arXiv subjects

Man Long Wong

Publications and source records attributed to Man Long Wong.

7 recordsLinked to original sources

arXiv2025

WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics

This paper presents a new open-source high-fidelity dataset for Machine Learning (ML) containing 355 geometric variants of the Windsor body, to help the development and testing of ML surrogate models for external automotive aerodynamics. Each Computational Fluid Dynamics (CFD) simulation was run with a GPU-native high-fidelity Wall-Modeled Large-Eddy Simulations (WMLES) using a Cartesian immersed-boundary method using more than 280M cells to ensure the greatest possible accuracy. The dataset contains geometry variants that exhibits a wide range of flow characteristics that are representative of those observed on road-cars. The dataset itself contains the 3D time-averaged volume & boundary data as well as the geometry and force & moment coefficients. This paper discusses the validation of the underlying CFD methods as well as contents and structure of the dataset. To the authors knowledge, this represents the first, large-scale high-fidelity CFD dataset for the Windsor body with a permissive open-source license (CC-BY-SA).

physics.flu-dyn↗

arXiv2022

A positivity-preserving Eulerian two-phase approach with thermal relaxation for compressible flows with a liquid and gases

A positivity-preserving fractional algorithm is presented for solving the four-equation homogeneous relaxation model (HRM) with an arbitrary number of ideal gases and a liquid governed by the stiffened gas equation of state. The fractional algorithm consists of a time step of the hyperbolic five-equation model by Allaire et al. and an algebraic numerical thermal relaxation step at an infinite relaxation rate. Interpolation and flux limiters are proposed for the use of high-order Cartesian finite difference or finite volume schemes in a general form such that the positivity of the partial densities and squared sound speed, as well as the boundedness of the volume fractions and mass fractions, are preserved with the algorithm. A conservative solution update for the four-equation HRM is also guaranteed by the algorithm which is advantageous for certain applications such as those with phase transition. The accuracy and robustness of the algorithm with a high-order explicit finite difference weighted compact nonlinear scheme (WCNS) using the incremental-stencil weighted essentially non-oscillatory (WENO) interpolation, are demonstrated with various numerical tests.

physics.comp-ph↗

arXiv2022

Analysis of second-moments and their budgets for Richtmyer-Meshkov instability and variable-density turbulence induced by re-shock

Nonlinear Richtmyer--Meshkov instability and mixing transition induced by a Mach 1.45 shock and subsequent re-shock at an interface between two ideal gases (sulfur hexafluoride and air) with high Atwood number are studied with second-moment analysis using data from high-resolution compressible Navier--Stokes simulations. The analysis first addresses the importance of two second-order moments: turbulent mass flux and density-specific-volume covariance, together with their transport equations. These quantities play an essential role in the development of Favre-averaged Reynolds stress and turbulent kinetic energy in this variable-density flow. Then, grid sensitivities and the time evolution of the turbulent quantities which include the second-moments are investigated, followed by a detailed study of the transport equations for the second-moments including the Reynolds stress and the turbulent kinetic energy with well-resolved data before re-shock. After re-shock, budgets of the same but large-scale turbulent quantities are studied with the effects of the subfilter-scale stress taken into account. The budgets of these large-scale quantities are shown to have an insignificant influence from the numerical regularization. Finally, the effects of the subfilter-scale stress on the budgets of the large-scale turbulent quantities with different degrees of filtering are also examined.

physics.flu-dyn↗

arXiv2021

A positivity-preserving high-order weighted compact nonlinear scheme for compressible gas-liquid flows

