Aluminium Silicon Carbide Metal Matrix Research Articles

Prediction of Wear Rate in Al/SiC Metal Matrix Composites Using a Neurosymbolic Artificial Intelligence (NSAI)-Based Algorithm

This research paper delves into an innovative utilization of neurosymbolic programming for forecasting wear rates in aluminum-silicon carbide (Al/SiC) metal matrix composites (MMCs). The study scrutinizes compositional transformations in MMCs with various weight percentages of SiC (0%, 3%, and 5%), employing comprehensive spectroscopic analysis. The effect of SiC integration on the compositional distribution and ratio of elements within the composite is meticulously examined. In a novel move for this field of research, the study introduces and applies neurosymbolic programming as a novel computational modeling approach. The performance of this cutting-edge methodology is compared to a traditional simple artificial neural network (ANN). The neurosymbolic algorithm exhibits superior performance, providing lower mean squared error (MSE) values and higher R-squared (R2) values across both training and validation datasets. This highlights its potential for delivering more precise and resilient predictions, marking a significant development in the field. Despite the promising results, the study recognizes that the performance of the model might vary based on specific characteristics of the composite material and operational conditions. Thus, it encourages future studies to authenticate and expand these innovative findings across a wider spectrum of materials and conditions. This research represents a substantial advancement towards a more profound understanding of wear rates in Al/SiC MMCs and emphasizes the potential of the novel neurosymbolic programming in predictive modeling of complex material systems.

Weight Optimization of Chassis of an Automotive Vehicle using ANSYS

The objective of this paper is to find out the most favourable material and immensely fitted cross-section for TATA 11O9 TRUCK ladder chassis. This research aims to optimize the weight of the chassis. For this we have taken three materials like structural steel, carbon fiber and Aluminium silicon carbide metal matrix composite. The automotive chassis is the vehicle's base, providing strength and support to the numerous body sections such as suspension, engine, power train, and so on. Recent advancements in the realm of automobiles have expanded rapidly, particularly in the current context. Problem faced by modern days vehicle is the heavy weight. So here we try to decrease the weight of chassis frame by using various method and increase the strength, efficiency of chassis. Reducing the weight of chassis results in increase in performance of vehicle, reduce fuel consumption, less wear and tear of tire. The designing of the chassis is done on software SOLIDWORKS and further analysis is done on ANSYS19.2. The current chassis mass with traditional material is 1560 Kg which is made up of structural steel, whereas the chassis mass with Aluminium carbide metal matrix composite material is 523.45 Kg. According to the analysis, the chassis mass has been reduced by 66.44%, which would eventually hinder the vehicle's performance.

Machinability and parametric optimization of aluminum silicon carbide metal matrix composite (Al-SiC MMC) machined through µ-EDM

Aluminum silicon carbide metal matrix composite (Al-SiC MMC) is widely used because of its exceptional mechanical and thermal properties. Some engineering applications include aerospace, automobile, electronics, and medical devices. In the present investigation, aluminum 7075 alloy (Al-7075) as a matrix material with reinforcement particles of 10% silicon carbide (SiC) is fabricated using stir casting. The developed Al-SiC MMC is machined using an in-house developed micro-electro discharge machine (µ-EDM) setup. Experiments are carried out with input parameters—voltage (V), capacitance (µF), and pulse-on time (µs)—to analyze the responses such as hole depth (HD), material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and circularity error (CE). Taguchi L16 orthogonal array is adopted to conduct 16 experiments with varying process parameters for 5 minutes’ duration with a copper tool electrode of Ø720 µm on the Al-SiC MMC workpiece of size 20 mm × 20 mm × 2.5 mm. The dielectric medium used for all experimentation is EDM oil. The resultant blind holes are characterized using scanning electron microscopy (SEM) images and a 3D profilometer. Later, the signal-to-noise ( S/N) ratio technique is used to optimize the process parameters to enhance individual output responses. The obtained results are discussed in the article. Further, analysis of variance (ANOVA) is performed to find out the contribution of each parameter to the output responses. Grey relational analysis (GRA) is also used for multiobjective optimization to get quality blind holes. The best parametric combination obtained through GRA are at 28 V, 100 µF, and 100 µs, resulting in 823 µm of HD, 0.38 mg/min of MRR, 0.10 mg/min of TWR, 8.98 µm of SR, and 48.37 µm of CE.

