An effective method for comparing the turbulence intensity from LDA measurements and CFD predictions within a ship propeller jet

The mean velocity and turbulence intensity are the two main inputs to investigate the ship propeller induced seabed scouring resulting from a vessel is manoeuvring within a port where the underkeel clearances are low. More accurate data including the turbulence intensity is now available by using the laser doppler anemometry (LDA) measurement system and computational fluid dynamics (CFD) approach. Turbulence intensity has a loose definition, which is the velocity fluctuation as the root mean square (RMS) referenced to a mean flow velocity. However, the velocity fluctuation and mean velocity can be the overall value includingx, y and z directions or the value of a single component. LDA and CFD results were obtained from two different acquisition systems (Dantec LDA system and Fluent CFD package) and therefore the outputs cannot be compared directly. An effective method is proposed for comparing the turbulence intensity between the experimental measurements and the computational predictions within a ship propeller jet. The flow patterns of turbulence intensity within a ship propeller jet are presented by using the LDA measurements and CFD results from turbulence models of standard k-e, RNG k-e, realizable k–e, standard k–?, SST k–?and Reynolds stresses.

Multicamera sport player tracking with Bayesian estimation of measurements

We propose a complete application capable of tracking multiple objects in an environment monitored by multiple cameras. The system has been specially developed to be applied to sport games, and it has been evaluated in a real association-football stadium. Each target is tracked using a local importance-sampling particle filter in each camera, but the final estimation is made by combining information from the other cameras using a modified unscented Kalman filter algorithm. Multicamera integration enables us to compensate for bad measurements or occlusions in some cameras thanks to the other views it offers. The final algorithm results in a more accurate system with a lower failure rate. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3114605]