Computers & Fluids最新文献

The Richtmyer–Meshkov (RM) instability widely exists in variety of industrial and scientific applications, such as in inertial confinement fusion, astrophysics explosions, supersonic combustion, bubble dynamics and cavitation. This study investigates the unfolding physical phenomena of RM instability at ${\text{SF}}_6$ elliptical bubbles using numerical simulations. In contrast to cylindrical bubble, both shocked horizontal/vertical-aligned elliptical bubbles with different aspect ratios are considered, emphasizing the aspect ratio effects on flow morphology, complex wave patterns, interface deformation, vorticity generation, and interface features. For this purpose, a two-dimensional system of compressible Navier–Stokes–Fourier equations for multicomponent flows are solved using by a mixed modal discontinuous Galerkin method. Numerical simulations illustrate that the aspect ratio of elliptical bubbles have a significant influence on the vortex dynamics and the associated RM instability flows in contrast to the cylindrical bubble. In horizontal-aligned elliptical bubbles, some additional complex waves pattern, including inward jet and secondary vortex rings are observed. While, in vertical-aligned elliptical bubbles, the interface between two primary vortex rings is always vertical and has a “hippocampus” appearance due to the enhancement of downstream velocity. The baroclinic vorticity due to misalignment of density and pressure gradients at interface affects the bubble deformation and induces the Kelvin–Helmholtz instability, which leads to turbulent mixing. It is observed that the complexity of the vorticity fields is enhanced with increasing aspect ratios. Further, these aspect ratio effects result in integral diagnostic of important spatially integrated fields, and various interface features.

The placement of temperature sensitive and safety-critical components is crucial in the automotive industry. It is therefore inevitable, even at the design stage of new vehicles, that these components are assessed for potential safety issues. However, with increasing number of design proposals, risk assessment using Computational Fluid Dynamics (CFD) quickly becomes expensive. We therefore present a parameterized surrogate model for the prediction of three-dimensional flow fields in aerothermal vehicle simulations. The proposed physics-informed neural network (PINN) design is aimed at learning families of flow solutions according to a geometric variation. The novelty of our method compared to existing works in the field of PINN lies in the extension of parametric flow prediction to three-dimensional space by applying a mini-batch based Quasi-Newton optimization. We contribute a parametric minibatch training algorithm which enables the utilization of the large datasets necessary for the three-dimensional flow modeling. Further, we introduce a continuous resampling algorithm that allows to represent domain variations, while operating on one static dataset of reduced size. In scope of this work, we could show that our nondimensional, multivariate scheme can be efficiently extended to predict the velocity and pressure distribution in three-dimensional space for different design scenarios and geometric scales. Every feature of our methodology is tested individually and verified against conventional CFD simulations. Finally, we apply our proposed method in context of an exemplary real-world automotive application.

Experimental tests accessing both fluid and structure behaviors are mandatory for a consistent and comprehensive assessment of fluid–structure interaction (FSI) numerical simulations. In this paper, recently published results of an experimental configuration of two in-line cantilever cylinders subjected to water cross-flow were considered: instantaneous fluid velocities measurements are available on several positions inside the test section, together with the cylinder vibrations. FSI simulations were performed by coupling Ansys Fluent (for the fluid domain) with Ansys Mechanical (for the solid domain). URANS simulations and Scale-Adaptive Simulations (SAS) were employed as CFD simulation approach. The structure displacements were taken into account through an Arbitrary Lagrangian–Eulerian approach. The fluid–structure coupling was 2-way explicit. Simulations were performed for two different water mass flow rates. For the highest one, vortex-induced resonance was observed experimentally. The numerical results show consistent agreement in terms of shedding frequency and velocity spectra behind the cylinders. The calculated vibration response is overall consistent, despite some underestimations, for the cylinders not featuring vortex-induced resonance; nevertheless, the experimentally observed vortex-induced resonance could not be reproduced by the numerical simulations.

Freezing tightly couples the water and heat flow. In most porous media, the interface between liquid and frozen water is not sharp and a slushy zone is present. There are two distinct approaches for mathematical modelling of freezing. It is the equilibrium approach which allows an instant freezing under given conditions and non-equilibrium approach where a specific timing in the freezing process is considered. In this contribution, we specifically target the equilibrium approach.

The key mathematical model for the equilibrium approach is the Clausius–Clapeyron equation, which allows the derivation of a soil freezing curve relating temperature to pressure head. Implementing freezing soil accurately is not a straight-forward. Using the Clausius–Clapeyron equation creates a discontinuity in the freezing rate and latent heat at the freezing point. Little attention has been paid to the adequate description of the numerical treatment of this phenomenon and to the computational challenges that it poses. Numerical approximation of this discontinuous system is prone to spurious oscillations. In this contribution, we show the application of regularization of the discontinuous term. This treatment successfully stabilizes the computation and can remove oscillations. To avoid over-regularization, we present here a minimax strategy to determine optimal regularization parameters. We further compare an over-regularized setup with the non-equilibrium approach, where we show that a successful regularization is equivalent to incorporating a minimal timing to the freezing process. Finally – for validating our implementation and computational approach – experimental laboratory data of the volumetric water content and temperature profiles from previously published soil freezing experiments were represented here with the optimally regulized equilibrium approach.