An overview of the effect of stirrer design on the mechanical properties of Aluminium Alloy Matrix Composites fabricated by stir casting

An overview of the effect of stirrer design on the mechanical properties of Aluminium Alloy Matrix Composites fabricated by stir casting

Determination of prediction model and optimization of process parameters for fabrication of Al-SiC composite using response surface methodology

ABSTRACT The study attempted to optimise the fabricating process parameters for Aluminium silicon carbide (Al-SiC) metal matrix composites (MMCs) in a centrifugal casting machine. The effects of centrifugal casting die speed, melting temperature, the wt.% of reinforcement, and particle size were investigated experimentally based on wear performance and coefficient of friction (CoF). The wt.% of reinforcement (SiC) varied from 10% to 20% and particle size from 40 to 100 µm. While the die speed and melting temperature varied from 800 to 1200 RPM and 800 to 900°C respectively. Experiments were performed according to the central composite design model. For optimisation and investigation of individual and interaction effect of each variable on wear loss, and CoF response surface methodology tool was used. The statistical study of experimental results showed that reinforcement wt.% is the most influential factor on wear, followed by die speed, particle size, and melting temperature, respectively. The increased wt.% of reinforcement, die speed, and particle size results in decreased wear loss. At the same time, the effect of melting temperature on wear loss was also observed. The effect of melting temperature on wear and CoF was the least, and an increase in melting temperature increases the wear loss, while particle size was the second most influential factor found after reinforcement wt.% on CoF. Abbreviations: MMCs Metal Matrix Composites PMCs Polymer Matrix Composites CMCs Ceramic Matrix Composites D.O.E. Design of Experiment FGMMC Functional Grade Metal Matrix Composites CoF Coefficient of FrictionCCD Central Composite Design RSM Response Surface Methodology ANN Artificial Neural Network GRA Grey Relational Analysis ASTM American Society for Testing and Materials ANOVA analysis of variance Al-SiC Aluminium Silicon Carbide

Investigating the influence of composite spur - worm gear model used in thermal press application

In the modern world, composites have dominated most industries over the forecast period and are an excellent replacement for the currently used metallic steel as a gear material. Hence, the main objective of the research work is to focus on designing an efficient composite spur–worm gear system, implementing analytical calculations with comparing different simulation studies to determine the overall strength and safety of the gears used in thermal hot press application. Here, both gears of Aluminium Silicon Carbide (Al-SiC) metal matrix composite material have been selected. The composite used in the study is cost-efficient compared to the remaining composite materials and proved to be of greater use in industrial applications. Different analysis was conducted on the spur–worm gear system to compare its performance for safer strength design and optimization of the gears. Total deformation and von-Mises equivalent stress were the results obtained through the investigation, which played a crucial role in determining the safety and strength of the gear system used in the thermal press application by satisfying the mesh convergence test.

Impact of Magnetic Field Environment on the EDM Performance of Al-SiC Metal Matrix Composite.

In the present work, a hybrid magnetic field assisted powder mixed electrical discharge machining had been carried out on the Aluminum-Silicon Carbide (Al-SiC) metal matrix composite. The aim of the study was to obtain higher surface finish, and enhanced material removal rate. The dielectric mediums employed were plain EDM oil, SiCp mixed and graphite powder mixed EDM oil for flushing through the tube electrode. The magnetic field intensity, discharge current, T-on/off duration and type of dielectric were the control variables used for present investigation. From the results, it was observed that the machining variables for instance, discharge current, T-on/off duration and type of dielectric conditions remarkably affected the material removal rate, micro-hardness and surface roughness of the machined composite material. The MRR augmented considerably with an increase in the magnetic field intensity along with peak current. Subsequently, the composite with lesser vol.% of SiC particulates witnessed sharp rise in MRR in maximum magnetic field environment (0.66T). In addition, quality of the machined surface improved significantly in graphite powder mixed dielectric flushing condition with intermediate external magnetic field environment. Besides, an enhancement of micro-hardness was quantified as compared to base material due to the transfer of the material (SiCp) during powder mixed ED machining.

