Numerical investigations are carried out to investigate the reduction in the aerodynamic drag of a vehicle by employing a dimpled non-smooth surface. The computational scheme was validated by the experimental data reported in literature. The mechanism and the effect of the dimpled non-smooth surface on the drag reduction were revealed by analysing the flow field structure of the wake. In order to maximize the drag reduction performance of the dimpled non-smooth surface, an aerodynamic optimization method based on a Kriging surrogate model was employed to design the dimpled non-smooth surface. Four structure parameters were selected as the design variables, and a 16-level design-ofexperiments method based on orthogonal arrays was used to analyse the sensitivities and the influences of the variables on the drag coefficient; a surrogate model was constructed from these. Then a multi-island genetic algorithm was employed to obtain the optimal solution for the surrogate model. Finally, the surrogate model and the simulation results showed that the optimal combination of design variables can reduce the aerodynamic drag coefficient by 5.20%.

Ride comfort and handling performances are known conflicts for off-road vehicles. Recent publications focus on passenger vehicles on class B and class C roads, while, for off-road vehicles, they should be able to run on rougher roads: class D, class E, or class F roads. In this paper, a quarter vehicle model with nonlinear damping is established to analyze the suspension performance of a medium off-road vehicle on the class F road. The ride comfort, road holding, and handling performance of the vehicle are indicated by the weighted root mean square (RMS) value of the vertical acceleration of the sprung mass, suspension travel, and tire deflection. To optimize these objectives, the genetic algorithm (GA), particle swarm optimization (PSO), and a genetic algorithm based on the particle swarm optimization (GA-PSO) are initiated. The efficiency and accuracy of these algorithms are compared to find the best suspension parameters. The effect of the optimized method is validated by the field test result. The ride comfort, road holding, and handling performance are improved by approximately 20%.

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Eddy current brake (ECB) is an attractive contactless brake whereas it suffers from braking torque attenuation when the rotating speed increases. To stabilize the ECB's torque generation property, this paper introduces the concept of anti-magneto-motive force to develop the ECB model on the fundamental of magnetic circles. In the developed model, the eddy current demagnetization and the influence of temperature which make the braking torque attenuation are clearly presented. Using the developed model of ECB, the external and internal characteristics of the ECB are simulated through programming by MATLAB. To find the sensibility of the influences on ECB's torque generation stability, the stability indexes are defined and followed by a sensibility analysis on the internal parameters of an ECB. Finally, this paper indicates that (i) the stability of ECB's torque generating property could be enhanced by obtaining the optimal combination of "demagnetization speed point and the nominal maximum braking torque. " (ii) The most remarkable influencing factor on the shifting the demagnetization speed point of ECB was the thickness of the air-gap. (iii) The radius of pole shoe's cross section area and the distance from the pole shoe center to the rotation center are both the most significant influences on the nominal maximum braking torque.

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The influence of variable operational conditions affects the performance of particle collection and separation of a regenerative air vacuum sweeper. Therefore, the purpose of this paper was to numerically investigate the factors affecting the particle suction efficiency of the pick-up head. Using computational fluid dynamics (CFD), a model of an integrated pick-up head was developed based on the particle suction process to evaluate the particle removal performance. The realizable k-ε and discrete particle models were utilized to study the gas flow field and solid particle trajectories. The particle structure, sweeping speed, secondary airflow, pressure drop, and distance between the particle suction port and the road surface, as factors that affect the particle removal efficiency, were investigated. The results indicate that the particle suction efficiency increases with decreasing sweeper speed. Furthermore, the particle overall removal efficiency increased with a reduction in the distance between the suction port and the road surface as well as the control of the secondary airflow in the system. By increasing the airflow rate at the suction port, high efficiencies were achieved at a high sweeper speed and high particle densities. At a sweeper speed of 6–10 km/h, the results showed that the secondary airflow recirculation varied between 60 to 80 %, while the high-pressure drop ranged from 2200 to 2400 Pa, and the particle suction efficiency recorded was 95%. The numerical analysis results provide a better understanding of the particle suction process and hence could lead to an improvement in the design of the pick-up head.

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