Numerical Background-Oriented Schlieren for Phase Reconstruction and Its Potential Applications

This study presents a comprehensive numerical framework for Background-Oriented Schlieren (BOS) to systematically evaluate its performance and reconstructive capabilities under complex flow conditions. This framework integrates two stages: forward modeling, using ray tracing to simulate image degrad...

Full description

Saved in:
Bibliographic Details
Main Authors: Shiwei Liu, Yichong Ren, Haiping Mei, Zhiwei Tao, Shuran Ye, Xiaoxuan Ma, Ruizhong Rao
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Photonics
Subjects:
Online Access:https://www.mdpi.com/2304-6732/12/7/626
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This study presents a comprehensive numerical framework for Background-Oriented Schlieren (BOS) to systematically evaluate its performance and reconstructive capabilities under complex flow conditions. This framework integrates two stages: forward modeling, using ray tracing to simulate image degradation, and inverse processing, using optical flow and a conjugate gradient algorithm to extract displacements and reconstruct phase information. This method is first validated using turbulent flow fields in the Johns Hopkins Turbulence Database, where the reconstructed phase screens closely match the original data, with relative errors below 4% and structural similarity indices above 0.75 in all cases, providing a possible restoration method for degraded flow field images. It is then applied to shock wave fields with varying Mach numbers; this method achieves meaningful reconstruction at short ranges but fails under long-range imaging due to severe wavefront distortions. However, even in degraded conditions, the extracted optical flow fields preserve structural features correlated with the underlying shock patterns, indicating potential for BOS-based target recognition. These findings highlight both the capabilities and limitations of BOS and suggest new pathways for extending its use beyond traditional flow visualization.
ISSN:2304-6732