01 | Module
The VVUQ Framework and Model Credibility
Verification, validation, and UQ defined, and the ASME credibility process.
Start module →Course 25 | Advanced Engineering Methods
Verification, Validation, and Uncertainty Quantification
Check whether models, simulations, and engineering results are credible through verification, validation, uncertainty, sensitivity, and evidence.
Course snapshot
- Purpose
- VVUQ teaches students how to judge whether a model or simulation result can be trusted for an engineering decision.
- Before this
- Next course
- Used in Career directions
- Content status
- Lesson hub
How to study this course
- State the model purpose
- Check implementation and solution quality
- Compare against data or simpler estimates
- Quantify uncertainty and sensitivity
- Document credibility and limits
01
How this course is designed
Verification before validation
You cannot judge a model against reality until you know the equations are solved correctly. The course keeps the ASME order: verify the mathematics first, then validate the physics, then quantify what remains uncertain.
Grounded in the ASME standards
The framework follows the ASME V&V standards, V&V 10 for solid mechanics, V&V 20 for fluids and heat transfer, and V&V 40 for credibility, so the vocabulary matches professional practice.
Every claim carries a number
Each module ends in a quantity: an order of accuracy, a grid convergence index, a validation uncertainty, a sensitivity index, or a margin, the evidence that turns a result into a defensible decision.
02
The 10 modules
02 | Module
Code Verification and Order of Accuracy
The method of manufactured solutions and the observed order of accuracy.
Start module →03 | Module
Solution Verification: Richardson Extrapolation and the GCI
Discretization error, Richardson extrapolation, and the grid convergence index.
Start module →04 | Module
Validation Experiments and the Validation Hierarchy
Comparing simulation to data and building validation from units to systems.
Start module →05 | Module
Validation Metrics and Validation Uncertainty
The ASME V&V 20 comparison error and validation uncertainty.
Start module →06 | Module
Sources and Classification of Uncertainty
Aleatory versus epistemic uncertainty and what can be reduced.
Start module →07 | Module
Uncertainty Propagation
Taylor-series propagation and Monte Carlo sampling.
Start module →08 | Module
Sensitivity Analysis
Local sensitivity coefficients and variance-based Sobol indices.
Start module →09 | Module
Model Calibration and Predictive Capability
Calibrating parameters to data and the uncertainty of a prediction.
Start module →10 | Module
Credibility Assessment and Decision-Making
Risk-informed credibility, adequacy for use, and margins.
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