The PIV Course 2025 will take place at DLR in Göttingen from March 17th to 21st, 2025

A significant feature of PIV and LPT is that a reliable basis of experimental flow field data is provided for direct comparison with numerical calculations and hence, for validation of flow simulation codes. During the last years an increasing number of scientists have started to utilize the PIV and LPT techniques to investigate the instantaneous structure of velocity fields in various areas of fluid mechanics. A large number of different approaches for the recording and evaluation of tracer particle images have been described in literature. This course, which is the 32nd Course on PIV since 1993 organized by DLR, will mainly concentrate on those aspects of the theory of PIV and LPT relevant to applications. Besides giving lectures on the fundamental aspects, special emphasis is placed on the presentation of practical and reliable solutions of problems which are faced during the implementation of these techniques in wind tunnels and other test facilities. During practice the participants will have the opportunity to carry out the recording and the evaluation of PIV and LPT images by themselves in small groups. Matured developments of the PIV technique such as Stereo PIV, Time Resolved PIV, Micro-PIV and Shake-The-Box (STB) as well as other 3D(t)-PIV/3D-LPT techniques (tomographic PIV, PTV) will be discussed and demonstrated.

 

The main interest of today’s research in fluid mechanics is more and more directed to problems where unsteady and separated flows are predominant. For investigations of flow fields with pronounced spatial structures and/or rapid temporal or spatial changes (transition from laminar to turbulent flow, coherent structures, pitching airfoils in transonic flows with shocks, rotors, test facilities with short run time, etc.) optical experimental techniques, such as Particle Image Velocimetry (PIV) and Lagrangian Particle Tracking (LPT) are required which allow to capture the flow velocity of large flow fields instantaneously.

Example: Flow of a turbulent boundary layer over a backward facing ramp using STB and FlowFit data assimilation

Flow of a turbulent boundary layer over a backward facing ramp visualized by iso-contour surfaces of Q-value color coded by streamwise velocity measured by STB and subsequent FlowFit data assimilation