Optimisation of Drilling Parameters of Metal Matrix Composites using Genetic Algorithm in the Taguchi Method

This work presents the machining parameters optimization on machining metal matrix composites using genetic algorithm in the Taguchi method with the objectives of minimization of surface roughness, cutting force, maximization of metal removal rate, cutting power, specific cutting energy, cutting power and machining time. Experiments were conducted on aluminium silicon carbide Metal Matrix composite using TiN coated HSS twist drills. Optimal setting of parameters have been identified using Taguchi Technique and Genetic algorithm. Genetic algorithm is developed in ‘C’ language. The presented work gives a better results and it can be used for any machining parameter optimization in solving multiple response problems.

Dielectric Fluid Parameter Optimization in Machining of Composite Material using WEDM Process

Wire Electric Discharge Machining (WEDM) has become most popular among the non-conventional machining processes because of precise machining and accuracy of parts. The process is preferable for accurate machining of complex geometries in hard materials such as Aluminium Silicon Carbide metal matrix composite. In this work, an attempt is made to analyze and optimize the dielectric fluid parameters in machining of Al/SiCp 10% work material. The input variables such as volume flow rate, flow velocity and chemical composition of dielectric medium used in the WEDM are chosen for this. Taguchi’s L9 orthogonal array is used to conduct experiments in WEDM machine and ANOVA results have confirmed the influence of chosen parameters on the output responses. Computer simulation model of the WEDM tank with dielectric fluid, work piece and nozzle is presented using Fluent software. The Fluent model is analyzed based on the maximum removal of debris in the work material. Optimization is carried out to maximize the Material Removal Rate (MRR) and minimize surface roughness. The results obtained from Taguchi’s optimization and Fluent analysis have been validated by carrying out tests on WEDM. The study shows that volume flow rate and flow pressure can adequately influence MRR and surface roughness.

Vibration and Acoustic Characteristics of Aluminium Silicon Carbide Metal Matrix Composite Under Uniform and Non Uniform Thermal Environment

Vibration and acoustic characteristics of metal matrix composite - (MMC) of aluminium Silicon carbide is compared with aluminium in lower frequencies. The free and forced vibration responses of different percentage of silicon carbide are examined for different percentage of buckling temperature under uniform and non uniform temperature distribution. The results show that temperature field at higher % of buckling temperature influences the acoustic response significantly. Also it is noticed that uniform temperature field, (T(x) = Tmax) and Increase and decrease temperature fields modelled by heating at the middle of the panel ( $T(x)= T_{max}[1-abs (1-\frac {2x}{L})^{2}]$ )) temperature field affects the response significantly. Further, it is noticed in all the aspects high % of silicon carbide contributes in high stiffness and there by reduces noises at low frequencies even under different temperature field. Also from the results obtained in lower frequencies, it is found that nearly 5 to 15 dB of noise is reduced for high stiffness associated mixture of silicon carbide reinforcement in aluminium matrix.

Study of Surface Quality During End Milling of SiC Reinforced Aluminium Metal Matrix Composite

In today’s world the composites materials are replacing many conventional materials due to their excellent properties. Aluminum is a less weight and cheap metal that is available in plenty. Silicon carbide is hard abrasive material with good mechanical properties. The aluminum silicon carbide metal matrix composite is finding increased applications in many fields such as automobile and aeronautical applications due to its excellent mechanical properties like high strength, light weight, high specific stiffness and good coefficient of thermal expansion. But their usage is restricted due to the difficulty in the machinability. In this paper two Al/SiC metal matrix composites (Al6061/10-SiCp and Al6061/5-SiCp) by varying the composition of SiC. The composites consist Silicon Carbide (SiC) of 5% and 10% by weight. The composites are prepared by stir casting process. Shell moulding technique is used in manufacturing of the composite materials. The microstructure, tensile strength, compression strength and hardness of the composites are studied. End milling operation is performed on the metal matrix composite slabs by varying the machining parameters. Feed rate and depth of cut were varied by fixing a single spindle speed. The number of experiments is determined using design of experiments (DOE). The effect of the machining parameters on the surface finish is observed by measuring the surface roughness. This process is done on the two metal matrix composites. The effect of SiC percentage in composite and variations in machining parameters on the surface finish was observed.

