A GENERALIZED OPTIMIZATION METHOD FOR DOUBLE PULSED PARTICLE IMAGE VELOCIMETRY

A new method is presented which allows for the optimisation of a doubl e pulsed particle image velocimetry (PN) system given a priori informa tion on the dynamic range and velocity gradients at a chosen local reg ion in the flow. The method is developed from considerations of the wo rst case signal-re-noise characteristics corresponding to the autocorr elation function obtained from this region. Optimisation permits the r iser to define a window of operation for a PIV system which, providing a minimum level of seeding is present, will ensure that from a series of experiments on average a minimum of 50% valid vectors will be obta ined from the chosen region. Validation of the method was carried out by using a Monte Carlo simulation based on the theoretical model. Opti misation and Monte Carlo prediction were shown to agree to within 1.5% . (C) 1997 Elsevier Science Ltd.