OQ-VMTK v1.0.1

What's Changed

• The SLF generator module has been updated to correct an issue in the regression selection logic. When the regression input argument is set to None, the module now evaluates all supported regression models and automatically selects and returns the functional form that provides the best fit based on the defined error metrics.

Contributors

• @K-Aljawhari contributed to this bug fix in #22

Full Changelog: v1.0.0...v1.0.1

OQ-VMTK v1.0.0

OQ-VMTK Release Notes

Vulnerability Modeller's Toolkit (OQ-VMTK) – Version 1.0.0

The OQ-VMTK is an open-source toolkit developed by the Global Earthquake Model (GEM) Foundation for earthquake engineers and vulnerability modellers. It enables modeling and assessment of structures via single- and multi-degree-of-freedom (SDOF/MDOF) systems, supporting both linear and nonlinear analyses, with a focus on improving the reliability of regional vulnerability models for large-scale earthquake risk applications.

Key Features

• Ground Motion Record Processing: Calculate ground shaking intensity based on various intensity measure (IM) types such as PGA, SA(T), Sa_avg, FIV3, etc.

• Modeling & Calibration: Define and model idealised stick-and-mass models with user-specific storey count and force-deformation relationships, powered by OpenSeesPy.

• Analysis Suite

  • Modal Analysis: Calculate modal properties (i.e., periods of vibration and mode shapes)
  • Nonlinear Static: Conduct static or cyclic pushover analyses to characterise the lateral load-resisting and energy dissipation capacity of the idealised model.
  • Nonlinear Dynamic: Conduct nonlinear time-history analyses (NLTHA) and extract engineering demand parameters such as peak floor displacements and accelerations, as well as inter-storey drifts.

• Fragility & Vulnerability

  • Probabilistic seismic demand modeling (IM-EDP relationships)
  • Fragility function fitting with multiple approaches (lognormal CDF, GLM, ordinal).
  • Generate storey loss functions (SLFs) to leverage the seismic demands from NLTHA for refined loss assessment applications
  • Vulnerability curve (Loss vs IM) modelling with uncertainty treatment.

• Visualization

  • Plot model overviews, peak response distributions, fragility functions, SLFs and vulnerability models.

Installation

• Supports Windows and Linux (Python 3.11/3.12).
• Virtual environment recommended.
• Install dependencies from requirements.txt and install the package in editable mode.

Getting Started

• Includes demo scripts accessible via Jupyter Lab.
• Documentation: https://gemsciencetools.github.io/oq-vmtk

License

• Licensed under AGPL v3.