Effect of Ceramic Reinforcement Amount on the Hardness of the Aluminum Matrix Composite

Composite are one of the necessity of the current industrial infrastructure because of change in day to day requirements of the consumers. One of the most useful composite in aeronautical and automobile industries are aluminum ceramic composites because of their improved mechanical and thermal properties. However, amount of reinforcement has significant effect the properties of the composites material. Therefore, it is necessary to find out optimum amount of reinforcement that has the significant effect on the particular property of the composite material. Therefore, in the current study, Al-SiC (Aluminum-Silicon Carbide) metal matrix composite was fabricated using stir casting method. Parameters like stirring speed and temperature were kept constant during the process. Sic particle of 200 mesh size was used in different proportions. The reinforcement amount was varied from 0 to 12.5%. The influence of the percentage variation of the composite was studied based on the hardness test, microstructure analysis, optical Emission Spectroscopy (OES) and SEM-EDX. The OES, microstructure analysis and SEM-EDX analysis show retention of SiC in pure aluminium. The SEM-EDX of composite with 7.5% SiC addition shows 5.94% SiC retention that suggests the 79 % efficiency of the process. Moreover, it was observed from the hardness analysis that increases in the percentage of SiC increases hardness. Optical Emission Spectroscopy (OES) and EDS show the inclusion of iron [Fe] from stirrer blade material in results.

Effect of milling time on the compressive high strain rate behavior of Al-SiC Composite

Aluminum-Silicon carbide (Al-SiC) metal matrix composite (MMC) have gained importance as a new class of material capable of serving the future generation brake material requirements. The presented study deals with the compressive high strain rate behavior of Al-SiC composite comprising 15% SiC by weight. The MMC specimens were fabricated by powder metallurgy route. Three different ball milling times were selected for the study purpose after optimizing all other processing parameters. Incorporation of SiC invariably enhanced the hardness, quasi-static and dynamic compressive strength of Al-SiC composite. Hardness was noted to enhance as a function of increasing ball milling time. However, the quasi-static and dynamic compression properties were recorded highest for the ball milling time of 240 minutes. The study confirms that minor addition of a suitable reinforcing material can significantly improve the properties of an MMC. Also, increasing the ball mill time may not necessarily enhance all the material properties.

Fracture Toughness Testing of 6061Al–Graphite Composites Using SENB Specimens

Aluminum-based metal matrix composites have been increasingly utilized as engineering materials over the last three decades replacing the conventional engineering materials. The effects on the KIc by addition of reinforcements have been comprehensively studied for aluminum-based metal matrix composites. Hence, engineers have been working on enhancing the fracture toughness (KIc) of metal matrix composites in recent years. Aim of the present work is to evaluate the fracture toughness (KIc) of aluminum (6061)–graphite particulate-reinforced composites produced using a stir casting method. 6061Al–graphite particulate composites for 3, 6, 9 and 12 wt% of graphite were produced. Single edge notch bend specimens are used for bending test to investigate the fracture toughness of the composites. Two-dimensional finite element analyses using ANSYS were carried out, and the outcomes are judged against with the experimental data. It has been shown that the predictions are in reasonable agreement with the experimental data. From the results, it is found that the aluminum–graphite MMC has more fracture toughness then aluminum-silicon carbide metal matrix composites for all compositions .

