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.

Numerical simulations of a spinning projectile with a diameter of 120 mm were conducted to predict the aerodynamic coefficients, and the CFD results were compared with the semiempirical method, PRODAS. Six coefficients or coefficient derivatives, including zero and the quadratic drag coefficient, lift force coefficient derivative, Magnus force coefficient derivative, overturning moment coefficient, and spinning damping moment coefficient, which are important parameters for solving the equations of motion of the spinning projectile, were investigated. Additionally, the nonlinear behavior of these coefficients and coefficient derivatives were analyzed through the predicted flow fields. The considered Mach number ranges from 0.14 to 1.2, and the nondimensional spinning rate (PD/2V) is set to 0.186. To calculate the coefficient derivative of the corresponding force or moment, additional simulations were conducted at the angle of attack of 2.5 degrees. The simulation results were able to predict nonlinear behavior, the especially abrupt change of the predicted coefficients and derivatives at the transonic Mach number, 0.95. The simulation results, including the skin friction, pressure, and velocity field, allow the characterization of the nonlinear behavior of the aerodynamic coefficients, thus, enabling better predictions of projectile trajectories.

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 ${\varphi }_s=\frac{1}{16},\frac{1}{11}$, and $\frac{1}{4}$, 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 ${\varphi }_s=\frac{1}{16}$ 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.