Incorporating grain-scale processes in macroscopic sediment transport models: A review and perspectives for environmental and geophysical applications
Research output: Contribution to journal › Review article › Contributed › peer-review
Contributors
Abstract
Sediment transport simulations face the challenge of accounting for vastly different scales in space and time that cannot be tackled by a unifying approach. Instead, processes are subdivided into a microscale at the particle level, a mesoscale of a large finite number of particles, and a macroscale that computes the sediment motion by means of advection–diffusion equations. The different processes occurring at different scales are simulated using different computational approaches. However, modeling sediment transport at multiple scales with high fidelity requires proper closure arguments that interconnect the different processes. Ultimately, we will need efficient macroscale models that can readily be utilized for engineering practices covering, e.g., entire river reaches or even estuaries. In recent years, highly resolved simulations have become a valuable tool to provide these closure arguments for sediment transport models on the continuum scale. In this paper, we will review the most relevant approaches to simulate sediment transport at different scales and discuss the perspectives of four most promising modeling techniques that can help to improve sediment transport modeling. On the grain scale, these enhancements include the impact of mechanical properties of cohesion and biocohesion as well as the shape of non-spherical sediment grains on fluid–particle and particle–particle interactions. On larger scales, we review constitutive equations for the macroscopic rheological behavior of sediment beds that may decouple the relevant scales for fluid and sediment motion. Furthermore, we discuss machine learning strategies as an efficient means to derive scaling arguments across multiple scales.
Details
Original language | English |
---|---|
Pages (from-to) | 2023–2050 |
Number of pages | 28 |
Journal | Acta mechanica |
Volume | 232 |
Issue number | 6 |
Publication status | Published - 19 Jun 2021 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
Scopus | 85103163017 |
---|