggested and its theoretical basis confirmed. The algorithm is based on a complex version of Lawson algorithm that is applied to a complex version of a rational least square approximation program. (author)

Normal modified stable processes

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2002-01-01

Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added flexibility in the modelling of the dynamics of financial time series, of importance especially as regards OU based stochastic volatility models for equities. In the special case of the tempered stable OU process......This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse...

A model for reducing health care employee turnover.

Science.gov (United States)

Nowak, Paul; Holmes, Gary; Murrow, Jim

2010-01-01

Explaining the rationale as to why employees leave their jobs has led to many different strategies to retain employees. The model presented here seeks to explain why employees choose to stay or to leave their place of employment. The information from the analysis will provide managers with well-tested tools to reduce turnover and to ascertain what employees value from their work environment in order to help the organization to retain those employees. The model identifies key factors that management can utilize to provide barriers to exit and retain professional employees in their health care units. Recommendations are provided that reward loyalty and build barriers to exit.

Characterization of Flow Dynamics and Reduced-Order Description of Experimental Two-Phase Pipe Flow

Science.gov (United States)

Viggiano, Bianca; SkjæRaasen, Olaf; Tutkun, Murat; Cal, Raul Bayoan

2017-11-01

Multiphase pipe flow is investigated using proper orthogonal decomposition for tomographic X-ray data, where holdup, cross sectional phase distributions and phase interface characteristics are obtained. Instantaneous phase fractions of dispersed flow and slug flow are analyzed and a reduced order dynamical description is generated. The dispersed flow displays coherent structures in the first few modes near the horizontal center of the pipe, representing the liquid-liquid interface location while the slug flow case shows coherent structures that correspond to the cyclical formation and breakup of the slug in the first 10 modes. The reconstruction of the fields indicate that main features are observed in the low order dynamical descriptions utilizing less than 1 % of the full order model. POD temporal coefficients a1, a2 and a3 show interdependence for the slug flow case. The coefficients also describe the phase fraction holdup as a function of time for both dispersed and slug flow. These flows are highly applicable to petroleum transport pipelines, hydroelectric power and heat exchanger tubes to name a few. The mathematical representations obtained via proper orthogonal decomposition will deepen the understanding of fundamental multiphase flow characteristics.

Best practices for use of stable isotope mixing models in food-web studies

Science.gov (United States)

Stable isotope mixing models are increasingly used to quantify contributions of resources to consumers. While potentially powerful tools, these mixing models have the potential to be misused, abused, and misinterpreted. Here we draw on our collective experiences to address the qu...

Stable water isotopes in the coupled atmosphere–land surface model ECHAM5-JSBACH

Directory of Open Access Journals (Sweden)

B. Haese

2013-09-01

Full Text Available In this study we present first results of a new model development, ECHAM5-JSBACH-wiso, where we have incorporated the stable water isotopes H218O and HDO as tracers in the hydrological cycle of the coupled atmosphere–land surface model ECHAM5-JSBACH. The ECHAM5-JSBACH-wiso model was run under present-day climate conditions at two different resolutions (T31L19, T63L31. A comparison between ECHAM5-JSBACH-wiso and ECHAM5-wiso shows that the coupling has a strong impact on the simulated temperature and soil wetness. Caused by these changes of temperature and the hydrological cycle, the δ18O in precipitation also shows variations from −4‰ up to 4‰. One of the strongest anomalies is shown over northeast Asia where, due to an increase of temperature, the δ18O in precipitation increases as well. In order to analyze the sensitivity of the fractionation processes over land, we compare a set of simulations with various implementations of these processes over the land surface. The simulations allow us to distinguish between no fractionation, fractionation included in the evaporation flux (from bare soil and also fractionation included in both evaporation and transpiration (from water transport through plants fluxes. While the isotopic composition of the soil water may change for δ18O by up to +8&permil:, the simulated δ18O in precipitation shows only slight differences on the order of ±1‰. The simulated isotopic composition of precipitation fits well with the available observations from the GNIP (Global Network of Isotopes in Precipitation database.

Reduction of static field equation of Faddeev model to first order PDE

International Nuclear Information System (INIS)

Hirayama, Minoru; Shi Changguang

2007-01-01

A method to solve the static field equation of the Faddeev model is presented. For a special combination of the concerned field, we adopt a form which is compatible with the field equation and involves two arbitrary complex functions. As a result, the static field equation is reduced to a set of first order partial differential equations

Kohn–Sham exchange-correlation potentials from second-order reduced density matrices

Energy Technology Data Exchange (ETDEWEB)

Cuevas-Saavedra, Rogelio; Staroverov, Viktor N., E-mail: vstarove@uwo.ca [Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7 (Canada); Ayers, Paul W. [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1 (Canada)

2015-12-28

We describe a practical algorithm for constructing the Kohn–Sham exchange-correlation potential corresponding to a given second-order reduced density matrix. Unlike conventional Kohn–Sham inversion methods in which such potentials are extracted from ground-state electron densities, the proposed technique delivers unambiguous results in finite basis sets. The approach can also be used to separate approximately the exchange and correlation potentials for a many-electron system for which the reduced density matrix is known. The algorithm is implemented for configuration-interaction wave functions and its performance is illustrated with numerical examples.

XY model with higher-order exchange.

Science.gov (United States)

Žukovič, Milan; Kalagov, Georgii

2017-08-01

An XY model, generalized by inclusion of up to an infinite number of higher-order pairwise interactions with an exponentially decreasing strength, is studied by spin-wave theory and Monte Carlo simulations. At low temperatures the model displays a quasi-long-range-order phase characterized by an algebraically decaying correlation function with the exponent η=T/[2πJ(p,α)], nonlinearly dependent on the parameters p and α that control the number of the higher-order terms and the decay rate of their intensity, respectively. At higher temperatures the system shows a crossover from the continuous Berezinskii-Kosterlitz-Thouless to the first-order transition for the parameter values corresponding to a highly nonlinear shape of the potential well. The role of topological excitations (vortices) in changing the nature of the transition is discussed.

The tempered one-sided stable density: a universal model for hydrological transport?

International Nuclear Information System (INIS)

Cvetkovic, Vladimir

2011-01-01

A generalized distribution for the water residence time in hydrological transport is proposed in the form of the tempered one-sided stable (TOSS) density. It is shown that limiting cases of the TOSS distribution recover virtually all distributions that have been considered in the literature for hydrological transport, from plug flow to flow reactor, the advection-dispersion model, and the gamma and Levy densities. The stable property of TOSS is particularly important, enabling a seamless transition between a time-domain random walk, and the Lagrangian (trajectory) approach along hydrological transport pathways.

Critical thickness of atomically ordered III-V alloys

Energy Technology Data Exchange (ETDEWEB)

France, R. M.; McMahon, W. E.; Guthrey, H. L. [National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401 (United States)

2015-10-12

The critical thickness model is modified with a general boundary energy that describes the change in bulk energy as a dislocation regularly alters the atomic structure of an ordered material. The model is evaluated for dislocations gliding through CuPt-ordered GaInP and GaInAs, where the boundary energy is negative and the boundary is stable. With ordering present, the critical thickness is significantly lowered and remains finite as the mismatch strain approaches zero. The reduction in critical thickness is most significant when the order parameter is greatest and the amount of misfit energy is low. The modified model is experimentally validated for low-misfit GaInP epilayers with varying order parameters using in situ wafer curvature and ex situ cathodoluminescence. With strong ordering, relaxation begins at a lower thickness and occurs at a greater rate, which is consistent with a lower critical thickness and increased glide force. Thus, atomic ordering is an important consideration for the stability of lattice-mismatched devices.

SUN-RAH: a nucleoelectric BWR university simulator based in reduced order models; SUN-RAH: simulador universitario de nucleoelectrica BWR basado en modelos de orden reducido

Energy Technology Data Exchange (ETDEWEB)

Morales S, J.B.; Lopez R, A.; Sanchez B, A.; Sanchez S, R.; Hernandez S, A. [DEPFI, Campus Morelos, en IMTA Jiutepec, Morelos (Mexico)]. e-mail: jms0620@yahoo.com

2003-07-01

The development of a simulator that allows to represent the dynamics of a nucleo electric central, with nuclear reactor of the BWR type, using reduced order models is presented. These models present the characteristics defined by the dominant poles of the system (1) and most of those premature operation transitories in a power station can be reproduced with considerable fidelity if the models are identified with data of plant or references of a code of better estimate like RAMONA, TRAC (2) or RELAP. The models of the simulator are developments or own simplifications starting from the physical laws and retaining the main terms. This work describes the objective of the project and the general specifications of the University student of Nucleo electric simulator with Boiling Water Reactor type (SUN-RAH) as well as the finished parts that fundamentally are the nuclear reactor, the one of steam supply (NSSS), the plant balance (BOP), the main controllers of the plant and the implemented graphic interfaces. The pendent goals as well as the future developments and applications of SUN-RAH are described. (Author)

An improved Armstrong-Frederick-Type Plasticity Model for Stable Cyclic Stress-Strain Responses Considering Nonproportional Hardening

Science.gov (United States)

Li, Jing; Zhang, Zhong-ping; Li, Chun-wang

2018-03-01

This paper modified an Armstrong-Frederick-type plasticity model for investigating the stable cyclic deformation behavior of metallic materials with different sensitivity to nonproportional loadings. In the modified model, the nonproportionality factor and nonproportional cyclic hardening coefficient coupled with the Jiang-Sehitoglu incremental plasticity model were used to estimate the stable stress-strain responses of the two materials (1045HR steel and 304 stainless steel) under various tension-torsion strain paths. A new equation was proposed to calculate the nonproportionality factor on the basis of the minimum normal strain range. Procedures to determine the minimum normal strain range were presented for general multiaxial loadings. Then, the modified model requires only the cyclic strain hardening exponent and cyclic strength coefficient to determine the material constants. It is convenient for predicting the stable stress-strain responses of materials in engineering application. Comparisons showed that the modified model can reflect the effect of nonproportional cyclic hardening well.