We present a robust, highly accurate, and efficient positivity- and boundedness-preserving diffuse interface method for the simulations of compressible gas-liquid two-phase flows with the five-equation model by Allaire et al. using high-order finite difference weighted compact nonlinear scheme (WCNS) in the explicit form. The equation of states of gas and liquid are given by the ideal gas and stiffened gas laws respectively. Under a mild assumption on the relative magnitude between the ratios of specific heats of the gas and liquid, we can construct limiting procedures for the fifth order incremental-stencil WCNS (WCNS-IS) with the first order Harten-Lax-van Leer contact (HLLC) flux such that positive partial densities and squared speed of sound can be ensured in the solutions, together with bounded volume fractions and mass fractions. The limiting procedures are discretely conservative for all conservative equations in the five-equation model and can also be easily extended for any other conservative finite difference or finite volume scheme. Numerical tests with liquid water and air are reported to demonstrate the robustness and high accuracy of the WCNS-IS with the positivity- and boundedness-preserving limiters even under extreme conditions.

physics.comp-ph↗

arXiv2020

Homogenized Flux-Body Force Treatment of Compressible Viscous Porous Wall Boundary Conditions

A homogenization approach is proposed for the treatment of porous wall boundary conditions in the computation of compressible viscous flows. Like any other homogenization approach, it eliminates the need for pore-resolved fluid meshes and therefore enables practical flow simulations in computational fluid domains with porous wall boundaries. Unlike alternative approaches however, it does not require prescribing a mass flow rate and does not introduce in the computational model a heuristic discharge coefficient. Instead, it models the inviscid flux through a porous wall surrounded by the flow as a weighted average of the inviscid flux at an impermeable surface and that through pores. It also introduces a body force term in the governing equations to account for friction loss along the pore boundaries. The source term depends on the thickness of the porous wall and the concept of an equivalent single pore. The feasibility of the latter concept is demonstrated using low-speed permeability test data for the fabric of the Mars Science Laboratory parachute canopy. The overall homogenization approach is illustrated with a series of supersonic flow computations through the same fabric and verified using supersonic, pore-resolved numerical simulations.

physics.flu-dyn↗

arXiv2020

Turbulence Enrichment using Physics-informed Generative Adversarial Networks

Generative Adversarial Networks (GANs) have been widely used for generating photo-realistic images. A variant of GANs called super-resolution GAN (SRGAN) has already been used successfully for image super-resolution where low resolution images can be upsampled to a $4\times$ larger image that is perceptually more realistic. However, when such generative models are used for data describing physical processes, there are additional known constraints that models must satisfy including governing equations and boundary conditions. In general, these constraints may not be obeyed by the generated data. In this work, we develop physics-based methods for generative enrichment of turbulence. We incorporate a physics-informed learning approach by a modification to the loss function to minimize the residuals of the governing equations for the generated data. We have analyzed two trained physics-informed models: a supervised model based on convolutional neural networks (CNN) and a generative model based on SRGAN: Turbulence Enrichment GAN (TEGAN), and show that they both outperform simple bicubic interpolation in turbulence enrichment. We have also shown that using the physics-informed learning can also significantly improve the model's ability in generating data that satisfies the physical governing equations. Finally, we compare the enriched data from TEGAN to show that it is able to recover statistical metrics of the flow field including energy metrics and well as inter-scale energy dynamics and flow morphology.

physics.comp-ph↗

arXiv2019

High-resolution Navier-Stokes simulations of Richtmyer-Meshkov instability with re-shock

The interaction of a Mach 1.45 shock wave with a perturbed planar interface between sulphur hexafluoride and air is studied through high-resolution two-dimensional (2D) and three-dimensional (3D) shock-capturing adaptive mesh refinement simulations of multi-species Navier-Stokes equations. The sensitivities of time-dependent statistics on grid resolution for 2D and 3D simulations are evaluated to ensure the accuracy of the results. The numerical results are used to examine the differences between the development of 2D and 3D Richtmyer-Meshkov instability during two different stages: (1) initial growth of hydrodynamic instability from multi-mode perturbations after first shock and (2) transition to chaotic or turbulent state after re-shock. The effects of the Reynolds number on the mixing in 3D simulations are also studied through varying the transport coefficients.

physics.flu-dyn↗