Prerequisites

Prerequisites#

This document focuses on how to run OpenSees within the DesignSafe ecosystem, not on how to build structural models from first principles.

You do not need to be an OpenSees expert to benefit from this guide — but you should have some familiarity with how OpenSees works conceptually.

Expected Background#

You will benefit most from this document if you:

  • Have run at least one OpenSees (Tcl) or OpenSeesPy script before

  • Understand what an OpenSees input script looks like

  • Are familiar with basic structural modeling concepts (nodes, elements, materials, sections, loads, analysis commands)

  • Have a general sense of what your model is intended to do

You do not need:

  • Deep knowledge of OpenSees internals

  • Advanced parallel computing experience

  • Prior experience with SLURM

  • Prior experience with Tapis APIs

Those infrastructure and execution concepts are explained here.

What This Document Does Not Cover#

This document is not:

  • A full OpenSees user manual

  • A modeling theory guide

  • A tutorial on structural analysis fundamentals

  • A comprehensive MPI programming reference

If you are completely new to OpenSees modeling, you may want to first explore:

  • Introductory OpenSees examples

  • Basic OpenSeesPy tutorials

  • Simple single-degree-of-freedom or 2D frame examples

Then return to this document to learn how to deploy those models on DesignSafe.

Technical Familiarity (Helpful but Not Required)#

Some exposure to the following will be helpful:

  • Basic command-line usage

  • File and directory structures

  • Python scripting (for OpenSeesPy workflows)

However, this guide introduces HPC execution, resource selection, job submission, and middleware concepts in a structured and gradual way.

Mindset#

More than specific technical skills, what you need is:

  • A willingness to think in terms of workflows

  • Curiosity about what happens “under the hood”

  • An interest in scaling your simulations beyond your local machine

This document bridges modeling and infrastructure — helping you move from running a script to designing a reproducible computational workflow.

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