Computers & Fluids最新文献

We propose third-order A-WENO finite difference schemes that are based on the recently introduced first-order numerical schemes in [N. K. Garg et al., Journal of Computational Physics, 407(2020)] for the systems of compressible Euler equations of gas dynamics. The convective components of these schemes (fluxes), both in one- and multi-dimensions, are free from complicated Riemann solvers. Third-order characteristic-wise WENO-Z interpolations are employed to obtain the third-order point values required for the numerical fluxes. To demonstrate the robustness and accuracy of the resulting schemes, we compare the numerical results with local Lax–Friedrichs (LLF) and Harten–Lax–van Leer (HLL) fluxes on various one- and two-dimensional examples. The obtained results outperform LLF and HLL fluxes in terms of enhancing the resolution of contact waves, especially near isolated steady and moving contact discontinuities, as well as in accurately resolving high-frequency waves in one dimension (1-D) and the small-scale structures in two dimensions (2-D).

An artificial compressibility approach is proposed to compute the solution of the compressible equations in the low Mach number limit, in closed domain with moving boundaries. The low Mach number stiffness is reduced by introducing an artificial sound speed, much lower than the physical one. This allows to avoid both the acoustic time step restriction and the loss of accuracy of classical compressible solvers, without solving a Poisson equation for the pressure or using the time-implicit discretization of the Turkel-type preconditioning technique. Moreover the proposed formulation involves the conservative variables plus the dynamic pressure, which facilitates the implementation of the approach in classical CFD codes for compressible flows. The numerical experiments presented show that the approach is both accurate and CPU efficient.

Recently, Qi et al. (2022) and Guo et al. (2023) proposed two alternative designs of an efficient mesoscopic method using the total-energy double-distribution-function (DDF) formulation, hereafter referred to as the Qi model and the Guo model. The two models share the same advantage of using only 40 discrete particle velocities to fully reproduce the Navier–Stokes-Fourier (NSF) system. However, the Guo model is based on a more rigorous kinetic consideration, while the Qi model relies on a more general design of the source term to allow for adjustable bulk-to-shear viscosity ratio. In this paper, we derive lifting relations for the Qi model based on two alternative approaches, namely, the Hermite expansion and the Chapman–Enskog expansion, which can be used to construct the boundary and initial conditions for the mesoscopic method. For three-dimensional compressible turbulence simulations, including compressible decaying homogeneous isotropic turbulence and Taylor–Green vortex flows, the derived two sets of lifting relations are applied to the initialization distribution function to study their impacts. Interestingly, for the Qi model, the two sets of lifting relations yield the same results without numerical artifacts, whereas for the Guo model, an appropriate lifting relation must be specified to avoid numerical artifacts resulting from the flow initialization (Qi et al., 2023).

Droplet-based microfluidics gained significant attention for its high technological impact in various fields like (bio)analysis and (bio)synthesis. Precise and controlled droplet size is critical, for the encapsulated products, or the yield of chemical reactions. In a broad range of experimental parameters, the understanding of how droplets form, interact and move with accurate predictive models is crucial. In this work, numerical prototypes of droplet generators were made with Basilisk, an open source software for solving partial differential equations on adaptive Cartesian meshes including grid adaptation and scalability for High-Performance Computing (HPC). This research aims to analyze and compare the obtained droplets against existing experimental data. The evaluation involves qualitative and quantitative comparisons, considering various channel geometries, flow rates, and rheological conditions. The validation of the proposed tool in terms of accuracy and computational performance, enable us to offer to the microfluidics community a reliable tool to design and optimize droplet generators.

A numerical scheme with good spectral properties is important for the simulation of compressible flows with various of length scales for fine flow scales resolving. The MDAD-HY scheme (Li et al., 2022) using a discontinuity detector and scale sensor achieves the minimized dispersion and adaptive dissipation property. However, the discontinuity detector is devised based on the ratio of the 1st-order and 2nd-order derivatives on two sides of the interface introducing excessive numerical cost. To address this issue, an efficient hybrid WENO scheme with minimized dispersion and adaptive dissipation properties is proposed in this work. Based on the characteristic-decomposition approach, the numerical flux of the present hybrid scheme is achieved by switching between the linear MDAD scheme and the MDAD-WENO scheme according to a new efficient non-dimensional discontinuity detector. The linear flux is reconstructed in a component-wise method to decrease the characteristic-projection operations. To further improve the spectral property of the present scheme, an adaptive parameter controlling the contribution of the optimal linear scheme according to the discontinuity indicator is introduced. Several benchmark test cases involving broadband of length scales and discontinuities are adopted to verify the efficiency and the high-resolution capability of the present scheme.

