S. Sivasankaran

Experimental Investigation on Mechanical and Turning Behavior of Al 7075/x% wt. TiB2-1% Gr In Situ Hybrid Composite

The present research work involves the study of AA 7075-TiB2-Gr in situ composite through stir casting route. This in situ method involves formation of reinforcements within the matrix by the chemical reaction of two or more compounds which also produces some changes in the matrix material within the vicinity. Titanium Diboride (TiB2) and graphite were the reinforcement in a matrix of AA 7075 alloy. The composite was prepared with the formation of the reinforcement inside the molten matrix by adding salts of Potassium Tetrafluoroborate (KBF4) and Potassium Hexafluorotitanate (K2TiF6). The samples were taken under casted condition and the properties of the composite were tested by conducting characterization using X-ray diffraction (XRD), hardness test, flexural strength by using three-point bend test, scanning electron microscope (SEM), optical microstructure, grain size analysis, and surface roughness. It was found that good/excellent mechanical properties were obtained in AA 7075-TiB2-Gr reinforced in situ hybrid composite compared to alloy due to particulate strengthening of ceramic particles of TiB2 in the matrix. Further, Al 7075-3% TiB2-1% Gr hybrid in situ composite exhibited improved machinability over the alloy and composites due to self-lubricating property given by the Gr particles in the materials.

Structural Characterization and Mechanical Behavior of Al 6061 Nanostructured Matrix Reinforced with TiO2 Nanoparticles for Automotive Applications

The main aims of the present chapter are to: learn synthesis procedure of AA 6061‐x wt.% TiO 2 nanocomposites (x = 0, 2, 4, 6, 8, 10 and 12 wt.%) by mechanical alloying (MA); inves‐ tigate structural characterization of manufactured nanocomposite powders using X‐ray line profile analysis, scanning electron microscope (SEM) and transmission electron microscope (TEM); examine consolidation method and mechanical behavior in terms of sintered density, Vickers hardness and compressive stress‐strain behavior; study the improvement of ductility in nanocomposites; and simulate the mechanical behavior using ANSYS. Here, the synthesized nanocomposites via MA were consolidated using conventional uniaxial die compaction; then, the green compacts were sintered at differ‐ ent temperatures. TEM microstructures of as‐milled powder samples showed the matrix crystallite sizes ranging from 45 to 75 nm, which depended on the amount of reinforce‐ ment. A remarkable decrease in matrix powder particles size with the function of rein‐ forcement was observed due to the ceramic nano TiO 2 particles acted as milling agent. The sintered nanocomposites yielded maximum strength of 1.126 GPa. The study of tri‐ modeled composite and its mechanical behavior revealed the possibility of achieving improvements in ductility and toughness for nanocomposites. The simulated mechanical behavior results using finite element method were good agreement with experimental results.

Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413) Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique

Artificial Neural Network (ANN) approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. The experiments are carried out with different controlled input variables such as squeeze pressure, die preheating temperature, and melt temperature as per Full Factorial Design (FFD). The accounted absolute process variables produce a casting with pore-free and ideal fine grain dendritic structure resulting in good mechanical properties such as hardness, ultimate tensile strength, and yield strength. As a primary objective, a feed forward back propagation ANN model has been developed with different architectures for ensuring the definiteness of the values. The developed model along with its predicted data was in good agreement with the experimental data, inferring the valuable performance of the optimal model. From the work it was ascertained that, for castings produced by squeeze casting route, the ANN is an alternative method for predicting the mechanical properties and appropriate results can be estimated rather than measured, thereby reducing the testing time and cost. As a secondary objective, quantitative and statistical analysis was performed in order to evaluate the effect of process parameters on the mechanical properties of the castings.

Multi-Objective Optimization of EDM Parameters Using Grey Relational Analysis for Titanium Alloy (Ti–6Al–4V)

In this paper optimization of the electrical discharge machining (EDM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis was studied and investigated. A grey relational grade obtained from the grey relational analysis is used to solve the EDM process. Optimal machining parameters are determined by considering the grey relational grade as the performance index. The input independent parameters of peak current, pulse on time and pulse off time were examined and optimized on multiple response characters (material removal rate, electrode wear ratio and surface roughness). Experimental results have shown that machining performance in the EDM process can be improved effectively through this approach.

