January 2, 2024 (v1) Software Open Software and DataSet of "A QA-SQP assisted FE for non-linear and history-dependent mechanics"

Click to #Development of QA-SQP for non-linear and history-dependent mechanical problems

This directory contains the source code and numerical benchmarks published in [^1]

Dependencies and Prerequisites

• Python, pandas, numpy, matplotlib are pre requisites.
• For generating mesh and for vizualization, gmsh (www.gmsh.info) is required.
• Dwave Ocean Tools (https://docs.ocean.dwavesys.com/en/stable/getting_started.html)

Structure of Repository

• src: Python source code
• examples: Some finite element tests
• paper: Python codes of the benchmarks in the paper [^1]

Run an analysis

For example, the example examples/J2-SA run a finite element simulation using Simulated Annealing

 python3 run.py

Reproduce paper[^1] results and figures

• The tests require access to the annealer.

  • Token needs to be provided in sampler = EmbeddingComposite(DWaveSampler(connection_close=True)) -> sampler = EmbeddingComposite(DWaveSampler(token="",connection_close=True))

• To use the Simulated Annealing instead, one has to replace the three lines

  • sampler = EmbeddingComposite(DWaveSampler(connection_close=True))
  • SA = lambda J: sampler.sample_qubo(J, num_reads=100,label="twoDTest")
  • quboOptFunc = lambda J: QUBO.qubo_solve_sampler(J,sampler)
  • by
  • SA = lambda J: SimulatedAnnealingSampler().sample_qubo(J,num_reads=100)
  • quboOptFunc =lambda J: QUBO.qubo_solve_sampler(J,SA)

• Figures 2, 3, and 4: in the folder paper/QA-SQP/1D-elastic

  • Run tests: python3 run.py
  • Extract figures: python3 plotData.py

• Figures 5, 6, and 7: in the folder paper/QA-SQP/1D-elastoplastic

  • Run tests: python3 run.py
  • Extract figures: python3 plotData.py

• Figures 9, 11, 12: in the folder paper/QA-SQP/2D-elastoplastic

  • Run classical finite element simulation: python3 runFEM.py
  • Run tests: python3 run.py
  • Extract figures: python3 plotData.py

Reproduce paper[^1] figures only

• Figures 2, 3, and 4: in the folder paper/QA-SQP-results/1D-elastic

  • Extract figures: python3 plotData.py

• Figures 5, 6, and 7: in the folder paper/QA-SQP-results/1D-elastoplastic

  • Extract figures: python3 plotData.py

• Figures 9, 11, 12: in the folder paper/QA-SQP-results/2D-elastoplastic

  • Extract figures: python3 plotData.py

[^1]: The work is described in:
"Nguyen V.-D., Wu L., Remacle F. and Noels L. (2024). A quantum annealing-sequential quadratic programming assisted finite element simulation for non-linear and history-dependent mechanical problems European Journal of Mechanics; A/Solids. doi:?????" which can be downloaded here. We would be grateful if you could cite this publication in case you use the files.add a brief description of the dataset (Markdown and LaTeX enabled).