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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 107
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING
Edited by:
Paper 36

A Study on the Performance of Parallel Solvers for Coupled Simulations of Partially Saturated Soils in Tunnel Engineering Applications

G. Bui and G. Meschke

Institute for Structural Mechanics, Ruhr University Bochum, Germany

Full Bibliographic Reference for this paper
G. Bui, G. Meschke, "A Study on the Performance of Parallel Solvers for Coupled Simulations of Partially Saturated Soils in Tunnel Engineering Applications", in , (Editors), "Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 36, 2015. doi:10.4203/ccp.107.36
Keywords: partially saturated soils, shield tunnelling, block preconditioning.

Summary
Mechanized tunnelling in soft ground is an intricate process which involves various interacting components such as the ground, the tunnel boring machine, the support measures such as the face support and the tail-void grouting. These components and their mutual interactions need to be considered in numerical simulations. To discretize this spatial-temporal system, a LBB-compatible mixed formulation is used for space discretization and the generalized-alpha method for temporal discretization. This results in an ill-conditioned system which poses substantial difficulties for iterative solvers to converge. In this paper, a linear solver for a distributed computing environment is presented to solve the resulting discretized system. In the numerical benchmark, a direct solver employing MPI is tested to investigate the weak scalability and performance. Also, an iterative solver with standard ILU preconditioner and alternatively, block preconditioner is investigated. The objective is to choose the best solver configuration for shield tunnelling simulations for various problem sizes. The benchmark is run on a local small cluster for easy customization and optimization for job-run configuration.

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