arXiv subjects

Charles Moulinec

Publications and source records attributed to Charles Moulinec.

4 recordsLinked to original sources

arXiv2025

Development of a Cost-Effective Simulation Tool for Loss of Flow Accident Transients in High-Temperature Gas-cooled Reactors

The aim of this work is to further expand the capability of the coarse-grid Computational Fluid Dynamics (CFD) approach, SubChCFD, to effectively simulate transient and buoyancy-influenced flows, which are critical in accident analyses of High-Temperature Gas-cooled Reactors (HTGRs). It has been demonstrated in our previous work that SubChCFD is highly adaptable to HTGR fuel designs and performs exceptionally well in modelling steady-state processes. In this study, the approach is extended to simulate a Loss of Flow Accident (LOFA) transient, where coolant circulation is disrupted, causing the transition from forced convection to buoyancy-driven natural circulation within the reactor core. To enable SubChCFD to capture the complex physics involved, corrections were introduced to the empirical correlations to account for the effects of flow unsteadiness, property variation and buoyancy. A 1/12th sector of the reactor core, representing the smallest symmetric unit, was modelled using a coarse mesh of approximately 60 million cells. This mesh size is about 6% of that required for a Reynolds Averaged Navier Stokes (RANS) model, where mesh sizes can typically reach the order of 1 billion cells for such configurations. Simulation results show that SubChCFD effectively captures the thermal hydraulic behaviours of the reactor during a LOFA transient, producing predictions in good agreement with RANS simulations while significantly reducing computational cost.

cs.CE↗

arXiv2023

The Propulsion Performance of Dual Heaving Foils in Tandem, with Spanwise Flexibility

The impact of spanwise flexibility on the propulsion performance of two foils arranged in tandem and subjected to a prescribed sinusoidal heaving motion has been studied at a Reynolds number of 100. This comprises a wide range of natural frequencies of the flexible foil, covering pre-resonance, resonance, and post-resonance regimes, with respect to the heaving frequency. The propulsion performance of the foils under different Strouhal numbers, with either fixed reduced frequency or fixed natural frequency, has also been investigated. We observed that the propulsion efficiency, thrust, and power consumption drop, but the tip deformation coefficient increases to its maximum when operating at resonance. The propulsion efficiency of the flexible dual foils increases significantly in the pre-resonance regime at small Strouhal numbers. Both thrust force and power consumption increase with the reduced frequency during the pre- and post-resonance regimes. An instability phenomenon is observed in the instantaneous tip deformation coefficient of the flexible dual foils in the post-resonance regimes. We also find that the dual heaving foils, with a larger resonance Strouhal number, achieve a greater thrust increment compared with that of rigid dual heaving foils when working at the pre-resonance regimes. Meanwhile, dual heaving foils with a smaller resonance Strouhal number can achieve a larger propulsion efficiency increment compared with that of rigid dual heaving foils when working at small Strouhal numbers.

physics.flu-dyn↗

arXiv2020

An Iterative Machine-Learning Framework for RANS Turbulence Modeling

Machine-learning (ML) techniques provide a new and encouraging perspective for constructing turbulence models for Reynolds-averaged Navier--Stokes (RANS) simulations. In this study, an iterative ML-RANS computational framework is proposed that combines an ML algorithm with transport equations of a conventional turbulence model. This framework maintains a consistent procedure for obtaining the input features of an ML model in both the training and predicting stages, ensuring a built-in reproducibility. The effective form of the closure term is discussed to determine suitable target variables for the ML algorithm, and the multi-valued problem of existing constitutive theory is studied to establish a proper regression system for ML algorithms. The developed ML model is trained under a cross-case strategy with data from turbulent channel flows at three Reynolds numbers and \textit{a posteriori} simulations of channel flows show that the framework is able to predict both the mean flow field and turbulent variables accurately. Interpolation tests for the channel flow show the proposed framework can reliably predict flow features that lie between the minimum and maximum Reynolds numbers associated with the training data. A further test related to the flow over periodic hills also demonstrates a better result than a traditional turbulence model, indicating a promising predictive capability of the developed ML model for separated flow even though the model is only trained with planar channel flow data.

physics.flu-dyn↗

arXiv2019

Thermal transients in a U-Bend

We study numerically the propagation of a hot thermal transient through a U-bend via an ensemble of wall-resolved large eddy simulations. Conjugate heat transfer between fluid and solid domains is accounted for. The flow is in a fully turbulent mixed convection regime, with a bulk Reynolds number of $10,000$, a Richardson number of $2.23$, and water as the working fluid (Prandtl number = $6$). These conditions lead to strong thermal stratification, with buoyancy-induced secondary flows, and the generation of a large and persistent recirculation region. The evolution of Dean vortices as the thermal transient passes is studied. It is found that baroclinic vorticity generation dominates over a large period of the transient, due to the thermal inertia of the wall. Gravitational buoyancy leads to a reversal of the counter-rotating vortex pair. The impact of this reversal on the swirl-switching and secondary-current losses is assessed. It is found that low frequency modes are suppressed in the reversed-vortex state.

physics.flu-dyn↗