ETIME 2021 Proceedings E-Book

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) PASTE THE NACA4420 AEROFOIL CODING IN EXCEL FILE. After Applying the NACA4420 Codes in the excel click on the macros and run the gsd_pointsplineloftfromexcel file so that aerofoil is form in the catia software . NACA4420AEROFOIL 66 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) AEROFOIL PADDING : Blade Profile: The wing section nomenclature is given by NAC ON Aeronautics as NACA four digit series, NACA five digit series, NACAsix digit series etc. We have chosen NACA4420 for this study. The importances of the four digits is, 4 - The maximum height of the camber line expressed as a percent of the wing length as 40 %. 4 - The horizontal location of the maximum camber line height in tenths of a chord length. 20 - The maximum thickness of the airfoil expressed as a percent of the airfoil chord length. Table 1 Blade Specifications Profile NACA4420 Length of aerofoil 299.88mm 45.145mm Width of wing Padding length 123mm ISBN: 978-0-13-601970-1 67

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) SELECT THE FRPC MATERIAL: TOTAL DEFORMATION : Max deformation value is 8.1924 68 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) EQUIVALENT STRAIN: The max strain value is 0.008357 EQUIVALENT STRESS: Max stress values is 561.08 ISBN: 978-0-13-601970-1 69

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Selecting the Titanium Material: Max Deformation value is 5 .9916. Equivalent Strain: The Max strain value is 0.0061045 70 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Equivalent stress: The Max stress value is 556.03 CONCLUSIONS: In these paper we have used Titanium and FRPC material, After comparing the results which are obtain from the Titanium and frpc materails.It is found that the Titanium material is possessing better results like having low stress and deformation when compared to frpc material, Titanium material is found to be better than the frpc material in these paper. The further analysis can be carried out with some more composites materails like Kevlar or glasss or fiber with which we can get the desired Results in the future. REFERENCES 1. Karna S. Patel, Saumil B. Patel, Utsav B. Patel, Prof. Ankit P. Ahuja, UVPCE, Ganpat University(www.uvpce.ac.in), \"CFD Analysis of anAerofoil\" International Journal of Engineering Research ISSN:2319-6890)(online),2347-5013(print), Volume No.3, Issue No.3, pp : 154-158 01 March 2014 2. Mayurkumar kevadiya, HemishA. Vaidya, \"2D ANALYSIS OF NACA4412 AIRFOIL\", International Journal of Innovative Research in Science, Engineering and Technology, Vol. 2, Issue 5, May 2013 3. Khil Yuvaraj Manda, Jithendra Sai Raja Chada, Sambhu Prasad Surapaneni ,Satish Geeri A \"Flow behaviour on aerofoils using CFD\", Pragati Engineering College, Surampalem, Andhra Pradesh, India. Issue 10 june 2020 . 4. AVNISH KUMARon\"INVESTIGATION OFAIRFOILDESIGN\" NATIONALINSTITUTE OFTECHNOLOGY, ROURKELA. India 5. Rajat Veer* , Kiran Shinde* , Vipul Gaikwad* , Pritam Sonawane* , *Student, Department of Mechanical Engineering, RMD Sinhgad School of Engineering, Pune. ISBN: 978-0-13-601970-1 71

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Performance of Eco Friendly Lubricant Oils’ in Large Hydroelectric Thrust Bearings D.V.Srikanth Associate Professor (Mechanical), SNIST, Ghatkesar, Hyderabad-501301, Telangana Email: [email protected] ABSTRACT In this paper the modified Reynold's and energy equations of a hydroelectric thrust bearing were solvedsimultaneously using a scheme of finite differences. Variations in viscosity across the pad film, as well as the hot oil carryover effect, were taken into account. The pad deformation was computed using ANSYS and a linked finite-element technique.. The analyzed lubricants were DTE heavy medium oil and a variety of next generation low tox turbine oils. An addititonal theoretical and established experimental analysis was used to estimate and compare lubricant toxicity. Unlike in previous studies, this study defines the independent factors which control the selection of a lubricant viz. its hydrodynamic efficiency and toxic content. KEYWORDS: mesh convergence, hydrodynamic, low toxicity, lubrication 1. INTRODUCTION Athrust bearing balances the spinning components and hydraulic load of a big vertical hydropower generator. [1] created a THD model of a pivoting pad bearing with radial and circumferential tilt. The temperature distribution of the pad oil film was taken into account. The viscosity and density were affected by both pressure and temperature.. Low tox turbine oils in the range of grades 6412 to 6414asdescribed in [2] produced a long-lasting performance equivalent to the tradititonal turbine oils.Theyhad lower toxic levels than biodegradable turbine oils. Theydid not need a shorteningof lubricant change intervals. Theyshowed excellent demusibiltyand were compliant with bearings. Low tox oils have resulted in a tenfold reduction in eco-toxicity and have been particularly suitable for use in hydroelectric installations. In [3] the efficiency of a water-lubricated thrust bearing was predicted using a finite element approach.Variation and Litz-Galerkin methods were used to derive finite elements from the turbulent Reynold and energy equations. The pressure field obtained was based on the model of finite elements. The pad's load capacity decreased with an increase in temperature.[4] investigated the thermophysical characteristics of non-Newtonian surrogate lubricants.Asteady state analysis was carried out for the bearings modelled inANSYS. To generate thermal stress, the temperature changed linearly on the pad's outer surface and non-linearly on its inner surface. The study focused on the temperature distribution of the bearings based on the lubricant's dependent thermophysical characteristics. [5] examined the lubricating systems for big tilting pad thrust bearings used in hydropower turbines. The viscous shearing of the lubricant generated a significant quantity of heat, which required forced cooling.Effective oil bath external cooling systems have some advantages compared to internal cooling systems but have become less efficient and simple. A theoretical analysis of the flow and efficiency parameters of a dimpled thrust bearing was conducted in [6]. The incompressible flow numerical solutions of Navier Stokes and energy equations were used to evaluate hydrodynamic efficiency. Realistic boundary conditions were taken into account.This studysuggested that proper rectangle dimples texturedon parallel thrust bearings resulted in a major increase in load capacity levels. Various 72 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) pressure profiles with grid independence were analysed in [7]. The Reynolds equation was solved on the pad surface using FDM techniques to determine the pressure distribution of the oil layer.It was discovered that the grid independence occurred after the 24×24 grid. This study analysed different pressure profiles and confirmed that the refining of the grid could have a major impact on the pressure values. The load-bearing capability of a thrust bearing with an elastic pad was evaluated in[8] in order to obtain optimum pad parameters. Thrust bearing analysis software used an FDM solution for flow and thermal equations as well as a FEM solution for pad deformation. Differences in theoreticallyprojected thrust bearing characteristics using two independentlydeveloped TEHD models were analysedin[9]. In the two versions, there was a strong agreement on the characteristics of the bearings for the isothermal case. The 2D model projected higher load capacity and loss of power resulting in a difference with experimental values.Astrong understanding was reached with the experimental results for the 3D model. Lubricating oils are essential products without which no equipment can operate as discussed in [10]. This paper investigated the oxidation resistance and thermal stability properties of lubricants in industrial systems. Laboratory tests for the evaluation of lubricant performance in accordance with OEM, national and international specifications wereidentified. The analysis of highlyrefined base oils with very low levels of aromatics and almost no sulphurwere conducted in[11]. Modern methods for the oxidation of bulk oils using various base materials under varying temperatures, metal catalysts and antioxidants wereintroduced. The solution to major environmental issues of pollution and degradation of hydrocarbons were discussed in[12]. Bioremediation was the best method for the treatment of this pollution. It was inexpensive and helped to biodegrade and mineralize organic contaminants into, water, carbon dioxide,inorganic chemicals, and cell protein. Biological microorganisms have also been used to convert complex organic pollutants into simpler organic pollutants.Stringent regulations on the use, storage and disposal of lubricants in power plant bearings was discussed in [13]. The goal was to use products that were less harmful and more readily biodegradable if they were accidentally released to the environment.Aproduct could be harmful to one organism and not toxic to another. Similarly, a product can easily biodegrade under certain conditions, but not under different conditions. Environmentally safe lubricant oils in use have been regularly checked. The literature review reveals that there are very few studies of the pressure and temperature characteristics of low toxicitylubricant oils in thrust bearings. The purpose of this studyis to create quick computational algorithms for evaluating the low tox oil film's hydrodynamic performance, including pad deformation.In addition, a novel independent method for estimating the toxic content of DTE heavy medium and low toxicturbine oils in the range 6412 to 6414 has been developed. Table 1 describes the structure, the working conditions of the bearings and the properties of these turbine oils. Unlike non-newtonian surrogate lubricants, it is noted that there are no major variations in viscosity for DTE heavy medium and low tox lubricants under consideration. ISBN: 978-0-13-601970-1 73

