Validation & Uncertainty Quantification

Validation & Uncertainty Quantification

Simulation software has advanced to the state of providing realistic simulations of full-scale processes. Computer hardware is now able to deliver one simulation in the time frame of a week or two on inexpensive, modestly parallel, multi-processor computers. However, even with the availability of these computational tools, the user of this predictive tool is left wondering about the accuracy of the output from the simulation. Our Validation/Uncertainty Quantification (VUQ) methodology employs Bayesian inference as the basis of its mathematical formulation. Through cycles of Bayesian analysis, the methodology draws on prior information and exploits a consistency requirement on the available experimental data sets and the simulations of these sets to quantify the uncertainty in model parameters, boundary conditions, experimental error and simulation outputs to produce predictivity.

philip-j-smith

Philip Smith

V/UQ

eric-g-eddings

Eric Eddings

Experimental data collection

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Benjamin Isaac

V/UQ

SeanSmith

Sean Smith

V/UQ

VUQ Project Sites:

 

Contact

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Mission

The mission of ICSE is education through interdisciplinary research on high-temperature fuel utilization processes for energy generation, and associated environmental, health, policy, and performance issues.