Fabrication of Wear-Resistant Ti3AlC2/Al3Ti Hybrid Aluminum Composites by Friction Stir Processing

Metallurgical and Materials Transactions A - Hybrid nanocomposites have potential as wear-resistant materials. However, synthesizing these nanocomposites by conventional molten state methods result...     

Numerical analysis of friction stir welding process

Friction stir welding (FSW), which has several advantages over the conventional welding processes, is a solid-state welding process where no gross melting of the material being welded takes place. Despite significant advances over the last decade, the fundamental knowledge of thermomechanical processes during FSW is still not completely understood. To gain physical insight into the FSW process and the evaluation of the critical parameters, the development of models and simulation techniques is a necessity. In this article, the available literature on modeling of FSW has been reviewed followed by details of an attempt to understand the interaction between process parameters from a simulation study, performed using commercially available nonlinear finite element (FE) code DEFORM. The distributions of temperature, residual stress, strain, and strain rates were analyzed across various regions of the weld apart from material flow as a means of evaluating process efficiency and the quality of the weld. The distribution of process parameters is of importance in the prediction of the occurrence of welding defects, and to locate areas of concern for the metallurgist. The suitability of this modeling tool to simulate the FSW process has been discussed. The lack of the detailed material constitutive information and other thermal and physical properties at conditions such as very high strain rates and elevated temperatures seems to be the limiting factor while modeling the FSW process.     

3D computer vision based on machine learning with deep neural networks: A review

Recent advances in the field of computer vision can be attributed to the emergence of deep learning techniques, in particular convolutional neural networks. Neural networks, partially inspired by the brain's visual cortex, enable a computer to “learn” the most important features of the images it is shown in relation to a specific, specified task. Given sufficient data and time, (deep) convolutional neural networks offer more easily designed, more generalizable, and significantly more accurate end‐to‐end systems than is possible with previously employed computer vision techniques. This review paper seeks to provide an overview of deep learning in the field of computer vision with an emphasis on recent progress in tasks involving 3D visual data. Through a backdrop of the mammalian visual processing system, we hope to also provide inspiration for future advances in automated visual processing.     

Damage Tolerant Magnesium Metal Matrix Composites: Influence of Reinforcement and Processing

A growing impetus to enhance our understanding of the behavior of magnesium-based alloys for use in weight critical applications resulted as a consequence of the low density of magnesium. In an attempt to enhance the applicability of magnesium for a wide spectrum of performance-critical applications, the addition of reinforcement to the alloy was considered as an economically affordable and potentially viable scientific alternative. In this paper are reported the results of a study aimed at understanding the influence of saffil alumina short fiber reinforcement on microstructural development of a squeeze-cast magnesium alloy. Preliminary results confirm promise of the reinforced alloy, which retains hardness, strength, and stiffness better at elevated temperatures compared to the unreinforced counterpart. However, impact strength and toughness of the reinforced alloy are inferior. The importance of the matrix alloy in governing the overall mechanical response of the composite microstructure is discussed based on fractographic observations. The importance of volume fraction of the reinforcing phase on properties of the composite microstructure is highlighted.     

Modeling and Optimization of Reactive Extraction of Gallic Acid Using RSM

Reactive extraction was experimentally investigated for recovery of gallic acid (GA) from the aqueous solution using tri-n-octylamine (TOA) as extractant in hexanol. All experiments were carried out according to statistical design in order to develop a regression model used to optimize the extraction of GA. Two independent variables were selected as: initial concentration of GA (C_GA0) in aqueous phase and concentration of TOA (C_TOA) in organic phase. The statistical analysis showed that both the independent variables had significant effect on response value, followed by the quadratic and interactive effect on response. A five-level central composite rotatable design (CCRD) was employed. Analysis of variance (ANOVA) showed a high coefficient of determination (R²?=?99.0%). The optimal extraction conditions of GA were determined as: C_GA0?=?2.01?g/L, C_TOA?=?6.8% v/v. At the optimum conditions, the experimental yield of GA was 91.9%, which was in close agreement with the predicted value of 93.2%.     

Reactive extraction of itaconic acid using tri‐n‐butyl phosphate and aliquat 336 in sunflower oil as a non‐toxic diluent

Itaconic acid finds a place in various industrial applications. It can be produced by biocultivation in a clean and environment friendly route but recovery of the acid from the dilute stream of the bioreactor is an economic problem. Reactive extraction is a promising method to recover carboxylic acid but suffers from toxicity problems of the diluent and extractant employed. So there is need for a non‐toxic extractant and diluent or a combination of less toxic extractants in a non‐toxic diluent that can recover acid efficiently. Effect of different extractants: tri‐n‐butylphosphate (TBP) (an organophosporous compound) and Aliquat 336 (a quaternary amine) in sunflower oil was studied to find the best extractant–sunflower oil combination. Equilibrium complexation constant, K_E, values of 1.789 and 2.385 m³ kmol^?1, respectively, were obtained for itaconic acid extraction using TBP and Aliquat 336 in sunflower oil. The problem of toxicity in reactive extraction can be reduced by using a natural non‐toxic diluent (sunflower oil) with the extractant. Copyright © 2010 Society of Chemical Industry     

