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Parallelisation of Nonlinear Structural Analysis using Dual Partition Super-Elements. G.A. Jokhio and B.A. Izzuddin. Overview. Introduction Proposed Structural Decomposition Approach Implementation by Parallelisation Verification Conclusions. Introduction.
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Parallelisation of Nonlinear Structural Analysis using Dual Partition Super-Elements G.A. Jokhio and B.A. Izzuddin
Overview • Introduction • Proposed Structural Decomposition Approach • Implementation by Parallelisation • Verification • Conclusions
Introduction • A new approach of structural domain partitioning • Parts of a structure replaced by partition super elements • Removed parts modelled separately as child structures • Dual partition super elements wrap the partition boundary of respective child structures What?
Introduction • Purpose • Reduction in computational time • By using parallel processing • By using reduced dimensional elements for non-critical parts • Simplification of modelling • By modular modelling • Freedom • To choose partitions • To use different integration schemes • To consider multi-physics Why?
Introduction • Implementation • Parallelisation of ADAPTIC • MPI • Verification Examples How?
Structural Domain Partitioning Case 2: A parent and a child partition (parent also models a part of structure made with other elements) Case 3: A parent and a child partition (Same as case 2 but parent and child roles reversed) Case 1: A parent and 2 child partitions (parent has only partition super elements) Partition super element on parent side Dual partition super element on child side
Structural Domain Partitioning • Hierarchical Approach 2nd Level of Partitioning 1st Level of Partitioning Partition super element on parent side Dual partition super element on child side
Rationale • Partitions ‘represented’ by partition super elements • Any solution procedure based on monolithic approach ‘will do’ • The child partition boundary is analogous to Essential Boundary Conditions • Compatibility: Parent sends these BCs to partitions • Equilibrium: Parent receives the tangent stiffness and resistance forces from partitions
Procedure • Load/Time Steps • Step wise loading/time-stepping controlled by the parent • The load factor/time is sent to the partitions • Equilibrium Convergence • Convergence at parent structure level • Convergence at partition level • Iteration • Iterative corrections to displacements sent to the partitions • Resulting forces and tangent stiffness received by the parent • The Frontal Method is most suitable – other methods can be used
Implementation • ADAPTIC • Source code available • Written in Fortran – Most widely used language in HPC • Analysis types: • Static Proportional Loading • Static Time History • Dynamic • Eigenvalue • A wide range of structural elements and material models available • Supports advanced adaptive techniques Other structural analysis programs can also be used
Implementation Start, Initialize MPI Overview of the Parent Structure Algorithm Send Load Factor, Incremental Displacements etc. to the Partitions` Next Iteration or Load Step? Get Resistance Forces and Tangent Stiffness from the Partitions Check Convergence End
Implementation Start, Initialize MPI Overview of the Partition/Child Algorithm Receive Instruction and the relevant data from the Parent Perform the relevant Task Send the Outcome of the relevant task to the parent Continue? End
Node 42 6 6 3 3 3 3 3 3 4 y 4 Original Structure Partition No. 1 Partition No. 2 x Verification • Example 1: A 4 storey Structure Accuracy Parent Structure
Verification • Example 2: I-Beam using 3D Brick Elements Computational Efficiency
Verification • Example 3: 3D Framed Structure Ease of Modelling
Conclusions • A new structural decomposition approach for partitioned analysis using parallel processing has been proposed • Uses dual partition-super elements • Can be used for the parallelisation of existing monolithic analysis codes • Has been implemented with ADAPTIC using a parallel MPI scheme • The results match exactly with those obtained from conventional monolithic analysis • Significant computational savings arise in the analysis of large structures, with great speedups achieved • The proposed partitioning approach can also simplify the modelling process through the use of modular partitions
Acknowledgements • Higher Education Commission of Pakistan • High Performance Computing (HPC) Services, Imperial College London
Questions? Thank You