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Git and CI/CD for Production CAE Automation Tools

30 Chapters
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01
Course overview
scope, concepts, and technical context of Git and CI/CD for production CAE automation tools.
technicalCI/CD
02
Version control fundamentals for CAE automation
repositories, commits, branches, and merges in the context of simulation scripts and solver input decks.
CAEautomation
03
Structuring a CAE automation repository
directory layout for scripts, templates, solver decks, post-processing utilities, and configuration files.
StructuringCAE
04
Git branching strategies for CAE tool development
feature branches, release branches, and hotfixes for solver wrappers and meshing automation.
branchingstrategies
05
Managing large binary and simulation artifacts with Git LFS
CAD files, mesh files, result databases, and solver restart files.
Managingsimulation
06
Writing effective commit messages and maintaining a changelog for CAE automation tools used by engineering teams.
Writing effective commit messages and maintaining a changelog for CAE automation tools used by engineering teams.
effectivemessages
07
Collaborative workflows for CAE automation
pull requests, code reviews, and merge conflict resolution in solver script repositories.
Collaborativeworkflows
08
Tagging and semantic versioning of CAE automation tools
releasing stable versions of meshing, solver, and post-processing utilities.
semanticversioning
09
Git hooks for CAE automation
pre-commit linting of Python scripts, input deck validation, and unit test execution.
CAEautomation
10
Introduction to CI/CD for CAE automation
concepts, benefits, and challenges specific to simulation toolchains.
CI/CDCAE
11
Setting up a CI pipeline for CAE automation tools
build, test, and package stages for solver wrappers and meshing scripts.
pipelineCAE
12
Automated testing of CAE automation tools
unit tests for geometry manipulation, mesh generation, and solver input generation.
AutomatedCAE
13
Integration testing with real solvers
running small verification cases in CI for structural, thermal, and fluid CAE tools.
Integrationverification
14
Continuous integration for CAE post-processing
automated validation of result extraction, plotting, and report generation scripts.
Continuousintegration
15
Managing dependencies and environments for CAE automation
virtual environments, conda, containers, and solver-specific runtimes.
Managingdependencies
16
Containerizing CAE automation tools with Docker
packaging solvers, dependencies, and scripts for reproducible CI runs.
ContainerizingCAE
17
CI/CD pipeline orchestration for CAE workflows
using Jenkins, GitLab CI, GitHub Actions, or Azure DevOps in simulation contexts.
CI/CDpipeline
18
Artifact management in CAE CI/CD
storing and versioning build outputs, test results, and generated simulation models.
Artifactmanagement
19
Continuous delivery and deployment of CAE automation tools
releasing to engineering teams, internal package registries, and shared environments.
Continuousdelivery
20
Monitoring and reporting in CAE CI/CD
dashboards, notifications, and metrics for pipeline health and simulation tool reliability.
Monitoringreporting
21
Security and compliance in CAE automation CI/CD
secrets management, license servers, and export-controlled simulation data.
Securitycompliance
22
Scaling CI/CD for CAE
parallel test execution, distributed runners, and handling long-running solver verification cases.
CI/CDCAE
23
Case study
end-to-end CI/CD for a parametric CAD and meshing automation toolchain.
end-to-endCI/CD
24
Case study
CI/CD for a solver wrapper that automates structural analysis and result extraction.
CI/CDautomates
25
Case study
CI/CD for a multidisciplinary CAE workflow combining thermal, structural, and fluid simulations.
CI/CDmultidisciplinary
26
Debugging and troubleshooting CI/CD pipelines for CAE automation
common failure modes and resolution strategies.
Debuggingtroubleshooting
27
Best practices for maintaining production CAE automation tools
documentation, deprecation policies, and backward compatibility.
practicesmaintaining
28
Integrating CI/CD with HPC job schedulers
Slurm, PBS, and LSF for automated solver runs in simulation pipelines.
IntegratingCI/CD
29
Performance optimization of CAE automation pipelines
caching, incremental builds, and efficient test selection.
Performanceoptimization
30
Future trends and advanced topics
GitOps, MLOps for CAE, cloud-native simulation, and AI-assisted automation in production CAE toolchains.
advancedGitOps