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This numerical study investigates flow and turbulence structure through and around a circular array of solid circular cylinders of diameter $d$ . The region containing the array of rigid cylinders resembles a porous circular cylinder of diameter $D$ . The porous cylinder Reynolds number defined with the steady incoming flow velocity is $\\mathit{Re}_{D}=10\\,000$ . Fully three-dimensional (3D) large eddy simulations (LES) are conducted to study the effects of the volume fraction of solids of the porous cylinder ( $0.023<\\text{SVF}<0.2$ ) and $d/D$ on the temporal variation and mean values of the drag/lift forces acting on the solid cylinders and on the porous cylinder. The effects of the bleeding flow through the circular porous cylinder on the wake structure and the influence of the SVF and $d/D$ on the onset of flow three-dimensionality within or downstream of the porous cylinder and transition to turbulence are discussed. Results are compared with experimental data, predictions of theoretical models available in the literature and also with the canonical case of a solid cylinder ( $\\text{SVF}=1,d/D=1$ ). Three-dimensional LES predict that large-scale wake billows are shed in the wake of the porous cylinder for $\\text{SVF}>0.05$ , similar to the von Karman vortex street observed for solid cylinders. As the SVF decreases, the length of the separated shear layers (SSLs) of the porous cylinder and the distance from the back of the porous cylinder at which wake billows form increase. For sufficiently low volume fractions of solids (e.g.  $\\text{SVF}=0.05$ , 0.023), no wake billows are shed and the interactions among the wakes of the solid cylinders are weak. Even for $\\text{SVF}=0.023$ , SSLs containing large-scale turbulent eddies form on the two sides of the porous cylinder, but their ends cannot interact to generate wake billows. In both regimes, the force acting on some of the solid cylinders within the array is highly unsteady. As opposed to results obtained based on 2D simulations, no intermediate regime in which the force acting on the solid cylinders is close to steady is present. Interestingly, an energetic low frequency corresponding to a Strouhal number defined with the diameter of the porous cylinder of approximately 0.2 is present within the porous cylinder and near-wake regions not only for cases where wake billows are generated but also for cases where no wake billows form. In the latter cases, this frequency is due to an instability acting on the SSLs which induces in-phase large-scale undulatory deformations of the two SSLs. A combined drag parameter for the porous cylinder ${\\it\\Gamma}_{D}=\\overline{C}_{d}\\,aD/(1-\\text{SVF})$ is introduced, where $aD$ is the non-dimensional frontal area per unit volume of the porous cylinder. This parameter characterizes by how much the velocity of the bleeding flow at the back of the porous cylinder is reduced compared with the incoming flow velocity for a given total drag force acting on the porous cylinder. Results from simulations conducted with different values of the SVF, $d/D$ and mean time-averaged solid cylinder streamwise drag parameter, $\\overline{C}_{d}$ , show that ${\\it\\Gamma}_{D}$ increases monotonically with increasing $aD$ . Several ways of defining the spatial extent of the wake region in a less ambiguous way are proposed.

This study investigates the effects of an air layer on drag reduction and turbulence dynamics in channel flow over a superhydrophobic surface (SHS). Employing the OpenFOAM platform, direct numerical simulation was conducted to investigate turbulent channel flow with an air layer over an SHS. The simulations, which take into account the interaction between water and air, analyze various parameters such as velocity distribution, drag reduction (DR), Reynolds stress, turbulent kinetic energy (TKE), and coherent structures near the water–air interface. The presence of an air layer significantly alters the velocity distribution, leading to higher velocities at the interface compared to simulations without the air layer. Notably, the thickness of the air layer emerges as an important factor, with larger thicknesses resulting in increased velocities and drag reduction. This study underscores the substantial impact of the air layer on TKE near the superhydrophobic surface, emphasizing its role in understanding and optimizing drag reduction. Furthermore, the nonlinear relationship between slip velocity, Q contours, and coherent structures near the SHS are investigated.

This paper presents a three-dimensional modeling approach to simulate the thermal performance of a Li-ion battery module for a new urban car. A single-battery cell and a 52.3 Ah Li-ion battery module were considered, and a Newman, Tiedemann, Gu, and Kim (NTGK) model was adopted for the electrochemical modeling based on input parameters from the discharge experiment. A thermal–electrochemical coupled method was established to provide insight into the temperature variations over time under various discharge conditions. The distribution temperature of a single-battery cell was predicted accurately. Additionally, in a 5C discharge condition without a cooling system, the temperature of the battery module reached 114 °C, and the temperature difference increased to 25 °C under a 5C discharging condition. This condition led to the activation of thermal runaway and the possibility of an explosion. However, the application of a reasonable fan circulation and position reduced the maximum temperature to 49.7 °C under the 5C discharge condition. Moreover, accurate prediction of the temperature difference between cell areas during operation allowed for a clear understanding and design of an appropriate fan system.

