As accuracy of optimization can not be guaranteed without high-quality samples, the distribution of a finite number of evaluation points where experiments should be conducted in design space is an important issue, particularly when the experiment to obtain sample is expensive. To utilize limited number of evaluation points to represent the design space, optimal latin-hypercube design (OLHD), with considerable space-filling quality, is widely used as a methodology in design of experiments (DOE). However, OLHD generation requires significant time. This study focuses on further improvement of efficiency in generation of OLHD in terms of both time and latin-hypercube design (LHD) optimization. Two modified algorithms, namely the modified enhanced stochastic evolutionary (MESE) and translational propagation modified enhanced stochastic evolutionary (TPMESE) algorithms, based on existing algorithms, are proposed. The MESE algorithm is modified from the enhanced stochastic evolutionary (ESE) algorithm by using a new update method for “temperature,” while the TPMESE algorithm optimizes the LHD via translational propagation (TPLHD) instead of optimizing a random LHD like the MESE algorithm does. Their performance is evaluated by comparison with several famous heuristic algorithms and each original algorithm using optimization tests of LHDs with various sizes. For all cases, proposed algorithms show better performance of convergence than other heuristic algorithms participated in our comparison. For large and medium LHDs, the MESE algorithm faster converges to a solution with the same level as original algorithm (ESE). For large LHDs, the TPMESE algorithm is the most time efficient algorithm in obtaining near-optimal or sufficient near-optimal designs.

In this study, skin friction around a ½-scale Ahmed body was measured experimentally at a Reynolds number of Re = 2 × 10⁵. The slant angle of the Ahmed body was 25 deg, and the yaw angles ranged from 0 deg to 8 deg. This study focused on the flow structure on the slant surface under different cross-wind conditions. A force balance system was applied to measure the aerodynamic drag of the model. The global skin-friction topology was measured by applying a luminescent oil layer with a subgrid data processing algorithm. The method used to measure the skin friction was conducted for the first time on the Ahmed body. The results indicated that the technique is highly capable of extracting the skin-friction topology. For a yaw angle below 3 deg, the flow on the slant surface was not significantly affected by the cross-wind condition, and the drag of the model was nearly constant. However, at yaw angles above 3 deg, the flow on the slant surface was highly affected by the roof longitudinal vortexes on the windward side, leading to a dramatic increase in the drag of the model. High consistency in the drag and skin-friction fields was observed. The detailed skin-friction structure at different yaw angles will be discussed in this study.

The effects of on-road disturbances on the aerodynamic drag are attracting attention in order to accurately evaluate the fuel efficiency of an automobile on a road. The present study investigated the effects of cornering motion on automobile aerodynamics, especially focusing on the aerodynamic drag. Using a towing tank facility, measurements of the fluid-dynamic force acting on Ahmed models during steady-state cornering were conducted in water. The investigation included Ahmed models with slant angles θ = 25° and 35°, reproducing the wake structures of two different types of automobiles. The drag increase due to steady-state cornering motion was experimentally measured, and showed good agreement with previous numerical research, with the measurements conducted at a Reynolds number of 6 × 10⁵, based on the model length. The Ahmed model with θ = 35° showed a greater drag increase due to the steady-state cornering motion than that with θ = 25°, and it reached 15% of the total drag at a corner with a radius that was 10 times the vehicle length. The results indicated that the effect of the cornering motion on the automobile aerodynamics would be more important, depending on the type of automobile and its wake characteristics.

Coastal areas often experience high population density and intense human activity owing to the considerable value of the ocean. Therefore, devices for monitoring marine disasters are crucial for ensuring the safety of human life. Herein, we develop hemispherical spring origami (SO) triboelectric nanogenerators (TENGs) (HSO-TENGs) for self-powered ocean wave monitoring. Optimization is performed using two approaches. First, swing machine experiments are conducted to investigate the monitoring performance of the HSO-TENGs regarding wave height and period with satisfactory accuracy. To increase power generation and monitoring accuracy, the internal inertia and centroid of gravity of the HSO-TENGs are optimized with respect to the structural parameters (i.e., magnet weight, hammer height, and external swing arm length). Second, numerical simulations are performed using the smoothed-particle hydrodynamics (SPH) method to determine the most suitable fixed condition for the HSO-TENGs for sensing wave changes. Subsequently, wave tank experiments are conducted on the HSO-TENGs to determine their ability to sense wave height, period, frequency, and direction. Tests related to supplying other sensors are also conducted. Eventually, the ability of the HSO-TENGs to monitor wave direction and spreading parameters is investigated in a numerical SPH circular wave tank. The results prove that the optimized HSO-TENGs can achieve powering and sensing through the same device.