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Table 1: Geometry of Thrust Bearing Diameter of the outside 1.275m Diameter of the inside 0.75m Pads in Number 6 width of the groove 84 mm Conditions of Operation Load 2.2 MN Rotational speed 14.28 rads/sec Pot oil temperature 313 º K Properties of Oil DTE heavy LowTox turbine oils Names of the oils Medium oil 6412 6413 6414 ISO grade 68 46 68 100 Viscosity at 313º K(cSt) 73 45.9 66.3 102.3 Viscosity at 373 º K(cSt) 10.7 6.6 8.64 11.61 ρ(kg/m3) 861 864 869 871 3. MODIFIED REYNOLD'S EQUATION The Reynolds equation was modified to a non-dimensional form using the foregoing replacements, as seenin equation (1): 4. HEAT ENERGY EQUATION Thermal impacts from viscous shearing of lubricant layers hinder performance in a variety of ways. Because of the decreased viscosity caused by heat production, the load capacity was reduced. The energy equation governed heat generation and transfer. Pressures and temperatures were calculated using partial differences. The energy equation for a laminar and incompressible flow was given by Equation (2). = (2) Equations (3, 4) calculated radial and circumferential flow, respectively, while equation (5) calculated heat dissipation rate. = (3) = (4) = (5) 74 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The fluctuation of viscosity with temperature was calculated using the Vogelpohl - Cameron equation (6). (6) 8. HYDRODYNAMIC COMPUTATIONAL METHOD: The mesh independence solution called fora grid of 81 nodes, as illustrated in Fig. 1, for theFDM discretization of the film. In order to solve the Reynolds' equation, the central difference form of the truncated Taylor series expansion was utilised. To assess the derivatives, the functional values of neighbouring nodes on either side were necessary. By expressing the Reynolds equation in finite difference form, a set of linear algebraic equations was generated. Fig.1: Pad discretization in Reynolds' equation M echanical Properties of Pad 195 The Young's modulus (GPa) 0.29 7850 The Poisson's ratio T he degree of d ensity (Kg/m3) 12.2e- 6 42.6 Therm al Pro perties of a Pad 473 T hermodynamicexpansion/ K 6.015e -4 30e -6 Thermal conductivity (W/m-K at 283K) Specific heat (J/kg-K ) Inner surfaceheat transfer coefficient(W/(m2K) Outer surfaceheat transfer coefficient(W /(m2K) Table 2. Pad Mechanical Properties The afore mentioned equation was written for each node, yielding a set of simultaneous linear algebraic equations asa result given in equation (7). (7) In the matrix form, the equations were written in equation (21) as: (8) Equation (8) was solved by matrix inversion and multiplication with available subroutines to yield the nodal non-dimensional pressure. Load capacity and centre of pressure location were obtained by integrating these pressures. ISBN: 978-0-13-601970-1 75

