This proposal develops a computational model for simulating numerous interactive particles in a fluid at various Reynolds numbers (Re). This model is novel in the computational efficiency and accuracy. It assimilates interdisciplinary knowledge and strengths of Eulerian and Lagrangian approaches. It uses one fixed mesh to resolve the fluid field with spectral accuracy and to track all particles in a Lagrangian reference. It avoids (1) fine mesh to resolve the boundary layers of particles, (2) repetitive re-meshing as particles move, 3) multi-gridding, and (4) many stiff constraints on the fluid field. Inherited the accuracy from its previous particle-resolving model for flow around spheres and spectral element methods, this model is capable of capturing drag forces of particles at moderate to high Re with the accuracy close to a direct numerical simulation. Since only one kernel function per particle is needed, this model simulates a flow of large numbers of particles with only a small extra percentage of the time for solving only the fluid phase and is one to two orders faster than a direct numerical simulation. This model provides a viable method for studying particulate flows involving so many particles that other particle-resolving methods could be cumbersome. Large-scale simulation of 100,000 to 1,000,000 sediment grains will be conducted in a wide range of Re to infer macro-scale parameters significant to coastal field application and coastal erosion.
More than 53% of the U.S. population lives in coastal regions, which are home to a wealth of natural and economic resources. Due to collective impacts of sea level rise, severe storms, and pervasive anthropogenic alterations of rivers and the coast over the past century, coastal regions are undergoing fast erosion. Mitigating coastal erosion requires improved capability of modeling sediment dynamics in rivers, estuaries and coastal seas in response to the detriment due to combined natural processes and anthropogenic activities. In addition to coastal and environmental engineering, the conjugate interactions of a fluid and large numbers of immersed particles are of vital significance to mechanical engineering, chemical engineering, combustion and petroleum processing etc. The proposed model provides an advanced simulation tool for many areas in science and engineering, and especially contributes to predicting sediment transport, mitigating coastal erosion, and improving environmental management. Knowledge in this multidisciplinary research will be used to train graduate students. The success of this project will accelerate our knowledge in computational particulate fluid flows and help better understand the mechanisms of coastal erosion. The discovery of this research will help prevent coastal erosion and protect the coastal inhabitants and infrastructure.
