Physically-based interactive schlieren flow visualization

Brownlee, Carson; Pegoraro, Vincent; Shankar, Siddharth; McCormick, Patrick; Hansen, Charles

doi:10.1109/pacificvis.2010.5429599

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…using a 4 th order Runge-Kutta algorithm following established methods in gradient-index optics literature. [26], [27] The refraction through the lens is modelled by Snell's law and the diffraction pattern on the image sensor is modeled using a Gaussian distribution as in synthetic PIV image generation. [28], [29] The computationally intensive ray tracing process is parallelized using Graphics Processing Units (GPUs) and images rendered using this methodology display real world features such as blurring and optical aberrations which can be adjusted in a controlled manner.…”

Section: Image Generation Methodologymentioning

confidence: 99%

Dot tracking methodology for background-oriented schlieren (BOS)

2019

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We propose a dot-tracking methodology for processing Background Oriented Schlieren (BOS) images. The method significantly improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32x32 pix.) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a "correlation correction", whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy driven turbulence rendered using ray tracing simulations, and experimental images of flow in the exit plane of a converging-diverging nozzle.

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Section: Image Generation Methodologymentioning

confidence: 99%

Dot tracking methodology for background-oriented schlieren (BOS)

2019

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“…An open-source implementation of solving Fermat's equation on a GPU with a piecewise linear approximation (1st order) was provided by SchlierenRay, an artificial schlieren image rendering software developed by Brownlee et al [15] Their methodology has been extended to include higher order discretizations and integrated with a full light field-based ray tracing approach for the present application.…”

Section: Tracing Rays Through Density Gradientsmentioning

confidence: 99%

PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design

Rajendran

Bane

Vlachos

2019

Meas. Sci. Technol.

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We present an image generation methodology based on ray tracing that can be used to render realistic images of particle image velocimetry (PIV) and background oriented schlieren (BOS) experiments in the presence of density/refractive index gradients. This methodology enables the simulation of aero-thermodynamics experiments for experiment design, error, and uncertainty analysis. Images are generated by emanating light rays from the particles or dot pattern, and propagating them through the density gradient field and the optical elements, up to the camera sensor. The rendered images are realistic, and can replicate the features of a given experimental setup, like optical aberrations and perspective effects, which can be deliberately introduced for error analysis. We demonstrate this methodology by simulating a BOS experiment with a known density field obtained from direct numerical simulations of homogeneous buoyancy driven turbulence, and comparing the light ray displacements from ray tracing to results from BOS theory. The light ray displacements show good agreement with the reference data. This methodology provides a framework for further development of simulation tools for use in experiment design and development of image analysis tools for PIV and BOS applications. An implementation of the proposed methodology in a Python-CUDA program is made available as an open source software for researchers.

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“…al. [7] Their methodology has been extended to include higher order approximations and integrated with a full light field-based ray tracing approach for the present application.…”

Section: Tracing Rays Through Density Gradientsmentioning

confidence: 99%

PIV/BOS Synthetic Image Generation in Variable Density Environments for Error Analysis and Experiment Design

Rajendran

Singh

Giarra

et al. 2017

55th AIAA Aerospace Sciences Meeting

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We present an image generation methodology based on ray tracing that can be used to render realistic images of Particle Image Velocimetry (PIV) and Background Oriented Schlieren (BOS) experiments in the presence of density/refractive index gradients. This methodology enables the simulation of aero-thermodynamics experiments for experiment design, error, and uncertainty analysis. Images are generated by emanating light rays from the particles or dot pattern, and propagating them through the density gradient field and the optical elements, up to the camera sensor. The rendered images are realistic, and can replicate the features of a given experimental setup, like optical aberrations and perspective effects, which can be deliberately introduced for error analysis. We demonstrate this methodology by simulating a BOS experiment with a known density field obtained from direct numerical simulations (DNS) of homogeneous buoyancy driven turbulence, and comparing the light ray displacements from ray tracing to results from BOS theory. The light ray displacements show good agreement with the reference data. This methodology provides a framework for further development of simulation tools for use in experiment design and development of image analysis tools for PIV and BOS applications. An implementation of the proposed methodology in a Python-CUDA program is made available as an open source software for researchers.

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Physically-based interactive schlieren flow visualization

Cited by 6 publications

References 19 publications

Dot tracking methodology for background-oriented schlieren (BOS)

Dot tracking methodology for background-oriented schlieren (BOS)

PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design

PIV/BOS Synthetic Image Generation in Variable Density Environments for Error Analysis and Experiment Design

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