The main purpose of this research is to design a high-fatigue performance hoop wrapped compressed natural gas (CNG) composite cylinder. To this end, an optimization algorithm was presented as a combination of finite element simulation (FES) and response surface analysis (RSA). The geometrical model was prepared as a variable wall-thickness following the experimental measurements. Next, transient dynamic analysis was performed subjected to the refueling process, including the minimum and maximum internal pressures of 20 and 200 bar, respectively. The time histories of stress tensor components were extracted in the critical region. Furthermore, RSA was utilized to investigate the interaction effects of various polymer composite shell manufacturing process parameters (thickness and fiber angle) on the fatigue life of polymer composite CNG pressure tank (type-4). In the optimization procedure, four parameters including wall-thickness of the composite shell in three different sections of the CNG tank and fiber angle were considered as input variables. In addition, the maximum principal stress of the component was considered as the objective function. Eventually, the fatigue life of the polymer composite tank was calculated using stress-based failure criterion. The results indicated that the proposed new design (applying optimal parameters) leads to improve the fatigue life of the polymer composite tank with polyethylene liner about 2.4 times in comparison with the initial design.

Tanks play an important role in storing crude oil. Therefore, the maintenance and service life of tanks are very important for oil companies. In this regard, knowledge on the state of the critical conditions of various existing defects, such as cracks and pitting corrosion defects, can play an essential role in providing a better service to these huge metal structures. In the present research, the basic theories relating to crack defects were discussed. Then, an oil reserve in one of the island states of the country was modeled and analyzed by considering different types of defects using Finite Element (FE) simulation. Next, the critical dimensions of cracks and corrosion holes were identified in a number of cases. Eventually, the Taguchi Approach (TA) was used to investigate the effect of different parameters related to the various defects, such as length, depth and diameter, on the maximum stress. The results indicated that the effect of the crack and pitting corrosion depth is superior to the effect of the length and diameter for defects of crack and pitting corrosion, respectively.

During the past decade, polymer nanocomposites attracted considerable investment in research and development worldwide. One of the key factors that affect the quality of polymer nanocomposite products in machining is surface roughness. To obtain high quality products and reduce machining costs it is very important to determine the optimal machining conditions so as to achieve enhanced machining performance. The objective of this paper is to develop a predictive model using a combined design of experiments and artificial intelligence approach for optimization of surface roughness in milling of polyamide-6 (PA-6) nanocomposites. A surface roughness predictive model was developed in terms of milling parameters (spindle speed and feed rate) and nanoclay (NC) content using artificial neural network (ANN). As the present study deals with relatively small number of data obtained from full factorial design, application of genetic algorithm (GA) for ANN training is thought to be an appropriate approach for the purpose of developing accurate and robust ANN model. In the optimization phase, a GA is considered in conjunction with the explicit nonlinear function derived from the ANN to determine the optimal milling parameters for minimization of surface roughness for each PA-6 nanocomposite.

Thermoelastic behaviour of a functionally graded rotating cylinder with short length subjected to thermal and mechanical loads is studied in this article. It is assumed that the cylinder is located on a friction bed and is rotating due to an external torque. The material property is assumed to be variable along radius according to a power law distribution. Thermal conductivity equation is solved to obtain temperature distribution in terms of thermal boundary conditions and the material grading index. First-order shear deformation theory is used to derive kinematic relations. The governing equations are derived using minimum total potential energy theory and Euler relations. These governing equations are solved using method of eigenvalue and eigenvector. The physical and loading boundary conditions are applied to obtain unknown coefficients. The numerical results including stresses, strains and displacements are presented to show the influence of in-homogeneity index in longitudinal direction of the cylinder. The numerical results show that the longitudinal distributions of stresses, strains and displacements experience sharp and sudden changes at the end of the cylinder where the torsional moment is applied.

In the current research, the authors have attempted to improve the mechanical properties and creep behavior of the magnesium alloy Mg–9Al–1Zn (AZ91) in three different stress levels. To this end, the present study investigated experimentally the addition effects of different values of yttrium oxide nanoparticles to the AZ91. In this regard, weight percentages of 0.5%, 1%, 1.5%, and 2% nanoparticles were added to the material using the vortex casting method. Then, various test specimens were fabricated based on the ASTM standards by utilizing a Computer Numerical Control lathe machine. Different experiments were performed, and the results of different groups were compared with each other. The results revealed that the addition of yttrium oxide (Y₂O₃) nanoparticles increases the strength of AZ91 magnesium alloy until the nanoparticles do not clump in the microstructure. In other words, the tensile strength of the nanocomposite increased by adding nanoparticles up to 1.5%, but by adding 2% of nanoparticles, we found that the tensile strength is lower than that of pure magnesium. Moreover, one of the most important achievements of this study is that if the nanoparticles do not clump in the material microstructure, the addition of Y₂O₃ increases the rate of stable creep (the secondary creep stage). Also, the experimental results indicated that the highest stable creep rate is related to the nanocomposite with 1.5% yttrium oxide nanoparticles. Furthermore, the maximum hardness of the material was obtained in the same case.

This paper presents a three-dimensional thermo-elastic analysis of a rotating cylindrical functionally graded shell subjected to inner and outer pressures, surface shear stresses due to friction, an...