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The Reynolds equation's boundary conditions were addressed in equation (9) as P=0 at (9) The energy equation was also solved using finite differences. As the energy equation (8) depended on the pressure gradient it was solved simultaneously with the Reynolds equation using the same grid. The energy equation, which included the components and , was written in finite differences to represent the local heat dissipation and in terms of . The first order of the equation showed that it was solved using the propagation technique. The temperature was provided along the whole leading edge, such that the starting values of were also known. was presented with temperature variation between neighbouring nodes in the circumferential and radial directions Using this approach, the temperature distribution was determined in a single sweep while accounting for the hot oil carry over effect. The Vogelpohl-Cameron equationincluded in the energy equation accounted for the viscosity and temperature fluctuations throughout the flow of oil. Using the new distribution of viscosity the Reynolds' equation was resolved for pressure. This iterative scheme converged quickly. ANSYS was used to calculate the coupled thermo-structural deformation of the pad using a finite element approach.. Table 2 shows the input thermal and structural parameters of the pad material. The initial phase in the investigation was to create a solid model and mesh it. To the greatest degree feasible, the problem symmetry was employed. This reduced the physical dimension and allowed for the adoption of the lowest mesh-size. The model was produced in the axi-coordinate system by connecting critical points, forming regions, and working around the axis.After that, the model was meshed using Solid 226 components and simulated for a load step. The nodal values of the elements of the bottom surface were identical to the corresponding values of the lubrication problem. The analysis was therefore coupled.There were 8 radial, 8 circumferential, and 8 longitudinal thickness elements in the linked thermo-structural deformation elemental plot of the pad, for a total of 512 hexahedral elements. 1) The pressure and load were applied to the bottom surface area A2 using the axi-symmetric boundary condition. 2) The convective heat transmission from Fig. 2's regions A1, A3, A4, and A6 was studied. The bulk oil temperature was 40°C, and the convection film coefficient was 4e6W/m2K. 3) The heat flux values derived from the energy equation solution were the same for the bottom pad's elemental surface nodes. 4) The heat transmission from the pad via radiation was ignored. The computed thermoelastic deformation was used to modify the oil film, yielding new pressure and temperature profiles that were then imported back into theANSYS model. 9. HYDRODYNAMIC RESULTS AND DISCUSSIONS The pad deformed to a maximum of 0.896e-3m at the bottom and outside circumferential edge in the coupled field analysis, as shown in Fig.3 for the 40mm thick pad. The pad deformations were of the same order of 76 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Fig. 2: Load-bearing and heat-transfer zones magnitude as the oil film thickness, which was in both cases to the order of 6m. Figure4 shows the pressure distributions for the low toxic 6414 grade oil. The pressure applied to the pad surface's leading edge was minimal. The pressure production was substantial in the area of the pad surface's trailing edge. The highest peak pressure was slanted to the trailing edge.The peak value of the pressure was reached when film thickness was minimum and counteracted the sliding surface external load.The temperature distributions for the above tested oilwas shown in Fig.5 they were characteristic of the viscosity values.The predominance of maximum temperature was signified by the border region of minimal film thickness and maximum rotation speed.The highest film temperature rise was seen at the trailing edge corner at the outer radius.The highest temperature was found at the intersection of the trailing edge and the outer radius.When comparing the left and right halves of the pad, the temperature change was smaller along the left side.The study revealed that the 6414 grade lubricant had the greatest maximum pressure and temperature, while the 6412 grade lubricant had the lowest. The oils were able to adapteffectively to boundary lubrication conditions during start up and shutdown. Fig.3. Deformation distribution of a coupled field. 77 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Fig.4: Pressure distribution in a low toxicity oil film of grade 6414 Fig. 5: Temperature distribution in the low toxicity oil film 6414 grade 10. VALIDATION The accuracy of the author's theoretical predictionsusing data in Table 1was compared with Yuan's [14] and Zhong De's [15] experimental data results. As in Figure6 the experimental pressures were lower than those oftheory. The relatively considerable disparities between the experimental data and the author's theoretical data were due to flaws in the theoretical modelling. Fig. 6: Pressures along the R cp, both theoretical and experimental 78 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Because predicted pressures were somewhat greater than observed pressures, the software programme overestimated pressure in areas where no measurements were recorded. The difference in temperatures as inFigure7 was on account of variation in input temperatures and viscosity. The differences in pressure and temperature were large as speeds and oil viscosities Fig.7: Temperatures along the R cp, both theoretical and experimental were higher for Yuans's data as with larger bearing diameter and load for Zhong De's data. Although not perfect, agreement with theoretical and practical results provided substantial evidence for the software package's value in forecasting large thrust bearing performance. 11. LUBRICANT OIL TOXICITY: A toxicological research was conducted to quantify the toxicity of turbine oils, namely DTE heavy medium oil, low tox, and used turbine oils, in the terrestrial environment over a predetermined biodegradation time.Toxicity levels were determined during the biodegradation period using Eruca Sativa (arugula seeds) and EiseniaAndrei (earthworms), as in [16].This studyprovided an indirect evaluation of microbial metabolism efficiencyin pollutants by evaluating the biodegradation process.Abbots' formulagiven in equation (30) below (30) was usedwhere I % denotes the percentage of inhibition, C- represents the number of germinated seeds in the negative control, and T refers to the number of germinated seeds in the sample treated a. The oil was deemed harmful when germination inhibition of seeds was greater than 40%, according to the toxicological examination. b. When germination inhibition was between 10% and 40% there was onset of toxicity c. Not harmful when inhibition present was 10%. Fig. 8: Toxicity of turbine oils (E. sativa) after 0, 60, 120, and 180 days of biodegradation. 79 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) In Fig. 8, utilising E. Sativa seeds, the oils had an initial high toxicity of more than 75% in all cases. The toxicity of the DTE heavy medium oil increased for 60 days and decreased thereafter.The toxicity of the new LE low tox oil dropped after the initial adaption time, but the toxicity of the used turbine oil remained high throughout the duration. The results in Fig. 9 for E.andrei showed that the toxicity of the LE low tox and DTE heavy medium oils had diminished in the 180 day period. The first oil showed no toxicity at the conclusion of the session, but the DTE heavy oil showed 5%. The toxicity of the utilised oil did not diminish. The above results were compared and validated with the MicrotoxLuminiscent bacteria bioassay test results in [2]. Fig. 9: Toxicity of turbine oils (E. Andrei) after 0, 60, 120, and 180 days of biodegradation The effective concentration was determined in milligrammes of oil per litre of water, and the EC50 values represented that.It displayed the effective concentration of the substance being tested as well as the amount required to lower bacterial luminescence metabolic activity by 50%.The EC values applied to oils that were not water soluble.The higher EC values indicated lower toxicity and vice versa.The EC value of the low tox 6413 grade oil tested was 112580 mg/l and that of DTE heavy oil was 48230 mg/l. In 28 days the low tox oils were biodegradeable by 55%. 12. CONCLUSIONS The finite difference approach was utilised in this work to solve the Reynolds and Energy equations of the large oil lubricated tilting pad thrust bearing. Low tox oils in the range of 6412-6414 were analysed and thepressure and temperature profiles plotted. The toxicity values of DTE heavy medium, low tox and used turbine oils were estimated over the bio-degradation period range of 0 to 180 days.According to the E.Andrei results biodegradation was effective for the LE low tox and DTE Heavy medium oils. The LE low tox oil had its toxicity dramatically reduced in only50 days. The application of low tox turbine oils was justified as theypossessed excellent demulsibilty and were compatible with mechanical seals. Theyhad minimum adverse impact on the environment. To the best of the knowledge of the author this study was unique in highlighting the importance of hydrodynamic performance and toxicity in the selection of a lubricant. 13. REFERENCES 1. Almquist T, Glavatskikh SB and Larsson R. THD Analysis of Tilting Pad Thrust Bearings-Comparison Between Theory and Experiments.Journal of Tribology, 2000, 122(2). 2. Lubricant Engineers, Product specification Handbook,Asset Reliability solutions,pp.1-2, 2015.. 3. Cheng D, Yao Z and Xue Y. Study on the Water Lubricated Large-scale Tilting Pad Thrust Bearing by Finite Element 80 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Method.Proceedings of the World Congress on Engineering and Computer Science, Oct. 21-23, 2015, San Francisco, USA. 4. Saini V, Raja Sekhar D and Kumar A. Thermal Analysis on Thrust Pad Bearing with Non-Newtonian Lubricant.InternationalJournal of Engineering Research & Technology,2015, 4(3):1140-1146. 5. Wasilczuk M. Friction and Lubrication of Large Tilting-Pad Thrust Bearings.Lubricants, 2015, 3: 164-180. 6. Papadopoulos CI, Kaiktsis L andFillon M. CFD Thermohydrodynamic analysis of 3-D sector-pad Thrust bearings with Rectangular Dimples.Proceedings of ASME Turbo Expo 2013, San Antonio, USA, June 3-7, 2013, Texas:ASME. 7. NajarFA, Harmain GA. Numerical Investigation of Pressure Profile in Hydrodynamic Lubrication Thrust Bearing.International Scholarly Research Notices 2014: 1-8. 8. Minculescu A, Cicone T. Parametric Analysis Of A Hydrodynamic Thrust Bearing With Elastic Slider.The Annals Of University \"Dun?rea De Jos \" ofGala?i Fascicle VIII2005, 101-106. 9. WodtkeM ,Fillon M and Wasilczuk M. Predicting performance of thrust bearings with use of contemporary models. 7th EDF/LMS Workshop on Operational Limits of Bearings: Improving of Performance through Modelling and ExperimentationatFuturoscope,October:2008, Volume:pp. 1-8. 10. Bouillon V. Overview of oxidationlaboratory tests on industrial lubricants.In:Euskalduna conference centre.Bulbao, Spain, 7-8 June 2016. 11. GattoV, MoehleW and Cobb T.Oxidation fundamentals and its application to Turbine oil testing.Journal of ASTM International,2006, 3(4): 1-20. 12. Das N and Chandran P. Microbial Degradation of petroleum Hydrocarbon Contaminants:An overview. BiotechnologyResearch International Volume 2011, 1-13. 13. Lubrication of Powerplant Equipment, Facilities, Instructions, Standards, and Techniques,US Department of the Interior Bureau ofReclamation, Denver,2004, Volume 2-4, pp. 23-27. 14. Yuan JH,Medley TB and Ferguson JH. Spring Supported Thrust Bearings Used in Hydro-Electric Generators: Comparison of experimental data with numerical predictions.TribologyTransactions2001, 44(1), 27-34. 15. Zhong-De W and Zhang H. Performance Analysis of Thrust Bearing for Three Gorges Generator. Large Electric Machine and HydraulicTurbine2011, 2(3). 16. Tamada IS, et al. Biodegradation and toxicological evaluation of lubricant oils, Brazilian archives of biology and technology, 2012, 55(6). 14. NOMENCLATURE a : the form of the oil film parameter,(ho- hi)/ ho ho : trailing edge oil film thickness, m hi : leading edgeoil film thickness, m i : radial node index j : circumferential node index k : composite node index m : number of radial nodes on the grid n : number of circumferential nodes on the grid p : oil film pressure, Pa r : coordinate in radial direction, m ro: bearing's outer radius,m. ISBN: 978-0-13-601970-1 81

