The Quantified Uncertainty with Optimization for the Finite Element Method (quoFEM) application is intended to advance the use of uncertainty quantification and optimization within the field of 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.

"Bayesian calibration of hierarchical models using an adaptive Metropolis-within-Gibbs sampling algorithm” is implemented in quoFEM Version 3.5. This feature enables users to quantify the dataset-to-dataset variability, also known as aleatory uncertainty, in the estimated parameters of a user-specified computational model, using user-provided data from multiple lab testing experiments. Example 15 demonstrates Bayesian calibration of a hierarchical model for the parameters of a uniaxial material model using a dataset consisting of stress-strain data from cyclic tests performed on several coupons of Grade 60 reinforcing steel.

Download the updated quoFEM (V3.5) release to take advantage of the new feature. Example 15 provided in the quoFEM documentation includes input files that can easily be used as a template.

How to cite:
Frank McKenna, Sang-ri Yi, Aakash Bangalore Satish, Adam Zsarnoczay, Kuanshi Zhong, Michael Gardner, & Wael Elhaddad. (2023). NHERI-SimCenter/quoFEM: Version 3.5.0 (v3.5.0). Zenodo. https://doi.org/10.5281/zenodo.10443180

Gregory G. Deierlein, Frank McKenna, Adam Zsarnóczay, Tracy Kijewski-Correa, Ahsan Kareem, Wael Elhaddad, Laura Lowes, Matt J. Schoettler, and Sanjay Govindjee (2020). A Cloud-Enabled Application Framework for Simulating Regional-Scale Impacts of Natural Hazards on the Built Environment. Frontiers in the Built Environment. 6:558706. DOI: 10.3389/fbuil.2020.558706