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ANALYSIS AND TRAINING OF AN ARTIFICIAL NEURAL NETWORK NETWORK NUCLEAR POWER PLANTACCIDENT DIAGNOSTIC ADVISOR

Award Information
Agency: Nuclear Regulatory Commission
Branch: N/A
Contract: N/A
Agency Tracking Number: 14787
Amount: $50,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 1991
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
5080 Shoreham Place Suite 201
San Diego, CA 92122
United States
DUNS: N/A
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dan Greenwood
 President
 () -
Business Contact
Phone: () -
Research Institution
N/A
Abstract

THE OBJECTIVE OF THE PROPOSED RESEARCH IS TO DEVELOP AN ARTIFICIAL-INTELLIGENCE FAULT-DIAGNOSTIC SYSTEM THAT WILL CLASSIFY, IN REAL-TIME, NUCLEAR POWER PLANT TRANSIENTS AND PROVIDE ERROR BOUNDS ON ITS DIAGNOSES. THE GOAL IS TO DEVELOP AN ARTIFICIAL NEURAL NETWORK (ANN) PARADIGM THAT IS CAPABLE OF NOT ONLY PROVIDING A PROPER CLASSIFICATION BUT ALSO GIVING A FIGURE OF MERIT FOR ITS ANSWER. THE PROPOSED DIAGNOSTIC ADVISOR WOULD BE INTEGRATED INTO THE PROCESS COMPUTER OR SAFETY PARAMETER DISPLAY SYSTEM. THE ADVISOR'S OBJECTIVE WOULD BE TO WARN AND INFORM PLANT OPERATORS AND ENGINEERS OF PLANT COMPONENT FAILURES IN A TIMELY MANNER. THE OBJECTIVE OF THE PROPOSED RESEARCH IS TO DEVELOP AN ARTIFICIAL-INTELLIGENCE FAULT-DIAGNOSTIC SYSTEM THAT WILL CLASSIFY, IN REAL-TIME, NUCLEAR POWER PLANT TRANSIENTS AND PROVIDE ERROR BOUNDS ON ITS DIAGNOSES. THE GOAL IS TO DEVELOP AN ARTIFICIAL NEURAL NETWORK (ANN) PARADIGM THAT IS CAPABLE OF NOT ONLY PROVIDING A PROPER CLASSIFICATION BUT ALSO GIVING A FIGURE OF MERIT FOR ITS ANSWER. THE PROPOSED DIAGNOSTIC ADVISOR WOULD BE INTEGRATED INTO THE PROCESS COMPUTER OR SAFETY PARAMETER DISPLAY SYSTEM. THE ADVISOR'S OBJECTIVE WOULD BE TO WARN AND INFORM PLANT OPERATORS AND ENGINEERS OF PLANT COMPONENT FAILURES IN A TIMELY MANNER. THE OBJECTIVE OF THE PROPOSED RESEARCH IS TO DEVELOP AN ARTIFICIAL-INTELLIGENCE FAULT-DIAGNOSTIC SYSTEM THAT WILL CLASSIFY, IN REAL-TIME, NUCLEAR POWER PLANT TRANSIENTS AND PROVIDE ERROR BOUNDS ON ITS DIAGNOSES. THE GOAL IS TO DEVELOP AN ARTIFICIAL NEURAL NETWORK (ANN) PARADIGM THAT IS CAPABLE OF NOT ONLY PROVIDING A PROPER CLASSIFICATION BUT ALSO GIVING A FIGURE OF MERIT FOR ITS ANSWER. THE PROPOSED DIAGNOSTIC ADVISOR WOULD BE INTEGRATED INTO THE PROCESS COMPUTER OR SAFETY PARAMETER DISPLAY SYSTEM. THE ADVISOR'S OBJECTIVE WOULD BE TO WARN AND INFORM PLANT OPERATORS AND ENGINEERS OF PLANT COMPONENT FAILURES IN A TIMELY MANNER.

* Information listed above is at the time of submission. *

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