To study the influence of energy accommodation of scattering gas molecules on flow fields during large expired spacecraft reentry, a more elaborated gas-surface interaction model, compared with full Maxwellian diffuse model, is employed in implicit algorithms based on Boltzmann model equation. The characteristic distributions around cylinder at different fluid regimes are accordingly obtained by implicit algorithms, Navier-Stokes solver and DSMC ((Direct Simulation Monte Carlo) method. And the consistency of these results is verified. It is confirmed that present algorithms are capable of solving external flow problems covering various fluid regimes. Then the simulation results see that under current conditions set in the paper, pressure and temperature are proportional to wall activation ($\omega =T_w/T_{\infty }$, $T_w$ is surface temperature, $T_{\infty }$ denotes as free stream temperature), but their amplitudes alter with $\omega$ at different fluid regimes. As for the effects of energy accommodation coefficients (${\alpha }_e$), both pressure and temperature profiles vary in a linear way with ${\alpha }_e$. However, the variation ranges of these parameters are diverse with regard to different fluid regimes. These observations are favor to the construction of efficient forecasting software, which could predict the flight path of large defunct spacecraft. In this forecasting software, the external ballistics computations and aerothermodynamic simulations are synchronously carried out.

The numerical treatment of fluid–particle systems is a very challenging problem because of the complex coupling phenomena occurring between the two phases. Although an accurate mathematical modelling is available to address this kind of applications, the computational cost of the numerical simulations is very expensive. The use of the most modern high performance computing infrastructures could help to mitigate such an issue but not completely to fix it. In this work we develop a non intrusive data-driven reduced order model (ROM) for Computational Fluid Dynamics (CFD) - Discrete Element Method (DEM) simulations. The ROM is built using the proper orthogonal decomposition (POD) for the computation of the reduced basis space and the Long Short-Term Memory (LSTM) network for the computation of the reduced coefficients. We are interested to deal both with system identification and prediction. The most relevant novelties rely on (i) a filtering procedure of the full order snapshots to reduce the dimensionality of the reduced problem and (ii) a preliminary treatment of the particle phase. The accuracy of our ROM approach is assessed against the classic Goldschmidt fluidized bed benchmark problem. Finally, we also provide some insights about the efficiency of our ROM approach.

This work introduces two new non-dimensional gradient-based adaptation indicators for feature-based polynomial adaptation with high-order unstructured methods when used for turbulent flows. Recently, the Flux Reconstruction (FR) approach has been introduced as a unifying framework for high-order unstructured spatial discretizations. To achieve high-order accuracy, FR utilizes an element-wise polynomial representation of the solution. In the current work, we consider three indicators for local adaptation of this polynomial degree. One, introduced previously, uses a non-dimensional maximal vorticity norm. Two new indicators are then introduced using the Frobenius norm of the velocity gradient, and the eigenvalue modulus of the velocity gradient, both normalized by the maximum local grid spacing and free stream velocity. These feature-based methods are simple to implement and have the potential to track small-scale turbulent structures that arise in scale-resolving simulations, such as Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES). The vorticity, gradient, and eigenvalue-based polynomial adaptation strategies with the FR approach are used to solve the compressible Navier–Stokes equations. DNS simulations are performed for unsteady laminar flow over a two-dimensional circular cylinder, turbulent flow over a three-dimensional sphere, and massively separated flow over a Martian helicopter rotor airfoil section. Results show a reduction in computational cost, with approximately one-quarter of the number of degrees of freedom relative to a non-adaptive case. The Frobenius norm method performs consistently well for all applications, and is identified as being a preferred method when compared to the vorticity and maximum eigenvalue approaches.

This paper focuses on the design and analysis of very high-order finite volume methods for the computation of simplified meso- and micro-scale atmospheric flows. In a dry atmosphere, these flows can be represented by the Euler equations with a gravitational source term. Two different approaches are considered here. While one of the approaches is fully conservative for the total energy, the other is formulated in a non-conservative form. The main focus of the paper is to analyze the performance of such models in combination with the traditional WENO reconstruction and the novel TENO reconstruction by examining the spectral properties of these reconstruction methods. The overarching goal is to determine whether the combination of these models and numerical schemes can be used to build an implicit Large Eddy Simulation framework, shedding light on their potential advantages or limitations in representing under-resolved atmospheric processes in the meso- and micro-scales.