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Title: Method for nonlinear optimization for gas tagging and other systems

Abstract

A method and system are disclosed for providing nuclear fuel rods with a configuration of isotopic gas tags. The method includes selecting a true location of a first gas tag node, selecting initial locations for the remaining n-1 nodes using target gas tag compositions, generating a set of random gene pools with L nodes, applying a Hopfield network for computing on energy, or cost, for each of the L gene pools and using selected constraints to establish minimum energy states to identify optimal gas tag nodes with each energy compared to a convergence threshold and then upon identifying the gas tag node continuing this procedure until establishing the next gas tag node until all remaining n nodes have been established. 6 figs.

Inventors:
; ;
Issue Date:
Research Org.:
Univ. of Chicago, IL (United States)
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
563689
Patent Number(s):
5706321
Application Number:
PAN: 8-640,699; TRN: 98:002113
Assignee:
Univ. of Chicago, IL (United States)
DOE Contract Number:  
W-31109-ENG-38
Resource Type:
Patent
Resource Relation:
Other Information: PBD: 6 Jan 1998
Country of Publication:
United States
Language:
English
Subject:
22 NUCLEAR REACTOR TECHNOLOGY; FUEL RODS; IDENTIFICATION SYSTEMS; ISOTOPE RATIO; NONLINEAR PROBLEMS; POSITIONING

Citation Formats

Chen, T, Gross, K C, and Wegerich, S. Method for nonlinear optimization for gas tagging and other systems. United States: N. p., 1998. Web.
Chen, T, Gross, K C, & Wegerich, S. Method for nonlinear optimization for gas tagging and other systems. United States.
Chen, T, Gross, K C, and Wegerich, S. Tue . "Method for nonlinear optimization for gas tagging and other systems". United States.
@article{osti_563689,
title = {Method for nonlinear optimization for gas tagging and other systems},
author = {Chen, T and Gross, K C and Wegerich, S},
abstractNote = {A method and system are disclosed for providing nuclear fuel rods with a configuration of isotopic gas tags. The method includes selecting a true location of a first gas tag node, selecting initial locations for the remaining n-1 nodes using target gas tag compositions, generating a set of random gene pools with L nodes, applying a Hopfield network for computing on energy, or cost, for each of the L gene pools and using selected constraints to establish minimum energy states to identify optimal gas tag nodes with each energy compared to a convergence threshold and then upon identifying the gas tag node continuing this procedure until establishing the next gas tag node until all remaining n nodes have been established. 6 figs.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1998},
month = {1}
}