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) B : circumferential length of the thrust pad, m CP : pressure centre D i : thrust bearing's inner diameter,m Do : thrust bearing's outer diameter, m H : oil film's non-dimensional thickness, h/ho L : thrust pad's radial length, m N : runner's angular speed, rpm P : pressure thatis not dimensional, (ph2)/U P : Reynolds' equation's pressure matrix R : radius thatis not dimensional, r/ro Rcp : pressure center's radial coordinate, m T : Temperature of lubricant, oC U,V : Paralleland normal velocity to surface, m/s W : bearing load, N X : pressure centre x-coordinate Z : Pad's count  : thrust pad's angular extent.  : ratio of film thickness  : oil viscosity, Pa.s : viscosity that is non dimensional  : angle relative to the leading edge, radian  : pressure centre angular position, radian. cp  : oil density, kg/m3  : runner angular velocity, radian /s r : radial grid division, m v : grid element volume, m3  : gridangular division, radian. x : Displacement differential, m 82 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Comparative Studies on Sandwich Structural Structures B. Lakshmi Bhargav1, C.Raviteja2, C. Vamshi Krishna3, A. Purushotham4 1,2,3UG Student, Sreenidhi Institute of Science & Technology: Hyderabad 4Faculty, Sreenidhi Institute of Science & Technology: Hyderabad Email: [email protected] ABSTRACT Multiple thin face sheets comprised of stiff and strong comparatively dense material such as metal or fibre composite are connected to a thick light weight material termed core in a structural sandwich. This design has been employed in a variety of lightweight applications, including aviation, maritime, military, and wind turbine blades. In this research, explicit analysis of several sandwich panels with steel and carbon fibre in the core and face sheets is carried out using the Ansys workbench, and the impact response of various materials is documented in order to develop an efficient impact resistance construction. The bullets and sheets have been utilised in a variety of study combinations. Key words: Impact response; Impact resistive structure; Ansys; explicit analysis; sandwich panels, and core. 1. INTRODCUTION The use of Impact resistive materials had gained a significant rise with advancements made in aerospace, military departments. There is a need to light weight, high stiffness, high Young's modulus, excellent toughness coupled with low coefficient of thermal expansion materials which can sustain high impacts in aerospace, military, civil engineering, motor-sports along with other competition sports sectors.In aeroplane design, the problem of building a structure as light as feasible without losing strength is critical.As a result, thin surfaces must be stabilised to endure tensile and compressive stresses, as well as the combination of the two, in tension, torsion, and bending. In 1849, for the Britannia Tubular Bridge in North Wales, W.Fairbairn is said to have been the first to define the sandwich construction idea. Iron compression sheets were riveted to both sides of a wood core in this sandwich. T. von Karman and P. Stock invented a glider plane in 1924 that used a sandwich construction for the fuselage. Naiketal[1] worked out the Composite Structures under Ballistic Impact. CompositeStructures.IMPACT ANALYSIS OFAPROJECTILE ONABODYARMOR done byDwarakanathvarunkumaretal[2].A.Gopichand et al. published Design And Analysis Of Corrugated Steel Sandwich Structures UsingAnsys Workbench [3]. The prediction of impact damage on sandwich composite panels was published byAktay et al[4]. Vaidya UK et al[5] investigated the impact response of multi-functional sandwich composites at high strain rates. The impact behaviour of a sandwich panel is rarely studied since it is dependent on numerous aspects such as mechanical characteristics of its parts, skins and cores, and the adhesive capability of the skin - core interface. The investigations on high-velocity impact behaviour and low-velocity impact behaviour were not thoroughly discussed. Carbon-fiber skins and a honeycomb core are the most significant components of aeronautical sandwich constructions because of their high specific strength and stiffness. These buildings will be subjected to high- velocity hits from low-weighted debris while in service. Sandwich constructions are particularly vulnerable to such forces. Despite much investigation, the impact resistant behaviour of sandwich structures is still a mystery. The main objectives of the paper are: To perform impact analysis of the plate on a single material plate and composite material plate usingAnsys workbench at different velocities and to compare the various parameters of single and composite material plates.Sandwich structures are weight-efficient components in aerospace applications. ISBN: 978-0-13-601970-1 83

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The paper is organized in the following manner: Section-1 details the introduction, past research work and the main objectives of the paper. The description simulation model is given in Section-2. The simulation results with different sandwich structures are detailed in the section-3. Finally conclusion are drawn in section-4. 2. SIMULATION MODELING Dimensions: Length of bullet = 20mm; diameterof bullet = 12mm.Speed of bullet = 700m/s; Plate = 70*70*10 mm.Material chosen: plates: Steel & Carbon fiber . Corrugated structure: Steel, Springs: Steel.When it comes to procedure, create the geometry and then make both the parts independent, mesh both the parts, then apply the boundary conditions and run the analysis with uniform loading conditions .To perform simulation, boundary conditions are made for bullet and plate. 700 m/svelocity is given to bullet in the direction of plate and it will hit the plate exactly at the center of the plate.All sides of the plate are fixed to make the degree of freedom of - 11 -plate to zero and for top layer all sides are made free and the end time is 9e-005 s that is show in figure below. Fig.2.1 Simulation model 3. SIMULATION RESULTS & DISCUSSIONS: 3.1 Single steel plate and steel bullet: After meshing and boundary condition, solve the model to obtain the displacement and plastic strain as shown in figure 3.1. It clearlystates that the maximum displacement as well as the plastic strain is maximum at the center of the plate and the maximum and minimum value of Plastic strain is 2.0187 and zero respectively.If we evaluate the result for stress we would obtain the results as shown in figure 3.3 where the maximum and minimum value of the stress is 6.1078e8 and 3.0938e7. 84 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Figure3.1: The front and side view of simulated plastic strain From the plot Figure 3.2, we can see that the maximum and minimum value of deformation is 0.030976 and 0 Figure 3.2 :Deformation of the single material plate. Fig 3.3 :Stress in conventional plate material 3.2 Composite material plate and steel bullet:- In the similar manner ,After the meshing and boundarycondition, solve the model and obtain the displacement and Plastic strain as shown in Figure 3.4 .It clearly states that the maximum displacement as well as the Plastic ISBN: 978-0-13-601970-1 85

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) strain is maximum at the center of the plate.And the maximum and minimum value of Plastic strain is 1.4949 and ZERO respectively.In Fig 3.6, we can see the stress plot where the maximum and minimum value of the stress is 1.0332e+10 and 4.1444e6. Fig 3.4:Plastic strain in composite material plate Fig 3.5:Elastic deformation in composite material plate Fig 3.6: stress in composite material The simulation results among the steel and composite plates are summarized as shown below: 86 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Param eter Single material Composite material Plastic Strain 2.0187 m/m 1.4949 m/m Plastic work 3318.9 joule 2113.4 joule Deformation 0.030976 m 0.02973 m 3.3 Corrugated core structure : The materials used are: {carbon fiber (top) + steel (bottom &steel (core).Fig 3.7 shows the tested panel with corrugated core and life like core.Here bullet is steel. The dimensions of various elements are similar to section2. Fig.3.7:sandwich panels with corrugated core The simulation results obtained on corrugated and leaf shaped structures are summerized below along with remarks. Criteria Corrugated Leaf shaped Comments structure structure Total deformation Less deformation in corrugated Equivalent von mises stress 0.31 m 0.35 m Higher von-mises criteria in corrugated structure. Equivalent Elastic strain 1.8121 Mpa 1.037 Mpa Slightly less strain in corrugated structure. Total energy 0.91 m/m 0.834 m/m More energy absorbed in corrugated core Energy error 3.89 mJ 3.12 mJ More energy error in corrugated core 0.4 mJ 0.25mJ 3.4 Sandwich panel with different impact angles: Corrugated core with top plate carbon fiber and bottom and core with steel was used for analysis. For analysis, same boundary conditions & mesh optimization was taken with different bullet angles. The angles considered for analysis are 0,30,45 degrees. C rite ria 0 degree 30 degree 45 degree Total deformation 0.0210 mm 0.0212 mm 0.0211 mm Equivalent (von mises) stress 1.55 pa 1.52 pa 1.50 pa Equivalent elastic strain 0.5406 mm/mm 0.5462 mm/mm 0.5749 mm/mm Equivalent plastic strain 1.47 mm/mm 1.49 mm/mm 1.49 mm/mm Total Energy 14236 J 14007 J 11259 J Energy error 1250 J 750 J 600 J 4. CONCLUSIONS In this paper the simulation studies are carried out on different sandwiched structures. The test environment chosen for impact analysis is a bullet firing on a sandwiched structures.The material combination behavior has ISBN: 978-0-13-601970-1 87

