Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

Uncertainty Quantification of Spalart–Allmaras Turbulence Model Coefficients for Simplified Compressor Flow Features

(2020) Xiao He et al.   JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME

Bayesian inference for Common cause failure rate based on causal inference with missing data

(2020) H.D. Nguyen et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A hybrid Gaussian process model for system reliability analysis

(2020) Meng Li et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Implementation of Framework for Assessment of Severe Accident Management Effectiveness in Nordic BWR

(2020) Sergey Galushin et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

An inverse-distance-based fitting term for 3D-Var data assimilation in nuclear core simulation

(2020) Helin Gong et al.   ANNALS OF NUCLEAR ENERGY

Uncertainty analysis of PIV measurements in bubbly flows considering sampling and bubble effects with ray optics modeling

(2020) Yang Liu et al.   NUCLEAR ENGINEERING AND DESIGN

Interface capturing simulations of droplet interaction with spacer grids under DFFB conditions

(2020) Nadish Saini et al.   NUCLEAR ENGINEERING AND DESIGN

Liquid-phase turbulence measurements in air-water two-phase flows using particle image velocimetry

(2020) Shanbin Shi et al.   PROGRESS IN NUCLEAR ENERGY

Deep Learning Interfacial Momentum Closures in Coarse-Mesh CFD Two-Phase Flow Simulation Using Validation Data

(2020) Han Bao et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

(2020) Han Bao et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Optimizing long-term monitoring of radiation air-dose rates after the Fukushima Daiichi Nuclear Power Plant

(2020) Dajie Sun et al.   JOURNAL OF ENVIRONMENTAL RADIOACTIVITY

Enhancement of risk informed validation framework for external hazard scenario

(2020) Saran Srikanth Bodda et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Uncertainty quantification of two-phase flow and boiling heat transfer simulations through a data-driven modular Bayesian approach

(2019) Yang Liu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

A data-driven framework for error estimation and mesh-model optimization in system-level thermal-hydraulic simulation

(2019) Han Bao et al.   NUCLEAR ENGINEERING AND DESIGN

Integrated framework for model assessment and advanced uncertainty quantification of nuclear computer codes under Bayesian statistics

(2019) Majdi I. Radaideh et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

On the prediction of critical heat flux using a physics-informed machine learning-aided framework

(2019) Xingang Zhao et al.   APPLIED THERMAL ENGINEERING

Surrogate modeling of advanced computer simulations using deep Gaussian processes

(2019) Majdi I. Radaideh et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Stochastic model reduction for polynomial chaos expansion of acoustic waves using proper orthogonal decomposition

(2019) Nabil El Moçayd et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Uncertainty and sensitivity analysis of a PWR LOCA sequence using parametric and non-parametric methods

(2019) Eneko Zugazagoitia et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Numerical evaluation of the uncertainty of double-sensor conductivity probe for bubbly flow measurement

(2018) D. Wang et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian process, Part 1: Theory

(2018) Xu Wu et al.   NUCLEAR ENGINEERING AND DESIGN

Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data

(2018) Xu Wu et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Data-driven modeling for boiling heat transfer: Using deep neural networks and high-fidelity simulation results

(2018) Yang Liu et al.   APPLIED THERMAL ENGINEERING

Integration of conductivity probe with optical and x-ray imaging systems for local air–water two-phase flow measurement

(2018) Dewei Wang et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Gaussian Process–Based Inverse Uncertainty Quantification for TRACE Physical Model Parameters Using Steady-State PSBT Benchmark

(2018) Chen Wang et al.   NUCLEAR SCIENCE AND ENGINEERING

Validation and Uncertainty Quantification for Wall Boiling Closure Relations in Multiphase-CFD Solver

(2018) Yang Liu et al.   NUCLEAR SCIENCE AND ENGINEERING

Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions

(2018) Roland Schöbi et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Hybrid computation of uncertainty in reliability analysis with p-box and evidential networks

(2017) Christophe Simon et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Risk assessment under deep uncertainty: A methodological comparison

(2017) Julie Shortridge et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Accuracy of Eulerian–Eulerian, two-fluid CFD boiling models of subcooled boiling flows

(2016) M. Colombo et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Development of a robust image processing technique for bubbly flow measurement in a narrow rectangular channel

(2016) Yucheng Fu et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

(2016) H. Xiao et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Measurements of liquid-phase turbulence in gas–liquid two-phase flows using particle image velocimetry

(2013) Xinquan Zhou et al.   MEASUREMENT SCIENCE and TECHNOLOGY

A Bayesian calibration approach to the thermal problem

(2008) Dave Higdon et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING