发表机构
Delft University of Technology（代尔夫特理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出结合最小二乘优化与物理约束的PIV表面压力重构方法，引入标准差加权函数与全局约束，使近前缘重构误差降低三分之一，与压力测孔数据吻合度好。
AI 中文摘要
本文提出一种基于PIV的物理信息表面压力重构方法，该方法将最小二乘优化与局部及全局物理约束相结合；在优化过程中引入表面法向压力梯度的标准差作为具有物理意义的加权函数，还引入全局物理约束以重构吸力区外的表面压力。结果表明，该方法与压力测孔数据吻合度极高，近前缘处表面压力重构误差降低了三分之一。
英文摘要
A physics-informed method for PIV-based surface pressure reconstruction that combines least-squares optimization with both local and global physical constraints is proposed. The standard deviation of the surface--normal pressure gradient is introduced as a physically meaningful weighting function in the optimization process. Moreover, a physical global constraint is also introduced to reconstruct surface pressure outside the suction region. The results show very good agreement with data obtained from pressure taps. Near the leading edge, the surface pressure reconstruction error has been reduced by one-third.
