A genetic algorithm particle pairing technique for 3D velocity field extraction in holographic particle image velocimetry |
| |
Authors: | J Sheng H Meng |
| |
Institution: | (1) Program for Complex Fluid Flow Mechanical and Nuclear Engineering Department Kansas State University, Manhattan, KS 66506, USA, US |
| |
Abstract: | This research explores a novel technique, using Genetic Algorithm Particle Pairing (GAPP) to extract three-dimensional (3D)
velocity fields of complex flows. It is motivated by Holographic Particle Image Velocimetry (HPIV), in which intrinsic speckle
noise hinders the achievement of high particle density required for conventional correlation methods in extracting 3D velocity
fields, especially in regions with large velocity gradients. The GA particle pairing method maps particles recorded at the
first exposure to those at the second exposure in a 3D space, providing one velocity vector for each particle pair instead
of seeking statistical averaging. Hence, particle pairing can work with sparse seeding and complex 3D velocity fields. When
dealing with a large number of particles from two instants, however, the accuracy of pairing results and processing speed
become major concerns. Using GA’s capability to search a large solution space parallelly, our algorithm can efficiently find
the best mapping scenarios among a large number of possible particle pairing schemes. During GA iterations, different pairing
schemes or solutions are evaluated based on fluid dynamics. Two types of evaluation functions are proposed, tested, and embedded
into the GA procedures. Hence, our Genetic Algorithm Particle Pairing (GAPP) technique is characterized by robustness in velocity
calculation, high spatial resolution, good parallelism in handling large data sets, and high processing speed on parallel
architectures. It has been successfully tested on a simple HPIV measurement of a real trapped vortex flow as well as a series
of numerical experiments. In this paper, we introduce the principle of GAPP, analyze its performance under different parameters,
and evaluate its processing speed on different computer architectures.
Received: 7 September 1997/Accepted: 3 February 1998 |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|