Bayesian Uncertainty Quantification of Physical Model in Thermal-Hydraulics System Code

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Contents:

• Quantifying Uncertainty of Computer Model: Forward and Backward
  • Computer Simulation and Safety Analysis of Nuclear Power Plant
  • Computer Experiment
  • Uncertainty Quantification
  • OECD/NEA PREMIUM
  • Problem and Objective
  • Scope and Limitations
  • Thesis Overview: Methodological Roadmap
• Reflood
• Sensitivity Analysis: Understanding Model Input/Output Relationship under Uncertainty
  • Parameters Screening
  • Variance Decomposition
  • Describing Variation of Time-Dependent Output
  • Implementation
  • Application to TRACE Model of FEBA
  • Chapter Summary
• Gaussian Process Metamodeling: Emulating Code Input/Output for Faster Evaluation
  • Gaussian Process Fundamentals
  • Metamodeling based on Gaussian Process
  • Constructing GP Metamodel
  • GP Metamodeling of a Simple Problem
  • Dimension Reduction
  • GP Metamodel of TRACE FEBA Model
  • Chapter Summary
• Bayesian Calibration of Computer Model: Connecting Uncertain Model and Uncertain Data
  • Statistical Formulation of Model Calibration Problem
  • Model Discrepancy and Its Modeling
  • Modular Bayesian Approach
  • Posterior Distribution Approximation: Markov Chain Monte Carlo Simulation
  • Identifiability Issue and Its Solution
  • Calibration of a Simple Problem
  • Calibration of TRACE Reflood Model using One Model Response
  • Calibration of TRACE Reflood Model using Multiple Model Responses
  • Chapter Summary
• Bibliography