PreprintCC BY-SA 4.0arXiv
A Physics-Informed, PIV-Based Method for Surface Pressure Reconstruction
Abstract
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.
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BibTeX
@misc{daliri2026physicsinformed,
title = {{A Physics-Informed, PIV-Based Method for Surface Pressure Reconstruction}},
author = {Abbas Daliri and Fulvio Scarano},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.30432},
eprint = {2608.30432},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.30432},
note = {CC BY-SA 4.0},
}
RIS
TY - UNPB
TI - A Physics-Informed, PIV-Based Method for Surface Pressure Reconstruction
AU - Abbas Daliri
AU - Fulvio Scarano
PY - 2026
DA - 2026/08/31
PB - arXiv
DO - 10.48550/arxiv.2608.30432
UR - https://arxiv.org/abs/2608.30432
AB - 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.
ER -