The Quantified Uncertainty with Optimization for the Finite Element Method (quoFEM) application is designed to advance the integration of uncertainty quantification and optimization in the field of natural hazards engineering. This application accomplishes this goal by integrating established finite element applications such as OpenSees and FEAPpv with uncertainty quantification tools like Dakota through a user-friendly interface. By combining tools like these, quoFEM enhances finite element applications with robust uncertainty quantification and optimization functionalities.
To address the challenge of computational overhead that can burden the execution of probabilistic analyses, users have the flexibility to specify that simulations be conducted on high-performance computing (HPC) resources. For instance, users can run simulations on the Frontera supercomputer at TACC, which is accessible through our NHERI partner, DesignSafe.
The quoFEM application offers a range of analytical capabilities, including:
Read the quoFEM Application Summary (V4.0).
To contribute to expanding workflow capabilities please reach out to NHERI-SimCenter@berkeley.edu.
Explore, Calibrate, and Propagate Uncertainties through Finite Element Models using quoFEM, Aakash Bangalore Satish, Postdoctoral Scholar, UC Berkeley, January 6, 2023
Global Sensitivity Analysis on a Structural System, Sang-ri Yi, Postdoctoral Researcher, UC Berkeley November 12, 2021
Global Sensitivity Analysis for High Dimensional Outputs using quoFEM, Sang-ri Yi, Postdoctoral Researcher, UC Berkeley, December 2, 2022
Bayesian model class selection using quoFEM, Dr. Aakash Bangalore Satish, Postdoctoral Scholar, UC Berkeley, January 12, 2024
Explore, Calibrate, and Propagate Uncertainties through Finite Element Models using quoFEM, Aakash Bangalore Satish, Postdoctoral Scholar, UC Berkeley, January 6, 2023
Calibrating an OpenSees Material Model using Experimental Data in quoFEM, Aakash Bangalore Satish, Postdoctoral Scholar, UC Berkeley, December 10, 2021
Bayesian Calibration of a Reduced Order Model for Structural Response Approximation, Dr. Aakash Bangalore Satish, April 29, 2022
Surrogate Modeling of Surface Wind Pressure Statistics, Sang-ri Yi, UC Berkeley, April 26, 2024
Replacing a Computationally Expensive Simulation with a Gaussian Process Surrogate Model in quoFEM, Sang-ri Yi, UC Berkeley, April 1, 2022
Tool Training Workshop: February 22-23, 2022
quoFEM Day 1: Introduction to the SimCenter and the quoFEM application: capabilities including Latin Hypercube Sampling, Monte Carlo Sampling, and Sensitivity Analysis. Plus, an introduction to the Custom UQ Engine - a new feature that invites advanced users to integrate and use their tools within the SimCenter's Application Framework and the benefits of Gaussian process-based surrogate modeling
quoFEM Day 2: Introduction to the custom FEM engine with demonstrations of two structural engineering examples. The first will drive ETABS to calibrate a moment frame structure using modal characteristics. The second example calibrates an MDOF model run through Matlab.
Tool Training Workshop: May 24-25, 2021
quoFEM Day 1: New features in quoFEM: Global Sensitivity Analysis and Bayesian Calibration
quoFEM Day 2: A presentation of quoFEM's advanced features and backend workflow
Tool Training Workshop: June 15-16, 2020
quoFEM Day 1: An Introduction to the the SimCenter, examples of research applications the SimCenter has developed, educational software and an overview of quoFEM
quoFEM Day 2: A demonstration of how quoFEM works with Python scripts, OpenSeesPy or other custom scripts. Calibration examples: conventional and Bayesian
Weekly Virtual UQ Office Hours:
Software Insights:
How to cite:
Frank McKenna, Kuanshi Zhong, Michael Gardner, Adam Zsarnoczay, Sang-ri Yi, Aakash Bangalore Satish, Charles Wang, Amin Pakzad, & Wael Elhaddad. (2024). NHERI-SimCenter/quoFEM: Version 4.0.0 (v4.0.0). Zenodo.
https://doi.org/10.5281/zenodo.13324130
Deierlein, G.G., McKenna, F., et al. (2020). A Cloud-Enabled Application Framework for Simulating Regional-Scale Impacts of Natural Hazards on the Built Environment. Frontiers in Built Environment. 6, 196. doi: 10.3389/fbuil.2020.558706.
