An international travel proposal to NSF requesting support of the PI to attend the 13th International Symposium on Particle Image Velocimetry

旅行资金将使PI能够应研讨会主席的邀请参加第13届粒子图像测速国际研讨会（ISPIV 2019, 7月22日至24日，德国慕尼黑），并发表具有重要科学意义的口头报告。口头报告和会议论文的题目是？从基于piv的压力梯度到全向积分法积分压力的误差传播？报告首次对误差传播特性进行了全面的理论分析和相应的数值和实验验证结果。全方位集成方法？与传统的泊松方程重构方法相比，该方法在数据精度方面具有更好的性能。出差支持将有助于证明和建立？平行射线全向积分法？用泊松方程方法从噪声嵌入实验数据中重建压力。此外，由于在科学和工程实践中有许多场合需要使用泊松方程从保守向量场解标量势，例如，从其相应的梯度重建温度或波前，因此？平行射线全向积分法？很容易适用于那些一般场合。因此，这种新的压力重建方法不仅将对流体学界产生持久的影响，而且在科学和工程应用方面也将有更多的受众。这个项目的目标是证明和建立？平行射线全向积分法？在基于噪声的实验数据压力重建中，采用泊松方程方法。表征PIV压力重建方法的准确性对于理解这些方法的能力和局限性至关重要。不幸的是，直到PI在ISPIV 2019上提出口头报告之前，还没有理论分析可以用于表征从测量压力梯度到重建压力场的误差传播的全方位积分方法。PI在ISPIV 2019上提出的报告和论文旨在填补这一空白，并根据理论分析、数值模拟和实验数据，帮助解决为什么全向方法比传统泊松方程性能更好的问题。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Travel funds will enable the PI, upon invitation by the symposium chair, to participate in the 13th International Symposium on Particle Image Velocimetry (ISPIV 2019, July 22-24, Munich, Germany) and deliver an oral presentation of significant scientific importance. The oral presentation and the conference paper titled ?Error propagation from the PIV-based pressure gradient to the integrated pressure by the omni-directional integration method? reports for the first time a comprehensive theoretical analysis and the corresponding numerical and experimental validation results for error propagation characteristics of the ?omni-directional integration method?, which is shown to have better performance in data accuracy in comparison with the conventional Poisson equation reconstruction approach. The travel support will help the effort in proving and establishing the advantage of the ?parallel ray omni-directional integration method? over the conventional Poisson equation approach for pressure reconstruction from noise embedded experimental data. Moreover, since there are numerous occasions in science and engineering practice that require solution of a scalar potential from a conservative vector field using Poisson equation, e.g., the reconstruction of temperature or wavefront from their corresponding gradients, the ?parallel ray omni-directional integration method? is readily applicable to those generic occasions. Thus, the new pressure reconstruction method will not only bring lasting impact to the fluids community, but also to a much larger audience in science and engineering applications as well.The goal of this project is to prove and establish the advantage of the ?parallel ray omni-directional integration method? over the conventional Poisson equation approach in pressure reconstruction from noise embedded experimental data. Characterization of the accuracy of the PIV pressure reconstruction methods is of critical importance in understanding the capabilities and limitations of these methods. Unfortunately, until the proposed oral presentation by the PI to be delivered at ISPIV 2019, there is no theoretical analysis available for the omni-directional integration method that characterizes the error propagation from the measured pressure gradient to the reconstructed pressure field. The proposed presentation and paper by the PI at ISPIV 2019 intends to fill the gap, and help settle the question about why the omni-directional method has better performance over the conventional Poisson equation based on theoretical analysis, numerical simulation and experimental data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.