The thermal performance of a lithium-ion battery module comprising three cells contained within a casing was investigated at discharge rates of 3C and 5C with three different cooling strategies: forced air, phase-change material (PCM), and a hybrid system using a combination of forced air and the PCM. Three levels of fan speed (5000 rpm; 7000 rpm; and 9000 rpm) for cooling air flow were considered. A numerical simulation of heat transfer was performed using the ANSYS Fluent software. The electrochemical modelling of a battery was developed based on the NTGK approach, and the phase-change phenomenon was treated as an enthesis–porosity problem. The composite PCM, aluminum metal foam embedded in n-octadecane, had better heat dissipation performance than forced air convection. The PCM is significantly more effective at heat dissipation than forced air. Interestingly, when using a hybrid cooling system that combines forced air and a PCM, although it meets the operational requirements for Li-ion batteries in regard to maximum temperature and temperature uniformity at a 3C discharge rate, the airflow appears to have a negligible effect on thermal management and yields an indiscernible change in temperature. This can be attributed to a complex flow pattern that developed in a casing as a result of the suboptimal design of the inlet and outlet. Further studies will be required for the optimal positioning of the inlet and outlet, as well as the effectiveness of combining liquid cooling methods.

In the present work, the three-dimensional heat and fluid flows around staggered pin-fin arrays are predicted using two hybrid RANS/LES models (an improved delayed detached eddy simulation (IDDES) model and a stress-blended eddy simulation (SBES) model), and one transitional unsteady Reynolds averaged Navier-Stokes (URANS) model, called k-ω SSTLM. The periodic segment geometry with a total of nine pins is considered with a channel height of 2D and a distance of 2.5D between each pin. The corresponding Reynolds number based on the pin diameter and the maximum velocity between pins is 10,000. The two hybrid RANS/LES results show the superior prediction of the mean velocity profiles around the pins, pressure distributions on the pin wall, and Nusselt number distributions. However, the transitional model, k-ω SSTLM, shows large discrepancies except in front of the pins where the flow is not fully developed. The vortical structures are well resolved by the two hybrid RANS/LES models. The SBES model is particularly adept at capturing the 3-D vortex structures after the pins. The effects of the blending function switching between RANS and LES mode of the two hybrid RANS/LES models are also investigated.

The exploration of superhydrophobic drag reduction has been and continues to be of significant interest to various industries. In the present work, direct numerical simulation (DNS) is utilized to investigate the effect of the parameters on the drag-reducing performance of superhydrophobic surfaces (SHS). Simulations with a friction Reynolds number of 180 were carried out at solid fraction values of ϕs=116,111, and 14, and three distribution shapes: aligned, staggered, and random. The top wall is the smooth one, and the bottom wall is a superhydrophobic surface (SHS). Drag reduction and Reynolds stress profiles are compared for all cases. The turbulent kinetic energy budget, including production, dissipation, and diffusion, is presented with respect to the solid fraction and type of distribution to investigate the drag reduction mechanism. The sizes of the longitudinal vortices and formation of hairpin vortices are investigated through the observation of coherent structures. The simulation of a post model is a useful method to study the drag reduction for different solid fraction values and distribution geometries. Our study demonstrates that the drag reduction could acquire 42% with the solid fraction value ϕs=116 and an aligned distribution shape for post superhydrophobic surface geometry. Our study also showed the relationship of the Reynolds stress component (R11, R22, and R33) to the drag reduction with the differences in the solid fraction values and distribution geometry. In which, the R11 component has the most change between an aligned distribution and a random one. The peak value of R11 tends to shift away from the SHS wall. In addition, the analysis of the TKE budget over the superhydrophobic surface was performed, which can be adopted as a useful resource in turbulence modeling based on RANS methodology.

In the present work, a comparative study of two major non-intrusive polynomial chaos methods, Point-Collocation Non-Intrusive Polynomial Chaos (NIPC) and Non-Intrusive Spectral Projection (NISP), was conducted for the transitional γ − R θ transitional model. Three multiple model coefficients, Ca2, Ce1, and Ce2 were considered with multiple random inputs with the assumption of uniform distributions with ±10% deviation. The target transitional flows were one around a flat plate and Aerospatiale A-airfoil. Deterministic solutions were obtained by employing the open source software OpenFOAM. The results of two methods were compared to the results of Monte Carlo simulation with 500 runs. The order convergence of the mean value and the standard deviation (STD) were compared in terms of the quantities of interest, drag and lift coefficients. Further, the most effective model coefficient for each transitional flow could be found through the calculation of the Sobol index.

