Abstract Convolutional neural networks (CNNs) offer an alternative to the image cross-correlation methods used in particle velocimetry (PIV) reconstruct fluid velocity field from experimental recording. Despite flexibility of CNNs, accuracy and robustness standard processing remains unsurpassed for general PIV data. As CNNs are non-linear typically entail up millions trainable parameters, they ...

in this work, result of experimental investigation on interaction of fuel spray generated by a swirled type injector, with air motion in a prototype cylinder are presented. experiments were carried out by planar imaging and particle image velocimetry (piv) techniques in order to provide information about the spray structure evolution and instantaneous velocity distribution of air motion and fue...

Particle Image Velocimetry (NV) has been used successfully for measuring instantaneous two dimensional velocity fields. Analyzing PIV images involves matching particle images capwred sequentially. In the usual practice, correlation (autoor cross-correlation) is used to find the displacement (hence velocity) of the particles within a large number of small "interrogation areas" in the field of vi...