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The effect of various reinforcements on the ablative composites has been discussed in this paper. The ability of phenolic resin to reside a char layer at high temperatures is the main reason to select it as a matrix. Analysis of the physical ablation process of a composite and low thermal conductivity of zirconium oxide is performed to produce Resole/carbon fabrics composites coated with a thin film of zirconium at the back side of the specimens. Different materials, such as carbon fabrics, glass fabrics, and also silica and zirconium powders have been used as reinforcements for synthesis of the composites. The specimens were prepared with three sets of compositions. The first set was produced with 37.5 wt% of Resole and 62.5 wt% of reinforcements. Another set of specimens were produced with 40wt% Resole, 40 wt% of silica and 20 wt% of zirconium. To explore the ablation characteristics of the composites in terms of insulation index, erosion rate and microscopic pattern of ablation, an oxyacetylene torch flame with heat flux of 8.35 Mw/m2 at approximately 3000°C was used. It was found from ablation test that the erosion rates of the Resole/carbon fabric specimens are 20% lower than that of the other specimens. Additionally the high insulation index of the Resole/carbon fabrics coated with zirconium, indicates that these composites are the best ablative materials in the present study. SEM observations show that the thermo mechanical and thermo physical erosion effects are the most important factors that influence the ablation process. The proper adhesion between reinforcements and matrix is important to achieve improved ablative properties.

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In this study a feed forward back propagation artificial neural network (ANN) model was established to predict Vickers microhardness in aluminum-alumina nanocomposites which have been synthesized by mechanical alloying and hot pressing. Volume percent of reinforcement, size of nanoparticles, force in microhardness test; and mechanical alloying parameters, such as time, ball to powder ratio (BPR) and speed of ball mill were used as the inputs and Vickers microhardness as the output of the model. Effective parameters in training such as learning rate, hidden layers and number of neurons, were determined by trail and error due to amount and percentage of errors. Regression analysis in train, validation and test stages; and mean squared error were used to verify the performance of neural network. Average error of predicted results was 2.67% or 2.25 Vickers. Also mean squared error for validation data was 7.76. As can be expected, ANN methods reduce the expenses of experimental investigations, by predicting the optimum parameters.

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Recently, great attention has been focused on epoxy polymers in different industrial and scientific activities, owing to superior mechanical properties and their stability in different environmental conditions. In this study, the molecular dynamics method was used to study the structure of cross-linked epoxy polymers and predict glass their transition temperature (Tg). The epoxy polymer with a certain degree of cross linking was constructed through the previously proposed cross linking procedure. A temperature cycle (300-600 K) with a constant rate was then applied to the cross-linked epoxy, and a rough estimate of the glass transition region was obtained through mean squared displacement curves. Thereafter, variation of density in terms of temperature was utilized to precisely calculate Tg. The estimated Tg was found to be in good agreement with experimental observations. Radial distribution function was finally used to investigate the effects of temperature and cross linking on the local structure of simulated polymer.

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Multi-pass welding process is one of the most applicative methods of welding in various industries. In this paper, temperature and residual stress distribution due to three pass welding of two plates made of AISI 321 stainless steel having different thicknesses is studied. Welding process consists of three welding passes of two Shielded Metal Arc Welding (SMAW) process and one Gas Tungsten Arc Welding (GTAW) process. First, the benchmark plates are manufactured and welding process is performed. The transient temperature distribution during the welding process is recorded using thermocouples attached to the welding plates. First this process simulated experimentally and temperature distribution during to welding process was measured using thermocouples. Furthermore, the final residual stress distribution after welding process is measured using incremental center hole drilling technique (ICHD). The three pass welding process was then simulated using ABAQUS finite element (FE) code. The finite element model consists of temperature-dependent properties of base metal and weld metal. Furthermore, moving heat source and the element-birth technique is implemented in FE model. Experimentally measured temperature and residual stresses provide an in-depth knowledge insight the complicated welding process. . Comparing between the results shows that the numerical predictions and experimental measurements have good agreement and therefore the FE developed model can be employed in designing and evaluating of welded structures.

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Combined shear extrusion (CSE) is a new severe plastic deformation (SPD) technique to produce bulk ultra-fine grained materials. CSE is obtained by the combination of simple and pure shear extrusion. This technique is based on definitions of pure and simple shear. In the present work, the nonlinear (large) deformation elasticity theory is used for obtaining the shear strain applied to the sample under pure shear extrusion with various angles of distortion. Also plastic deformation characteristics of CSE method were analyzed with finite element analysis using commercial Deform 3D software. Shear strain and effective strain applied to the sample, the load required to carry out the process and the final shape of the cross-sectional area were studied for different angles of distortion. Analytical results and finite element analysis shows by increasing the angles of distortion, shear strain and increased rate of shear strain applied to the sample increased so the effective strain and load required to carry out the process increases. Analysis of finite element and geometry of the die shows that distribution of shear strain and effective strain is inhomogeneously and symmetrical in specimen’s cross section which increases from the center to the corners and by increasing the angles of distortion, distribution of strain becomes more inhomogeneously, also the final shape of the cross-sectional area deforms more.

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The most successful ‘‘top–down’’ approach to produce bulk ultra-fine grained or nanostructured materials involves the use of severe plastic deformation (SPD) processing. The amount of higher effective plastic strain per pass plays a key role on the final microstructure of SPD processed samples. In the present study the numerical experiments of the combination of the equal channel angular pressing (ECAP) and simple shear extrusion (SSE) as a new process entitled “planar twist channel angular extrusion (PTCAE)” was performed based on the Response Surface Methodology (RSM), as a statistical design of experiment approach, in order to investigate the effect of parameters on the response variations, achieving the mathematical equations, predicting the results to impose higher effective plastic strain values. Α and ϕ angles, radius and friction coefficient was imposed as the input parameters while average, minimum and maximum effective strain and maximum load was imposed as the output parameters. Governing regression equations obtained after analysis of the simulation data by Minitab software. Optimum process parameters are: α=450, Φ =450, r=2 mm and µ=0.1. Verification of the optimum results using simulation experiment was done. Good agreement between simulation, experimental and optimization was occurred.