Heat treatment effect on CNC turning of Incoloy 800H superalloy

ABSTRACT Nuclear power plant components, high-temperature furnace, and most of the nuclear reactors are in need of high creep rupture which can be attained by Incoloy 800H superalloy. Based on this, the present research work is aimed to relate the microstructure, mechanical, and machinability of Incoloy 800H in various conditions, namely, solution treated, heat-treated with air cooling, and heat-treated with furnace cooling. The samples were initially heated till 975°C after solution treated and then subjected to the aforesaid heat treatments. The optical microstructures revealed that the fine grains’ structure was obtained in the air-cooled sample, whereas coarse grain structure was obtained in a furnace-cooled sample. The heat-treated samples were machined using CNC dry turning process and the machining parameter effects on the machinability aspects were studied, investigated, and reported. Experimental investigations explained clearly that the machinability aspects were significantly influenced by the cooling medium. Furnace-cooled sample had shown improvement in mechanical and machinability performances.

Cold deformation of dezincification resistant yellow brass for plumbing applications

ABSTRACT In the present work, the room temperature deformation behavior of dezincification-resistant (DZR) brass was performed by varying strain rates (1 × 10−4 s−1, 0.55 × 10−3 s−1, 1 × 10−3 s−1, 0.55 × 10−2 s−1, 1 × 10−2 s−1) and percent cold works (15 to 65% with step of 10%). These parameters are important to plumbing parts of its forming. Room temperature deformation workability map was developed that provides the selection of safe deformation parameters without cracking. The as-received and deformed DZR brass samples were carefully characterized by various microscopes. The results revealed that more dislocations lines and twinning were observed through transmission electron microscope images as the strain rate (SR) increases which led to early failure of the sample before reaching the set height reduction. It was determined that more amount of strain hardening with designed height reduction was achieved at lower SR whereas less amount of strain hardening was achieved at higher SR due to strain mismatching phenomenon and various deformation mechanisms.

Experimental Investigation of Friction Stir Processed Al7075 Aluminium Plate Reinforced with Al2O3/1% Gr Hybrid Surface Nanocomposite

Hybrid Metal matrix composites provide huge opportunities to optimize the engineering enforcement in metal matrix composites for applicable in the automotive and aerospace industries, where unique filler content and selective protected areas of reinforcements are needed. There are various efforts have been carried out to study the mechanical action of particle reinforced aluminium based composites. In this present study, Friction stir processing (FSP) is used to carry out reinforcement study on the commercially available Al7075 Al sheet metals reinforced with aluminium oxide of different sizes (75μm,150μm & 200μm) and percentage (2%, 4%, 6% & 8% -Al2O3) and 1% graphite (Gr). It has been described that these composites showed significant development in hardness, strength and related properties, as well as improved wear performance compared to fundamental alloys. It is well known that MMCs containing small-size reinforcements which are ideal materials for application in high performance and wear resistant components due to their appealing physical and mechanical properties. To meet the above requirements, the samples were subjected to microstructure examination and hardness study. It was noted that there is significant improvement in the hardness value and the grain size was considerably reduced.

Optimizing the Supercharger Effect on the Performance and Emission of Biogas Diesel Engine using ANFIS

An Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was introduced in this study, to optimize the supercharger effect in performance and emission of a single cylinder diesel engine which uses a fuel blend of biogas and diesel. The input parameters used in the ANFIS model are the fuel blend ratios of Biogas with Diesel and load where as the output parameters are specific fuel consumption (SFC), brake thermal efficiency (BTE), indicated thermal efficiency (ITE), mechanical efficiency (ME), indicated mean effective pressure (IMEP), carbon monoxide (CO) and oxides of nitrogen (NOx). The ANFIS model result is to check the feasibility for predicting the relationships between the input and the output parameters and they were assessed with experimental values. Thus experimental and ANFIS model results show the correlation coefficient of 99.85% for ITE, IMEP and 99.99% for CO, NOx emission.

Investigations on the microstructure and mechanical property of friction stir processed AA6061 aluminium sheet metal reinforced with Al2O3 surface composite

Friction stir processing (FSP) is an emerging surface engineering technology that can eliminate casting defects locally by refining microstructures, thereby, improving the mechanical properties of the material. In this study, the influence of the FSP on the microstructure and mechanical properties in terms of hardness for commercially available AA6061 Al sheet metals reinforced with aluminium oxide was studied and investigated. Samples were subjected to FSP by varying the rotational and traverse speed. From the microstructural evaluation, it was observed that the grain size of the processed area was around 70% decreased as compared to unprocessed parent metal. The hardness results showed that the strength of stirred surface area was around 1.75 times higher than the unstirred surface area. Further wear test showed that the wear resistance were increased with respect to increase in rotational and traverse speed.