Nearshore Bedload Sediment Transport
Thomas G. Drake
Award #: N00014-98-1-0474 (AASERT) http://www.meas.ncsu.edu/faculty/drake/drake.html LONG-TERM GOALS To understand the physics of sediment transport by waves and currents and to use that understanding to predict the evolution of nearshore bathymetry given the nearshore fluid velocity and acceleration fields. A secondary goal is to interpret the environment of deposition and the offshore wave climate from the sedimentary record. OBJECTIVES Objectives are to theoretically describe and numerically
... model the substantial effects of fluid acceleration on sheet flow bedload transport in the surf zone, to determine the dominant processes governing grain segregation by size and density during transport, to generate computer simulation models for evolution of nearshore morphology and other grain-scale sedimentary processes, and to suggest field and laboratory experiments needed to advance understanding of sediment transport processes. APPROACH Discrete particle models for bedload transport processes describe the motion of individual sediment grains subjected to fluid and body forces by integrating F=ma at small time steps. Our models predict transport rates, dispersion and sorting of grains having a distribution of sizes and densities. They are well-suited for describing transport processes as a function of grain size in the swash and surf zones, where variations in particle size (as well as other properties) may be large. Description of such variations does not merely refine existing models; for instance, large and small grains in the nearshore have been observed to move in opposite directions. The model is also well-suited for studies of other sea-bed phenomena, for instance, the penetration of impactors into the sea floor as described below. We continue to address fundamental problems concerning fluid-particle interactions within the discrete-particle modeling framework. Cellular automata models use sediment transport relationships codified from discrete-particle models to extend those calculations to longer length and time scales, in effect coarser-graining the particle-by particle models. Our work using cellular automata models is still in its exploratory stages and shows considerable promise.