Numerical investigations of the coupled DEM-LBM technique with application to leakage-soil interaction due to a leaking pipe

Li, Jun (2013). Numerical investigations of the coupled DEM-LBM technique with application to leakage-soil interaction due to a leaking pipe. University of Birmingham. Ph.D.

[img]
Preview
JunLi13PhD.pdf
PDF - Accepted Version

Download (2MB)

Abstract

This thesis is motivated by developing a numerical tool, FPS-BHAM, in exploring the large-scale fluid-particle system with local interaction behaviours being captured. A blocked partitioning domain decomposition strategy with the philosophies of parallel computing and combination with a large-scale modelling technique is proposed in this thesis.

The illustration of detailed implementation of DEM-LBM, with its verification in FPS-BHAM and its validation using a pipe leakage problem, are subsequently conducted. A good parallel behaviour is achieved by applying the blocked partitioning domain decomposition strategy, which is proposed in this thesis. The DEM-DFF technique is also successfully implemented in FPS-BHAM as well. Furthermore, a combination strategy between DEM-LBM and DEM-DFF is proposed in this thesis. A good computational benefit is found to be achieved by adopting the proposed combination strategy. Finally, different behaviours between LBM and DFF during the dynamic propagation to the steady state are investigated by parametric studies.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Supervisor(s):
Supervisor(s)EmailORCID
Chan, Andrew H. C.UNSPECIFIEDUNSPECIFIED
Bridgeman, JohnUNSPECIFIEDUNSPECIFIED
Licence:
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Engineering, Department of Civil Engineering
Funders: None/not applicable
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
URI: http://etheses.bham.ac.uk/id/eprint/4016

Actions

Request a Correction Request a Correction
View Item View Item

Downloads

Downloads per month over past year