Shirinzad, A.; Jaber, K.; Xu, K.; Sullivan, P.E. An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units. Fluids2023, 8, 285.
Shirinzad, A.; Jaber, K.; Xu, K.; Sullivan, P.E. An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units. Fluids 2023, 8, 285.
Shirinzad, A.; Jaber, K.; Xu, K.; Sullivan, P.E. An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units. Fluids2023, 8, 285.
Shirinzad, A.; Jaber, K.; Xu, K.; Sullivan, P.E. An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units. Fluids 2023, 8, 285.
Abstract
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 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, monetary velocity fields, and vortices.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
