Towards Uncertainty Quantification of LES and URANS for the Buoyancy-Driven Mixing Process between Two Miscible Fluids—Differentially Heated Cavity of Aspect Ratio 4

Philipp J Wenig,Markus Klein,Stephan Kelm,Ruiyun Ji

doi:10.3390/fluids6040161

Philipp J Wenig, Markus Klein + Show 2 more

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https://doi.org/10.3390/fluids6040161

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Abstract

Numerical simulations are subject to uncertainties due to the imprecise knowledge of physical properties, model parameters, as well as initial and boundary conditions. The assessment of these uncertainties is required for some applications. In the field of Computational Fluid Dynamics (CFD), the reliable prediction of hydrogen distribution and pressure build-up in nuclear reactor containment after a severe reactor accident is a representative application where the assessment of these uncertainties is of essential importance. The inital and boundary conditions that significantly influence the present buoyancy-driven flow are subject to uncertainties. Therefore, the aim is to investigate the propagation of uncertainties in input parameters to the results variables. As a basis for the examination of a representative reactor test containment, the investigations are initially carried out using the Differentially Heated Cavity (DHC) of aspect ratio 4 with Ra=2×109 as a test case from the literature. This allows for gradual method development for guidelines to quantify the uncertainty of natural convection flows in large-scale industrial applications. A dual approach is applied, in which Large Eddy Simulation (LES) is used as reference for the Unsteady Reynolds-Averaged Navier–Stokes (URANS) computations. A methodology for the uncertainty quantification in engineering applications with a preceding mesh convergence study and sensitivity analysis is presented. By taking the LES as a reference, the results indicate that URANS is able to predict the underlying mixing process at Ra=2×109 and the variability of the result variables due to parameter uncertainties.

Highlights

Numerical approximations and mathematical models are used to solve technical issues in computational science and engineering
An important representative of this category in the field of Computational Fluid Dynamics (CFD) is the reliable prediction of hydrogen distribution and pressure build-up in nuclear reactor containment during an accident scenario, which is of utmost importance with regard to maintaining the integrity of the containment and preventing the release of radioactive substances [1,2]
An initial stratification with 40 vol% helium was defined in the upper third of the Differentially Heated Cavity (DHC) in addition to air

Summary

Introduction

Numerical approximations and mathematical models are used to solve technical issues in computational science and engineering. An important representative of this category in the field of Computational Fluid Dynamics (CFD) is the reliable prediction of hydrogen distribution and pressure build-up in nuclear reactor containment during an accident scenario, which is of utmost importance with regard to maintaining the integrity of the containment and preventing the release of radioactive substances [1,2]. Decay heat production of the core leads first to heating and to evaporation of the water in the reactor pressure vessel. Large quantities of hydrogen are produced after the failure of the reactor pressure vessel during nuclear meltdown of the fuel when the concrete decomposes (Figure 1c). An ignitable hydrogen air–steam gas mixture can be formed from the hydrogen, the atmospheric oxygen present in the containment, and the evaporated water. For safety, it is essential to understand the transport and mixing processes of hydrogen in the containment [3,4,5]

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