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) been studied.After the analysis of different set of sandwiched structural structures, a leaf spring sandwich structure showing a high impact resistive structure with lowest possible values of its thickness. The content present in this paper enhances the understanding of utilities of sandwiched structure for impact applications. ACKNOWLEDGEMENT The authors thank principal, director and Head of the Department of Sreenidhi Institute of Science and Technology: Hyderabad for helping to use resources REFERENCES 1. Naik, N.K., and Shrirao, P. (2004). Composite Structures under Ballistic Impact. Composite Structures, Vol.66, pp 579-590 2. ACOMPARATIVE STUDY ON IMPACTANALYSIS OFAPROJECTILE ONABODYARMOR Dwarakanathvarunkumar, Mr. Kannan Ramalingam Department of Production Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India. 3. Design And Analysis Of Corrugated Steel Sandwich Structures Using Ansys Workbench A.Gopichand , 2 Dr.G.Krishnaiah, 3B.Mahesh Krishna, 4Dr.Diwakar Reddy.V, 5A.V.N.L.Sharma 4. Aktay L, Johnson AF, Holzapfel M. Prediction of impact damage on sandwich composite panels. Comput Mater Sci 2005; 32:252-60. 5. Vaidya UK, Nelson S, Sinn B, Mathew B. Processing and high strain rate impact response of multi-functional sandwich composites. Compos Struct 2001;52:429-40. 88 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Machining Parameters Optimization ofAluminium Metal Matrix Composite- Grey RelationalApproach K.Srinivasulu Reddy Professor, Department of Mechanical Engineering, Sreenidhi Institute of Science and Technology, Hyderabad Email : [email protected] ABSTRACT This work is aimed to find the impact of machining parameters over material removal rate and surface roughness. Based on a hybrid grey relational analysis, the optimum conditions were determined. Grey relational analysis were used so as to arrive at a grey relational grade and further to evaluate the multi-characteristic output from grey relational coefficient of each response. The experiments were designed on the basis of Taguchi's design of experiments in which a L16 orthogonal array was chosen for three parameters that differed through four levels. Using a response table, the optimal setting was identified whereas the impact of input parameters on the output was measured using ANOVA. Using this technique, the study improved the performance characteristics of the machining process which was proved with the results retrieved from the conformation experiment. Key words: Grey relational Analysis, ANOVA, Taguchi design I. INTRODUCTION With improved properties, MMCs (Metal Matrix Composites) render a wide range of excellent options in designing new products. MMCs have increased strength, enhanced stiffness, water resistance, dimensional stability even at highest temperatures and low coefficient of thermal expansion. When it comes toAMCs, aluminium alloy remains the matrix material whereas the other phases comprise of B4C, SiC, Gr,Al2O3 etc., [1,2]. The composite's mechanical strength as well as it wear resistance increase when the ceramic particles are incorporated inAluminium alloys. The machinability of MMCs has received much consideration due to the high tool wear rate during machining.Alongside, the MMC's are reinforced with SiC particles are more challenging to conduct the machining operation (turning, drilling, machining grinding, etc.) due to their extreme abrasiveness [3-5]. In [6], Hung et al. discussed the hardness of the MMC's are improved with increasing the amount of FA/SiC than the base alloy. Alongside, Reddy and Gopi et al., [7] developed an MMC's by varying the weight percentage of reinforcements that is, 5% and 10 % and conducted mechanical and microstructural analysis. TheAl7075/FA/Sic with 10% wt shows better mechanical properties compared with base and Al7075/FA/Sic with 5% wt composite. Present investigation is focused on turning performance ofA7075/Fly ash/SiCAMMC in terms of Ra and MRR under dry machining condition with uncoated carbide tipped tool inserts. K Gajalakshmi et al. [8]. experimentallystudied onAA6026 drysliding wear parameter using GRAcombined with RSM. The optimum minimum wear has been attained at 35.21 N in load, 375.65 r/min in speed and 11.53 mm in track diameter with the output errors lie within 3% to 6 % by the current model compared to the gained result from the confirmation tests. SityAiny Nor Mohamed et al [9]. is used integration of Taguchi-GRAfor rice husk composite to optimize injection molding parameters. It is found that the injection pressure is affected highly around 59.6%, the injection speed (14.7%), the melting temperature (15.9%) and the cooling time (9.9%). A. Mahamani et al. [10] has reported the laser power, standoff distance and laser speed are 68.05%, 17.85% and 13.33% respectively for AA6061-TiB2/ZrB2 composite in laser drilling parameter optimization by GRA. The result shows that the laser power has the highest influence compare to other two parameters. ISBN: 978-0-13-601970-1 89

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) With the help of sensitivity, a multiple criteria optimization approach was proposed by Isik and Kentli [11] and the studyconsidered two objectives such as the mitigation of cutting forces and increased removal of material, while at the same time, when the unidirectional glass fibers are turned, the polyester rods get reinforced. In order to diminish the specific cutting pressure, surface roughness and toolwear and further to maximize the material removal, a research was conducted by Palanikumar [12] which made use of grey relational grade and Taguchi method. In that study, the GFRP/Epoxy composites were turned on with the help of carbide (K10) tool. Deng [13] introduced the grey system which is an influential tool that can make use of poor, incomplete and vague data too. GRA is the hot research topic among today's researchers who effectively used it to trace the intricate relationships among different objectives in a wide rangeofmanufacturing fields [14-17]. GRG is determined byaveraging the GRC of everyresponse for converting the optimization ofmultifaceted performance characteristics into optimization of a single GRG [17]. II. EXPERIMENTATION Composites are made by adopting standard stir casting procedure. Melting ofA7075 ingots was performed in an electric furnace with graphite crucible.At 770°C, molten metal pool was stirred at the centre of the crucible with the help of a mechanical stirrer that rotates at 500 rpm. SiC and flyash particulates were preheated and dropped in a uniform fashion into the melt. With the purpose of avoiding agglomeration at the time of stirring, the particles were ensured to have a smooth and continuous flow. Since the cast gets exposed to the atmosphere while stirring, argon inert gas-based shielding was maintained throughout for 2 to 3 minutes to avoid oxidation. Then, molten metal is poured into cast iron molds which is preheated to 2000C. The fabricated ingots were kept in a muffle furnace at 1100C for 24 hours to remove any residual stresses induced in the castings and to reduce the chemical inhomogeneity. Uncoated tungsten carbide inserts are used as cutting tool. Rough turning on fabricated ingots is first performed on Lathe machine to make specimens of uniform diameter as shown in figure 1,2. Initially, based on the available feeds, and speeds on the Lathe, pilot experiments were conducted to find the range of feeds and speeds for material removal rate as well as good surface finish. Once the levels were identified for depth of cut, cutting speed and feed, the Taguchi's L16 orthogonal array was opted to develop the experimental design. Table 1 lists all the factors and their selected levels. Figure.1 Schematic diagram showing the stir casting process 90 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Figure.2 Composite specimens Table 1. Factors and levels selected S.No Factor Un it Levels of Factors 1 234 1 Cutting speed, v m/min 20 50 75 115 2 Feed, f mm/rev 0.05 0.10 0.16 0.20 3 0.2 0.4 0.6 0.8 Depth of cut, d mm Mitutoyo's Surf test SJ-210, an instrument which is generally used to measure the surface roughness, was used in this experiment to calculate the average surface roughness (Ra) of 16 specimens bymeasuring the surface roughness at three various locations. III. METHODS Grey Relational Analysis (GRA) GRAchanges the optimization of multiple response characteristics into single GRG. The procedure involves: (i) conversion of experimental data into normalized values, (iii) evaluation of GRCs and (iv) generating GRG. In this work it is decided to optimize simultaneously Ra and MRR. Experimental data sets based on L16 orthogonal array was used. The response values are normalized to (i.e., 0< <1) utilizing the third equation (Eq.1) for smaller better type whereas for larger better type, the equation 4 is used. = (1) In the equation above, n denotes the number of replications while denotes the observed response value with i =1, 2, ....,n and j =1, 2,...,k. = (2) Equation 3 is nothing but the GRC () which can be exhibited as the relation that exist between the ideal best and actual normalized experimental values ISBN: 978-0-13-601970-1 91

