five

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

收藏
DataCite Commons2025-12-18 更新2025-04-16 收录
下载链接:
https://purr.purdue.edu/publications/3560/1
下载链接
链接失效反馈
官方服务:
资源简介:
<p>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.</p> <p> </p>
提供机构:
Purdue University Research Repository
创建时间:
2020-08-12
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作