The Quantified Uncertainty with Optimization for the Finite Element Method (quoFEM) application (formerly uqFEM) is intended to advance the use of uncertainty quantification and optimization within the field natural hazards engineering. The application achieves this by combining existing finite element applications, e.g. FEAPpv, with uncertainty quantification (UQ) applications, e.g. Dakota, behind a simple user interface (UI). The combined application will enhance the finite element applications with uncertainty quantification and optimization capabilities. To overcome the issue of computational overhead, which typically precludes these types of probabilistic analysis from being performed, the user has the option of specifying that the simulations take place on HPC resources, e.g. the TACC Frontera supercomputer made available through DesignSafe-CI.

The specific types of analyses that the quoFEM application provides are:

  • Uncertainty Quantification
  • Calibration and Bayesian Calibration
  • Optimization
  • Sensitivity

Read the quoFEM Application Summary (V3.4.0).

To help expand the workflow capabilities with your contributions, contact NHERI-SimCenter@berkeley.edu or join the SimCenter Forum conversation.


Explore, Calibrate, and Propagate Uncertainties through Finite Element Models using quoFEM
Aakash Bangalore Satish, Postdoctoral Scholar,
UC Berkeley,
January 6, 2023
Global Sensitivity Analysis for High Dimensional Outputs using quoFEM
Sang-ri Yi, Postdoctoral Researcher
UC Berkeley, December 2, 2022
Replacing a Computationally Expensive Simulation with a Gaussian Process Surrogate Model in quoFEM
Sang-ri Yi, UC Berkeley, April 1, 2022
Global Sensitivity Analysis on a Structural System Sang-ri Yi, Postdoctoral Researcher, UC Berkeley
November 12, 2021
Calibrating an OpenSees Material Model using Experimental Data in quoFEM
Aakash Bangalore Satish Postdoctoral Scholar,
UC Berkeley, December 10, 2021

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

Join the User Forum Conversation:

  • submit questions and get answers
  • provide user feedback
  • post feature requests
  • submit bug reports

Weekly Virtual UQ Office Hours: 

  • Every Friday noon (Pacific Time)
  • Register here

Software Insights:

Current Capabilities

Recent Updates

Future Plans


How to cite:

Frank McKenna, bsaakash, Sang-ri Yi, claudioperez, Adam Zsarnoczay, nickberkeley, Michael Gardner, Charles Wang, Noam-Elisha, Kuanshi Zhong, Peter Mackenzie-Helnwein, Wael Elhaddad, ZGGhauch, & yisangri. (2023). NHERI-SimCenter/quoFEM: Version 3.4.0 (v3.4.0). Zenodo. https://doi.org/10.5281/zenodo.8400732

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.