Auto-PHSSCW ABAQUS: An integrated, python-based workflow for automated buckling-to-collapse analysis of H-shaped steel composite walls

Auto-PHSSCW ABAQUS is an open-source Python package that automates the parametric buckling-to-collapse modeling of H-shaped steel composite walls in Abaqus/CAE. Unlike standard macro-based scripts, this tool employs an integrated workflow combining geometric modeling, mesh generation, and multi-step solver orchestration. A key novel technical solution is the implementation of an anchor-based smart keyword injection algorithm, which dynamically manipulates the Abaqus keyword block to automate the injection of eigenmode-based geometric imperfections—a process traditionally requiring manual input files (.inp) editing to bypass standard API limitations. Furthermore, to ensure robustness during high-throughput parametric studies, the software utilizes coordinate-based bounding box algorithms for topological identification, eliminating mesh dependency errors common in index-based scripting. The workflow also features a closed-loop data transfer protocol that autonomously links linear eigenvalue results to non-linear Static-Riks collapse analysis. The tool supports continuous, separated, and bolted splice joints, and has successfully generated over 140,000 simulations to generate datasets for machine learning, significantly lowering the computational barrier for stability research.

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Publication Details

Journal
SoftwareX
Published
2026-02-01
DOI
https://doi.org/10.1016/j.softx.2026.102535
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00
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article

Auto-PHSSCW ABAQUS: An integrated, python-based workflow for automated buckling-to-collapse analysis of H-shaped steel composite walls

Lijian Ren
SoftwareX
Topology Optimization in Engineering
article

Auto-PHSSCW ABAQUS: An integrated, python-based workflow for automated buckling-to-collapse analysis of H-shaped steel composite walls

Lijian Ren
article en

Abstract

Auto-PHSSCW ABAQUS is an open-source Python package that automates the parametric buckling-to-collapse modeling of H-shaped steel composite walls in Abaqus/CAE. Unlike standard macro-based scripts, this tool employs an integrated workflow combining geometric modeling, mesh generation, and multi-step solver orchestration. A key novel technical solution is the implementation of an anchor-based smart keyword injection algorithm, which dynamically manipulates the Abaqus keyword block to automate the injection of eigenmode-based geometric imperfections—a process traditionally requiring manual input files (.inp) editing to bypass standard API limitations. Furthermore, to ensure robustness during high-throughput parametric studies, the software utilizes coordinate-based bounding box algorithms for topological identification, eliminating mesh dependency errors common in index-based scripting. The workflow also features a closed-loop data transfer protocol that autonomously links linear eigenvalue results to non-linear Static-Riks collapse analysis. The tool supports continuous, separated, and bolted splice joints, and has successfully generated over 140,000 simulations to generate datasets for machine learning, significantly lowering the computational barrier for stability research.

SoftwareXVol. 33
Hohai University (CN), Inner Mongolia University of Technology (CN)
Openalex Percentile: Top 70%
Topology Optimization in Engineering
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