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) (k) = (3) Where i=1,2,….n; k=1,2,…n; = (k) - (k) ; = (k) - (k) . When taking an average of GRCs of every performance characteristic, then it results in GRG ( ) and Eq. (4) denotes the same. = (k) (4) where denotes the GRG for experiment whereas k denotes the number of performance characteristics. Analysis of variance: Analysis of Variance (ANOVA) is conducted in order to measure the difference present among the available set of sources. It is generally applied in order to calculate the contribution made by the input parameters chosen for the study than the output response. The results and the inferences made from theANOVA can be utilized to find out the parameters that can be held accountable for the performance of the selected process and it can regulate the parameters for better performance. III. RESULTS & DISCUSSIONS Implementation of GRA Step 1 The output responses are normalized using Eqs. (1), (2) which is given in Table 2. Step 2 GRA operation has been performed. Calculate the GRC for the output response values by using Eq. (3). The value for max has been considered as 0.5 in Eq. (3) and equal weightage is given to all the process parameters [18]. Moreover, the results related to the GRC are given in Table 3. Step 3 Further, the GRG can be determined using Eq. (4). Finally, the gray relation grades are used to optimize the multi response parameters which are given in Table 3. Table 2. Normalized values Exp. No. MRR Ra 1 0.000 0.859 2 0.078 0.685 3 0.200 0.215 4 0.217 0.000 5 0.096 0.725 6 0.090 0.872 7 0.591 0.349 8 0.521 0.322 9 0.500 0.966 10 0.826 0.886 11 0.217 0.443 12 0.709 0.376 13 0.522 1.000 14 0.557 0.946 15 0.870 0.732 16 1.000 0.537 92 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Table 3. Grey Relational Grade values Exp. No. MRR Ra Grey Relational Grade 1 0.333 0.780 0.557 2 0.352 0.613 0.482 3 0.385 0.389 0.387 4 0.390 0.333 0.362 5 0.356 0.645 0.501 6 0.355 0.797 0.576 7 0.550 0.434 0.492 8 0.511 0.425 0.468 9 0.500 0.937 0.719 10 0.742 0.814 0.778 11 0.390 0.473 0.431 12 0.632 0.445 0.538 13 0.511 1.000 0.756 14 0.530 0.903 0.716 15 0.793 0.651 0.722 16 1.000 0.519 0.760 Table 4. Response table for GRG. Machining Parameters L1 L2 L3 L4 Delta Rank Cutting Speed 0.472 0.550 0.60 3 0.731 0.259 1 Feed 0.619 0.671 0.57 2 0.494 0.177 2 Depth of cut 0.523 0.578 0.60 3 0.652 0.129 3 Main Effects Plot for SN ratios Data Means vfd -3 Mean of SN ratios -4 -5 -6 -7 20 50 75 115 0.05 0.10 0.16 0.20 0.2 0.4 0.6 0.8 Signal-to-noise: Larger is better Fig. 2. Response graph for every level of machining parameters On the basis of Table 4 and figure 2, the optimum values in case of machining process parameters are listed as follows; depth of cut at level four (0.80 mm) (d4); feed at level two (0.10 mm/rev) (f2); cutting speed at level four (115 m/min) (v4). Simultaneously, when these conditions are used, it diminishes Ra and enhances MRR along machining with all the investigated factors. Equation 5 shows the response equation of GRG. The maximum value (rank 1) of cutting speed (v) highly influenced its multi-performance which can also be understood from the figure 2. GRG = 0.681 - 0.00013 v - 0.95 f - 0.694 d + 0.000000 v*v - 14.61 f*f - 0.037 d*d + 0.0179 v*f + 0.00457 v*d + 6.03 f*d (5) ANOVA, having executed at 95% confidence level, was done so in order to assess the role played by every factor in multiple performance characteristics. Table 5 shows theANOVAresults. The % contribution of cutting speed was determined as 46.08 as mentioned in ANOVA table of GRG which infers that a prominent role was played by cutting speed in the determination of GRG. ISBN: 978-0-13-601970-1 93

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The confirmatory experiment was used to verify the results obtained. In table 5, the confirmation results are listed for surface roughness and MRR corresponding to initial and optimal machining conditions. From the results, it is clear that when optimal parameter combination is preferred during machining, it minimizes the Ra from 1.52 to 1.44 µm and MRR from 0.020 to 0.023 g/sec. Equation 6 was used to calculate the estimated or predicted GRG ( ) at the optimum level of the machining process parameters. =+ -) (6) In the equation, denotes the mean value of GRGs for all experimental runs whereas denotes GRG mean at the optimum level of parameter. In the equation, q represents the number of machining parameters that significantlyaffect GRG. As per table 5, it is obvious that when using optimal setting during machining, the GRG got significantly improved i.e., 0.3193 and 0.2949 for experimental and predicted values respectively. So, the current research work clearly infers that the greyrelational method in combination with Taguchi-based experimental design remains a useful technique with minimum experimental trails. It also eases the optimization of multi performance characteristics of machiningAl7075 hybrid metal matrix composites. Table 4:ANOVAof GRG Source DF Seq SS Adj MS F-Value Cont. v 1 0.1415 0.0000 0.00 46.08% f 1 0.0439 0.0008 0.29 14.32% d 1 0.0341 0.0067 2.44 11.10% v*v 1 0.0006 0.0000 0.00 0.20% f*f 1 0.0207 0.0189 6.81 6.75% d*d 1 0.0000 0.0000 0.01 0.01% v*f 1 0.0081 0.0069 2.52 2.64% v*d 1 0.0076 0.0070 2.52 2.50% f*d 1 0.0336 0.0336 12.11 10.96% 6 0.0166 0.0027 5.43% E rror 15 0.3071 100 .00% T otal Table 5: Conformation Experiments Levels Initial machining Optimum machining parameters level parameters level Ra v=20 f=0.05 d=0.2 v=115 f=0.1 d=0.8 Experimental MRR P redicte d 1.44 GRG 1.52 0.23 Improvement in the GRG 0.02 0 0.8760 0.8516 0 .5567 0.3193 0.2949 IV. CONCLUSIONS The machining ofAl-10%FA/SiC metal matrix composite was conducted in the current research work with cutting speed, feed rate and depth of cut are the input parameters. whereas the surface roughness and MRR in lathe machine being the response parameters. In the present research work, a Taguchi's L16 orthogonal array has been designed to perform turning operation on the composite. The optimal combination of input parameters was found to be as follows; cutting speed 115 m/min, feed rate 0.1 mm/rev and depth of cut 0.80 mm. 94 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Based on the ANOVA statistics, it is understood that the cutting speed remains the most impacting fact when it comes to effecting the output parameters So, the study can be concluded that the optimization process conducted in this research notable enhanced the production of turning ofAl-10%FA/SiC metal matrix composite. REFERENCES 1. Surappa, M. K. (2003). Aluminium matrix composites: Challenges and opportunities. Sadhana, 28(1-2), 319-334. 2. Gopalakrishnan, S., & Murugan, N. (2012). Production and wear characterisation of AA 6061 matrix titanium carbide particulate reinforced composite by enhanced stir casting method. Composites Part B: Engineering, 43(2), 302-308. 3. Alaneme, K. K., Ademilua, B. O., & Bodunrin, M. O. (2013). \"Mechanical properties and corrosion behaviour of aluminium hybrid composites reinforced with silicon carbide and bamboo leaf ash\". Tribology in Industry, 35(1), 25-35. 4. Özel, T., & Karpat, Y. (2005). \"Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks\". International Journal of Machine Tools and Manufacture, 45(4-5), 467-479. 5. Reddy, B. S., Padmanabhan, G., & Reddy, K. V. K. (2008). \"Surface roughness prediction techniques for CNC turning\". Asian Journal of Scientific Research, 1(3), 256-264. 6. Hung, N. P., Venkatesh, V. C., & Loh, N. L. (1999). Machining of metal matrix composites. Manufacturing Engineering And Materials Processing, 53, 295-356. 7. Reddy, V. V., Krishna, M. G., Kumar, K. P., Kishore, B. N., Rao, J. B., & Bhargava, N. R. M. R. (2018, February). Studies on microstructure and mechanical behaviour of A7075-Flyash/SiC hybrid metal matrix composites. In IOP Conference Series: Materials Science and Engineering (Vol. 310, No. 1, p. 012047). IOP Publishing. 8. Gajalakshmi, K., Senthilkumar, N., & Prabu, B. (2019). Multi-response optimization of dry sliding wear parameters of AA6026 using hybrid gray relational analysis coupled with response surface method. Measurement and Control, 0020294019842603. 9. Mohamed, S. A. N., Zainudin, E. S., Sapuan, S. M., Deros, M. A. M., & Arifin, A. M. T. (2019). Integration of Taguchi-Grey Relational Analysis Technique in Parameter Process Optimization for Rice Husk Composite. BioResources, 14(1), 1110- 1126. 10. Mahamani, A., & Chakravarthy, V. A. (2019). Multi-response Optimization of Process Parameters in Laser Drilling of AA6061-TiB 2/ZrB 2 In Situ Composite Produced by K 2 TiF 6-KBF 4-K 2 ZrF 6 Reaction System. In Advances in Manufacturing Processes (pp. 421-432). Springer, Singapore. 11. I??k, B., & Kentli, A. (2009). Multicriteria optimization of cutting parameters in turning of UD-GFRP materials considering sensitivity. The International Journal of Advanced Manufacturing Technology, 44(11-12), 1144-1153. 12. Palanikumar, K., Karunamoorthy, L., & Karthikeyan, R. (2006). Multiple performance optimization of machining parameters on the machining of GFRP composites using carbide (K10) tool. Materials and Manufacturing Processes, 21(8), 846-852. 13. Deng, J. (1989). Introduction to grey system theory. Journal of Grey system, 1(1), 1-24. 14. Mia, M., Rifat, A., Tanvir, M. F., Gupta, M. K., Hossain, M. J., & Goswami, A. (2018). Multi-objective optimization of chip- tool interaction parameters using Grey-Taguchi method in MQL-assisted turning. Measurement, 129, 156-166. 15. Huang, C. H., Yang, A. B., & Hsu, C. Y. (2018). The optimization of micro EDM milling of Ti-6Al-4V using a grey Taguchi method and its improvement by electrode coating. The International Journal of Advanced Manufacturing Technology, 96(9-12), 3851-3859. 16. Samson, R. M., Geethapriyan, T., Raj, A. A., Ashok, A., & Rajesh, A. (2019). Parametric Optimization of Abrasive Water Jet Machining of Beryllium Copper Using Taguchi Grey Relational Analysis. In Advances in Manufacturing Processes(pp. 501-520). Springer, Singapore. 17. Hussain, M. Z., Khan, S., & Sarmah, P. (2019). Optimization of powder metallurgy processing parameters of Al2O3/Cu composite through Taguchi method with Grey relational analysis. Journal of King Saud University-Engineering Sciences. 18. Tosun, N. (2006). Determination of optimum parameters for multi-performance characteristics in drilling by using grey relational analysis. The International Journal of Advanced Manufacturing Technology, 28(5-6), 450-455. ISBN: 978-0-13-601970-1 95

