SBIR/STTR Research Award

A NEURAL NETWORK APPROACH TO NUCLEAR PLANT MONITORING

Award identifier 74b37bbd94ba5b3dabfbef91b125eaa083b723840f6c6d1e656ae5f6f2c6e360Awarding agency Department of Energy

Award amount

$500,000

Program and phase

SBIR · Phase II

Award year

1992

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
CHARLES RIVER ANALYTICS, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
DD1BYN8SN355
Solicitation number
Not reported
Topic code
Not reported

Research abstract

THE MAJOR OBJECTIVE OF NUCLEAR PLANT MONITORING SYSTEMS IS TO ENABLE THE OPERATOR TO MAKE CORRECT DECISIONS THAT ENSURESAFE PLANT OPERATIONS WHILE PROVIDING A RELIABLE ENERGY SOURCE. THE USUAL DIFFICULTIES ENCOUNTERED BY NUCLEAR PLANT OPERATORS ARE INCORRECT ASSUMPTIONS OF PLANT STATUS, INSUFFICIENT INFORMATION FOR FAULT DIAGNOSIS, AND INNACCURATE PREDICTION OF SCENARIOS THAT WOULD RESULT FROM VARIOUS COURSES OF ACTION. TO ALLEVIATE THESE DIFFICULTIES,THE HYBRID INTEGRATION OF ARTIFICIAL NEURAL NETWORKS (ANNS) AND KNOWLEDGE-BASED EXPERT SYSTEMS (KBS) IS BEING OPTIMIZED TO PROVIDE INTELLIGENT RECOMMENDATIONS FOR SAFE NUCLEAR PLANT OPERATIONS. THE INTEGRATION OF ANNS AND KBS IS AN IDEAL STEP IN THE DEVELOPMENT OF INTELLIGENT SYSTEMS. IN GENERAL, ANNS PROVIDE "SOFT" CONSTRAINTS, WHILE KBS ALLOW "HARD" CONSTRAINTS. THE TWO METHODS COMPLEMENT EACH OTHER IN A MANNER SIMILAR TO THE HEMISPHERES THAT CONTAIN THE HUMAN MIND. ANNS, CORRESPONDING TO THE RIGHT HEMISPHERE OF THE BRAIN, PROVIDE ADAPTABLE PATTERN RECOGNITION AND CLASSIFICATION CAPABILITIES THAT CONTINUE TO PERFORM EVEN IF SOME PROCESSING UNITS FAIL; KBS, WHICH RELATE TO THE LEFTHEMISPHERE, INVOLVE A STRUCTURED, RULE-BASED REPRESENTATION OF EXPERT KNOWLEDGE AND STEP-BY-STEP DECISION STRATEGIES. THIS PROJECT TAKES ADVANTAGE OF THE COMPLEMENTARY STRENGTHS AND WEAKNESSES OF EACH METHOD TO CREATE A HYBRID SENSOR MONITORING SYSTEM THAT CAN OUTPERFORM EITHER METHOD ALONE. IN THIS PHASE I STUDY, NEURAL NETWORK AND HYBRID NEURAL-NETWORK/KNOWLEDGE-BASED STRATEGIES ARE BEING DEVELOPED FOR INTELLIGENT SENSOR MONITORING CAPABILITIES WITHIN NUCLEAR POWERPLANT APPLICATIONS. THE ANN FOCUS INVOLVES DETERMINING PLANT OPERATING STATES, INCLUDING NORMAL AND OFF-NORMAL CONDITIONS, AND INVESTIGATING THE TEMPORAL SIGNATURES OF THE VARIOUS SENSOR MEASUREMENTS. THEHYBRID STRATEGIES FOCUS ON INTEGRATING THE ANN RESULTS WITH EXPERT ASSESSMENT AND PREDICTION KNOWLEDGE IN ORDER TO PROVIDE THE PLANT OPERATOR WITH INTELLIGENT RECOMMENDATIONS.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

961 SBIR/STTR records share this UEI (1984–2026). Reported award amounts total $386,500,110. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Homeland Security, Department of Transportation, Department of Energy

Agency intelligence

Department of Energy

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