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This paper presents an optimal vehicle and seat suspension design for a half-car vehicle model to reduce human-body vibration (whole-body vibration). A genetic algorithm is applied to search for the optimal parameters of the seat and vehicle suspension. The desired objective is proposed as the minimization of a multi-objective function formed by the combination of seat suspension working space (seat suspension deflection), head acceleration, and seat mass acceleration to achieve the best comfort of the driver. With the aid of Matlab/Simulink software, a simulation model is achieved. In solving this problem, the genetic algorithms have consistently found near-optimal solutions within specified parameters ranges for several independent runs. For validation, the solution obtained by GA was compared to the ones of the passive suspensions through sinusoidal excitation of the seat suspension system for the currently used suspension systems.

Original scientific paper https://doi.org/10.2298/TSCI160413083AThe effects of Hall current and Joule heating on flow and heat transfer of a nanofluid along a vertical cone in the presence of thermal radiation is considered. The flow is subjected to a uniform strong transverse magnetic field normal to the cone surface. Similarity transformations are used to convert the non-linear boundary-layer equations for momentum and energy equations to a system of non-linear ordinary differential equations which are then solved numerically with appropriate boundary conditions. The solutions are presented in terms of local skin friction, local Nusselt number, velocity, and temperature profiles for values of magnetic parameter, Hall parameter, Eckert number, radiation parameter, and nanoparticle volume fraction. Comparison of the numerical results made with previously published results under the special cases, the results are found to be in an excellent agreement. It is also found that, nanoparticle volume fraction parameter and types of nanofluid play an important role to significantly determine the flow behavior.

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The study of rotating nanofluid flows has a vital role in several applications such as in food processing, rotating machinery, cooling systems, and chemical fluid. The aims of the present work are to improve the thermophysical properties of convective flow and heat transfer for unsteady nanofluid past a moving rotating plate in the presence of ohmic, viscous dissipations, Brownian, and thermophoresis diffusion. The system is strained under the effect of strong magnetic field, and then the Hall current is considered. For this investigation, three different types of the nanoparticles Cu (copper), Al2O3 (aluminium oxide), and TiO2 (titanium dioxide) with various shapes (spherical, cylindrical, and brick) are considered, and water is used as a base nanofluid. The system governing equations are solved semianalytically using homotopy perturbation technique. In order to validate the present work, different comparisons are made under some special cases with previously published results and found an excellent agreement. It is observed that the shape of nanoparticles plays a substantial role to significantly determine the flow behaviour. Also, it can be found that the use of the cylindrical nanoparticle shape has better improvement for heat transfer rate compared with the other nanoparticle shapes.

Many biodynamic models have been derived using trial and error curve-fitting technique, such that the error between the computed and measured biodynamic response functions is minimum. This study developed a biomechanical model of the human body in a sitting posture without backrest for evaluating the vibration transmissibility and dynamic response to vertical vibration direction. In describing the human body motion, a three biomechanical models are discussed (two models are 4-DOF and one model 7-DOF). Optimization software based on stochastic techniques search methods, Genetic Algorithms (GAs), is employed to determine the human model parameters imposing some limit constraints on the model parameters. In addition, an objective function is formulated comprising the sum of errors between the computed and actual values (experimental data). The studied functions are the driving-point mechanical impedance, apparent mass and seat- to-head transmissibility functions. The optimization process increased the average goodness of fit and the results of studied functions became much closer to the target values (Experimental data). From the optimized model, the resonant frequencies of the driver parts computed on the basis of biodynamic response functions are found to be within close bounds to that expected for the human body

Many biodynamic models have been derived using trial and error curve-fitting technique, such that the error between the computed and measured biodynamic response functions is minimum. This study developed a biomechanical model of the human body in a sitting posture without backrest for evaluating the vibration transmissibility and dynamic response to vertical vibration direction. In describing the human body motion, a three biomechanical models are discussed (two models are 4-DOF and one model 7-DOF). Optimization software based on stochastic techniques search methods, Genetic Algorithms (GAs), is employed to determine the human model parameters imposing some limit constraints on the model parameters. In addition, an objective function is formulated comprising the sum of errors between the computed and actual values (experimental data). The studied functions are the driving-point mechanical impedance, apparent mass and seatto-head transmissibility functions. The optimization process increased the average goodness of fit and the results of studied functions became much closer to the target values (Experimental data). From the optimized model, the resonant frequencies of the driver parts computed on the basis of biodynamic response functions are found to be within close bounds to that expected for the human body.

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