Shock-wave imaging by density recovery from intensity measurements

Area of Science:

• Fluid dynamics
• Optical diagnostics
• Computational physics

Background:

• Quantitative density estimation is crucial for analyzing high-speed compressible flows.
• Optical methods offer non-intrusive measurement capabilities for flow fields.
• Wavefront distortion analysis provides a pathway to infer flow properties.

Purpose of the Study:

• To develop and validate a novel optical method for quantitative density variation estimation in high-speed flows.
• To assess the performance of iterative algorithms for wavefront and refractive index recovery.
• To visualize and analyze shock-wave-induced flow fields using the developed technique.

Main Methods:

• Utilizing light as an interrogating tool to measure wavefront distortions induced by flow density gradients.
• Employing iterative algorithms (Gauss-Newton and ensemble Kalman filter) to recover wavefront phase and refractive index distributions.
• Applying ray tomography to reconstruct density fields from recovered phase information.
• Conducting experiments in a shock-tunnel facility for validation.

Main Results:

• Quantitative visualization of shock-wave-induced flow fields was achieved.
• Reconstructed density cross-sections were obtained and compared with computational fluid dynamics (CFD) results.
• Iterative algorithms demonstrated superior performance compared to methods based on the transport-of-intensity equation.
• The stochastic (ensemble Kalman filter) iterative scheme showed better results than the deterministic (Gauss-Newton) method.

Conclusions:

• The developed light-based iterative method provides accurate quantitative estimation of density variations in high-speed flows.
• Stochastic iterative algorithms are particularly effective for reconstructing flow density fields.
• The technique offers a valuable tool for flow field analysis and validation of CFD models.