کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4925443 | 1431398 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Bubble tracking analysis of PWR two-phase flow simulations based on the level set method
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Bubbly flow is a common natural phenomenon and a challenging engineering problem yet to be fully understood. More insights from either experiments or numerical simulations are desired to better model and predict the bubbly flow behavior. Direct numerical simulation (DNS) has been gaining renewed interests as an attractive approach towards the accurate modeling of two-phase turbulent flows. Though DNS is computationally expensive, it can provide highly reliable data for model development along with experiments. The ever-growing computing power is also allowing us to study flows of increasingly high Reynolds numbers. However, the conventional simulation and analysis methods are becoming inadequate when dealing with such 'big data' generated from large-scale DNS. This paper presents our recent effort in developing the advanced analysis framework for two-phase bubbly flow DNS. It will show how one can take advantage of the 'big data' and translate it into in-depth insights. Specifically, a novel bubble tracking method has been developed, which can collect detailed two-phase flow information at the individual bubble level. Due to the importance of subcooled boiling phenomenon in pressurized water reactors (PWR), the bubbly flow is simulated within a PWR subchannel geometry with the bubble tracking capability. It has been demonstrated that bubble tracking method significantly improves the data extraction efficiency for level-set based interface tracking simulations. Statistical analysis was introduced to post-process the recorded data to study the dependencies of bubble behavior with local flow dynamics.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Engineering and Design - Volume 323, November 2017, Pages 68-77
Journal: Nuclear Engineering and Design - Volume 323, November 2017, Pages 68-77
نویسندگان
Jun Fang, Igor A. Bolotnov,