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Reduced Order Modeling of Dynamic Systems for Decreasing Computational Burden in Uncertainty Quantification

Abstract Details

2018, Master of Science, Ohio State University, Nuclear Engineering.
Dynamic Probabilistic Risk Assessment (DPRA) is a method that has demonstrated usefulness for safety analysis of nuclear power plants. DPRA is based on constructing computer models of a system and sampling the model many times to quantify the consequence and frequency of the impact of associated uncertainties. Since models of nuclear power plants are very complex and take many hours or days to run, using full scale plant modes is infeasible given the number of times models need to be run for such a purpose. Reduced order models (ROMs), which approximate the result of a more complex model, have seen use as a way of reducing the necessary computer resources. Several ROM options are considered for multiple systems to investigate their applicability. A procedure is presented for determining the applicability of different ROMs for seismic analysis. It is shown that a reduction in the number of necessary samples from 20,000 to fewer than 6,000 can be obtained with the choice of the appropriate ROM run, which is proportional to the run time.
Tunc Aldemir (Advisor)
Carol Smidts (Committee Member)
68 p.

Recommended Citations

Citations

  • Cohn, B. E. (2018). Reduced Order Modeling of Dynamic Systems for Decreasing Computational Burden in Uncertainty Quantification [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531425355869627

    APA Style (7th edition)

  • Cohn, Brian. Reduced Order Modeling of Dynamic Systems for Decreasing Computational Burden in Uncertainty Quantification. 2018. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1531425355869627.

    MLA Style (8th edition)

  • Cohn, Brian. "Reduced Order Modeling of Dynamic Systems for Decreasing Computational Burden in Uncertainty Quantification." Master's thesis, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531425355869627

    Chicago Manual of Style (17th edition)