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Post-Processing Approach for Massive Output Data From Large-Scale TSPA in APro

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  • URLhttps://db.koreascholar.com/Article/Detail/431181
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한국방사성폐기물학회 학술논문요약집 (Abstracts of Proceedings of the Korean Radioactive Wasts Society)
한국방사성폐기물학회 (Korean Radioactive Waste Society)
초록

APro, a process-based total system performance assessment (TSPA) tool for a geological disposal system, has a framework for simulating the radionuclide transport affected by thermal, hydraulic, mechanical or geochemical changes occurred in the disposal system. APro aims to be applied for the TSPA to long-term (> 100,000) evolution scenarios in real-world repository having more than 10,000 boreholes. In this large-scale TSPA, it is important not only to develop a high-performance numerical approach, but also to apply an efficient post-processing approach to massive spatiotemporal data. The post-processing refers to validating numerical analysis results, analyzing and evaluating target systems through data processing or visualization. Since APro uses COMSOL interface, the postprocessing function in COMSOL can be used. However, when the data size increases due to largescale numerical analysis, the time for the COMSOL post-processing increases, resulting in a problem that the analysis and evaluation are not performed effectively. In this case, it is possible to extract necessary data using the COMSOL exporting function and importing it into an external postprocessing program for the analysis and evaluation. In this study, the efficiency of external post-processing with extracted data from COMSOL was reviewed. And, we derived a proper data extraction approach (format and structure) that can increase efficiency of external post-processing.

저자
  • Hong Jang(Korea Atomic Energy Research Institute (KAERI)) Corresponding author
  • Jung-Woo Kim(Korea Atomic Energy Research Institute (KAERI))