An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units

Autor: Ali Shirinzad, Khodr Jaber, Kecheng Xu, Pierre E. Sullivan
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Fluids, Vol 8, Iss 11, p 285 (2023)
Druh dokumentu: article
ISSN: 2311-5521
DOI: 10.3390/fluids8110285
Popis: Particle Image Velocimetry (PIV) is a widely used experimental technique for measuring flow. In recent years, open-source PIV software has become more popular as it offers researchers and practitioners enhanced computational capabilities. Software development for graphical processing unit (GPU) architectures requires careful algorithm design and data structure selection for optimal performance. PIV software, optimized for central processing units (CPUs), offer an alternative to specialized GPU software. In the present work, an improved algorithm for the OpenPIV–Python software (Version 0.25.1, OpenPIV, Tel Aviv-Yafo, Israel) is presented and implemented under a traditional CPU framework. The Python language was selected due to its versatility and widespread adoption. The algorithm was also tested on a supercomputing cluster, a workstation, and Google Colaboratory during the development phase. Using a known velocity field, the algorithm precisely captured the time-average flow, momentary velocity fields, and vortices.
Databáze: Directory of Open Access Journals