Bedform Evolution Under a Steady Shear Flow: Application to Deep Marine Settings

Abstract

The pathways of sediment gravity flows in deep sea basins are often characterised by the development of large-scale bedforms. Predicting the dynamics of turbidity currents overpassing self-generated or inherited bedforms is key to understanding particle erosion/deposition and thus flow run out and deposit location. Although erosion and suspension are dependent on flow turbulence, measuring the turbulent flow field around bedforms, in particular close to the wall region, is not practical. Here we describe the use of numerical methods to enable study of these processes. On the assumption that the lower half of turbidity currents (up to the velocity maximum) is well approximated by shear layer flow, this study focuses on using computational fluid dynamics approaches to (i) model the two-way coupling between the shear flow and the bed, (ii) build an associated morphodynamical bed evolution model, and (iii) link bedform evolution to evolution of the overpassing flow. Here, steady state flow conditions were assumed, approximating to quasi-steady turbidity current body flow. The computational grid system is deformed in response to the change in bed level with a logarithmic mesh stiffness algorithm close to lower boundary, coupled with periodic re-meshing. An algebraic slip model has been employed to calculate the relative motion of sediments and water in the liquid mixture. Initial simulations are conducted for a turbulent shear flow (Re ≈10⁶) over low-angled periodic symmetric dunes to investigate the inherent system evolution. Preliminary results indicate that the bedforms eventually evolve to reach a quasi-equilibrium condition, in which they change cyclically. The computed substrate topography is analysed and compared with published field data. The mutual adaption of flow and bedforms dictates a change in the energy budget of the flow, i.e. with increasing frictional drag potential energy is gained, through decreased flow stratification, whilst kinetic energy is lost, through overcoming bed roughness. This adaption of the flow energy budget is crucial to understanding how self-generated or inherited bedforms may control flow run out length.

AAPG Datapages/Search and Discovery Article #90216 ©2015 AAPG Annual Convention and Exhibition, Denver, CO., May 31 - June 3, 2015