Transcript Imperial College London

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
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
Introduction
•Implementation
• Parallelisation of ADAPTIC
• MPI
•Verification Examples
Structural Domain Partitioning
Case 1:
2: A parent and 2
3:
a
child partitions
partition (Same
(parent
(parent
also
as
has
case
only
models
2partition
buta parent
partsuper
of
structure
and
elements)
child roles
made with
other elements)
reversed)
Partition super element on
parent side
Dual partition super element
on child side
Structural Domain Partitioning
Hierarchical Approach
st Level
2
1nd
Level of
of Partitioning
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
Send Load Factor, Incremental
Displacements etc. to the
Partitions`
Get Resistance Forces and
Tangent Stiffness from the
Partitions
Check Convergence
Next Iteration
or Load Step?
End
Implementation
Start, Initialize MPI
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
Verification
Example 1: A 4 storey Structure
6
Node 42
6
3
3
3
3
4
3
3
4
y
Original Structure
x
Parent Structure
Partition No. 1
Partition No.
2
Verification
Example 2: I-Beam using 3D Brick Elements
Time taken for monolithic analysis
188 seconds
Time taken for partitioned analysis with 3 80 seconds
partitions
Time saved
57.4 %
Verification
Example 3: 3D Framed Structure
Load
steps Initial Loading Time-history
completed (in
72 hours) for:
Total
Monolithic
1
analysis
Partitioned
1
analysis with
11 partitions
9
10
120
121
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?