Owing to their frequent occurrence in the natural environment, there has been significant interest in refining our understanding of flow over dunes and other bedforms. Recent work in this area has focused, in particular, on their shear-layer characteristics and the manner by which flow structures are generated. However, field-based studies, are reliant on single-, or multi-point measurements, rather than delimiting flow structures from the velocity gradient tensor, as is possible in numerical work. Here, we extract pointwise time series from a well-resolved large eddy simulation as a means to connect these two approaches. The at-a-point analysis technique is termed the velocity-intermittency quadrant method and relates the fluctuating, longitudinal velocity, $u_{1}^{\\prime }(t)$ , to its fluctuating pointwise Hölder regularity, $\\unicode[STIX]{x1D6FC}_{1}^{\\prime }(t)$ . Despite the difference in boundary conditions, our results agree very well with previous experiments that show the importance, in the region above the dunes, of a quadrant 3 ( $u_{1}^{\\prime }<0$ , $\\unicode[STIX]{x1D6FC}_{1}^{\\prime }<0$ ) flow configuration. Our higher density of sampling beneath the shear layer and close to the bedforms relative to experimental work reveals a negative correlation between $u_{1}^{\\prime }(t)$ and $\\unicode[STIX]{x1D6FC}_{1}^{\\prime }(t)$ in this region. This consists of two distinct layers, with quadrant 4 ( $u_{1}^{\\prime }>0$ , $\\unicode[STIX]{x1D6FC}_{1}^{\\prime }<0$ ) dominant near the wall and quadrant 2 ( $u_{1}^{\\prime }<0$ , $\\unicode[STIX]{x1D6FC}_{1}^{\\prime }>0$ ) dominant close to the lower part of the separated shear layer. These results are consistent with a near-wall advection of vorticity into a region downstream of a temporarily foreshortened reattachment region, and the entrainment of slow moving and quiescent fluid into a faster, more turbulent shear layer. A comparison of instantaneous vorticity fields to the velocity-intermittency analysis shows how the pointwise results reflect larger-scale organisation of the flow. We illustrate this using results from two instantaneous datasets. In the former, extreme velocity-intermittency events corresponding to a foreshortened recirculation region (and high pressures on the stoss slope of the dune immediately downstream) arise, and the development of intense flow structures occurs as a consequence. In the other case, development of a ‘skimming flow’ with relatively little exchange between the inner and outer regions results in exceedances because of the coherence associated with this high velocity, high turbulence outer region. Thus, our results shed further light on the characteristics of dune flow in the near-wall region and, importantly for field-based research, show that useful information on flow structure can be obtained from single-point single velocity component measurements.

The thermal performance of a large-format (52.3 Ah) Li-ion pouch battery with an n-octadecane PCM was investigated. A simplified 1D model was employed to estimate the transient thermal behavior. Two design parameters, the thickness and the thermal conductivity of the PCM, were considered. A 0.5 mm thick n-octadecane PCM integrated with aluminum foam reduced the battery temperature to 34.3 °C and 50.7 °C at the end stage of discharging under 3C and 5C discharge rates, respectively. The 1D results compared to the 3D results were able to predict the temperature dissipation by the PCM method at the end of discharging. The 1D approach clearly produced reliable results in predicting the thermal behavior of the PCM cooling and was superior in practical applications with its low cost and time consumption. A 3D CFD simulation was able to describe the detailed temperature uniformity in the cell, which is an important factor in the design and evaluation of a battery cooling system.

In the present work, supersonic flows over an axisymmetric base and a 24-deg compression ramp are investigated using the generalized k-ω (GEKO) model implemented in the commercial software, ANSYS FLUENT. GEKO is a two-equation model based on the k-ω formulation, and some specified model coefficients can be tuned depending on the flow characteristics. Uncertainty quantification (UQ) analysis is incorporated to quantify the uncertainty of the model coefficients and to calibrate the coefficients. The Latin hypercube sampling (LHS) method is used for sampling independent input parameters as a uniform distribution. A metamodel is constructed based on general polynomial chaos expansion (gPCE) using ordinary least squares (OLS). The influential coefficient closure is obtained by using Sobol indices. The affine invariant ensemble algorithm (AIES) is selected to characterize the posterior distribution via Markov chain Monte Carlo sampling. Calibrated model coefficients are extracted from posterior distributions obtained through Bayesian inference, which is based on the point-collocation nonintrusive polynomial chaos (NIPC) method. Results obtained through calibrated model coefficients by Bayesian inference show superior prediction with available experimental measurements than those from original model ones.