Method for nonlinear optimization for gas tagging and other systems

• US 5,706,321 A
• Filed: 05/01/1996
• Issued: 01/06/1998
• Est. Priority Date: 05/01/1996
• Status: Expired due to Fees

• Current Assignee: University of Chicago The (University of Chicago)
• Original Assignee: University of Chicago
• Inventors: Gross, Kenny C., Chen, Ting, Wegerich, Stephan
• Primary Examiner(s): Wasil, Daniel D.
• Application Number:
  US08/640,699
• Time in Patent Office: 615 Days
• Field of Search: 376/250, 376/251, 376/253, 376/260, 376/261, 376/412, 376/413, 376/450, 376/463
• US Class Current: 376/463
• CPC Class Codes: G21C 17/048 characterised by a special construction of fuel elements, e.g. by a confined "tracer"
• CPC Class Codes: G21D 3/001 Computer implemented control
• CPC Class Codes: Y02E 30/00 Energy generation of nuclear origin
• CPC Class Codes: Y02E 30/30 Nuclear fission reactors

Abstract

A method and system 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.

Claims

1. A method of generating a configuration design of gas tag nodes for nuclear fuel rods, the nodes being characteristic of a unique set of tag gas compositions, comprising the steps of:

(a) selecting a true location of a first node characteristic of an isotopic gas tag;

(b) selecting initial locations for (n-1) remaining nodes based on a table of target gas tag compositions;

(c) generating L random gene pools representing L sets of nodes, p^l p^L ;

(d) applying a Hopfield network for computing an energy for each of said L gene pools and repeating said computing step to minimize said energy using selected constraints to determine optimal gas tag nodes;

(e) each value of said energy being compared to a convergence threshold and upon achieving a minimum energy a next gas tag node is established; and

(f) repeating said steps (d) and (e) using the remaining n-2 nodes until establishing the next gas tag node and thereafter continuing until all of the n nodes have been established, thereby establishing the configuration design of gas tag nodes.

2. The method as defined in claim 1 further including the step of creating a new set of gene pools if no values of said energy satisfy the convergence condition.

3. The method as defined as claim 2 further including the step of saving best values of said gene pools upon creating said new set of gene pools.

4. The method as defined in claim 3 wherein said new set of gene pools are applied to the input of the Hopfield network.

5. The method as defined in claim 1 wherein said selected constraints include (a) there is only one optimal location for each said tag gas node to be blended, (b) a total number of optimal locations for said gas tag nodes to be blended is equal to the number of said gas tag nodes, (c) said gas tag nodes are to be distributed in the most compact configuration for reducing cost of noble gas used to create said gas tags, (d) the closest distance between any said gas tag node and the line connecting any other two gas tag nodes should be greater than a minimum separation distance, (e) no four gas tag nodes lie in any one plane and (f) no three gas tag nodes lie on a straight line.