R-Stable Embedded DIRKN Method of Orders 4(3) for Solving ...

African Journals Online (AJOL)

The motivation for this work comes from the fact that not much work seems to have been done on the embedded implicit RKN methods compared to the explicit case. In the present consideration, we derive coefficients of the method with minimized truncation error coefficients and show that it is R-stable.

A model to secure a stable iodine concentration in milk

Directory of Open Access Journals (Sweden)

Gisken Trøan

2015-12-01

Full Text Available Background: Dairy products account for approximately 60% of the iodine intake in the Norwegian population. The iodine concentration in cow's milk varies considerably, depending on feeding practices, season, and amount of iodine and rapeseed products in cow fodder. The variation in iodine in milk affects the risk of iodine deficiency or excess in the population. Objective: The first goal of this study was to develop a model to predict the iodine concentration in milk based on the concentration of iodine and rapeseed or glucosinolate in feed, as a tool to securing stable iodine concentration in milk. A second aim was to estimate the impact of different iodine levels in milk on iodine nutrition in the Norwegian population. Design: Two models were developed on the basis of results from eight published and two unpublished studies from the past 20 years. The models were based on different iodine concentrations in the fodder combined with either glucosinolate (Model 1 or rapeseed cake/meal (Model 2. To illustrate the impact of different iodine concentrations in milk on iodine intake, we simulated the iodine contribution from dairy products in different population groups based on food intake data in the most recent dietary surveys in Norway. Results: The models developed could predict iodine concentration in milk. Cross-validation showed good fit and confirmed the explanatory power of the models. Our calculations showed that dairy products with current iodine level in milk (200 µg/kg cover 68, 49, 108 and 56% of the daily iodine requirements for men, women, 2-year-old children, and pregnant women, respectively. Conclusions: Securing a stable level of iodine in milk by adjusting iodine concentration in different cow feeds is thus important for preventing excess intake in small children and iodine deficiency in pregnant and non-pregnant women.

Alaska Northern Fur Seal Foraging Habitat Model Stable Isotope Data, 2006-2008

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These data sets were used by Zeppelin et al. (2015) to model northern fur seal foraging habitats based on stable isotope values measured in plasma and red blood...

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

Science.gov (United States)

Xu, Kuan-Man

2015-01-01

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC

A comparison of zero-order, first-order, and Monod biotransformation models

International Nuclear Information System (INIS)

Bekins, B.A.; Warren, E.; Godsy, E.M.

1998-01-01

Under some conditions, a first-order kinetic model is a poor representation of biodegradation in contaminated aquifers. Although it is well known that the assumption of first-order kinetics is valid only when substrate concentration, S, is much less than the half-saturation constant, K S , this assumption is often made without verification of this condition. The authors present a formal error analysis showing that the relative error in the first-order approximation is S/K S and in the zero-order approximation the error is K S /S. They then examine the problems that arise when the first-order approximation is used outside the range for which it is valid. A series of numerical simulations comparing results of first- and zero-order rate approximations to Monod kinetics for a real data set illustrates that if concentrations observed in the field are higher than K S , it may be better to model degradation using a zero-order rate expression. Compared with Monod kinetics, extrapolation of a first-order rate to lower concentrations under-predicts the biotransformation potential, while extrapolation to higher concentrations may grossly over-predict the transformation rate. A summary of solubilities and Monod parameters for aerobic benzene, toluene, and xylene (BTX) degradation shows that the a priori assumption of first-order degradation kinetics at sites contaminated with these compounds is not valid. In particular, out of six published values of K S for toluene, only one is greater than 2 mg/L, indicating that when toluene is present in concentrations greater than about a part per million, the assumption of first-order kinetics may be invalid. Finally, the authors apply an existing analytical solution for steady-state one-dimensional advective transport with Monod degradation kinetics to a field data set

Entropy Stable Staggered Grid Discontinuous Spectral Collocation Methods of any Order for the Compressible Navier--Stokes Equations

KAUST Repository

Parsani, Matteo

2016-10-04

Staggered grid, entropy stable discontinuous spectral collocation operators of any order are developed for the compressible Euler and Navier--Stokes equations on unstructured hexahedral elements. This generalization of previous entropy stable spectral collocation work [M. H. Carpenter, T. C. Fisher, E. J. Nielsen, and S. H. Frankel, SIAM J. Sci. Comput., 36 (2014), pp. B835--B867, M. Parsani, M. H. Carpenter, and E. J. Nielsen, J. Comput. Phys., 292 (2015), pp. 88--113], extends the applicable set of points from tensor product, Legendre--Gauss--Lobatto (LGL), to a combination of tensor product Legendre--Gauss (LG) and LGL points. The new semidiscrete operators discretely conserve mass, momentum, energy, and satisfy a mathematical entropy inequality for the compressible Navier--Stokes equations in three spatial dimensions. They are valid for smooth as well as discontinuous flows. The staggered LG and conventional LGL point formulations are compared on several challenging test problems. The staggered LG operators are significantly more accurate, although more costly from a theoretical point of view. The LG and LGL operators exhibit similar robustness, as is demonstrated using test problems known to be problematic for operators that lack a nonlinear stability proof for the compressible Navier--Stokes equations (e.g., discontinuous Galerkin, spectral difference, or flux reconstruction operators).

Spatial-Frequency Azimuthally Stable Cartography of Biological Polycrystalline Networks

Directory of Open Access Journals (Sweden)

V. A. Ushenko

2013-01-01

Full Text Available A new azimuthally stable polarimetric technique processing microscopic images of optically anisotropic structures of biological tissues histological sections is proposed. It has been used as a generalized model of phase anisotropy definition of biological tissues by using superposition of Mueller matrices of linear birefringence and optical activity. The matrix element M44 has been chosen as the main information parameter, whose value is independent of the rotation angle of both sample and probing beam polarization plane. For the first time, the technique of concerted spatial-frequency filtration has been used in order to separate the manifestation of linear birefringence and optical activity. Thereupon, the method of azimuthally stable spatial-frequency cartography of biological tissues histological sections has been elaborated. As the analyzing tool, complex statistic, correlation, and fractal analysis of coordinate distributions of M44 element has been performed. The possibility of using the biopsy of the uterine wall tissue in order to differentiate benign (fibromyoma and malignant (adenocarcinoma conditions has been estimated.

Mixed-order phase transition in a one-dimensional model.

Science.gov (United States)

Bar, Amir; Mukamel, David

2014-01-10

We introduce and analyze an exactly soluble one-dimensional Ising model with long range interactions that exhibits a mixed-order transition, namely a phase transition in which the order parameter is discontinuous as in first order transitions while the correlation length diverges as in second order transitions. Such transitions are known to appear in a diverse classes of models that are seemingly unrelated. The model we present serves as a link between two classes of models that exhibit a mixed-order transition in one dimension, namely, spin models with a coupling constant that decays as the inverse distance squared and models of depinning transitions, thus making a step towards a unifying framework.

Tempered stable laws as random walk limits

OpenAIRE

Chakrabarty, Arijit; Meerschaert, Mark M.

2010-01-01

Stable laws can be tempered by modifying the L\\'evy measure to cool the probability of large jumps. Tempered stable laws retain their signature power law behavior at infinity, and infinite divisibility. This paper develops random walk models that converge to a tempered stable law under a triangular array scheme. Since tempered stable laws and processes are useful in statistical physics, these random walk models can provide a basic physical model for the underlying physical phenomena.

A servo-controlled canine model of stable severe ischemic left ventricular failure.

Science.gov (United States)

Wagner, Richard L; Hood, William B; Howland, Peter A

2009-12-01

Reversible left ventricular failure was produced in conscious dogs by compromise of the coronary circulation. In animals with prior left anterior descending coronary artery occlusion, mean left atrial pressure (LAP) was incorporated into an automatic feedback control system used to inflate a balloon cuff on the circumflex (Cfx) coronary artery. The system could produce stable increases in LAP to 15-20 mm Hg. The dominating system transfer function was the ratio of LAP to balloon volume (BV), which was characterized by a fixed delay (5 s), with LAP/BV = (8e(-jomegatau ))/(0.02 + jomega). The system was stabilized by a phase lead network to reduce oscillations of LAP. A total of seven experiments were conducted in three dogs, and testing of inotropic agents was possible in three experiments under stable conditions with the pump off after an hour or more of operation. Problems encountered were 0.003-0.008 Hz oscillations in LAP in three experiments, which could usually be controlled by reducing the system gain. Late stage ventricular fibrillation occurred in all three animals, but defibrillation was easily accomplished after deflating the Cfx balloon. This system produces reversible left ventricular failure solely due to ischemia, thus closely simulating clinical heart failure due to coronary insufficiency.