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Modeling and StructuralAnalysis of Composite Material BasedAutomobile Chassis A. Pavan Kumara, D. Kondayya1,b, N. Yashaswini2,c 1Department of Mechanical Engineering, Sreenidhi Institute of Science and Technology, Ghatkesar, Hyderabad, Email: Corresponding author: [email protected], [email protected], [email protected] ABSTRACT The truck chassis is one of the giant systems of a vehicle. It is overall made of metallic, which holds the frame and all components of a truck vehicle. More precisely, vehicle chassis is a support element on which diverse parts like suspension, engine air filter, fuel tank, power source (battery), guidance etc., are mounted, in order to provide flexibility and strength to the vehicle. In the present paper, we are replacing the material of with composite fiber materials like E - Glass and S - Glass epoxy. The ladder-type chassis body is designed in CATIA V5 software after which it's imported to ANSYS workbench 2021 R1. The evaluation is performed on selected materials subjected to comparable situations like that of chassis made of metallic (steel). The effects are then envisioned to finalize the suitable the amongst 3 materials. Keywords: Chassis, E-Glass Epoxy, S-Glass, Structural Steel. Catia v5 software is used for designing, ANSYS student version 2021 is used for analysis. INTRODUCTION The word chassis first used by French country and was primarily used to refer to the main structure of the vehicle chassis. \"chassis\" consists of long cross members and support beams that support a human made designed and use. It looks like skeleton of animal structure. Chassis body plays a most crucial position in every vehicle it acts as a major structure for automobiles nearly all of the critical elements are connected with chassis frame like engine, suspension gadget, guidance system, tires, and also hold nearly all components that are designed to run the vehicle and chassis frame additionally heavy so chassis frame must be sufficient to withstand vibrations, electrical shocks, vibrations and chassis withstand (overcome) all the stresses and deformations developed on the vehicle. LITERATURE REVIEW 1. Swami K.I. et al.An essential consideration in chassis structure design is having adequate flexural stiffness for better handling characteristics. This article was about the work done for the static structural analysis of the truck frame. Structural systems such as the framework can be easily analyzed using finite element techniques. 2. Pankaj Saini andAshish Goel stated that the comparative analysis between conventional steel leaf springs and composite materials such as glass fiber reinforced polymer of carbon epoxide, epoxy-based glass, and graphite-based epoxy was used for the design of the leaf spring. DESIGN METHODOLOGY Verification of analytical results for design review can be done on final prototype.Three-dimensional geometric modeling of the various components of chassis has been carried out in part model using Catia. The properties, 96 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) viz. cross-sectional area, beam height, area moments of inertia of these 3-D modelled parts are estimated in Catia V5 R20. Then the design of the chassis file is converted into an IGES file it allows the specific file format to exchange information among computer-aided designing (CAD). These properties are provided as input while performing FEAusingAnsys. FEAis performed to find the results of total deformation and equivalent von mises stress. SPECIFICATIONS OF TATA LPT 2515 EX BS-3 FIGURE 1. Chassis Tata truck parts, Designed in Catia V5 FIGURE 2. Chassis Tata truck complete view, Designed in Catia V5 97 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Problem Statement Problem Statement Some of the major problems listed in the chassis must overcome in the development stage before manufacturing the component of the chassis. it is very important that the chassis must withstand the failure caused due to fatigue. Usually, the chassis structure moves up and down along with the wheels as they move over uneven profiled roads. steel cannot resist corrosion and weight is more, the density of steel is high when the vehicle weight increases it needs more energy to move the truck, and fuel consumption is more when vehicle weight increases. Improved design to improve the fatigue resistance of the frame for uneven roads conditions, weight optimization of basic designs to reduce costs in batch production. • In the present work the Tata LPT 2515 Model. Chassis is replaced with the composite material • To improve the fuel efficiency by reducing mass (weight) of the vehicle • Composites are flexible and more durable than steel Design Process Part modelling: Catia V5 R20 software is used for design of chassis, in this module various parts of chassis are modelled. Initially we designed the parts of the chassis according to the specifications of the tata truck 2015. The parts are involving in chassis are the long members, cross members, front and rear overhangs are modelled with given constrains. Assembly: In this all the parts of the structure are provided with required constrains and connected together to form the complete structure of Tata truck chassis. SIMULATION AND ANALYSIS RESULTS Static structural Analysis: The chassis catia file is converted in to IGES format is directly imported in to ansys workbench Static investigation FEA is performed to find the results of total deformation, equivalent stress. FIGURE 3. Meshing is done on model with 19158 nodes and 11028 elements. 98 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) FIGURE 4. Total deformation and stress developed in structural steel FIGURE 5. Total deformation and equivalent stress developed in S-Glass epoxy FIGURE 6. Total deformation and equivalent stress developed in E-Glass epoxy Factor of safety analysis ISBN: 978-0-13-601970-1 99

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) FIGURE 7. FOS of steel, s-glass epoxy, e-glass epoxy FIGURE8. Graphs TABLE 1. Analysis Results S .N o Materials Total Deformation Equivalent stress Factor of safety (mm) (Mpa) (FOS) 1. STEEL 0.35353 1.161 2. S-GLASS 0.017128 0.34969 1.741 3. E-GLASS EPOXY 0.007540 0.34829 2.048 0.000241 CONCLUSION In this paper, the results of S-Glass and E-Glass epoxy have been compared to that of steel vehicle chassis. By using composite material for the vehicle chassis there is weight optimization when compared to original results. Structural and modal analysis is done using three materials which is steel, S-Glass, and E-GLASS EPOXY. Considering the analysis results the values of assumed materials are lesser than the permissible limits. By using the layers to maintain the same thickness of the chassis, Deformation is high in steel and less in composite materials. So, using this composite for chassis is a safe and composites alternative to steel, the weight of the chassis reduces because the density of composite materials is less than the steel density. 100 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) REFERENCES 1. Yucheng Liu, Finite component Truck Chassis Model, Impact Resistance Analysis Model, Department of engineering science, University of American state, Lafayette, LA 70504, USA 2. Vijaykumar V. Patel, RIPatel, Structural Analysis of a step Frame Structure \", World Journal of Science and Technology 2012, 3. Hemant.Patil, Sharad.Kachave, Eknath.Deore, Automotive Frame Stress Analysis with totally different Thickties\", IOSR Journal of Mechanical and applied science (IOSRJMCE), vol. 6, Nummer 1 4. A. Rahman, R., Taemin, MN, Kurdi, O., 2008, \"Stress analysis of significant Truck Chassis exploitation Finite component Method\", Journal Mechanical 5. s Autar K. Kaw. Composite Materials. 2e, Taylor et Francis cluster, LLC, 2006. 6. Nitin S.Praktische Finite-Elemente-Analyse von Gokhale 7. C. Karaoglu, NS Kuralay, Bolt Joint Truck Frame Tension Examination, Finite parts in Analysis and style, 38, (2002), 11151130. ISBN: 978-0-13-601970-1 101

