Showing papers in "Computers & Fluids in 2022"

TL;DR: Agarwal et al. as mentioned in this paper reviewed recent developments for each of these components and present open-source tools available for aerodynamic shape optimization and discussed some of the issues encountered, including comparing Euler and RANS results and design space multimodality.

TL;DR: In this article , a deep learning approach for the transonic flow field predictions around airfoils is presented, which is integrated into the neural network model by utilizing Reynolds-averaged Navier-Stokes (RANS) simulations.

TL;DR: In this paper , a core analysis for the tip and hub vortices was performed using both Eulerian and Lagrangian methodologies to reproduce the wake of a marine propeller.

TL;DR: In this paper , a general family of subcell limiting strategies to construct robust high-order accurate nodal discontinuous Galerkin (DG) schemes is presented, which can be used on unstructured curvilinear meshes, are locally conservative, can handle strong shocks efficiently while directly guaranteeing physical bounds on quantities such as density, pressure or entropy.

TL;DR: In this paper , the adaptive mesh refinement wavepacket tracking (AMR-WPT) method has been developed as an efficient alternative to conventional direct numerical simulations (DNS).

TL;DR: In this paper , a physics-inspired neural network (PINN) model is proposed for direct prediction of hydrodynamic forces and torques experienced by individual particles in stationary beds of randomly distributed spheres.

TL;DR: In this paper , a data-driven approach to derive new RANS models in the wind-energy setting is presented, using a deterministic symbolic regression method to infer algebraic correction as a function of the (resolved) mean-flow.

TL;DR: In this article , a gradient-based reconstruction approach for simulations of compressible single and multi-species Navier-Stokes equations is presented, where the higher-order accurate gradients of the velocity components are reused to compute viscous fluxes for efficiency and significantly improve the solution and gradient quality.

TL;DR: In this article , the authors presented an efficient and parallel fully resolved direct numerical simulation (FR-DNS) of settling suspensions on multiple CPU cores based on the boundary-thickening direct forcing immersed boundary method (BTDF-IBM) and incompressible lattice Boltzmann method (LBM).

TL;DR: In this article , a modified lattice Boltzmann pseudopotential multiphase/multicomponent model is developed for simulating large density/viscosity ratios and tunable surface tension.

TL;DR: In this article , the effect of different numerical discretization strategies on wall-resolved and wall-modeled LES outcomes is discussed, and a turbulent boundary layer setup over a flat plate in both super- and hypersonic conditions is used to illustrate the effect.

TL;DR: In this paper, a hybrid partitioned deep learning framework for the reduced-order modeling of moving interfaces and predicting fluid-structure interaction is presented, which combines two separate data-driven models for fluid and solid subdomains via DL-ROMs.

TL;DR: In this paper , a hybrid partitioned deep learning framework for the reduced-order modeling of moving interfaces and predicting fluid-structure interaction is presented, which combines two separate data-driven models for fluid and solid subdomains via DL-ROMs.

TL;DR: In this article , the authors used the implicit Reynolds Averaged Navier-Stokes (RANS) equations and the two-equation shear stress transport (SST) k-ω turbulence model to simulate the SWBLI flow control induced by the secondary recirculation jet numerically.

TL;DR: In this paper , a Neural Network is used to extract a corrective forcing that can be applied to a low-order solution with the aim of recovering high-order accuracy, which can be used to run a low order solution (low cost) and correct the solution to obtain high order accuracy.

TL;DR: In this article, a data-driven approach to derive new RANS models in the wind-energy setting is presented, using a deterministic symbolic regression method to infer algebraic correction as a function of the (resolved) mean-flow.

TL;DR: The ability to perform gradient-free aerodynamic shape optimization using Large Eddy Simulation (LES) with the Mesh Adaptive Direct Search (MADS) optimization algorithm with a Dynamic Polynomial Approximation (DPA) procedure is demonstrated.

TL;DR: In this paper , a deep neural network based model was developed for turbulent flow around airfoil at high Reynolds numbers, which is then used to replace the Spalart-Allmaras (SA) turbulence model to mutually couple with the CFD solver.

TL;DR: In this paper, a modified projection method was proposed to recover second-order temporal accuracy for reverse osmosis in steady and unsteady flow regimes with semi-permeable membranes.

TL;DR: In this paper , a Proper Orthogonal Decomposition (POD)-Galerkin based Reduced Order Model (ROM) was developed for the efficient numerical simulation of the parametric Navier-Stokes equations in the stream function-vorticity formulation.

TL;DR: In this paper , a novel high-order bounded advection scheme is proposed in the context of the Total Variation Diminishing and Normalized Variable Diagram (TVD-NVD) constraints and then is utilized for discretization of the convection terms in the Navier-Stokes and transport equations.

TL;DR: The specific substencils of the original targeted essentially non-oscillatory (TENO) scheme, which is effective against discontinuities with a high-order interpolation, are combined with WCNS, which has the flexibility to select a numerical flux and is easily applied to general coordinates.

TL;DR: In this paper , an alternative formulation of targeted ENO scheme (AFTENO) is proposed for hyperbolic conservation laws, which can deal with strong discontinuities robustly and achieve low dissipation.

TL;DR: In this article , an explicit Poisson pressure equation (PPE) was introduced to address particle instability by improving the pressure calculation, referred to as the Weakly Compressible Moving Particle Explicit (WCMPE) method.

TL;DR: In this article , a finite volume and two Lattice-Boltzmann unsteady flow solvers using LES (Large Eddy Simulation) were compared in a swirling flow configuration, typical of aeronautical combustion chambers.

TL;DR: In this article , a second order decoupled time discretization method for solving the unsteady incompressible magneto-hydrodynamic (MHD) equations is presented.

TL;DR: In this article , a fully compressible multiphase model for simulating compressible interfacial flows is proposed, which is formulated on the basis of the typical conservation laws for mixtures, including mass, momentum, and energy balance.

TL;DR: In this article , a hybrid lattice Boltzmann model is applied to simulate low-Reynolds number viscoelastic instabilities, where the hydrodynamic field is solved using a lattice model and the polymer field is separately solved with a high-resolution finite difference scheme with the logarithmic Cholesky decomposition.

TL;DR: In this article , a physics-based reduced order model is presented as a viable approach to accurately predict unsteady flowfield solutions at a fraction of the computational time that is required by high fidelity computational fluid dynamics solvers.

TL;DR: In this article , a modified projection method was proposed to recover second-order spatial-temporal accuracy in reverse osmosis systems with semi-permeable membranes. But the method is not suitable for water desalination and advanced water treatment.