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Khuwaileh, Bassam A.;Turinsky, Paul J.
- Nuclear Engineering and Technology
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- v.49 no.6
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- pp.1219-1225
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- 2017
In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.
https://doi.org/10.1016/j.net.2017.08.007 인용 PDF KSCI

Singh, Pooja;Singh, Lalit Kumar
- Nuclear Engineering and Technology
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- v.51 no.5
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- pp.1289-1296
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- 2019
Non-functional requirements plays a critical role in designing variety of applications domain ranges from safety-critical systems to simple gaming applications. Performance is one of the crucial non-functional requirement, especially in control and safety systems, that validates the design. System risk can be quantified as a product of probability of system failure and severity of its impact. In this paper, we devise a technique to do the performance analysis of safety critical and control systems and to estimate performance based risk factor. The technique elaborates Petri nets to estimate performability to ensure system dependability requirements. We illustrate the technique on a case study of Nuclear Power Plant system. The technique has been validated on 17 safety critical and control systems of Nuclear Power Plant.
https://doi.org/10.1016/j.net.2019.02.014 인용 PDF KSCI