Stable Lévy motion with inverse Gaussian subordinator

Science.gov (United States)

Kumar, A.; Wyłomańska, A.; Gajda, J.

2017-09-01

In this paper we study the stable Lévy motion subordinated by the so-called inverse Gaussian process. This process extends the well known normal inverse Gaussian (NIG) process introduced by Barndorff-Nielsen, which arises by subordinating ordinary Brownian motion (with drift) with inverse Gaussian process. The NIG process found many interesting applications, especially in financial data description. We discuss here the main features of the introduced subordinated process, such as distributional properties, existence of fractional order moments and asymptotic tail behavior. We show the connection of the process with continuous time random walk. Further, the governing fractional partial differential equations for the probability density function is also obtained. Moreover, we discuss the asymptotic distribution of sample mean square displacement, the main tool in detection of anomalous diffusion phenomena (Metzler et al., 2014). In order to apply the stable Lévy motion time-changed by inverse Gaussian subordinator we propose a step-by-step procedure of parameters estimation. At the end, we show how the examined process can be useful to model financial time series.

Reduced {sup 123}I-BMIPP uptake implies decreased myocardial flow reserve in patients with chronic stable angina

Energy Technology Data Exchange (ETDEWEB)

Kageyama, Hiroyuki; Morita, Koichi; Katoh, Chietsugu; Mabuchi, Megumi; Tamaki, Nagara [Hokkaido University Graduate School of Medicine, Department of Nuclear Medicine, Sapporo (Japan); Tsukamoto, Takahiro; Noriyasu, Kazuyuki; Naya, Masanao [Hokkaido University, Department of Cardiovascular Medicine, Sapporo (Japan); Hokkaido University Graduate School of Medicine, Department of Nuclear Medicine, Sapporo (Japan); Kawai, Yuko [Hokko Memorial Hospital, Department of Cardiovascular Medicine, Sapporo (Japan)

2006-01-01

Long-chain fatty acid (LCFA) is the main energy source for normal myocardium at rest, but in ischemic myocardium, the main energy substrate shifts from LCFA to glucose. {sup 123}I-BMIPP is a radiolabeled LCFA analog. In chronic stable angina without previous infarction, we suppose that reduced {sup 123}I-BMIPP uptake is related to the substrate shift in myocardium with decreased myocardial flow reserve (MFR). The purpose of this study was to relate {sup 123}I-BMIPP uptake to rest myocardial blood flow (MBF), hyperemic MBF, and MFR assessed with {sup 15}O-water positron emission tomography (PET). We enrolled 21 patients with chronic stable angina without previous infarction, all of whom underwent {sup 123}I-BMIPP single-photon emission computed tomography (SPECT) and {sup 15}O-water PET. The left ventricle was divided into 13 segments. In each segment, rest MBF and hyperemic MBF were measured by PET. {sup 123}I-BMIPP uptake was evaluated as follows: score 0=normal, 1=slightly decreased uptake, 2=moderately decreased uptake, 3=severely decreased uptake, and 4=complete defect. {sup 123}I-BMIPP uptake was compared with rest MBF, hyperemic MBF, and MFR. The numbers of segments with {sup 123}I-BMIPP scores 0, 1, 2, 3, and 4 were 178, 40, 25, 24, and 0, respectively. The rest MBFs for scores 0, 1, 2, and 3 were 0.93{+-}0.25, 0.86{+-}0.21, 0.97{+-}0.30, and 0.99{+-}0.37 ml/min/g, respectively. The hyperemic MBFs for scores 0, 1, 2, and 3 were 2.76{+-}1.29, 1.84{+-}0.74, 1.37{+-}0.39, and 1.08{+-}0.40 ml/min/g, respectively. The MFRs for scores 0, 1, 2, and 3 were 3.01{+-}1.38, 2.20{+-}0.95, 1.44{+-}0.22, and 1.10{+-}0.26, respectively. As {sup 123}I-BMIPP uptake declined, hyperemic MBF and MFR decreased. In chronic stable angina without previous infarction, reduced {sup 123}I-BMIPP uptake implies decreased MFR. (orig.)

The stable model semantics under the any-world assumption

OpenAIRE

Straccia, Umberto; Loyer, Yann

2004-01-01

The stable model semantics has become a dominating approach to complete the knowledge provided by a logic program by means of the Closed World Assumption (CWA). The CWA asserts that any atom whose truth-value cannot be inferred from the facts and rules is supposed to be false. This assumption is orthogonal to the so-called the Open World Assumption (OWA), which asserts that every such atom's truth is supposed to be unknown. The topic of this paper is to be more fine-grained. Indeed, the objec...

Modeling anomalous diffusion by a subordinated fractional Lévy-stable process

International Nuclear Information System (INIS)

Teuerle, Marek; Wyłomańska, Agnieszka; Sikora, Grzegorz

2013-01-01

Two phenomena that can be discovered in systems with anomalous diffusion are long-range dependence and trapping events. The first effect concerns events that are arbitrarily distant but still influence each other exceptionally strongly, which is characteristic for anomalous regimes. The second corresponds to the presence of constant values of the underlying process. Motivated by the relatively poor class of models that can cover these two phenomena, we introduce subordinated fractional Lévy-stable motion with tempered stable waiting times. We present in detail its main properties, propose a simulation scheme and give an estimation procedure for its parameters. The last part of the paper is a presentation, via the Monte Carlo approach, of the effectiveness of the estimation of the parameters. (paper)

Synthesis of models for order-sorted first-order theories using linear algebra and constraint solving

Directory of Open Access Journals (Sweden)

Salvador Lucas

2015-12-01

Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.

Scoring predictive models using a reduced representation of proteins: model and energy definition.

Science.gov (United States)

Fogolari, Federico; Pieri, Lidia; Dovier, Agostino; Bortolussi, Luca; Giugliarelli, Gilberto; Corazza, Alessandra; Esposito, Gennaro; Viglino, Paolo

2007-03-23

Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 A). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url: http://www.dstb.uniud.it/~ffogolari/download/.

A reduced fidelity model for the rotary chemical looping combustion reactor

KAUST Repository

Iloeje, Chukwunwike O.

2017-01-11

The rotary chemical looping combustion reactor has great potential for efficient integration with CO capture-enabled energy conversion systems. In earlier studies, we described a one-dimensional rotary reactor model, and used it to demonstrate the feasibility of continuous reactor operation. Though this detailed model provides a high resolution representation of the rotary reactor performance, it is too computationally expensive for studies that require multiple model evaluations. Specifically, it is not ideal for system-level studies where the reactor is a single component in an energy conversion system. In this study, we present a reduced fidelity model (RFM) of the rotary reactor that reduces computational cost and determines an optimal combination of variables that satisfy reactor design requirements. Simulation results for copper, nickel and iron-based oxygen carriers show a four-order of magnitude reduction in simulation time, and reasonable prediction accuracy. Deviations from the detailed reference model predictions range from 3% to 20%, depending on oxygen carrier type and operating conditions. This study also demonstrates how the reduced model can be modified to deal with both optimization and design oriented problems. A parametric study using the reduced model is then applied to analyze the sensitivity of the optimal reactor design to changes in selected operating and kinetic parameters. These studies show that temperature and activation energy have a greater impact on optimal geometry than parameters like pressure or feed fuel fraction for the selected oxygen carrier materials.

Wind Turbine Model and Observer in Takagi-Sugeno Model Structure

International Nuclear Information System (INIS)

Georg, Sören; Müller, Matthias; Schulte, Horst

2014-01-01

Based on a reduced-order, dynamic nonlinear wind turbine model in Takagi- Sugeno (TS) model structure, a TS state observer is designed as a disturbance observer to estimate the unknown effective wind speed. The TS observer model is an exact representation of the underlying nonlinear model, obtained by means of the sector-nonlinearity approach. The observer gain matrices are obtained by means of a linear matrix inequality (LMI) design approach for optimal fuzzy control, where weighting matrices for the individual system states and outputs are included. The observer is tested in simulations with the aero-elastic code FAST for the NREL 5 MW reference turbine, where it shows a stable behaviour in turbulent wind simulations

Numerical modelling of ultrasonic waves in a bubbly Newtonian liquid using a high-order acoustic cavitation model.

