University College London
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Campaigns of Uncertainty Quantification

posted on 2024-03-06, 11:11 authored by Sharp C. Y. LoSharp C. Y. Lo

This item contains the campaigns of the uncertainty quantification described in the paper titled "Uncertainty Quantification of the Impact of Peripheral Arterial Disease on Abdominal Aortic Aneurysms in Blood Flow Simulations" by Sharp C. Y. Lo, Jon W. S. McCullough, Xiao Xue, and Peter V. Coveney (2024), where the corresponding author is Prof. Peter V. Coveney (

The files that end with "order2" and "order3" are the campaigns using the 2nd- and 3rd-order polynomial chaos expansion method respectively. In each of these files,

  • and are the Python scripts used to perform the campaign. The former is used in the first execution, whereas the latter is used in the succeeding executions when all simulations are finished;
  • the jobs directory contains the job scripts used to launch the campaign and the outputs of the jobs on ARCHER2;
  • venv.txt is the list of Python packages installed in the virtual environment when the campaign was performed in the study;
  • is the simulation model of the campaign. It outlines the workflow of the preprocessing, execution, and postprocessing of one single simulation of blood flow described in the paper. HemePure (git commit hash: 554e8bef2cd68) is used to simulate the blood flow, and HemeLB_Tools is used for the preprocessing and postprocessing of the simulation;
  • the run directory is the output of the campaign. It contains sub-directories each of which corresponds to one set of input parameters, also called a sample;
  • analyseCampaign.ipynb is a Python notebook file used to analyse the outputs of the campaign and produce the figures in the paper
  • the results directory contains the results of the analysis of the campaign. In particular, list_runs.json contains the list of input parameters and the results of the quantities of interest of all samples.
  • the remaining files on the root level are data needed by