Design and analysis of an automotive bumper beam in low-speed frontal crashes

In this paper, the most important parameters including material, thickness, shape and impact condition are studied for design and analysis of an automotive front bumper beam to improve the crashworthiness design in low-velocity impact. The simulation of original bumper under condition impact is according to the low-speed standard of automotives stated in E.C.E. United Nations Agreement, Regulation no. 42, 1994. The bumper beam analysis is accomplished for composite and aluminum material to compare the weight and impact behavior. The strength in elastic mode is investigated with energy absorption and impact force in maximum deflection situation.A good design of this part of automotives must prepare for the safety of passengers; meanwhile, should have low weight. Beside the role of safety, fuel efficiency and emission gas regulations are being more important in recent years that encourage manufacturer to reduce the weight of passenger cars.In this research, a front bumper beam made of three materials: aluminum, glass mat thermoplastic (GMT) and high-strength sheet molding compound (SMC) is studied by impact modelling to determine the deflection, impact force, stress distribution and energy-absorption behavior. The mentioned characteristics are compared to each other to find best choice of material, shape and thickness. The results show that a modified SMC bumper beam can minimize the bumper beam deflection, impact force and stress distribution and also maximize the elastic strain energy. In addition, the effect of passengers in the impact behavior is examined. The time history of the calculated parameters is showed in graphs for comparison. Furthermore, beside the above-mentioned benefits, some more advantages like easy manufacturing due to simple shape without-ribs, economical aspects by utilizing low-cost composite material and reducing weight with respect to others can be achieved by SMC material.     

The effect of Persian Gulf tidal zone exposure on durability of mixes containing silica fume and blast furnace slag

In this research the performance of cement paste and concrete mixes incorporating 7% and 10% of silica fume (SF) as a cement replacement was investigated in three exposure conditions. The results showed that plain type II portland cement performed better than blended SF cement under cyclic wetting and drying conditions. Silica fume specimens under cyclic wetting and drying conditions in simulated seawater exhibited higher strength loss compared to plain type II portland cement where cured under potable water. In addition, the greater the silica fume amount used in the mixes, the more the capillary water absorption under tidal zone exposure or/and under wetting and drying simulation. Further, the ternary blended ground granulated blast furnace slag (GGBS) mix was the worst performing mix in all exposure conditions.     

ARO: A new model-free optimization algorithm inspired from asexual reproduction

This paper proposes a new individual based optimization algorithm, which is inspired from asexual reproduction known as a remarkable biological phenomenon, called as Asexual Reproduction Optimization (ARO). ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, each individual produces an offspring called bud through a reproduction mechanism; thereafter parent and its offspring compete according to a performance index obtained from the underlying objective function of the given optimization problem. This process leads to the fitter individual. ARO's adaptive search ability and its strong and weak points are described in this paper. Furthermore, the ARO convergence to the global optimum is mathematically analyzed. To approve the effectiveness of the ARO performance, it is tested with several benchmark functions frequently used in the area of optimization. Finally, the ARO performance is statistically compared with that of Particle Swarm Optimization (PSO). Results of simulation illustrate that ARO remarkably outperforms PSO.     

Estimation of Kinetic Parameters for Hydrogenation Reactions Using a Genetic Algorithm

The kinetics of acetylene hydrogenation in a fixed‐bed reactor of a commercial Pd/Al₂O₃ catalyst has been studied. The hydrogenation reactor considered in this work is an essential part of a vinyl chloride monomer (VCM) plant. Three well‐known kinetic models were used to simulate the hydrogenation reactor under industrial operating conditions. Since none of the models provide appropriate prediction, the industrial data and calculated values were compared and optimum kinetic parameters were evaluated utilizing a genetic algorithm (GA) technique. The best kinetic parameters for the three models were determined under specified industrial operating conditions. The hydrogenation reactor was simulated using the estimated optimum kinetic parameters of the three models. Simulation results from the three models were compared to industrial data and the best kinetic model was found. This kinetic model with the evaluated optimum kinetic parameters can well predict the behavior of the industrial hydrogenation reactor to improve the performance of the process.     

Extraction of indium from zinc plant residues

The main purpose of this study was to extract indium from the Irankoh zinc plant residue. The Irankoh zinc plant residue contained 145 ppm indium. The optimum conditions for leaching of indium and reduction of ferric ion in reductive leaching were obtained at temperature of 90 °C for a leaching duration of 3 h with sulfuric acid concentration of 100 g/L and the amount of required sodium sulfide for reduction of ferric was 1.5 times of stoichiometric quantity of iron. Then, to prepare concentrated indium solution, indium was selectively precipitated from the leach solution. The pH of leach solution was adjusted to 6 with ammonia solution in 90 °C for selective indium precipitation, and reaction time was considered to be 10 min. Then the resulting precipitation was dissolved using hot sulfuric acid solution, and the solution was subject to solvent extraction and cementation using zinc powder to recover indium.     

