A study of local scouring near wall-mounted cylinders with the aid of particle-resolved direct numerical simulations

• Applicant: Professor Dr. Markus Uhlmann
• Subject Area: Geotechnics, Hydraulic Engineering
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 545951052

Local scouring, i.e. the enhanced flow-induced erosion of sediment grains from the bed of a water body in the vicinity of hydraulic structures, represents one of the main causes for failures of bridge piers, submarine pipelines or offshore wind turbines. There is hence a large interest in reliable predictions of the sediment bed evolution over the lifetime of hydraulic buildings. The tools at hand to predict such scour processes, however, still feature a considerable amount of uncertainty, since the complex interaction between the turbulent flow, the hydraulic structure and the erodible sediment bed is even nowadays not fully understood. Laboratory experiments have helped to gain insight into many aspects of scouring, but simultaneous time- and space-resolved measurements of the turbulent flow dynamics and of the sediment motion remain a formidable challenge. Past numerical simulations of local scouring, on the other hand, have been computationally feasible only for simplified systems, the vast majority of them not resolving the flow around individual mobile sediment grains. In the planned project, we will make use of particle-resolved direct numerical simulation techniques to investigate scouring near a wall-mounted cylinder from first principles. We will address open questions, such as the cause for the transition from a wake scour pattern to a horseshoe-vortex scour pattern as the Shields number is increased and the effect of passing bedforms upon scouring dynamics in the live-bed regime. The newly generated high-fidelity database is expected to further our current understanding of the physical mechanisms driving local scouring, which should be of significant value for the improvement of existing scour prediction techniques used in engineering practice.

• DFG Programme: Research Grants
• Co-Investigator: Dr.-Ing. Markus Scherer