Science.gov (United States)

Lebon, G S Bruno; Tzanakis, I; Djambazov, G; Pericleous, K; Eskin, D G

2017-07-01

To address difficulties in treating large volumes of liquid metal with ultrasound, a fundamental study of acoustic cavitation in liquid aluminium, expressed in an experimentally validated numerical model, is presented in this paper. To improve the understanding of the cavitation process, a non-linear acoustic model is validated against reference water pressure measurements from acoustic waves produced by an immersed horn. A high-order method is used to discretize the wave equation in both space and time. These discretized equations are coupled to the Rayleigh-Plesset equation using two different time scales to couple the bubble and flow scales, resulting in a stable, fast, and reasonably accurate method for the prediction of acoustic pressures in cavitating liquids. This method is then applied to the context of treatment of liquid aluminium, where it predicts that the most intense cavitation activity is localised below the vibrating horn and estimates the acoustic decay below the sonotrode with reasonable qualitative agreement with experimental data. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Modeling Ability Differentiation in the Second-Order Factor Model

Science.gov (United States)

Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

2011-01-01

In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

A Novel Method for Decoding Any High-Order Hidden Markov Model

Directory of Open Access Journals (Sweden)

Fei Ye

2014-01-01

Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

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Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Hidden discriminative features extraction for supervised high-order time series modeling.

Science.gov (United States)

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2016-11-01

In this paper, an orthogonal Tucker-decomposition-based extraction of high-order discriminative subspaces from a tensor-based time series data structure is presented, named as Tensor Discriminative Feature Extraction (TDFE). TDFE relies on the employment of category information for the maximization of the between-class scatter and the minimization of the within-class scatter to extract optimal hidden discriminative feature subspaces that are simultaneously spanned by every modality for supervised tensor modeling. In this context, the proposed tensor-decomposition method provides the following benefits: i) reduces dimensionality while robustly mining the underlying discriminative features, ii) results in effective interpretable features that lead to an improved classification and visualization, and iii) reduces the processing time during the training stage and the filtering of the projection by solving the generalized eigenvalue issue at each alternation step. Two real third-order tensor-structures of time series datasets (an epilepsy electroencephalogram (EEG) that is modeled as channel×frequency bin×time frame and a microarray data that is modeled as gene×sample×time) were used for the evaluation of the TDFE. The experiment results corroborate the advantages of the proposed method with averages of 98.26% and 89.63% for the classification accuracies of the epilepsy dataset and the microarray dataset, respectively. These performance averages represent an improvement on those of the matrix-based algorithms and recent tensor-based, discriminant-decomposition approaches; this is especially the case considering the small number of samples that are used in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

Science.gov (United States)

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

On the Nonlinear Structural Analysis of Wind Turbine Blades using Reduced Degree-of-Freedom Models

DEFF Research Database (Denmark)

Holm-Jørgensen, Kristian; Larsen, Jesper Winther; Nielsen, Søren R.K.

2008-01-01

, modelling geometrical and inertial nonlinear couplings in the fundamental flap and edge direction. The purpose of this article is to examine the applicability of such a reduced-degree-of-freedom model in predicting the nonlinear response and stability of a blade by comparison to a full model based...... on a nonlinear co-rotating FE formulation. By use of the reduced-degree-of-freedom model it is shown that under strong resonance excitation of the fundamental flap or edge modes, significant energy is transferred to higher modes due to parametric or nonlinear coupling terms, which influence the response...... of the small number of included modes. The qualitative erratic response and stability prediction of the reduced order models take place at frequencies slightly above normal operation. However, for normal operation of the wind turbine without resonance excitation 4 modes in the reduced-degree-of-freedom model...

Stable configurations in social networks

Science.gov (United States)

Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

2018-06-01

We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

Investigation of Effectiveness of Order Review and Release Models in Make to Order Supply Chain

Directory of Open Access Journals (Sweden)

Kundu Kaustav

2016-01-01

Full Text Available Nowadays customisation becomes more common due to vast requirement from the customers for which industries are trying to use make-to-order (MTO strategy. Due to high variation in the process, workload control models are extensively used for jobshop companies which usually adapt MTO strategy. Some authors tried to implement workload control models, order review and release systems, in non-repetitive manufacturing companies, where there is a dominant flow in production. Those models are better in shop floor but their performances are never been investigated in high variation situations like MTO supply chain. This paper starts with the introduction of particular issues in MTO companies and a general overview of order review and release systems widely used in the industries. Two order review and release systems, the Limited and Balanced models, particularly suitable for flow shop system are applied to MTO supply chain, where the processing times are difficult to estimate due to high variation. Simulation results show that the Balanced model performs much better than the Limited model if the processing times can be estimated preciously.

Spiking and bursting patterns of fractional-order Izhikevich model

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Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

Reduced-Order Model for the Geochemical Impacts of Carbon Dioxide, Brine and Trace Metal Leakage into an Unconfined, Oxidizing Carbonate Aquifer, Version 2.1

Energy Technology Data Exchange (ETDEWEB)

Bacon, Diana H.

2013-03-31

The National Risk Assessment Partnership (NRAP) consists of 5 U.S DOE national laboratories collaborating to develop a framework for predicting the risks associated with carbon sequestration. The approach taken by NRAP is to divide the system into components, including injection target reservoirs, wellbores, natural pathways including faults and fractures, groundwater and the atmosphere. Next, develop a detailed, physics and chemistry-based model of each component. Using the results of the detailed models, develop efficient, simplified models, termed reduced order models (ROM) for each component. Finally, integrate the component ROMs into a system model that calculates risk profiles for the site. This report details the development of the Groundwater Geochemistry ROM for the Edwards Aquifer at PNNL. The Groundwater Geochemistry ROM for the Edwards Aquifer uses a Wellbore Leakage ROM developed at LANL as input. The detailed model, using the STOMP simulator, covers a 5x8 km area of the Edwards Aquifer near San Antonio, Texas. The model includes heterogeneous hydraulic properties, and equilibrium, kinetic and sorption reactions between groundwater, leaked CO2 gas, brine, and the aquifer carbonate and clay minerals. Latin Hypercube sampling was used to generate 1024 samples of input parameters. For each of these input samples, the STOMP simulator was used to predict the flux of CO2 to the atmosphere, and the volume, length and width of the aquifer where pH was less than the MCL standard, and TDS, arsenic, cadmium and lead exceeded MCL standards. In order to decouple the Wellbore Leakage ROM from the Groundwater Geochemistry ROM, the response surface was transformed to replace Wellbore Leakage ROM input parameters with instantaneous and cumulative CO2 and brine leakage rates. The most sensitive parameters proved to be the CO2 and brine leakage rates from the well, with equilibrium coefficients for calcite and dolomite, as well as the number of illite and kaolinite

On the properties of energy stable flux reconstruction schemes for implicit large eddy simulation

Science.gov (United States)

Vermeire, B. C.; Vincent, P. E.

2016-12-01

We begin by investigating the stability, order of accuracy, and dispersion and dissipation characteristics of the extended range of energy stable flux reconstruction (E-ESFR) schemes in the context of implicit large eddy simulation (ILES). We proceed to demonstrate that subsets of the E-ESFR schemes are more stable than collocation nodal discontinuous Galerkin methods recovered with the flux reconstruction approach (FRDG) for marginally-resolved ILES simulations of the Taylor-Green vortex. These schemes are shown to have reduced dissipation and dispersion errors relative to FRDG schemes of the same polynomial degree and, simultaneously, have increased Courant-Friedrichs-Lewy (CFL) limits. Finally, we simulate turbulent flow over an SD7003 aerofoil using two of the most stable E-ESFR schemes identified by the aforementioned Taylor-Green vortex experiments. Results demonstrate that subsets of E-ESFR schemes appear more stable than the commonly used FRDG method, have increased CFL limits, and are suitable for ILES of complex turbulent flows on unstructured grids.

A reduced-order modeling approach to represent subgrid-scale hydrological dynamics for land-surface simulations: application in a polygonal tundra landscape

Science.gov (United States)

Pau, G. S. H.; Bisht, G.; Riley, W. J.

2014-09-01

Existing land surface models (LSMs) describe physical and biological processes that occur over a wide range of spatial and temporal scales. For example, biogeochemical and hydrological processes responsible for carbon (CO2, CH4) exchanges with the atmosphere range from the molecular scale (pore-scale O2 consumption) to tens of kilometers (vegetation distribution, river networks). Additionally, many processes within LSMs are nonlinearly coupled (e.g., methane production and soil moisture dynamics), and therefore simple linear upscaling techniques can result in large prediction error. In this paper we applied a reduced-order modeling (ROM) technique known as "proper orthogonal decomposition mapping method" that reconstructs temporally resolved fine-resolution solutions based on coarse-resolution solutions. We developed four different methods and applied them to four study sites in a polygonal tundra landscape near Barrow, Alaska. Coupled surface-subsurface isothermal simulations were performed for summer months (June-September) at fine (0.25 m) and coarse (8 m) horizontal resolutions. We used simulation results from three summer seasons (1998-2000) to build ROMs of the 4-D soil moisture field for the study sites individually (single-site) and aggregated (multi-site). The results indicate that the ROM produced a significant computational speedup (> 103) with very small relative approximation error (training the ROM. We also demonstrate that our approach: (1) efficiently corrects for coarse-resolution model bias and (2) can be used for polygonal tundra sites not included in the training data set with relatively good accuracy (< 1.7% relative error), thereby allowing for the possibility of applying these ROMs across a much larger landscape. By coupling the ROMs constructed at different scales together hierarchically, this method has the potential to efficiently increase the resolution of land models for coupled climate simulations to spatial scales consistent with

Ca2Cr0.5Ga1.5O5—An extremely redox-stable brownmillerite phase

International Nuclear Information System (INIS)

Luo, Kun; Amano Patino, Midori; Hayward, Michael A.