Numerical simulation of gas flow in low permeability formations is a challenging task due to the high nonlinearity induced by (i) the compressibility of the gas, (ii) the Klinkenberg slippage effect and (iii) the Langmuir adsorption of the gas on the pore surface. Because of these nonlinearities, modeling gas flow in low permeability formations requires a great deal of computational effort. In this work, we develop an efficient numerical model using advanced spatial and temporal discretization methods for a simultaneous solution of the coupled equations of gas flow, cubic Peng-Robinson equation of state, slippage effect and Langmuir adsorption. The spatial discretization is performed with the lumped hybrid formulation of the mixed finite element method which is well adapted for fluid flow in heterogeneous porous media. The time integration is performed with high-order methods via the method of lines (MOL) which allows large time steps and efficient solution of the nonlinear system of equations. Numerical experiments, performed for gas extraction in a heterogeneous domain, point out the high efficiency of the new model since it can be until 10 times more efficient than the classical first-order time discretization method. Results of global sensitivity analysis show that the intrinsic gas-phase permeability and the Klinkenberg factor are the most influential parameters controlling the pumping rate in the case of gas extraction in a homogeneous domain.

This study assesses various subgrid-scale models within the framework of Large Eddy Simulation (LES) using a remeshed Vortex method (RVM). RVM is a semi-Lagrangian method discretizing the vorticity-velocity Navier–Stokes equations that has proven to be a stable and less dissipative alternative to more classical Eulerian methods. The subgrid-scale models are first tested on the well-known Taylor–Green Vortex case at $Re=5000$. Notably, the Variational Multiscale (VMS) variant of the Smagorinsky model and the Spectral Vanishing Viscosity (SVV) approaches emerge as the best-suited to the RVM, as they add diffusion to only the smallest resolved vorticity scales. Then, a stochastic uncertainty quantification analysis is conducted for both selected models, and the model coefficients are calibrated against direct numerical simulation. These coefficients are then applied to additional cases (different regimes, grid resolutions and test cases), showing the robustness of the calibration within the RVM-LES framework.

Our paper proposes an innovative approach for modeling Fluid–Structure Interaction (FSI). Our method combines both traditional monolithic and partitioned approaches, creating a hybrid solution that facilitates FSI. At each time iteration, the solid mesh is immersed within a fluid–solid mesh, all while maintaining its independent Lagrangian hyperelastic solver. The Eulerian mesh encompasses both the fluid and solid components and accommodates various physical phenomena. We enhance the interaction between solid and fluid through anisotropic mesh adaptation and the Level-Set methods. This enables a more accurate representation of their interaction. Together, these components constitute the Adaptive Immersed Mesh Method (AIMM). For both solvers, we utilize the Variational Multi-Scale (VMS) method, mitigating potential spurious oscillations common with piecewise linear tetrahedral elements. The framework operates in 3D with parallel computing capabilities. Our method’s accuracy, robustness, and capabilities are assessed through a series of 2D numerical problems. Furthermore, we present various three-dimensional test cases and compare their results to experimental data.

The Rayleigh–Taylor (RT) instability in inertial confinement fusion implosions evolves at the unstable interface of two fluids when the light fluid is pushing the heavy one. The effects of the initial amplitude and transition layer on the compressible RT instability are investigated numerically by using the discrete Boltzmann method. On the one hand, during the RT evolution, higher initial amplitudes initially increase the global density gradient and non-equilibrium area, with a subsequent reversal. The increasing initial amplitude leads to an initial rise followed by a decline in the system’s maximum Mach number. On the other hand, the impact of the transition layer is generally opposite to the one of initial amplitude in the RT process. These findings offer significant insights into controlling and understanding RT instability in fusion implosion scenarios, emphasizing novel aspects relative to existing literature.

The motion and coalescence of a coaxial bubble pair rising in a liquid metal column under horizontal magnetic fields were numerically examined using the VOF method in this present paper. The MHD (Magnetohydrodynamics) effects on the characteristics of rise velocity, flow field, and coalescence process of bubble pair by considering various wall confinement ratios (Cr) were analyzed. The results indicate that the effects of magnetic field and wall confinement on the coalescence of the coaxial bubbles are non-monotonic. For smaller Cr, a higher initial rise velocity of the bubbles is generated by strengthening the counter-rotating toroidal vortices around bubbles in the initial stage, but the terminal rise velocity decreases in the stable stage. In the presence of the magnetic field, both the initial rise velocity and terminal rise velocity decrease. A horizontal magnetic field makes the flow field around the bubbles be anisotropic by weakening the toroidal vortices on both sides of the bubbles along the magnetic field direction, which also dampens the wake vortices of the leading bubble and thus reduces the attractive force of wake effect acting on the tailing bubble. On the other hand, the downward Lorentz force induced by the magnetic field on the top of the leading bubble suppresses its upward motion, which makes the tailing bubble collide with the leading bubble earlier. As the competition between the above two mechanisms varies with the magnetic field strength, the coalescence time of the bubble pair also changes accordingly. Particularly, a strong horizontal magnetic field tends to promote the bubbles coalescence under the wall effects and delay that when the wall effects are minor or negligible. For Ha=771, bubbles coalescence at Cr=2 is about 32 % earlier than that at Cr=4.

The computation of periodic flows is typically conducted over multiple periods. First, a number of periods is used to develop periodic characteristics, and afterwards statistics are collected from averages over multiple periods. As a consequence, it is uncertain whether the numerical results are exactly time-periodic, and additionally, the time domain might be needlessly long. In this article, we circumvent these concerns by using a time-periodic function space. Consequently, the boundary conditions and solutions are exactly periodic. We employ the isogeometric analysis framework to achieve higher-order smoothness in both space and time. The discretization is performed using residual-based variational multiscale modeling and weak boundary conditions are adopted to enhance the accuracy near the moving boundaries of the computational domain. We enforce the time-periodic boundary condition within the isogeometric discretization spaces, which converts the two-dimensional time-dependent problem into a three-dimensional boundary value problem. Furthermore, we determine the boundary velocities of moving hydrofoils directly from the computational mesh and use a conservation methodology for force extraction. Application of the computational setup to heaving and pitching hydrofoils displays very accurate and exactly periodic results for lift and drag.