Increasing Bending Strength of Aluminium Silicon Carbide Metal Matrix Composite Spur Gear by Increasing Fillet Radius

Increasing Bending Strength of Aluminium Silicon Carbide Metal Matrix Composite Spur Gear by Increasing Fillet Radius

Characterization of Stir Cast Aluminium Silicon Carbide Metal Matrix Composite

Aluminium silicon carbide metal matrix composites (Al-SiC MMC) are gaining wider acceptance in various fields like aerospace, aircrafts, automobile, substrate in electronics, turbine blades, etc, due to their high strength, stiffness, high corrosion and wear resistance, good thermal and electrical properties and good damping capability. In this work Al-SiC MMCs are fabricated by mixing molten aluminium with Silicon carbide by the aid of mechanical stirring, called stir casting method. Also in this work, the stir casting process parameters are optimized within the range to obtain good mechanical characteristics and uniform mixing of reinforcement, which is a major concern in stir casting. The processing parameters that were investigated include stirrer speed, volume fraction of reinforcement, number of blades on stirrer and diameter ratio. Microstructure observed through optical microscope was correlated to clustering tendency of reinforcement particles. The results of mechanical characterization study and microstructure study show that the stirrer speed, volume fraction of reinforcement, diameter ratio, and number of blades on stirrer appears to have significant effect on mechanical properties and clustering tendency of reinforcement particles

Experimental Design and Analysis of Camshaft by Using Aluminium Alloy(8090) and Silicon Carbide (Sic) Metal Matrix Composite

Experimental Design and Analysis of Camshaft by Using Aluminium Alloy(8090) and Silicon Carbide (Sic) Metal Matrix Composite

Analysis of Stir Cast Aluminium Silicon Carbide Metal Matrix Composite: A Comprehensive Review

Aluminium silicon carbide metal matrix composites are used in various fields like aerospace, aircrafts, underwater, automobile, substrate in electronics, golf clubs, turbine blades, brake pads etc. Several fabrication techniques are available for the production of aluminium silicon carbide metal matrix composites (Al-SiC MMC). Among the various methods, stir casting route is simple, less expensive, and used for mass production. The main limitations of stir cast Al-SiC MMC are improper distribution of SiC reinforcement in matrix and less wettablity of SiC reinforcement particle with molten Al. Literature survey indicate that various properties of stir cast Al-SiC MMC depends upon fabrication method, volume fraction, shape, size of particles and distribution and properties of constituents. Since metal matrix composites (MMC) lack structural simplicity its analytical modeling is complex. Further, the involvement of several parameters which affect composite properties, makes the experiments difficult. This review paper contemplates the need of simulation or numerical methods for the prediction of mechanical characteristics of Al-SiC MMC.

A Numerical Study on Stir Casting Process in a Metal Matrix Composite Using CFD Approach

This work brings out the numerical simulation of the stir casting technique for aluminium silicon carbide Metal Matrix Composite (MMC) in a closed crucible and the effect of the blade geometry and rotational velocity on solidification of the metal matrix composite has been predictedusing Computational Fluid Dynamics (CFD) approach. The material used in the crucible is silicon carbide in aluminiummetal matrix. Geometric modelling and meshing have been carried out using ANSYS ICEM CFD. Computer simulations have been carried using the commercial CFD package, ANSYS FLUENT. The calculations used 2-D discrete phase, solidification and melting model and enthalpy method. Mushy state mixing, indicative of the solidification patterns have been studied to predict the most suitable ratio of crucible to blade dimensions and speed of stirring to obtain the most uniform type of solidification which in turn induces some enhanced mechanical properties to the casting.

New Theoretical Modelling of Thermo-Elastic Behaviour Using the Geometric Average: Theoretical and Numerical Investigations

For the first time, Eshelby–Kroner self-consistent model extended to thermo-elastic loading is developed using the geometric mean for performing the set average operations. A new homogenization Eshelby–Kroner self-consistent approach is developed using a geometric average during thermo-mechanical loading. The description of the material thermo-elastic behaviour is carried out through new, appropriate, geometric polarisation tensors. In this paper, the classical Eshelby–Kroner thermo-elastic model based upon the arithmetic mean is used as a reference. A discussion and comparison between both average types is also provided. In particular, the coefficient of thermal expansion of silicon carbide, identified in the range 398–998 K from the knowledge of the thermal expansion of aluminium–silicon carbide metal matrix composites and pure aluminium samples do not depend on the average type chosen for achieving the computations.