444
Views
5
CrossRef citations to date
0
Altmetric
Research papers

A new 1D coupled hydrodynamic discrete element model for floating debris in violent shallow flows

, , , &
Pages 778-789 | Received 01 Oct 2018, Accepted 16 Sep 2019, Published online: 05 Dec 2019
 

Abstract

The effect of floating objects has so far rarely been considered in flood modelling and risk assessment, despite having significant implications for structural design in flood-prone and coastal areas. In this work, a novel two-way method is proposed to fully couple a discrete element model to a hydrodynamic model to simulate complex debris-enriched flow hydrodynamics. The adopted hydrodynamic model solves the nonlinear shallow water equations (SWEs) using a finite volume shock-capturing numerical method. After being validated against an idealized analytical test, the new coupled model is used to reproduce flume experiments of floating debris driven by dam-break waves. The numerical results agree well with the experimental measurements, demonstrating the model’s capability in simulating the complex fluid–debris interactions induced by violent shallow flows.

Additional information

Funding

This work is partly funded by the UK Natural Environment Research Council (NERC) through the UK NERC SINATRA and TENDERLY projects (grant number NE/K008781/1) and WeACT project (grant number NE/S005919/1) and the National Natural Science Foundation of China (grant number 51579090).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 203.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.