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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 106
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by:
Paper 252
An Effective, Robust and Parallel Implementation of an Interior Point Algorithm for Limit State Optimization N. Dollerup, M.S. Jepsen, C. Frier and L. Damkilde
Institute of Structures, Materials and Geotechnics, Aalborg University, Esbjerg, Denmark N. Dollerup, M.S. Jepsen, C. Frier, L. Damkilde, "An Effective, Robust and Parallel Implementation of an Interior Point Algorithm for Limit State Optimization", in , (Editors), "Proceedings of the Twelfth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 252, 2014. doi:10.4203/ccp.106.252
Keywords: finite element, limit state analysis, lower bound solution, element renumbering, frontal method, interior point optimization, parallel computing..
Summary
A robust and effective finite element based implementation of lower bound limit state
analysis applying an interior point formulation is presented in this paper. The lower
bound formulation results in a convex optimization problem consisting of a number of
linear constraints from the equilibrium equations and a number of convex non-linear
constraints from the yield criteria. The computational robustness has been improved
by eliminating a large number of the equilibrium equations a priori leaving only the
statical redundant variables as free optimization variables. The elimination of equilibrium
equations is based on a optimized numbering of elements and stress variables
based on the frontal method approach used in the standard finite element method.
The optimized numbering secures sparsity in the formulation. The convex non-linear
yield criteria are treated directly in the interior point formulation and calculation of
the search gradients takes into account the curvature of the yield criteria. Contrary
to the cone based optimization methods the present implementation allows for fully
general yield criteria. The optimized numbering secures an effective calculation of
the Hessian matrix used in the determination of the search direction in each iteration
step, and the formualtion also allows for parallel computation. The implementation
has been used in load optimization of reinforced concrete slabs but is fully general.
Different examples are treated to benchmark the algorithm with previous work in the
field of lower bound optimization problems.
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