2015-01-01

Investigation of the Ca 2 Cr x Ga 2−x O 5 compositional series reveals a maximum chromium solubility of 25%. The most chromium rich composition, Ca 2 Cr 0.5 Ga 1.5 O 5 , adopts a brownmillerite-type anion deficient perovskite structure described in space group Pnma (a=5.368 Å, b=14.547 Å, c=5.593 Å). Neutron powder diffraction data reveals rigorous B-site cation order, with all of the tetrahedral coordination sites occupied exclusively by gallium and the octahedral coordination sites occupied by gallium or chromium. Annealing studies reveals Ca 2 Cr 0.5 Ga 1.5 O 5 is stable in both oxidizing (100% O 2 ) and reducing (5% H 2 in N 2 ) conditions up to 800 °C, suggesting it could find application as a stable host lattice for fuel cell electrodes or electrolytes with suitable doping to enhance catalytic behaviour and/or anionic conductivity. - Graphical abstract: Ca 2 Cr 0.5 Ga 1.5 O 5 , adopts a brownmillerite-type anion deficient perovskite structure yet it is stable in both oxidizing (100% O 2 ) and reducing (5% H 2 in N 2 ) conditions up to 800 °C. - Highlights: • Anion deficient oxide stable to both oxidation and reduction up to 800 °C. • Cation-ordered brownmillerite structure determined by powder neutron diffraction. • Low solubility of Cr 3+ in framework due to spherical d 3 electron configuration

CISOCUR - Hydrodynamic circulation in the Curonian Lagoon inferred through stable isotope measurements and numerical modelling

Science.gov (United States)

Umgiesser, Georg; Razinkovas-Baziukas, Arturas; Barisevičiūtė, Ruta; Baziukė, Dalia; Ertürk, Ali; Gasiūnaitė, Jovita; Gulbinskas, Saulius; Lubienė, Irma; Maračkinaite, Jurgita; Petkuvienė, Jolita; Pilkaitytė, Renata; Ruginis, Tomas; Zemlys, Petras; Žilius, Mindaugas

2013-04-01

The spatial pattern of the hydrodynamic circulation of the Curonian lagoon, the largest European coastal lagoon, is still little understood. In absence of automatic current registration data all the existing models relied mostly on such data as water levels leaving high level of uncertainty. Here we present CISOCUR, a new project financed by the European Social Fund under the Global Grant measure. The project applies a new methodology that uses the carbon stable isotope (SI) ratio of C12 and C13 that characterize different water sources entering the lagoon and may be altered by internal kinetic processes. Through the tracing of these isotope ratios different water masses can be identified. This gives the possibility to validate several hypotheses of water circulation and validate hydrodynamic models. In particular it will be possible to 1) trace water masses entering the lagoon through the Nemunas and the Klaipeda strait; 2) test the hypothesis of sediment transport mechanisms inside the lagoon; 3) evaluate the importance of physical forcing on the lagoon circulation. The use of a hydrodynamic finite element model, coupled with the SI method, will allow for a realistic description of the transport processes inside the Curonian lagoon. So the main research goal is to apply the stable isotope tracers and a finite element model to determine the circulation patterns in the Curonian lagoon. Overall, the project will develop according to 4 main phases: 1) A pilot study to measure the isotope composition of different carbon compounds (dissolved and suspended) in different water bodies that feed water into the central lagoon. Through this pilot study the optimal study sites for the seasonal campaign will be identified as well. 2) Seasonal field campaigns in the monitoring stations identified in phase 1 to measure the carbon isotope ratio. 3) Development of a model that describes the kinetics of carbon isotopes and its transformation. 4) Application of a hydrodynamic model

Notification: Implementation of Executive Order 13771, “Reducing Regulation and Controlling Regulatory Costs”

Science.gov (United States)

Project #OA&E-FY18-0177, April 10, 2018. The OIG plans to begin preliminary research on the Office of the Administrator's Office of Policy implementation of Executive Order 13771, Reducing Regulation and Controlling Regulatory Costs.

Adaptive parametric model order reduction technique for optimization of vibro-acoustic models: Application to hearing aid design

DEFF Research Database (Denmark)

Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Naets, Frank

2018-01-01

Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system...... by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we...

Stable isotope composition of atmospheric carbon monoxide. A modelling study

International Nuclear Information System (INIS)

Gromov, Sergey S.

2014-01-01

This study aims at an improved understanding of the stable carbon and oxygen isotope composition of the carbon monoxide (CO) in the global atmosphere by means of numerical simulations. At first, a new kinetic chemistry tagging technique for the most complete parameterisation of isotope effects has been introduced into the Modular Earth Submodel System (MESSy) framework. Incorporated into the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model, an explicit treatment of the isotope effects on the global scale is now possible. The expanded model system has been applied to simulate the chemical system containing up to five isotopologues of all carbon- and oxygen-bearing species, which ultimately determine the δ 13 C, δ 18 O and Δ 17 O isotopic signatures of atmospheric CO. As model input, a new stable isotope-inclusive emission inventory for the relevant trace gases has been compiled. The uncertainties of the emission estimates and of the resulting simulated mixing and isotope ratios have been analysed. The simulated CO mixing and stable isotope ratios have been compared to in-situ measurements from ground-based observatories and from the civil-aircraft-mounted CARIBIC-1 measurement platform. The systematically underestimated 13 CO/ 12 CO ratios of earlier, simplified modelling studies can now be partly explained. The EMAC simulations do not support the inferences of those studies, which suggest for CO a reduced input of the highly depleted in 13 C methane oxidation source. In particular, a high average yield of 0.94 CO per reacted methane (CH 4 ) molecule is simulated in the troposphere, to a large extent due to the competition between the deposition and convective transport processes affecting the CH 4 to CO reaction chain intermediates. None of the other factors, assumed or disregarded in previous studies, however hypothesised to have the potential in enriching tropospheric CO in 13 C, were found significant when explicitly simulated. The

Low-Order Modeling of Dynamic Stall on Airfoils in Incompressible Flow

Science.gov (United States)

Narsipur, Shreyas

Unsteady aerodynamics has been a topic of research since the late 1930's and has increased in popularity among researchers studying dynamic stall in helicopters, insect/bird flight, micro air vehicles, wind-turbine aerodynamics, and ow-energy harvesting devices. Several experimental and computational studies have helped researchers gain a good understanding of the unsteady ow phenomena, but have proved to be expensive and time-intensive for rapid design and analysis purposes. Since the early 1970's, the push to develop low-order models to solve unsteady ow problems has resulted in several semi-empirical models capable of effectively analyzing unsteady aerodynamics in a fraction of the time required by high-order methods. However, due to the various complexities associated with time-dependent flows, several empirical constants and curve fits derived from existing experimental and computational results are required by the semi-empirical models to be an effective analysis tool. The aim of the current work is to develop a low-order model capable of simulating incompressible dynamic-stall type ow problems with a focus on accurately modeling the unsteady ow physics with the aim of reducing empirical dependencies. The lumped-vortex-element (LVE) algorithm is used as the baseline unsteady inviscid model to which augmentations are applied to model unsteady viscous effects. The current research is divided into two phases. The first phase focused on augmentations aimed at modeling pure unsteady trailing-edge boundary-layer separation and stall without leading-edge vortex (LEV) formation. The second phase is targeted at including LEV shedding capabilities to the LVE algorithm and combining with the trailing-edge separation model from phase one to realize a holistic, optimized, and robust low-order dynamic stall model. In phase one, initial augmentations to theory were focused on modeling the effects of steady trailing-edge separation by implementing a non-linear decambering

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. Parameter and state estimation

Science.gov (United States)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-09-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online parameter identification technique based on a weighted recursive least quadratic squares parameter estimator to determine the parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.

Reduced-Order Model for Leakage Through an Open Wellbore from the Reservoir due to Carbon Dioxide Injection

Energy Technology Data Exchange (ETDEWEB)

Pan, Lehua [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oldenburg, Curtis M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2017-07-26

Potential CO₂ leakage through existing open wellbores is one of the most significant hazards that need to be addressed in geologic carbon sequestration (GCS) projects. In the framework of the National Risk Assessment Partnership (NRAP) which requires fast computations for uncertainty analysis, rigorous simulation of the coupled wellbore-reservoir system is not practical. We have developed a 7,200-point look-up table reduced-order model (ROM) for estimating the potential leakage rate up open wellbores in response to CO₂ injection nearby. The ROM is based on coupled simulations using T2Well/ECO2H which was run repeatedly for representative conditions relevant to NRAP to create a look-up table response-surface ROM. The ROM applies to a wellbore that fully penetrates a 20-m thick reservoir that is used for CO₂ storage. The radially symmetric reservoir is assumed to have initially uniform pressure, temperature, gas saturation, and brine salinity, and it is assumed these conditions are held constant at the far-field boundary (100 m away from the wellbore). In such a system, the leakage can quickly reach quasi-steady state. The ROM table can be used to estimate both the free-phase CO₂ and brine leakage rates through an open well as a function of wellbore and reservoir conditions. Results show that injection-induced pressure and reservoir gas saturation play important roles in controlling leakage. Caution must be used in the application of this ROM because well leakage is formally transient and the ROM lookup table was populated using quasi-steady simulation output after 1000 time steps which may correspond to different physical times for the various parameter combinations of the coupled wellbore-reservoir system.

