Bridge Pressure Flow Scour at Clear Water Threshold Condition

Bridge pressure flow scour at clear water threshold condition is studied theoretically and experimentally.The flume experiments reveal that the measured scour profiles under a bridge are more or less 2-dimensional;all the measured scour profiles can be described by two similarity equations,where the horizontal distance is scaled by the deck width while the local scour by the maximum scour depth;the maximum scour position is located just under the bridge about 15% deck width from the downstream deck edge;the scour begins at about one deck width upstream the bridge while the deposition occurs at about 2.5 deck widths downstream the bridge;and the maximum scour depth decreases with increas-ing sediment size,but increases with deck inundation.The theoretical analysis shows that:bridge scour can be divided into three cases,i.e.downstream unsubmerged,partially submerged,and totally submerged.For downstream unsubmerged flows,the maximum bridge scour depth is an open-channel problem where the conventional methods in terms of critical velocity or bed shear stress can be applied;for partially and totally submerged flows,the equilibrium maximum scour depth can be described by a scour and an inundation similarity number,which has been confirmed by experiments with two decks and two sediment sizes.For application,a design and field evaluation procedure with examples is presented,including the maximum scour depth and scour profile.

3D Surface Reconstruction of Coarse Aggregate Particles from Occlusion-Free Multi-View Images

Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.