SBIR/STTR Research Award

SafeCBM: NPP Safety-constrained CBM Optimization & Diagnosis

Award identifier 4c38cad4849d7ec4e8fc1d72e053a3534195590f22de38eb234f4093da6ee66eAwarding agency Department of Energy

Award amount

$1,095,989

Program and phase

SBIR · Phase II

Award year

2022

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
INFOBEYOND TECHNOLOGY LLC
Proposal award date
2022-08-22
Contract end date
2024-08-21
UEI
JMXHCAK12LZ7
Solicitation number
Not reported
Topic code
C52-39h

Research abstract

A joint report in 2020 by International Energy Agency and Nuclear Energy Agency concludes that prolonging the operation of existing NPPs (instead of building new large NPPs) is the most affordable low-carbon solution. This calls for advanced NPP Prognostics and Health Management (PHM) technology to achieve sustainable NPP electricity generation and supply in a safe and economic way. However, current approaches are still limited for such a capability evidenced by the recent NPP shutdowns, e.g., Duke Energy’s Oconee Nuclear Station Unit 2 in 2022. To fill this gap, InfoBeyond propose SafeCBM (NPP Safety-constrained CBM Optimization & Diagnosis) to provide cost-effective Predictive Maintenance capability subject to NPP strict safety and reliability constraints. SafeCBM enables condition-based monitoring with dynamic-scheduled inspection for NPP components. For such a purpose, SafeCBM defines new equipment and materials classifications based on International Standard ISO 15926 standardized information models to enhance the results of risk-based CBM (Condition-Based Maintenance) optimization. Next, deep learning models using LSTM (Long Short Term Memory) neuron networks is proposed to predict the equipment RUL (Reminding Useful Lifetime) to indicate when the equipment will fail or the failure probability at the given future time. Finally, a CBM optimization model with NPP safety constraints assuming imperfect inspection is constructed to provide optimal maintenance policies. Such a policy is based on optimal maintenance cost CBM probability before a component’s lifetime failure occurs. For practicability of maintenance decision, the proposed optimization model, which minimizes the expected long-term cost rate with safety constraints, also considers the influence of imperfect inspection. SafeCBM is the first safety-integrated PHM solution that leverages AI-based process automation, machine intelligence, and computer aided decision making for NPP modernization that enhances both core operations and PHM activities. Business Benefits: SafeCBM achieves several impressive benefits: • Conditional Monitoring/CBM Enhancement: SafeCBM can enhance the plant’s CMMS (Computerized Maintenance Management Systems) performance by minimizing overall maintenance cost, improving PLiM (Plant Life Management), and increasing process productivity, all while integrating NPP safety constraints and dynamic inspection scheduling criteria. It considers plant safety constraints and measurement errors when calculating maintenance cost optimizations and strategies. It supports CBM decision-making by suggesting predictive correction of components and accessories likely to fail in the future. • Advanced Oil, Gas, Power Plant and Other Energy Facility Maintenance: SafeCBM’s benefits can be extended to Oil & gas plants (e.g., Port Arthur Refinery), Hydroelectric plants (Robert Moses Niagara Power Plant), Coal, solar, and wind plants (e.g., Meadow Lake Wind Farm), power stations, and other energy facilities. Monitoring the health of machines effectively enables the users to schedule repair and maintenance of the system ensuring less downtime, thereby enhancing its lifetime and production volume. • Industrial Machinery Maintenance and Facility Management & Maintenance: SafeCBM offers these facilities management/maintenance activities in terms of reliability, availability, and serviceability. SafeCBM ensures continuous facility operability in multi-tier aspects. Its optimal CBM model is able to integrate patient and staff equipment risk and link that risk to the equipment or area being serviced. It streamlines their facility and maintenance operations.

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

44 SBIR/STTR records share this UEI (2010–2025). Reported award amounts total $13,013,950. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Energy, Department of Commerce, Department of Transportation

Agency intelligence

Department of Energy

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