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Porous hydraulic structures, such as Large Woody Debris (LWD) and Engineered Log Jams (ELJs), play a very important role in erosion control and habitation conservation in rivers. Previous experimental research has shed some light on the flow and sediment dynamics through and around porous structures. It was found that the scour process is strongly dependent on porosity. Computational models have great value in revealing more details of the processes which are difficult to capture in laboratory experiments. For example, previous computational modeling work has shown that the level of resolution of the complex hydraulic structures in computer models has great effect on the simulated flow dynamics. The less computationally expensive porosity model, instead of resolving all geometric details, can capture the bulk behavior for the flow field, especially in the far field. In the near field where sediment transport is most intensive, the flow result is inaccurate. The way in which this error is translated to the sediment transport results is unknown. This work aims to answer this question. More specifically, the suitability and limitations of using a porosity model in simulating scour around porous hydraulic structures are investigated. To capture the evolution of the sediment bed, an immersed boundarymore »method is implemented. The computational results are compared against flume experiments to evaluate the performance of the porosity model.« less

Characterization of the accuracy of the pressure reconstruction methods is of critical importance in understanding their capabilities and limitations. This paper reports for the first time a comprehensive theoretical analysis, numerical simulation and experimental validation of the error propagation characteristics for the omni-directional integration method, which has been used for pressure reconstruction from the PIV measured pressure gradient. The analysis shows that the omni-directional integration provides an effective mechanism in reducing the sensitivity of the reconstructed pressure to the random noise imbedded in the measured pressure gradient. Both the numerical and experimental validation results show that the omni-directional integration methods, especially the rotating parallel ray method, have better performance in data accuracy than the conventional Poisson equation approach in reconstructing pressure from noise embedded experimental data.