Application of impact energy absorption systems in different industries especially in automotive industries as a solution to minimize the effect of impact onto the travelers and increasing car safety is especially significant. In order to increase the car security in accidents and incidents of cars, several efforts have been done by corporations. For this purpose, different energy absorption systems have been utilized. From all of them, thin-walled tubes due to lightness, high value of energy absorption capacity, long crushing length, and high ratio of energy absorption into weight have everincreasing application as one of the effective energy absorption systems. In this research, by carrying out experiments and finite element simulations, crushing manner, energy absorption value, mean crushing load, and initial buckling load of grooved thin-walled tubes with different geometric dimensions have been investigated and compared. Simulation of tested specimens has been executed in three-dimensional model by explicit method. Experimental and simulation results have a correlation. Results demonstrate that crushing manner and absorbed energy value in axial crushing of grooved thin-walled tubes could be controlled by introducing different groove distances.
In this paper, the He's variational iteration method and Adomian's decomposition method are employed to solve the Prochhammer–Chree equation which include various models. Results derived from the two methods are compared graphically. Figures illustrate that results obtained from both methods are in excellent agreement and show powerful reliability and efficiency of these methods.
High-pressure jet-assisted turning is an effective method to decrease the cutting force and surface roughness. Efficiency of this process is related to application of proper jet pressure proportional to other process parameters. In this research, experiments were conducted for high-pressure jet-assisted turning in finishing AISI 304 austenitic stainless steel, based on response surface method. Against the expectations, the maximum jet pressure could not lead to the most efficient results, which means that applying high-pressure jet-assisted turning without considering optimal process parameters will diminish the improving effects of high-pressure jet assistance. For this purpose, two artificial neural networks were trained by genetic algorithm to model the surface roughness and cutting force based on the process parameters. Ultimately, nondominated sorting genetic algorithm was implemented for multi-objective optimization of process. Results demonstrated that the employed method provides an effective approach that indicates optimized range of process parameters.
In this research, axial crushing of grooved thin-walled steel tubes with different geometric dimensions has been investigated by carrying out experiments and finite element simulation. The crushing manner, load-displacement curves and initial crushing load have been studied. The simulations have been performed by ABAQUS 6.7 software in 3-D model and explicit method. Grooves were modeled circumferentially and alternately inside and outside the tubes. Quasi-static axial load was applied. The results obtained from experiments and simulations are in a good agreement. Results demonstrate that crushing manner and initial crushing load in axial crushing of grooved thin-walled tubes could be controlled by introducing different groove distances.
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