Improving city breathability has been confirmed as one feasible measure to improve pollutant dilution in the urban canopy layer (UCL). Building height variability enhances vertical mixing, but its ...impacts remain not completely explored. Therefore, both wind tunnel experiments and computational fluid dynamic (CFD) simulations are used to investigate the effect of building height variations (six height standard deviations σH = 0%–77.8%) associated to building packing densities namely λp/λf = 0.25/0.375 (medium-density) and 0.44/0.67 (compact) on city breathability. Two bulk variables (i.e. the in-canopy velocity (UC) and exchange velocity (UE)) are adopted to quantify the horizontal and vertical city breathability respectively, which are normalized by the reference velocity (Uref) in the free flow, typically set at z = 2.5H0 where H0 is the mean building height.
Both flow quantities and city breathability experience a flow adjustment process, then reach a balance. The adjustment distance is at least three times longer than four rows documented in previous literature. The medium-density arrays experience much larger UC and UE than the compact ones. UE is found mainly induced by vertical turbulent fluxes, instead of vertical mean flows. In height-variation cases, taller buildings experience larger drag force and city breathability than lower buildings and those in uniform-height cases. For medium-density and compact models with uniform height, the balanced UC/Uref are 0.124 and 0.105 respectively, moreover the balanced UE/Uref are 0.0078 and 0.0065. In contrast, the average UC/Uref in height-variation cases are larger (115.3%–139.5% and 125.7%–141.9% of uniform-height cases) but UE/Uref are smaller (74.4%–79.5% and 61.5%–86.2% of uniform-height cases) for medium-density and compact models.
•City breathability is assessed by in-canopy velocity (UC) and exchange velocity (UE).•Six building height variations withλp/λf = 0.25/0.375 and 0.44/0.67 are studied.•Flow adjustment distance is much longer than the literature (more than 10 units).•Urban model with λp/λf = 0.25/0.375 produces larger UC and UE than λp/λf = 0.44/0.67.•Taller buildings attain better ventilation but lower ones obtain smaller UC -UE.
Three-dimensional transient CFD (Computational Fluid Dynamics) simulations are performed to study the hydrodynamic performance of an ocean current turbine with a 3.0 m diameter 3-bladed rotor. ...Simulations are based on the RANS (Reynolds Averaged Navier–Stokes) equations and the shear stress transport k-ω turbulent model is utilized. The influence of yaw angle and upstream TI (turbulence intensity) on the turbine performance is studied. The CFD method is first validated using existing experimental data and good agreement is obtained. The performance of the turbine, including power, thrust and wake characteristics are then studied at different TSR (tip speed ratios). The turbine obtains a maximum coefficient of power (Cp) of 0.4642 at TSR = 6 and the coefficient of thrust (Ct) increases over the entire evaluated TSR range to a value of 0.8788 at a TSR = 10. Simulations are also performed at four different yaw angles, 0°, 5°, 10° and 15° which show that both Cp and Ct decrease as yaw angle increases. Finally simulations of three different TIs, 3%, 6% and 9%, are performed and analyzed. Results show that TI minimally affects Cp and Ct for the considered TI range, but greatly influences the downstream wake structure.
•CFD study of a 20 kW in-stream hydrokinetic turbine is performed.•Power and thrust of the turbine decrease as yaw angle increases.•Turbulence intensity hardly affects the power and thrust but influences the wake structures.
•CFD-DEM formulation, including heat and mass transfer and long-range forces is described.•Implementation of CFD-DEM in simulation of different processes is discussed.•Different applications, ...including drying, coating, mixing combustion, gasification and etc. are discussed.
With increasing the computational resources, the number of publications about coupled computational fluid dynamics – discrete element method is in the rise in the recent years. This technique is very useful, especially in simulation of fluid-solid flows in process engineering. This paper provides an introduction to CFD-DEM modeling in process engineering systems, including heat and mass transfer and long range forces, and reviews the major researches in simulation of two-phase processes such as drying, coating, granulation, crystallization, chemical reactions (including combustion, gasification and pyrolysis) and mixing. Details of implementing unresolved CFD-DEM in these applications are explained in details and major assumptions and findings are discussed.
Multiphase compressible flows are often characterized by a broad range of space and time scales, entailing large grids and small time steps. Simulations of these flows on CPU-based clusters can thus ...take several wall-clock days. Offloading the compute kernels to GPUs appears attractive but is memory-bound for many finite-volume and -difference methods, damping speedups. Even when realized, GPU-based kernels lead to more intrusive communication and I/O times owing to lower computation costs. We present a strategy for GPU acceleration of multiphase compressible flow solvers that addresses these challenges and obtains large speedups at scale. We use OpenACC for directive-based offloading of all compute kernels while maintaining low-level control when needed. An established Fortran preprocessor and metaprogramming tool, Fypp, enables otherwise hidden compile-time optimizations. This strategy exposes compile-time optimizations and high memory reuse while retaining readable, maintainable, and compact code. Remote direct memory access realized via CUDA-aware MPI and GPUDirect reduces halo-exchange communication time. We implement this approach in the open-source solver MFC 1. Metaprogramming results in an 8-times speedup of the most expensive kernels compared to a statically compiled program, reaching 46% of peak FLOPs on modern NVIDIA GPUs and high arithmetic intensity (about 10 FLOPs/byte). In representative simulations, a single NVIDIA A100 GPU is 7-times faster compared to an Intel Xeon Cascade Lake (6248) CPU die, or about 300-times faster compared to a single such CPU core. At the same time, near-ideal (97%) weak scaling is observed for at least 13824 GPUs on OLCF Summit. A strong scaling efficiency of 84% is retained for an 8-times increase in GPU count. Collective I/O, implemented via MPI3, helps ensure the negligible contribution of data transfers (<1% of the wall time for a typical, large simulation). Large many-GPU simulations of compressible (solid-)liquid-gas flows demonstrate the practical utility of this strategy.
