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TU Braunschweig Leichtweiß-Institute for Hydraulic Engineering and Water Resources / Division of Hydraulic Engineering and River Morphology

Country: Germany

TU Braunschweig Leichtweiß-Institute for Hydraulic Engineering and Water Resources / Division of Hydraulic Engineering and River Morphology

1 Projects, page 1 of 1
  • Funder: French National Research Agency (ANR) Project Code: ANR-21-CE30-0050
    Funder Contribution: 206,640 EUR

    Understanding sediment transport in rivers, lakes and along the ocean floor is key to sustainable management of open water bodies and aquatic ecosystems. Prominent processes are river morphodynamics, turbidity currents, and tsunamis running up a beach. Predicting and managing these processes requires in-depth knowledge of the rheology to describe macroscopic properties of the fluid-sediment mixture. However, the constitutive laws to describe these processes have so far mostly been based on studies of dense suspensions of neutrally buoyant particles in either highly viscous shearing flows or at much larger flow rates where inertial effects play the dominant role. The transition between the two regimes, however, has not been investigated in a systematic manner yet, and, hence, remains only poorly understood. This may be problematic for the predictive modeling of situations that are more relevant for engineering practices and natural flows involving sediment transport. This transitional regime will be the focus of the present study and our objectives are twofold: First, the French and German partners aim to conduct a joint complementary campaign of state-of-the art sediment transport experiments and numerical simulations, respectively. The campaign will yield highly-resolved data of laminar pressure-driven shearing flows across an idealized sediment bed for a wide range of Stokes numbers as the ratio of competing inertial and viscous effects. In a second step, these data will be used to improve existing two-phase modeling approaches that have become popular for macroscopic sediment transport models.

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