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一个基于压力的溶解器的分离的减少顺序模型,用于乱的可压缩流
Matteo Zancanaro1, Valentin Nkana Ngan1, Giovanni Stabile2
1Mathematics Area, mathLab, SISSA, via Bonomea 265, I-34136 Trieste, Italy.
概括
这项研究引入了一种新的减少顺序建模框架,用于流式可压缩流. 它实现了高雷诺兹和马赫数的准确预测,独立于特定的流模型.
科学领域:
- 流体动力学 流体动力学
- 计算科学 计算科学
- 航空航天工程 航空航天工程
背景情况:
- 流压缩流的高保真模拟在计算上是昂贵的.
- 由于加勒金投影的局限性,现有的减少顺序模型往往难以准确.
- 分离式溶解器在全序流量解决方案中很常见,但与经典的减少方法有所不同.
研究的目的:
- 为流式可压缩流量开发一个减少顺序的建模框架.
- 创建一个模型,提供与高保真场相比的准确解决方案.
- 在减少顺序建模中实现流模型独立性.
主要方法:
- 使用分离的减少顺序算法进行流量分辨率.
- 采用混合方法,将纳维埃-斯托克斯投影与数据驱动的粘度近似计算相结合.
- 应用神经网络或插值用于粘度场预测.
主要成果:
- 该框架准确地预测了高雷诺兹数和马赫数流的解决方案.
- 达到接近完全顺序流量场的准确性.
- 证明独立于特定的旋粘度流模型.
结论:
- 拟议的减少顺序建模框架为流压缩流分析提供了一个高效和准确的替代方案.
- 混合方法有效地解决了在减少顺序上下文的流建模的挑战.
- 这种方法可以对复杂的空气动力学场景进行可靠的预测.
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