A Python-based Post-processing Toolset For Seismic Analyses

TL;DR

This paper presents a new Python-based post-processing toolset designed to improve the flexibility, maintainability, and usability of seismic analysis data for UK's nuclear power stations, enabling engineers with limited software training.

Contribution

Developed a flexible, maintainable Python framework with embedded interpreter and visualization tools tailored for seismic data post-processing in nuclear engineering.

Findings

Enhanced ease of use for engineers with minimal programming experience

Improved flexibility over previous tools

Successful integration with existing seismic analysis workflows

Abstract

This paper discusses the design and implementation of a Python-based toolset to aid in assessing the response of the UK's Advanced Gas Reactor nuclear power stations to earthquakes. The seismic analyses themselves are carried out with a commercial Finite Element solver, but understanding the raw model output this produces requires customised post-processing and visualisation tools. Extending the existing tools had become increasingly difficult and a decision was made to develop a new, Python-based toolset. This comprises of a post-processing framework (aftershock) which includes an embedded Python interpreter, and a plotting package (afterplot) based on numpy and matplotlib. The new toolset had to be significantly more flexible and easier to maintain than the existing code-base, while allowing the majority of development to be carried out by engineers with little training in software development. The resulting architecture will be described with a focus on exploring how the design drivers were met and the successes and challenges arising from the choices made.