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Languages : en
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Book Description
Adaptive Core Simulation
Author: Adaptive Core Simulation
Author: Hany Samy Abdel-KhalikPublisher:
ISBN:
Category :
Languages : en
Pages : 210
Book Description
Keywords: Discrete Inverse Theory, Efficient Subspace Methods, Boiling Water Reactors Core Simulation, Regularization of Ill-Posed Problems.
Inverse Method Applied to Adaptive Core Simulation
Author: Hany Samy Abdel-KhalikPublisher:
ISBN:
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Languages : en
Pages : 98
Book Description
Keywords: parameter estimation, regularization, discrete inverse theory, core simulators, adaptive simulation, ill-posedness, vector spaces optimization.
Inverse Method Applied to Adaptive Core Simulation
Author: Publisher:
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Languages : en
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The work presented in this thesis is a part of an ongoing research project conducted to gain insight into the applicability of inverse methods to developing adaptive simulation capabilities for core physics problems. Adaptive simulation is a simulation that utilizes past and current reactor measurements of reactor observables (e.g. core reactivity and incore instrumentation readings) to adapt the simulation in a meaningful way to improve agreement with reactor observables. To perform such adaption, we utilize a group of mathematical techniques which address the problem of given a current core simulator model and the associated input data (e.g. cross-sections, thermal-hydraulic parameters), how should the values of selected input data be adjusted to improve agreement with observables without changing the core simulator model, (i.e. how can we obtain the best agreement utilizing our current modeling capability). This is usually referred to as an inverse problem, which is difficult to solve due to its ill-posedness nature. Major advances have been made by mathematicians to overcome the ill-posedness nature of such problems. The proposed project is of an exploratory nature serving to develop expertise in this area, to which the nuclear power community has not participated to any great extent over the last two decades since their earlier contribution during the design, research and developments stages of a proto-typical fast breeder reactor. Exploratory research projects, such as this one, serve to develop insight, form general ideas about areas where little expertise is available, and to provide a basis on whether there is potential for the proposed techniques to be useful and successful. The current work addresses BWR core simulators since their prediction accuracy is inferior to PWRs', providing marginally acceptable agreement between measured and predicted core attributes. This implies that BWRs could benefit from utilizing an adaptive simulation tool. In the work do.
The Application of Adaptive Model Refinement to Nuclear Reactor Core Simulation
Author: Sterling Justin SatterfieldPublisher:
ISBN:
Category :
Languages : en
Pages : 210
Book Description
Embedded Systems and Artificial Intelligence
Author: Vikrant BhatejaPublisher: Springer Nature
ISBN: 9811509476
Category : Technology & Engineering
Languages : en
Pages : 880
Book Description
This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2–3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.
Multicycle Adaptive Simulation of Boiling Water Reactor Core Simulators
Author: Christopher Michael BriggsPublisher:
ISBN:
Category :
Languages : en
Pages : 69
Book Description
Keywords: regularization, inverse theory, uncertainty, cross section uncertainty, cross section adjustment, least squares, adaptive simulation, data adjustment.
Further Development of the Application of Adaptive Model Refinement to Nuclear Reactor Core Simulation
Author: Beth Ellen AldridgeMulticycle Adaptive Simulation of Boiling Water Reactor Core Simulators
Author: Publisher:
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Languages : en
Pages :
Book Description
Adaptive simulation (AS) is an algorithm utilizing a regularized least squares methodology to correct for the discrepancy between core simulators predictions and actual plant measurements. This is an inverse problem that will adjust the cross sections input to a core simulator within their range of uncertainty to obtain better agreement with the plant measurements. The cross section adjustments are constrained to their range of uncertainty using the covariance matrix of the few-group cross sections and in imposing the regularization on the least squares solution. This few-group covariance matrix is obtained using the covariance matrix of the multi-group cross sections and the corresponding lattice physics sensitivity matrix. To perform the adaption, one must also have the sensitivity matrix of the core simulator. Constructing the sensitivity matrix of both the lattice physics code and core simulator would be a daunting task using the traditional brute-force method of computing a forward solve for a perturbation of every input. To avoid this, a singular value decomposition (SVD) is used to construct a low rank approximation of the covariance matrices, thus drastically reducing the number of required forward solves. Until now, AS has been used on a single depletion cycle to correct for discrepancies resulting from errors introduced by incorrect cross sections only. Adapting to a single depletion cycle means that the cross sections of cycle m were adjusted so that the core simulator better predicts the actual measurements of cycle m (and future cycles if the algorithm is robust). This, however, does not account for the reloaded burnt fuel number density errors at the beginning-of-cycle (BOC) m. By definition a burnt assembly has been used and depleted in a previous cycle. If adaption changes the cross sections of that burnt assembly in cycle m, those cross sections should have also been changed in any cycle preceding m which would have resulted in different BOC m numbe.
From Animals to Animats 2
Author: Jean-Arcady MeyerPublisher: MIT Press
ISBN: 9780262631495
Category : Adaptability (Psychology)
Languages : en
Pages : 1018
Book Description
More than sixty contributions in From Animals to Animats 2 byresearchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fieldsinvestigate behaviors and the underlying mechanisms that allow animals and, potentially, robots toadapt and survive in uncertain environments. Jean-Arcady Meyer is Director of Research, CNRS, Paris.Herbert L. Roitblat is Professor of Psychology at the University of Hawaii at Manoa. Stewart W.Wilson is a scientist at The Rowland Institute for Science, Cambridge,Massachusetts. Topics covered: The Animat Approach to Adaptive Behavior,Perception and Motor Control, Action Selection and Behavioral Sequences, Cognitive Maps and InternalWorld Models, Learning, Evolution, Collective Behavior.