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Title: Artificial Neural Network Solutions of Slab-Geometry Neutron Diffusion Problems

Abstract

Artificial neural network (ANN) methods have been researched extensively within the nuclear community for applications in systems control, diagnostics, and signal processing. We consider here the use of multilayer perceptron ANNs as an alternative to finite-difference and finite-element methods for obtaining solutions to neutron diffusion problems. This work is based on a method proposed by van Milligen et. al. to obtain solutions of the differential equations arising in plasma physics applications. This ANN method has the potential advantage of yielding an accurate, differentiable approximation to the solution of diffusion problems at all points in the spatial domain.

Authors:
Publication Date:
Research Org.:
Lawrence Livermore National Lab., CA (US)
Sponsoring Org.:
USDOE Office of Defense Programs (DP) (US)
OSTI Identifier:
793624
Report Number(s):
UCRL-JC-139281
TRN: US0205251
DOE Contract Number:  
W-7405-Eng-48
Resource Type:
Conference
Resource Relation:
Conference: 2000 International Winter Meeting and Embedded Topical Meetings, Washington, DC (US), 11/12/2000--11/16/2000; Other Information: PBD: 12 Jun 2000
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; DIFFERENTIAL EQUATIONS; DIFFUSION; FINITE ELEMENT METHOD; NEURAL NETWORKS; NEUTRONS; PHYSICS; PLASMA

Citation Formats

Brantley, P S. Artificial Neural Network Solutions of Slab-Geometry Neutron Diffusion Problems. United States: N. p., 2000. Web.
Brantley, P S. Artificial Neural Network Solutions of Slab-Geometry Neutron Diffusion Problems. United States.
Brantley, P S. Mon . "Artificial Neural Network Solutions of Slab-Geometry Neutron Diffusion Problems". United States. https://www.osti.gov/servlets/purl/793624.
@article{osti_793624,
title = {Artificial Neural Network Solutions of Slab-Geometry Neutron Diffusion Problems},
author = {Brantley, P S},
abstractNote = {Artificial neural network (ANN) methods have been researched extensively within the nuclear community for applications in systems control, diagnostics, and signal processing. We consider here the use of multilayer perceptron ANNs as an alternative to finite-difference and finite-element methods for obtaining solutions to neutron diffusion problems. This work is based on a method proposed by van Milligen et. al. to obtain solutions of the differential equations arising in plasma physics applications. This ANN method has the potential advantage of yielding an accurate, differentiable approximation to the solution of diffusion problems at all points in the spatial domain.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2000},
month = {6}
}

Conference:
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