Synthesis, Characterization And Testing With Multi-Objective Parametric Optimization Of Titanium Metal Matrix Reinforced Composites With Nano Particles

Abstract

The Pure Titanium, Although Widely Recognized For Its Strength-To-Weight Ratio And Corrosion Resistance, Has Limitations In Aerospace And Automotive Applications Due To Low Wear Resistance, Limited Machinability, And Susceptibility To Deformation. To Improve Performance, Titanium Metal Matrix Composites (Timmcs) Incorporating Reinforcing Components Are Being Developed. Hybrid Titanium Metal Matrix Composites (Htmmcs) Are A New Class Of Advanced Materials That Can Be Customized And Engineered To Achieve Specific Properties For Specific Applications In Specific Environments. Htmmcs Find A Wide Range Of Popularity In The Transportation Sector Because Of Their Lower Noise And Lower Fuel Consumption Compared To Other Materials. Therefore, This Study Investigates Timmcs Composition And Processing Methods, With A Focus On Enhancing Wear Resistance, Thermal Stability, And Overall Performance In Certain Applications. The Main Objective Of This Research Is To Experimentally Synthesize, Characterize, Test And Perform Multi-Objective Parametric Optimization Of A Titanium Metal Matrix Reinforced Composites.The Nanoparticles In Different Weight Percentages Of Zro2, Sic, B4c, And Mos2have Been Used In The Form Of Rein forcements. The Effects Of Process Parameters And Compositions On Tribological, Metallurgical, And Mechanical Properties Of Reinforced Htmmcs Have Been Studied Fabricated Via Powder Metallurgy (Pm) Process. The Multi-Objective Optimization Through Hybrid Grey Relational Analysis And Taguchi Method As Well As By Artificial Neural Network (Ann) And Genetic Algorithm (Ga) Has Also Been Carried Out In Order To Achieve The Optimum Value Of Input Process Parameters. Htmmcs Were Synthesized For Titanium Grade 5 Matrix With Variable Wt% Of Reinforcements (2.5, 5, 7, 12, 5 Wt% Sic), (2.5, 5, 7, 12, 5 Wt% B4c), (2.5, 5, 7, 12, 5 Wt% Zro2) And Constant (4 Wt% Mos2). The Multi-Response Optimization Through L27 Orthogonal Array Experimental Design Using Taguchi-Based Grey Relational Analysis (Tgra) And Response Surface Methodology (Rsm) Usingbox?�?Behnken Designs (4 Parameters And 3 Levels) Samples Are Optimized With An Integrated Artificial Neural Network (Ann) And Genetic Algorithm (Ga). This Investigation Was Intended To Explore The Influence Of Hybrid Reinforcements Containing (2.5,5,7.5 Wt% Sic, 2.5,5,7.5 Wt% B4c, 2.5,5,7.5 Wt% Zro2, And Constant 4 Wt% Mos2) On The Physico-Mechanical Properties Of Htmmcs When Milling Time, Compaction Pressure, And Sintering Temperature Were Varied. The Research Investigation Included Characterization And Testing Utilizing X-Ray Diffraction (X-Rd), Scanning Electron Microscopy (Sem), Thermal Analysis, Ftir, Micro Hardness, Compressive Strength, Wear Rate, Corrosion Rate, And Fractography. The Xrd Findings Demonstrated That All Of The Synthesized Htmmcs In All Proportions Contain Main Peaks That Are Ti And Hybrid Reinforcements As Miner Peaks, With No Unwanted Peaks.Sem Analysis Illustrates That The Htmmcs Tgra Optimal Sample With Wt% (7.5% Zro2, 7.5% B4c, 4% Mos2, 5% Sic, And 76% Ti) Showed A Lower Micropore Size With A Dense And Uniform Microstructure. The Increase In Wt% Of B4c And Sic Reinforcements Decreases Both Density And Porosity While Increases Hardness And Compressive Strength Up To A Certain Level, Above Which It Begins To Reverse Because Of The Increase In Wt% Of Hard Particles Of B4c, Sic, Zro2, And Mos2. The Rockwell Hardness And Compressive Strength Of The Integrated Ann-Ga Optimized Sample (7.5% Zro2, 7.5% B4c, 4% Mos2, 5% Sic, And 73.5% Ti) Sample Htmmcs Were Improved By 1.99 And 2.87 Times, Respectively. The Wear Loss And Friction As Well As The Corrosio