基于有限体积的耦合与分离降阶模型在参数化域不可压缩流动中的比较研究
A Comparative Study of Finite-Volume-based Coupled and Segregated Reduced-Order Models for Incompressible Flows in Parametrized Domains
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中文总结 AI 辅助
本文比较了参数化域中不可压缩流动的耦合与分离降阶模型，发现耦合方法收敛快但需更多自由度，分离SIMPLE算法在低维空间精度更高但收敛慢。
中文摘要 AI 辅助
本研究对几何参数化域内不可压缩流体动力学中应用的降阶模型（ROMs）进行了比较分析。研究并比较了两种不同的降阶求解策略：一种单片耦合求解器与一种基于SIMPLE的分离算法。它们的性能在两个稳态二维基准案例上进行了评估：顶盖驱动空腔流动和圆柱障碍物绕流。两种算法在流场评估和气动系数预测方面进行了比较。计算结果突显了精度与数值效率之间的基本权衡。一方面，经过适当的supremizers富集后，耦合方法保证了更快的收敛速度，尽管需要更多的自由度。另一方面，分离的SIMPLE算法在降阶空间维度较低时尤其能产生更优的重建精度，但以较慢的收敛速率为代价。
英文摘要
This work presents a comparative analysis of Reduced-Order Models (ROMs) applied to incompressible fluid dynamics within geometrically parametrized domains. Two distinct reduced-order solution strategies are investigated and compared: a monolithic coupled solver and a segregated SIMPLE-based algorithm. Their performance is assessed on two steady, two-dimensional benchmark cases: a lid-driven cavity flow and a flow past a cylindrical obstacle. The two algorithms are compared in terms of fields evaluation and aerodynamic coefficients prediction. The computational results highlight a fundamental trade-off between accuracy and numerical efficiency. On the one hand, after an opportune supremizers enrichment, the coupled approach guarantees a faster convergence, despite the need of a larger number of degrees of freedom. On the other hand, the segregated SIMPLE algorithm yields superior reconstruction accuracy, particularly for lower-dimensional reduced spaces, at the cost of a slower convergence rate.
发表机构
- Mathlab, Mathematics area, SISSA（数学实验室，数学区域，SISSA）
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