•Heat pipe copper sheets (HPCS) for the battery thermal management system is designed.•A battery thermal management system is simulated and validated with experiments.•Temperature variation of a ...battery module in various initial conditions is reported.
This paper presents the concept of a hybrid thermal management system (TMS), including air cooling and heat pipe for electric vehicles (EVs). Mathematical and thermal models are described to predict the thermal behavior of a battery module consisting of 24 cylindrical cells. Details of various thermal management techniques, especially natural air cooling and forced-air cooling TMS are discussed and compared. Moreover, several optimizations comprising the effect of cell spacing, air velocity, different ambient temperatures, and adding a heat pipe with copper sheets (HPCS) are proposed. The mathematical models are solved by COMSOL Multiphysics®, the commercial computational fluid dynamics (CFD) software. The simulation results are validated against experimental data indicating that the proposed cooling method is robust to optimize the TMS with HPCS, which provides guidelines for further design optimization for similar systems. Results indicate that the maximum module temperature for the cooling strategy using forced-air cooling, heat pipe, and HPCS reaches 42.4 °C, 37.5 °C, and 37.1 °C which can reduce the module temperature compared with natural air cooling by up to 34.5%, 42.1%, and 42.7% respectively. Furthermore, there is 39.2%, 66.5%, and 73.4% improvement in the temperature uniformity of the battery module for forced-air cooling, heat pipe, and HPCS respectively.
Flows of solid particles are known to exhibit a clustering instability-dynamic microstructures characterized by a dense region of highly concentrated particles surrounded by a dilute region with ...relatively few particles-that has no counterpart in molecular fluids. Clustering is pervasive in rapid flows. Its presence impacts momentum, heat, and mass transfer, analogous to how turbulence affects single-phase flows. Yet predicting clustering is challenging, again analogous to the prediction of turbulent flows. In this review, we focus on three key areas: (
a
) state-of-the-art mathematical tools used to study clustering, with an emphasis on kinetic theory-based continuum models, which are critical to the prediction of the larger systems found in nature and industry, (
b
) mechanisms that give rise to clustering, most of which are explained via linear stability analyses of kinetic theory-based models, and (
c
) a critical review of validation studies of kinetic theory-based models to highlight the accuracies and limitations of such theories.
Over the last decade impressive progress has been made in the theoretical understanding of transport properties of clean, one-dimensional quantum lattice systems. Many physically relevant models in ...one dimension are Bethe-ansatz integrable, including the anisotropic spin- 1 / 2 Heisenberg (also called the spin- 1 / 2 XXZ chain) and the Fermi-Hubbard model. Nevertheless, practical computations of correlation functions and transport coefficients pose hard problems from both the conceptual and technical points of view. Only because of recent progress in the theory of integrable systems, on the one hand, and the development of numerical methods, on the other hand, has it become possible to compute their finite-temperature and nonequilibrium transport properties quantitatively. Owing to the discovery of a novel class of quasilocal conserved quantities, there is now a qualitative understanding of the origin of ballistic finite-temperature transport, and even diffusive or superdiffusive subleading corrections, in integrable lattice models. The current understanding of transport in one-dimensional lattice models, in particular, in the paradigmatic example of the spin- 1 / 2 XXZ and Fermi-Hubbard models, is reviewed, as well as state-of-the-art theoretical methods, including both analytical and computational approaches. Among other novel techniques, matrix-product-state-based simulation methods, dynamical typicality, and, in particular, generalized hydrodynamics are covered. The close and fruitful connection between theoretical models and recent experiments is discussed, with examples given from the realms of both quantum magnets and ultracold quantum gases in optical lattices.
In the literature on nonlinear projection-based model order reduction for computational fluid dynamics problems, it is often claimed that due to modal truncation, a projection-based reduced-order ...model (PROM) does not resolve the dissipative regime of the turbulent energy cascade and therefore is numerically unstable. Efforts at addressing this claim have ranged from attempting to model the effects of the truncated modes to enriching the classical subspace of approximation in order to account for the truncated phenomena. The objective of this paper is to challenge this claim. Exploring the relationship between projection-based model order reduction and semi-discretization and using numerical evidence from three relevant flow problems, this paper argues in an orderly manner that the real culprit behind most if not all reported numerical instabilities of PROMs for turbulence and convection-dominated turbulent flow problems is the Galerkin framework that has been used for constructing the PROMs. The paper also shows that alternatively, a Petrov-Galerkin framework can be used to construct numerically stable and accurate PROMs for convection-dominated laminar as well as turbulent flow problems, without resorting to additional closure models or tailoring of the subspace of approximation. It also shows that such alternative PROMs deliver significant speed-up factors.
•Challenges instability claims for projection-based model order reduction of turbulent flow models.•Argues that the often-observed instabilities are due to the Galerkin framework used for constructing the reduced-order model.•Demonstrates several Petrov-Galerkin projection-based reduced-order models for convection-dominated and turbulent flow problems.