Dynamic polar diagram

The polar diagram [C.I. Grima, A. Márquez, L. Ortega, A new 2D tessellation for angle problems: The polar diagram, Computational Geometry 34 (2006) 58-74] of a set of points on the plane and the contracted dual of polar diagram (CDPD) [B. Sadeghi Bigham, A. Mohades, The dual of polar diagrams and its extraction, in: International Conference of Computational Methods in Sciences and Engineering ICCMSE, vol. 7, Greece, 2006, pp. 451-454] have been introduced recently. In this paper, we introduce the Dynamic Polar Diagram and present an algorithm to find it using CDPD and a hash structure for point location problem. In the dynamic polar diagram, the points can be added to or removed from the point set. For this problem, a brute-force method runs in O(nlogn) time and also there is a sketch of an algorithm in [C.I. Grima, A. Márquez, L. Ortega, A new 2D tessellation for angle problems: The polar diagram, Computational Geometry 34 (2006) 58-74] that takes O(n) time in all cases (best, average and worst). In our approach, we first determine an area out of which the polar diagram does not change due to insertion or deletion of a site. Then we present a new algorithm to solve the problem in O(kp) time where kp is the number of the sites whose polar regions are affected by the new addition or deletion of p.     

Effect of synthesis conditions on the properties of wet spun polypyrrole fibres

High molecular weight doped polypyrrole (PPy) has been synthesized by the incorporation of the di(2-ethylhexyl) sulfosuccinate dopant anion which renders the polymer soluble in various organic solvents. The intrinsic viscosity of PPy solutions show that the molecular weight of PPy is very sensitive to the polymerization temperature. A significant increase in molecular weight was achieved by reducing the polymerization temperature from 0 to −15 °C. The resultant solutions were amenable to a wet-spinning process that produced continuous, doped polypyrrole fibres. The ultimate tensile strength, elastic modulus and elongation at break of the higher molecular weight fibres were 136 MPa, 4.2 GPa and 5%, respectively. These values were 500%, 250% and 280% higher than obtained from the lower molecular weight fibers. X-ray diffraction showed that the low temperature PPy powder exhibited a similar degree of ordering to the standard PPy powder. UV and FT-IR spectroscopy showed that the conjugation length of PPy could be increased significantly depending on the polymerization conditions. Cyclic voltammetry demonstrated the electroactivity of the polypyrrole fibres. These fibres are likely to be important for bionic, electronic textile, artificial muscles, battery and sensor applications.     

Neural network approach for determination of fatigue crack depth profile in a metal, using alternating current field measurement data

A neural-network-based technique is described to determine the depth profile of a fatigue crack in a metal from the output signal of an alternating current field measurement (ACFM) probe. The main feature of this technique is that it requires only the measurements along the crack opening. The network uses the multilayer perceptron structure for which the training database is established by systematically producing semi-elliptical multi-hump cracks with narrow openings and random lengths and depth profiles. A fast pseudo-analytic ACFM probe output simulator is also used to produce network input data around each crack for a specified inducer. To demonstrate the accuracy of the proposed inversion technique, the simulated results of cracks with both common and complex geometries are studied. The comparison of the actual and reconstructed depth profiles substantiates the technique introduced here. To further validate the technique, the experimental results associated with several fatigue cracks of complex geometries are presented.     

High performance 1.28 /spl mu/m GaInNAs double quantum well lasers

The use of multiple quantum wells and GaAs barriers favours the temperature stability and modulation bandwidth of GaInNAs lasers. It is shown that a very low threshold current density and a high characteristic temperature can be achieved for GaInNAs/GaAs double quantum well lasers, emitting at 1.28 /spl mu/m, when grown by molecular beam epitaxy under favourable conditions.     

Rehabilitation of the Parkinson's tremor by using robust adaptive sliding mode controller: a simulation study

One of the efficient methods in controlling the Parkinson''s tremor is Deep Brain Stimulation (DBS) therapy. The stimulation of Basal Ganglia (BG) by DBS brings no feedback though the existence of feedback reduces the additional stimulatory signal delivered to the brain. So this study offers a new adaptive architecture of a closed‐loop control system in which two areas of BG are stimulated simultaneously to decrease the following three indicators: hand tremor, the level of a delivered stimulation signal in the disease condition, and the level of a delivered stimulation signal in health condition to the disease condition. One area (STN: subthalamic nucleus) is stimulated with an adaptive sliding mode controller and the other area (GPi: Globus Pallidus internal) with partial state feedback controller. The simulation results of stimulating two areas of BG showed satisfactory performance.Inspec keywords: bioelectric phenomena, diseases, variable structure systems, brain models, biomedical electrodes, adaptive control, closed loop systems, state feedback, feedback, neurophysiology, brain, robust controlOther keywords: DBS, additional stimulatory signal, adaptive architecture, closed‐loop control system, hand tremor, delivered stimulation signal, disease condition, health condition, partial state feedback controller, Parkinson''s tremor, robust adaptive sliding mode controller, simulation study, efficient methods, Deep Brain Stimulation therapy, Basal Ganglia