Dynamical models of happiness with fractional order

Science.gov (United States)

Song, Lei; Xu, Shiyun; Yang, Jianying

2010-03-01

This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.

Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem.

Science.gov (United States)

Hopkins, John B; Ferguson, Jake M; Tyers, Daniel B; Kurle, Carolyn M

2017-01-01

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change.

Fractional Order Models of Industrial Pneumatic Controllers

Directory of Open Access Journals (Sweden)

Abolhassan Razminia

2014-01-01

Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.

Gravity Waves and Wind-Farm Efficiency in Neutral and Stable Conditions

Science.gov (United States)

Allaerts, Dries; Meyers, Johan

2018-02-01

We use large-eddy simulations (LES) to investigate the impact of stable stratification on gravity-wave excitation and energy extraction in a large wind farm. To this end, the development of an equilibrium conventionally neutral boundary layer into a stable boundary layer over a period of 8 h is considered, using two different cooling rates. We find that turbulence decay has considerable influence on the energy extraction at the beginning of the boundary-layer transition, but afterwards, energy extraction is dominated by geometrical and jet effects induced by an inertial oscillation. It is further shown that the inertial oscillation enhances gravity-wave excitation. By comparing LES results with a simple one-dimensional model, we show that this is related to an interplay between wind-farm drag, variations in the Froude number and the dispersive effects of vertically-propagating gravity waves. We further find that the pressure gradients induced by gravity waves lead to significant upstream flow deceleration, reducing the average turbine output compared to a turbine in isolated operation. This leads us to the definition of a non-local wind-farm efficiency, next to a more standard wind-farm wake efficiency, and we show that both can be of the same order of magnitude. Finally, an energy flux analysis is performed to further elucidate the effect of gravity waves on the flow in the wind farm.

There is no non-zero stable fixed point for dense networks in the homogeneous Kuramoto model

International Nuclear Information System (INIS)

Taylor, Richard

2012-01-01

This paper is concerned with the existence of multiple stable fixed point solutions of the homogeneous Kuramoto model. We develop a necessary condition for the existence of stable fixed points for the general network Kuramoto model. This condition is applied to show that for sufficiently dense n-node networks, with node degrees at least 0.9395(n−1), the homogeneous (equal frequencies) model has only one stable fixed point solution over the full space of phase angles in the range −π to π. This is the zero fixed point solution defined by all phase angle differences being zero. This result, together with existing research, proves a conjecture of Verwoerd and Mason (2007 Proc. of the American Control Conf. pp 4613–8) that for the complete network and the homogeneous model, the zero fixed point has a basin of attraction consisting of the entire space minus a set of measure zero. The necessary conditions are also tested to see how close to sufficiency they might be by applying them to a class of regular degree networks studied by Wiley et al (2006 Chaos 16 015103). (paper)

Freedom: a transient fission-product release model for radioactive and stable species

International Nuclear Information System (INIS)

Macdonald, L.D.; Lewis, B.J.; Iglesias, F.C.

1989-05-01

A microstructure-dependent fission-gas release and swelling model (FREEDOM) has been developed for UO 2 fuel. The model describes the transient release behaviour for both the radioactive and stable fission-product species. The model can be applied over the full range of operating conditions, as well as for accident conditions that result in high fuel temperatures. The model accounts for lattice diffusion and grain-boundary sweeping of fusion products to the grain boundaries, where the fission gases accumulate in grain-face bubbles as a result of vacancy diffusion. Release of fission-gas to the free void of the fuel element occurs through the interlinkage of bubbles and cracks on the grain boundaries. This treatment also accounts for radioactive chain decay and neutron-induced transmutation effects. These phenomena are described by mass balance equations which are numerically solved using a moving-boundary, finite-element method with mesh refinement. The effects of grain-face bubbles on fuel swelling and fuel thermal conductivity are included in the ELESIM fuel performance code. FREEDOM has an accuracy of better than 1% when assessed against an analytic solution for diffusional release. The code is being evaluated against a fuel performance database for stable gas release, and against sweep-gas and in-cell fission-product release experiments at Chalk River for active species

Study on dynamic characteristics of reduced analytical model for PWR reactor internal structures

International Nuclear Information System (INIS)

Yoo, Bong; Lee, Jae Han; Kim, Jong Bum; Koo, Kyeong Hoe

1993-01-01

The objective of this study is to establish the procedure of the reduced analytical modeling technique for the PWR reactor internal(RI) structures and to carry out the sensitivity study of the dynamic characteristics of the structures by varying the structural parameters such as the stiffness, the mass and the damping. Modeling techniques for the PWR reactor internal structures and computer programs used for the dynamic analysis of the reactor internal structures are briefly investigated. Among the many components of RI structures, the dynamic characteristics for CSB was performed. The sensitivity analysis of the dynamic characteristics for the reduced analytical model considering the variations of the stiffnesses for the lower and upper flanges of the CSB and for the RV Snubber were performed to improve the dynamic characteristics of the RI structures against the external loadings given. In order to enhance the structural design margin of the RI components, the nonlinear time history analyses were attempted for the RI reduced models to compare the structural responses between the reference model and the modified one. (Author)

Reduced order generalized integrators with phase compensation for three-phase active power filter

DEFF Research Database (Denmark)

Xie, Chuan; Li, Kai; Zhao, Xin

2017-01-01

-order generalized integrators (SOGIs) are utilized to achieve those objectives. However, it will increase the computational burden due to calculation of the multiple paralleled SOGIs. To overcome this issue, phase compensated reduced order generalized integrator (ROGI) is proposed in this paper. Compared...... paralleled ROGIs in positive and negative resonant frequencies. Moreover, the controller parameters are designed and optimized by means of Nyquist diagrams and sensitivity functions in z-domain for directly digital implementation. Finally, the laboratory tests of APF are performed to validate the feasibility...

Gamow-Jordan vectors and non-reducible density operators from higher-order S-matrix poles

International Nuclear Information System (INIS)

Bohm, A.; Loewe, M.; Maxson, S.; Patuleanu, P.; Puentmann, C.; Gadella, M.

1997-01-01

In analogy to Gamow vectors that are obtained from first-order resonance poles of the S-matrix, one can also define higher-order Gamow vectors which are derived from higher-order poles of the S-matrix. An S-matrix pole of r-th order at z R =E R -iΓ/2 leads to r generalized eigenvectors of order k=0,1,hor-ellipsis,r-1, which are also Jordan vectors of degree (k+1) with generalized eigenvalue (E R -iΓ/2). The Gamow-Jordan vectors are elements of a generalized complex eigenvector expansion, whose form suggests the definition of a state operator (density matrix) for the microphysical decaying state of this higher-order pole. This microphysical state is a mixture of non-reducible components. In spite of the fact that the k-th order Gamow-Jordan vectors has the polynomial time-dependence which one always associates with higher-order poles, the microphysical state obeys a purely exponential decay law. copyright 1997 American Institute of Physics

Large-eddy simulation of stable atmospheric boundary layers to develop better turbulence closures for climate and weather models

Science.gov (United States)

Bou-Zeid, Elie; Huang, Jing; Golaz, Jean-Christophe

2011-11-01

A disconnect remains between our improved physical understanding of boundary layers stabilized by buoyancy and how we parameterize them in coarse atmospheric models. Most operational climate models require excessive turbulence mixing in such conditions to prevent decoupling of the atmospheric component from the land component, but the performance of such a model is unlikely to be satisfactory under weakly and moderately stable conditions. Using Large-eddy simulation, we revisit some of the basic challenges in parameterizing stable atmospheric boundary layers: eddy-viscosity closure is found to be more reliable due to an improved alignment of vertical Reynolds stresses and mean strains under stable conditions, but the dependence of the magnitude of the eddy viscosity on stability is not well represented by several models tested here. Thus, we propose a new closure that reproduces the different stability regimes better. Subsequently, tests of this model in the GFDL's single-column model (SCM) are found to yield good agreement with LES results in idealized steady-stability cases, as well as in cases with gradual and sharp changes of stability with time.

