Uncertainty Quantification in Nuclear Thermal-Hydraulics

Uncertainty quantification in nuclear thermal-hydraulics addresses the rigorous estimation and propagation of errors and variabilities inherent in mathematical models, numerical algorithms and experimental inputs used to predict reactor coolant system behaviour under both normal and accident conditions. This discipline integrates probabilistic methods with deterministic simulations to derive confidence intervals for key safety metrics such as peak cladding temperature, core heat fluxes and containment pressures. Central to this effort is the Best Estimate Plus Uncertainty (BEPU) paradigm, which replaces conservative bounding approaches with realistic modelling augmented by systematic uncertainty analysis. State-of-the-art practices encompass Monte Carlo sampling of input distributions, global sensitivity analysis to identify dominant contributors to output variance, surrogate modelling for computational efficiency and advanced statistical inference to calibrate model parameters against experimental benchmarks. Applications extend from large-break and small-break loss-of-coolant accident scenarios to station blackout sequences and severe accident progression, informing design verification, regulatory decision-making and the optimisation of safety systems. By quantifying margins with defined confidence levels, uncertainty quantification underpins risk-informed safety assessments and supports the global nuclear industry’s transition towards more flexible licensing frameworks and enhanced defence-in-depth strategies.

Research from Nature Portfolio

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Research from all publishers

Recent projects under the EU Horizon-2020 framework have advanced the systematic application of Best Estimate Plus Uncertainties methods to severe accident codes. These efforts deploy multiple uncertainty quantification techniques to assess radiological source-term predictions for Gen II and Gen III designs, integrating both model parameters and boundary-condition variabilities. A complementary approach, the Extended BEPU methodology, enriches deterministic safety analyses by embedding probabilistic safety assessment insights and defence-in-depth considerations, enabling the detection of cliff-edge effects and incorporating system availability as an explicit uncertain item in design-basis event evaluations. Detailed nodal sensitivity studies using a leading severe-accident code have revealed the significance of mesh resolution on in-vessel phenomena predictions, demonstrating that coarse meshes can underpredict core relocation rates and hydrogen generation while finer discretisations yield more accurate heat-structure interactions. Together, these advances illustrate a trend towards harmonising high-fidelity simulation, statistical sampling and risk insights to deliver robust, tractable uncertainty bounds in thermal-hydraulic safety analysis.

Uncertainty Quantification in Nuclear Thermal-Hydraulics publication trend

The graph below shows the total number of articles in uncertainty quantification in nuclear thermal-hydraulics across all publications each year (not limited to Nature Index journals).

Technical terms

Uncertainty Quantification: The process of characterising and propagating input and model uncertainties to quantify confidence in simulation outputs.

Best Estimate Plus Uncertainty (BEPU): A methodology combining realistic model predictions with statistical treatment of uncertainties to derive safety margins.

Extended BEPU (E-BEPU): An enhanced BEPU framework that integrates probabilistic safety analysis and system availability uncertainties into deterministic assessments.

Monte Carlo Sampling: A computational technique that employs random sampling of input distributions to estimate output variability.

Sensitivity Analysis: Methods for determining which uncertain inputs most strongly influence key outputs.

Nodalisation: The discretisation scheme defining spatial divisions within a system code model that can impact prediction accuracy.

References

1. The EC MUSA Project on Management and Uncertainty of Severe Accidents: Main Pillars and Status. Energies (2021).
2. A nodal sensitivity study of MELCOR simulation for severe accidents in a pressurized water reactor. Annals of Nuclear Energy (2021).
3. Demonstration of the E-BEPU methodology for SL-LOCA in a Gen-III PWR reactor. Reliability Engineering & System Safety (2022).