Response of Materials During Sliding on Various Surface Textures

In the present investigation, soft materials, such as Al-4Mg alloy, high-purity Al and pure Mg pins were slid against hard steel plates of various surface textures to study the response of materials during sliding. The experiments were conducted using an inclined pin-on-plate sliding apparatus under both dry and lubricated conditions in an ambient environment. Two kinds of frictional response, namely steady-state and stick-slip, were observed during sliding. In general, the response was dependent on material pair, normal load, lubrication, and surface texture of the harder material. More specifically, for the case of Al-4Mg alloy, the stick-slip response was absent under both dry and lubricated conditions. For Al, stick-slip was observed only under lubricated conditions. For the case of Mg, the stick-slip response was seen under both dry and lubricated conditions. Further, it was observed that the amplitude of stick-slip motion primarily depends on the plowing component of friction. The plowing component of friction was the highest for the surfaces that promoted plane strain conditions and was the lowest for the surfaces that promoted plane stress conditions near the surface.     

Thermal degradation and ageing behavior of microcomposites of natural rubber,carboxylated styrene butadiene rubber latices,and their blends

The effect of microfillers on the thermal stability of natural rubber (NR), carboxylated styrene butadiene rubber (XSBR) latices, and their 70/30 NR/XSBR blend were studied using thermogravimetric method. Microcomposites of XSBR and their blend were found to be thermally more stable than unfilled samples. The activation energy needed for the degradation of polymer chain was calculated from Coats‐Redfern plot. Activation energy needed for the thermal degradation of filled samples was higher than unfilled system. It indicated the improved thermal stability of the filled samples. The ageing resistance of the micro‐filled samples was evaluated from the mechanical properties of aged samples. The thermal ageing was carried out by keeping the samples in hot air oven for 7 days at 70°C. The mechanical properties such as tensile strength, modulus at 300% elongation, and strain at break were computed. As compared to unfilled samples, micron‐sized fillers reinforced systems exhibited higher ageing resistance. Finally, an investigation was made on the influence of ion‐beam irradiation on microcomposites of NR, XSBR latices, and their 70/30 blend systems using ²⁸Si⁸⁺ performed at 100 MeV. The surface changes of the samples after irradiation were analyzed using X‐ray photoelectron spectroscopy. The results of XPS measurements revealed that the host elements were redistributed without any change in binding energies of C_1s, O_1s, and Si_2p. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Near surface stress analysis strategies for axisymmetric fretting

Fretting is essentially a surface phenomenon, but bulk stresses and material properties contribute to subsequent failure. This feature of fretting demands a thorough understanding of near surface stresses under the joint action of normal, shear and thermal loading. Axisymmetric fretting is of great concern in piping and coupling design. In this paper, we develop design tools for Near Surface Analysis (NSA) for understanding axisymmetric fretting. Axisymmetric Fretting Analysis (AFA) becomes formidable owing to localised tractions that call for Fourier transform techniques. We develop two different NSA strategies based on two-dimensional plane strain models: 2D strip model (2DS) and half-plane Flamant model (2DF). We compare the results of 2DS and 2DF with the exact results for AFA obtained using Love’s stress function in conjunction with Fourier transform. There is a good correspondence between stress components obtained from 2D-models.     

Optimization of fused filament fabrication process parameters for mechanical responses of weather-resistant polymer (acrylonitrile styrene acrylate)

Additively manufactured polymeric products for automotive, aerospace, and biomedical applications are usually intended for service in an outdoor environment with high mechanical loading conditions. The strength and sustainability of the products can be significantly degraded due to the outdoor environmental conditions such as UV light, moisture, heat, and so forth. In this research work, a novel weather-resistant polymer (WRP) material, that is, acrylonitrile styrene acrylate (ASA), has been studied. Furthermore, this work aims to study the effect of process parameters and enhance the strength of WRP (ASA) specimens using the FFF process. The optimized process parameters, that is, build orientation (BO), extrusion temperature (ET), layer thickness (LT), and printing speed (PS), were identified based on the tensile and flexural strength using the Taguchi technique and statistical analysis. The best tensile and flexural strengths for the specimen were achieved at both orientations (XYZ and ZXY) TS: 255°C ET, 0.14 mm LT, 50 mm/s PS; and FS: 245°C ET, 0.28 mm LT, 50 mm/s PS, respectively. Regression model was developed to investigate the correlation between the process parameters with tensile and flexural strength. A validation test confirmed the findings, and the error between the actual and predicted values is less than ±10%.