Time-Discrete Higher-Order ALE Formulations: Stability

KAUST Repository

Bonito, Andrea

2013-01-01

Arbitrary Lagrangian Eulerian (ALE) formulations deal with PDEs on deformable domains upon extending the domain velocity from the boundary into the bulk with the purpose of keeping mesh regularity. This arbitrary extension has no effect on the stability of the PDE but may influence that of a discrete scheme. We examine this critical issue for higher-order time stepping without space discretization. We propose time-discrete discontinuous Galerkin (dG) numerical schemes of any order for a time-dependent advection-diffusion-model problem in moving domains, and study their stability properties. The analysis hinges on the validity of the Reynold\\'s identity for dG. Exploiting the variational structure and assuming exact integration, we prove that our conservative and nonconservative dG schemes are equivalent and unconditionally stable. The same results remain true for piecewise polynomial ALE maps of any degree and suitable quadrature that guarantees the validity of the Reynold\\'s identity. This approach generalizes the so-called geometric conservation law to higher-order methods. We also prove that simpler Runge-Kutta-Radau methods of any order are conditionally stable, that is, subject to a mild ALE constraint on the time steps. Numerical experiments corroborate and complement our theoretical results. © 2013 Society for Industrial and Applied Mathematics.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

Science.gov (United States)

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Model's sparse representation based on reduced mixed GMsFE basis methods

Energy Technology Data Exchange (ETDEWEB)

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn [Institute of Mathematics, Hunan University, Changsha 410082 (China); Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn [College of Mathematics and Econometrics, Hunan University, Changsha 410082 (China)

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in

Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem.

Directory of Open Access Journals (Sweden)

John B Hopkins

Full Text Available Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos in the Greater Yellowstone Ecosystem (GYE. In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10% and other plant foods (56±10% were more important than meat (9±8% to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout, as such information could be useful in predicting how the population will adapt to future environmental change.

0.1 Trend analysis of δ18O composition of precipitation in Germany: Combining Mann-Kendall trend test and ARIMA models to correct for higher order serial correlation

Science.gov (United States)

Klaus, Julian; Pan Chun, Kwok; Stumpp, Christine

2015-04-01

Spatio-temporal dynamics of stable oxygen (18O) and hydrogen (2H) isotopes in precipitation can be used as proxies for changing hydro-meteorological and regional and global climate patterns. While spatial patterns and distributions gained much attention in recent years the temporal trends in stable isotope time series are rarely investigated and our understanding of them is still limited. These might be a result of a lack of proper trend detection tools and effort for exploring trend processes. Here we make use of an extensive data set of stable isotope in German precipitation. In this study we investigate temporal trends of δ18O in precipitation at 17 observation station in Germany between 1978 and 2009. For that we test different approaches for proper trend detection, accounting for first and higher order serial correlation. We test if significant trends in the isotope time series based on different models can be observed. We apply the Mann-Kendall trend tests on the isotope series, using general multiplicative seasonal autoregressive integrate moving average (ARIMA) models which account for first and higher order serial correlations. With the approach we can also account for the effects of temperature, precipitation amount on the trend. Further we investigate the role of geographic parameters on isotope trends. To benchmark our proposed approach, the ARIMA results are compared to a trend-free prewhiting (TFPW) procedure, the state of the art method for removing the first order autocorrelation in environmental trend studies. Moreover, we explore whether higher order serial correlations in isotope series affects our trend results. The results show that three out of the 17 stations have significant changes when higher order autocorrelation are adjusted, and four stations show a significant trend when temperature and precipitation effects are considered. Significant trends in the isotope time series are generally observed at low elevation stations (≤315 m a

Group-ICA model order highlights patterns of functional brain connectivity

Directory of Open Access Journals (Sweden)

Ahmed eAbou Elseoud

2011-06-01

Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.

Charge ordering in two-dimensional ionic liquids

Science.gov (United States)

Perera, Aurélien; Urbic, Tomaz

2018-04-01

The structural properties of model two-dimensional (2D) ionic liquids are examined, with a particular focus on the charge ordering process, with the use of computer simulation and integral equation theories. The influence of the logarithmic form of the Coulomb interaction, versus that of a 3D screened interaction form, is analysed. Charge order is found to hold and to be analogous for both interaction models, despite their very different form. The influence of charge ordering in the low density regime is discussed in relation to well known properties of 2D Coulomb fluids, such as the Kosterlitz-Thouless transition and criticality. The present study suggests the existence of a stable thermodynamic labile cluster phase, implying the existence of a liquid-liquid "transition" above the liquid-gas binodal. The liquid-gas and Kosterlitz-Thouless transitions would then take place inside the predicted cluster phase.

Stable isotopes as tracers for radionuclides

International Nuclear Information System (INIS)

Giussani, A.; Bartolo, D. de; Cantone, M.C.; Zilker, T.; Greim, H.; Roth, P.; Werner, E.

2000-01-01

The assessment of internal dose after incorporation of radionuclides requires as input data the knowledge of the uptake into the systemic circulation, the distribution and retention in selected organs, the excretion pathways. Realistic biokinetic models are needed for reliable estimates, correct interpretation of bioassay measurements, appropriate decision-making in radiological emergencies. For many radionuclides, however, the biokinetic models currently recommended are often generic, with very few specific parameters, due to the lack of experimental human data. The use of stable isotopes as tracers enables to determine important biokinetic parameters such as the fractional uptake, the clearance from the transfer compartment, the excretion patterns under experimentally controlled conditions. The subjects investigated are not exposed to any radiation risk, so this technique enables to obtain biokinetic information also for sensitive groups of the population, such as children or pregnant women, and to determine age- and gender-specific model parameters. Sophisticated analytical method, able to discriminate and quantitate different isotopes of the same element in complex matrices such as biological fluids, have to be purposely developed and optimized. Activation analysis and mass spectrometry are the most proper techniques of choice. Experiments were conducted with molybdenum, tellurium, ruthenium and zirconium. Activation analysis with protons, thermal ionization mass spectrometry and inductively coupled mass spectrometry were employed for the determination of stable isotopes of these elements in blood plasma and urine samples. Several deviations from the predictions of the ICRP models were observed. For example, modifications to the current model for molybdenum have been suggested on the basis of these results. The dose coefficients to the target regions calculated with this proposed model are even of one order of magnitude different than the ICRP estimates

Heterogeneous traffic flow modelling using second-order macroscopic continuum model

Science.gov (United States)

Mohan, Ranju; Ramadurai, Gitakrishnan

2017-01-01

Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the 'gap filling' behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.

The birth order puzzle.

Science.gov (United States)

Zajonc, R B; Markus, H; Markus, G B

1979-08-01

Studies relating intellectual performance to birth order report conflicting results, some finding intellectual scores to increase, others to decrease with birth order. In contrast, the relationship between intellectual performance and family size is stable and consistently replicable. Why do these two highly related variables generate such divergent results? This birth order puzzle is resolved by means of the confluence model that quantifies the influences upon intellectual growth arising within the family context. At the time of a new birth, two opposing influences act upon intellectual growth of the elder sibling: (a) his or her intellectual environment is "diluted" and (b) he or she loses the "last-born's handicap" and begins serving as an intellectual resource to the younger sibling. Since these opposite effects are not equal in magnitude, the differences in intellectual performance among birth ranks are shown to be age dependent. While elder children may surpass their younger siblings in intellectual performance at some ages, they may be overtaken by them at others. Thus when age is taken into consideration, the birth order literature loses its chaotic character and an orderly pattern of results emerges.

Stability Analysis and H∞ Model Reduction for Switched Discrete-Time Time-Delay Systems

Directory of Open Access Journals (Sweden)

Zheng-Fan Liu

2014-01-01

Full Text Available This paper is concerned with the problem of exponential stability and H∞ model reduction of a class of switched discrete-time systems with state time-varying delay. Some subsystems can be unstable. Based on the average dwell time technique and Lyapunov-Krasovskii functional (LKF approach, sufficient conditions for exponential stability with H∞ performance of such systems are derived in terms of linear matrix inequalities (LMIs. For the high-order systems, sufficient conditions for the existence of reduced-order model are derived in terms of LMIs. Moreover, the error system is guaranteed to be exponentially stable and an H∞ error performance is guaranteed. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.

Fractional-order mathematical model of an irrigation main canal pool

Directory of Open Access Journals (Sweden)

Shlomi N. Calderon-Valdez

2015-09-01

Full Text Available In this paper a fractional order model for an irrigation main canal is proposed. It is based on the experiments developed in a laboratory prototype of a hydraulic canal and the application of a direct system identification methodology. The hydraulic processes that take place in this canal are equivalent to those that occur in real main irrigation canals and the results obtained here can therefore be easily extended to real canals. The accuracy of the proposed fractional order model is compared by deriving two other integer-order models of the canal of a complexity similar to that proposed here. The parameters of these three mathematical models have been identified by minimizing the Integral Square Error (ISE performance index existing between the models and the real-time experimental data obtained from the canal prototype. A comparison of the performances of these three models shows that the fractional-order model has the lowest error and therefore the higher accuracy. Experiments showed that our model outperformed the accuracy of the integer-order models by about 25%, which is a significant improvement as regards to capturing the canal dynamics.

