Engineering topics

Nistor, Jonathan

Publications and source records attributed to Nistor, Jonathan.

3 records

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Development of a Cloud-based Application to Enable a Scalable Risk-informed Predictive Maintenance Strategy at Nuclear Power Plants

Light-water reactor operations and maintenance (O&M) costs are prohibitively high, thus contributing to the premature decommissioning of nuclear power plants (NPPs). This is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology by virtue of its low costs, computing and storage adaptability, and ability to host applications over numerous types of virtual infrastructures. Cloud computing can be a cost-effective alternative to onsite storage and diagnostics. This paper conducts a techno-economic assessment of a provisional cloud deployment architecture for a NPP predictive monitoring (PdM) system. The cloud-based monitoring system would enable maintenance and diagnostics (M&D) analysts and other authorized plant users to remotely monitor equipment functionality so as to enable PdM practices and early detection of faults. The Microsoft Azure cloud platform is included in the proposed cloud architecture to provide data processing and storage, sensor device networking, and database management; however, this analysis could be extended to other cloud computing service providers as well. For the techno-economic assessment, technical feasibility is measured in terms of network performance metrics such as response time, latency, and throughput, whereas economic feasibility is measured in terms of operational costs and capital expenditures. Finally, this report covers certain regulatory and security aspects that may concern licensees looking to implement cloud computing. The report focuses on the integration of sensor database storage, the application of cloud resources to PdM, and the identification of technological and economic hurdles associated with moving to a cloud-computing-based architecture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Test of nuclear decay rate variation due to an antineutrino flux

Unexplained variations of the decay rate parameter for weak interaction decays such as β ± decay, electron capture, as well as strong interaction α decay have been reported. Because these variations have been presented by a number of groups, at various locations, using various types of detectors, different isotopes, and over extended periods of time, some researchers have interpreted the source of these variations as not from ambient environmental factors such as temperature, pressure, and humidity but via an unexplained fundamental interaction. The state of decay rate parameter variations experiments is reviewed, and the reported results are placed into a common comparable context by defining a phenomenological cross section. After that we make decay parameter measurements as a function of time at the level of 10 -5 in the presences of an antineutrino flux with an on-off cycle time of ≈ 30 days. This level of precision requires a detailed understanding of both systematic and statistical errors; otherwise, systematic errors in the measurement may mimic the decay events of fundamental interactions. The experiment searched for variation of the $^{54}_{25}$Mn, e - capture decay rate parameter and $^{137}_{55}$Cs, β - decay rate parameter both to a level of precision of 1 part in ≈10 5 by comparing the difference between the decay rate in the presence of an antineutrino flux ≈ 3 x 10 12 $\bar{ν}$ cm -2 s -1 and no flux measurements. The experiment was located 6.53 m from the reactor core of the High Flux Isotope Reactor at the Oak Ridge National Laboratory. Two weak interaction decays, one via electron capture and the other via β - decay, were selected because the final state and the time reverse state each contain a neutrino and antineutrino, covering arguments that the antineutrino flux may interact differently or not at all in one of the cases. The $\gamma$ spectra from both decays were collected and analyzed independently. The measured variation in the decay rate parameters are found to be δλ/λ =(0.034 ± 1.38) x10 -5 for $^{54}_{25}$Mn and δλ/λ =(0.67±1.56) x10 -5 for $^{137}_{55}$Cs. These results are consistent with no measurable decay rate parameter variation due to an antineutrino flux, yielding a 68% confidence level upper limit sensitivity for $^{54}_{25}$Mn δλ/λ ≤ 1.31 x 10 -5 or σ ≤ 1.29 x10 -25 cm 2 in cross section and for $^{137}_{55}$Cs δλ/λ ≤ 2.23 x 10 -5 or σ ≤ 5.69 x10 -27 cm 2 . The cross-section upper limit obtained in these null or no observable effect measurements are ≈ 10 4 times more sensitive than past experiments reporting positive results in 54 Mn and 137 Cs. . .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