Deflagration to detonation transition (DDT) is a challenging subject in computational fluid dynamics both from a standpoint of the phenomenon nature understanding and from extremely demanding computational efforts. In recent years, as the development of computer technology and improvement of numerical schemes was achieved, some more direct methods have been found to reproduce the DDT mechanistically without additional numerical or physical models. In the current work, highly resolved DDT simulations of hydrogen-air and of hydrogen-oxygen mixtures in 2D channel with regular repeating obstacles are present. The technique of local mesh refinement (ALMR) is implemented in the simulations to minimize the computational efforts. The criteria for the ALMR are examined and optimized in simulations.
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2016 24th International Conference on Nuclear Engineering
June 26–30, 2016
Charlotte, North Carolina, USA
Conference Sponsors:
- Nuclear Engineering Division
ISBN:
978-0-7918-5004-6
PROCEEDINGS PAPER
Adaptive LMR Simulation of DDT in Obstructed Channel
Ke Ren,
Ke Ren
Karlsruhe Institute of Technology, Karlsruhe, Germany
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Alexei Kotchourko,
Alexei Kotchourko
Karlsruhe Institute of Technology, Karlsruhe, Germany
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Alexander Lelyakin
Alexander Lelyakin
Karlsruhe Institute of Technology, Karlsruhe, Germany
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Ke Ren
Karlsruhe Institute of Technology, Karlsruhe, Germany
Alexei Kotchourko
Karlsruhe Institute of Technology, Karlsruhe, Germany
Alexander Lelyakin
Karlsruhe Institute of Technology, Karlsruhe, Germany
Paper No:
ICONE24-61105, V004T10A031; 10 pages
Published Online:
October 25, 2016
Citation
Ren, K, Kotchourko, A, & Lelyakin, A. "Adaptive LMR Simulation of DDT in Obstructed Channel." Proceedings of the 2016 24th International Conference on Nuclear Engineering. Volume 4: Computational Fluid Dynamics (CFD) and Coupled Codes; Decontamination and Decommissioning, Radiation Protection, Shielding, and Waste Management; Workforce Development, Nuclear Education and Public Acceptance; Mitigation Strategies for Beyond Design Basis Events; Risk Management. Charlotte, North Carolina, USA. June 26–30, 2016. V004T10A031. ASME. https://doi.org/10.1115/ICONE24-61105
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