A hybrid simulation model for a stable auroral arc

Directory of Open Access Journals (Sweden)

P. Janhunen

Full Text Available We present a new type of hybrid simulation model, intended to simulate a single stable auroral arc in the latitude/altitude plane. The ionospheric ions are treated as particles, the electrons are assumed to follow a Boltzmann response and the magnetospheric ions are assumed to be so hot that they form a background population unaffected by the electric fields that arise. The system is driven by assumed parallel electron energisation causing a primary negative charge cloud and an associated potential structure to build up. The results show how a closed potential structure and density depletion of an auroral arc build up and how they decay after the driver is turned off. The model also produces upgoing energetic ion beams and predicts strong static perpendicular electric fields to be found in a relatively narrow altitude range (~ 5000–11 000 km.

Key words. Magnetospheric physics (magnetosphere-ionosphere interactions; auroral phenomena – Space plasma physics (numerical simulation studies

Fractional-Order Nonlinear Systems Modeling, Analysis and Simulation

CERN Document Server

Petráš, Ivo

2011-01-01

"Fractional-Order Nonlinear Systems: Modeling, Analysis and Simulation" presents a study of fractional-order chaotic systems accompanied by Matlab programs for simulating their state space trajectories, which are shown in the illustrations in the book. Description of the chaotic systems is clearly presented and their analysis and numerical solution are done in an easy-to-follow manner. Simulink models for the selected fractional-order systems are also presented. The readers will understand the fundamentals of the fractional calculus, how real dynamical systems can be described using fractional derivatives and fractional differential equations, how such equations can be solved, and how to simulate and explore chaotic systems of fractional order. The book addresses to mathematicians, physicists, engineers, and other scientists interested in chaos phenomena or in fractional-order systems. It can be used in courses on dynamical systems, control theory, and applied mathematics at graduate or postgraduate level. ...

Bounded excursion stable gravastars and black holes

Energy Technology Data Exchange (ETDEWEB)

Rocha, P [Instituto de Fisica, Universidade Federal Fluminense, Avenida Litoranea, s/n, Boa Viagem 24210-340, Niteroi, RJ (Brazil); Miguelote, A Y; Chan, R [Coordenacao de Astronomia e Astrofisica, Observatorio Nacional, Rua General Jose Cristino, 77, Sao Cristovao 20921-400, Rio de Janeiro, RJ (Brazil); Da Silva, M F; Wang, Anzhong [Departamento de Fisica Teorica, Instituto de Fisica, Universidade do Estado do Rio de Janeiro, Rua Sao Francisco Xavier 524, Maracana 20550-900, Rio de Janeiro-RJ (Brazil); Santos, N O, E-mail: pedrosennarocha@gmail.com, E-mail: yasuda@on.br, E-mail: chan@on.br, E-mail: mfasnic@gmail.com, E-mail: N.O.Santos@qmul.ac.uk, E-mail: anzhong_wang@baylor.edu [LERMA/CNRS-FRE 2460, Universite Pierre et Marie Curie, ERGA, Boite 142, 4 Place Jussieu, 75005 Paris Cedex 05 (France)

2008-06-15

Dynamical models of prototype gravastars were constructed in order to study their stability. The models are the Visser-Wiltshire three-layer gravastars, in which an infinitely thin spherical shell of stiff fluid divides the whole spacetime into two regions, where the internal region is de Sitter, and the external one is Schwarzschild. It is found that in some cases the models represent the 'bounded excursion' stable gravastars, where the thin shell is oscillating between two finite radii, while in other cases they collapse until the formation of black holes occurs. In the phase space, the region for the 'bounded excursion' gravastars is very small in comparison to that of black holes, but not empty. Therefore, although the possibility of the existence of gravastars cannot be excluded from such dynamical models, our results indicate that, even if gravastars do indeed exist, that does not exclude the possibility of the existence of black holes.

A variable-order fractal derivative model for anomalous diffusion

Directory of Open Access Journals (Sweden)

Liu Xiaoting

2017-01-01

Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.

Effect of ionization, bedding, and feeding on air quality in a horse stable.

Science.gov (United States)

Siegers, Esther Willemijn; Anthonisse, Milou; van Eerdenburg, Frank J C M; van den Broek, Jan; Wouters, Inge M; Westermann, Cornélie Martine

2018-05-01

Organic dust is associated with Equine asthma. Ionization should reduce airborne dust levels. To determine the effect of ionization of air, type of bedding, and feed on the levels of airborne dust, endotoxin, and fungal colonies in horse stables. 24 healthy University-owned horses occupied the stables. A randomized controlled cross-over study. Four units with 6 stables were equipped with an ionization installation (25 VA, 5000 Volt Direct Current). Horses were kept either on wood shavings and fed haylage (2 units), or on straw and fed dry hay (2 units). Measurements were performed with and without activated ionization, during daytime and nighttime, repeatedly over the course of a week and repeatedly during 4-6 weeks. Statistical analysis was performed using a mixed effect model with Akaike's Information Criterion for model reduction and 95% profile (log) likelihood confidence intervals (CI). Ionization did not alter concentrations of dust, endotoxin, or fungi, fewer. In the units with straw and hay, the concentration of dust, endotoxin, and fungi (difference in logarithmic mean 1.92 (95%CI 1.71-2.12); 2.86 (95%CI 2.59-3.14); 1.75 (95%CI 1.13-2.36)) were significantly higher compared to wood shavings and haylage. The installation of a negative air-ionizer in the horse stable did not reduce concentrations of dust, endotoxin, and viable fungal spores. The substantial effect of low dust bedding and feed is confirmed. Copyright © 2018 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

An Automated Approach to Very High Order Aeroacoustic Computations in Complex Geometries

Science.gov (United States)

Dyson, Rodger W.; Goodrich, John W.

2000-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. And for smooth problems, this is best accomplished with very high order in space and time methods on small stencils. But the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewslci recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that are located near wall boundaries. These procedures are used to automatically develop and implement very high order methods (>15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

Reduced α-stable dynamics for multiple time scale systems forced with correlated additive and multiplicative Gaussian white noise

Science.gov (United States)

Thompson, William F.; Kuske, Rachel A.; Monahan, Adam H.

2017-11-01

Stochastic averaging problems with Gaussian forcing have been the subject of numerous studies, but far less attention has been paid to problems with infinite-variance stochastic forcing, such as an α-stable noise process. It has been shown that simple linear systems driven by correlated additive and multiplicative (CAM) Gaussian noise, which emerge in the context of reduced atmosphere and ocean dynamics, have infinite variance in certain parameter regimes. In this study, we consider the stochastic averaging of systems where a linear CAM noise process in the infinite variance parameter regime drives a comparatively slow process. We use (semi)-analytical approximations combined with numerical illustrations to compare the averaged process to one that is forced by a white α-stable process, demonstrating consistent properties in the case of large time-scale separation. We identify the conditions required for the fast linear CAM process to have such an influence in driving a slower process and then derive an (effectively) equivalent fast, infinite-variance process for which an existing stochastic averaging approximation is readily applied. The results are illustrated using numerical simulations of a set of example systems.

Roof planes detection via a second-order variational model

Science.gov (United States)

Benciolini, Battista; Ruggiero, Valeria; Vitti, Alfonso; Zanetti, Massimo

2018-04-01

The paper describes a unified automatic procedure for the detection of roof planes in gridded height data. The procedure exploits the Blake-Zisserman (BZ) model for segmentation in both 2D and 1D, and aims to detect, to model and to label roof planes. The BZ model relies on the minimization of a functional that depends on first- and second-order derivatives, free discontinuities and free gradient discontinuities. During the minimization, the relative strength of each competitor is controlled by a set of weight parameters. By finding the minimum of the approximated BZ functional, one obtains: (1) an approximation of the data that is smoothed solely within regions of homogeneous gradient, and (2) an explicit detection of the discontinuities and gradient discontinuities of the approximation. Firstly, input data is segmented using the 2D BZ. The maps of data and gradient discontinuities are used to isolate building candidates and planar patches (i.e. regions with homogeneous gradient) that correspond to roof planes. Connected regions that can not be considered as buildings are filtered according to both patch dimension and distribution of the directions of the normals to the boundary. The 1D BZ model is applied to the curvilinear coordinates of boundary points of building candidates in order to reduce the effect of data granularity when the normals are evaluated. In particular, corners are preserved and can be detected by means of gradient discontinuity. Lastly, a total least squares model is applied to estimate the parameters of the plane that best fits the points of each planar patch (orthogonal regression with planar model). Refinement of planar patches is performed by assigning those points that are close to the boundaries to the planar patch for which a given proximity measure assumes the smallest value. The proximity measure is defined to account for the variance of a fitting plane and a weighted distance of a point from the plane. The effectiveness of the

Complex functionality with minimal computation: Promise and pitfalls of reduced-tracer ocean biogeochemistry models

Science.gov (United States)

Galbraith, Eric D.; Dunne, John P.; Gnanadesikan, Anand; Slater, Richard D.; Sarmiento, Jorge L.; Dufour, Carolina O.; de Souza, Gregory F.; Bianchi, Daniele; Claret, Mariona; Rodgers, Keith B.; Marvasti, Seyedehsafoura Sedigh

2015-12-01

Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of-the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded in the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. These results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate "sub-ecosystem-scale" parameterizations.