136 citations · 357 across the 8 of their papers we have counts for
4 papers · 1 filter
Bayesian Inverse Uncertainty Quantification of a MOOSE-based Melt Pool Model for Additive Manufacturing Using Experimental Data
Ziyu Xie, Wen Jiang, Congjian Wang +1
Additive manufacturing (AM) technology is being increasingly adopted in a wide variety of application areas due to its ability to rapidly produce, prototype, and customize designs.…
A Comprehensive Survey of Inverse Uncertainty Quantification of Physical Model Parameters in Nuclear System Thermal-Hydraulics Codes
Xu Wu, Ziyu Xie, Farah Alsafadi +1
Uncertainty Quantification (UQ) is an essential step in computational model validation because assessment of the model accuracy requires a concrete, quantifiable measure of uncerta…
Demonstration of the Relationship between Sensitivity and Identifiability for Inverse Uncertainty Quantification
Xu Wu, Koroush Shirvan, Tomasz Kozlowski
Inverse Uncertainty Quantification (UQ), or Bayesian calibration, is the process to quantify the uncertainties of random input parameters based on experimental data. The introducti…
Inverse Uncertainty Quantification using the Modular Bayesian Approach based on Gaussian Process, Part 2: Application to TRACE
Xu Wu, Tomasz Kozlowski, Hadi Meidani +1
Inverse Uncertainty Quantification (UQ) is a process to quantify the uncertainties in random input parameters while achieving consistency between code simulations and physical obse…