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Review on Laser Drilling on GFRP Composites G.Guru Mahesh1, C.Ganesn2, G.Guru Sai Prasad3, Dr.N.Rajesh4, D.Raju5 1,3,5Assistant Professor, 2UG Student, 4Associate Professor, 1,2,3,4,5Department of Mechanical Engineering, S V College of Engineering, Tirupati. 1. ABSTRACT Composite materials are nowadays having gained a lot of interest. Through numerous studies, the damage to glass fibre-reinforced polymer (GFRP) composites increased, while traditional machining processes, like cutting and drilling. This is due to the fact that difference in the material properties of fibre and matrix. However, unconventional methods showed minimal damage to the surface with precision. The damage occurred in GFRP composite comprised of delamination, cracking of the material at the edge as well as tool wear so laser machining is generally preferred as there is no contact between tool and workpiece, any tool wear and vibrations. The objective of this study to give an overview of the cutting of GFRP composite and the quality of cut surface by analysing the heat- affected zone, taper angle and kerf width. The aim of this study to reveal the damages occurred due to operational parameters and found that the surface quality improved by optimising laser power, scan speed and standoff distancing is a category of plastic composites. Here, fiberglass materials are used to mechanically improve the strength and hardness of plastics. Fiberglass composites have a relatively higher strength-to-weight ratio than other materials GFRP Has Excellent impact resistance. By applying artificial neural network to input parameters and optimize for getting good quality of circular hole. 2. INTRODUCTION Fiber reinforced plastic (GFRP) was introduced in the 1940s. Fiberglass is used to improve the mechanical strength and hardness of polymers. Fiberglass reinforced plastic (GFRP) is an advanced composite material based on an epoxy matrix., (Rao B et al. 2019, p. 1459)Due to its low cost and high quality, GFRP is used in various industries such as automotive, aerospace, sporting goods and electronics. In addition, GFRP has a high strength-to-weight ratio among impact resistant materials..(Solati et al. 2019b, p. 791). Traditional methods such as turning, milling, grinding, and drilling are common for GFRP cutting / machining. (Rao B et al. 2019, p. 1459) 3. CONVENTIONAL AND UNCONVENTIONAL MACHINING PROCESS 3.1. ConventionalMachining Conventional machining can be defined as a process using mechanical energy.In these \"traditional\" or \"conventional\" machining processes, machine tools, such as lathes, milling machines, drill presses, or others, are used with a sharp cutting tool to remove material to achieve a desired geometry. 3.1.1 Turning In addition to drilling, milling, and trimming, turning is one of the most commonly used cutting processes for processing GRP composites, and is used for rotational symmetric parts such as shafts, pipes, gears, and spindles.By using statistical techniques based on analysis of orthogonal sequences and variance, we studied the effects of various shear parameters on surface roughness and specific shear pressures.With respect to the cutting parameters, it has been shown that the feed rate has the most effect on the surface roughness (Ra) and the specific cutting 102 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) pressure (KS). Further the manual lamination process achieved at lower specific cutting pressure values and lower surface roughness as compared to filament winding, resulting in the highest machinabilityindex with optimal cutting parameters. (vc = 400 m/min, f = 0.1 mm/rev). (Caggiano 2018) Artificial neural networks (ANNs) has been developed to predict surface roughness. The predictive model results in providing good agreement with experimental measurements with a maximum test error of about 6%.(Caggiano 2018) 3.1.2. Drilling The drilling process for GFRP composites is one of the most widely used treatment methods for GFRP materials, as a mechanical connections such as rivets are widely used instead of welded or adhesive connections. The main challenges of GFRP drilling are rapid tool wear and damage to the integrity and surface quality of the material. (Caggiano 2018). The Comprehensive analysis of pollution using various bits, including traditional twist bits and special bits such as pinch bits, saws, core bits, and step bits.a high performance sintered carbide drill was investigated for drilling of CFRP composites.TIN and DLC coatings are used to reduce the high wear rate of sintered carbide chips, and coating performance has been studied in terms of material damage, shear forces, and torque generated during machining .The damage produced by drilling was due to spalling, chip-out, and matrix cracking. The coatings were not found to reduce either tool wear or damage to the composite. (Caggiano 2018) We analyzed hole quality parameters such as hole diameter, roundness, peel release, and extrusion release (below fig..). The feed rate has been shown to have a greater effect on thrust, output thrust delamination, and hole diameter (smaller feeds have a greater effect on thrust delamination and hole diameter (the higher the feed rate). The slower, the higher the compressive force. And the pollution output. , A faster feed rate will produce holes closer to the nominal diameter, but spindle speed is one of the main determinants of borehole roundness.(Caggiano 2018) Figure:(a) Peel-up and (b) push-out delamination induced by drilling of fibre reinforced plastic (FRP) laminates. Orbital drilling generated a better hole quality with lower process forces, but required a more complex/ dynamic machine tool and longer process times. Up to three times higher axial feed forces occur in conventional drilling, when compared to orbital drillingwherethe axial feedforces, after initial wear, remain constant. Significantly less hole exit damages (spalling, delamination, or uncut fibres, see below Figure) and less bore channel damages ISBN: 978-0-13-601970-1 103

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) (fibre cracks, pull-out, and bending) are generated in orbital drilling, but the process time is twice the process time of conventional drilling.(Caggiano 2018) FIG :CarbonFibre reinforced plastic (CFRP) drilled hole exit damage: delamination, spalling and uncut fibres. 3.2. Unconventional Machining Non-traditional(unconventional) machining technologies such as laser beam machining, electrical discharge machining due to specific problems that occur when cutting composite materials. This may be due to material damage due to high tool wear or high mechanical force. 3.2.1 Laser Beam Machining Laser machining (LBM) is an alternative to traditional CFRP cutting techniques, avoiding mechanical effects that can damage the workpiece and rapid wear of the tool by abrasive fibers.(Caggiano 2018) The laser cutting process produces consistently high-quality cut edges. Cutting speed, laser power, stall distance, and gas pressure are important factors for cutting GFRP composites. The expected benefits of lasers depend on the thermal nature of the manufacturing process. Laser systems typically have a high cost of capital, but laser cutting has the advantages of narrow cutting width, local material damage, and rapid cutting speed. The main challenge in laser beam processing of fiber reinforced plastic composites is the creation of thermally altered regions that cause matrix settling, fiber deformation, and contamination. Careful selection of process parameters can reduce the HAZ range with special consideration of laser power, pulse energy, and overlap factor. In addition, the use of cryogenic parameters appears to be a promising process development.(Caggiano 2018) Composite cutting of materials involves three types of lasers, which are described below. a) CO2 laser A CO2 laser is a continuous wave laser with a peak output of 100 kW and efficiency of 10 to 15%. The active laser medium is a gas discharge that can be air-cooled (water-cooled for high-power applications). The exhaust gas in the discharge pipe is made of CO2, N2 and He gas in the ratio of 3: 8: 4. Alaser yield wavelength of 10.6 m is used to refer to medical material handling and application. They have relatively high efficiency and very good beam quality. (Below figure1) shows below CO2 laser processing equipment. 104 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The laser used as the industrial laser, where CO2 is the active gas, which can function, in both continuous mode and pulse mode. The laser operating in continuous mode are classified as CO2 laser of low power (3-100 W), CO laser power of intermediary (300-3000 W) and a CO laser with high power. 22 Figure 1. Schematic representation of CO2 laser. b). Nd: YAG laser ND: YAG lasers are solid-state lasers that operate in both pulsed and continuous modes. Produces a laser beam with a wavelength of 1,064 m. It has several advantages such as much higher power consumption, higher gain, and efficiency than ruby lasers. Solid state ND: YAG laser is used to drill holes in metal. The Nd: YAG laser machining system as shown in Figure 2. Figure 2. Schematic representation of Nd: YAG laser beam machining system. c) Fibre and excimer laser A fiber laser is a laser in which the active gain medium is an optical fiber doped with rare earth elements such as erbium, neodymium, and ytteriumFiber laser. Mainlyused in materials processing applications such as marking, ISBN: 978-0-13-601970-1 105

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) engraving and cutting.An excimer laser is a pulse gas laser that uses a mixture of rare gas and halogen gas as an active medium. Excimer lasers mainly operate in the UV range of mixtures of noble gases (argon, krypton, or xenon) and halide molecules (chlorine or fluorine). Lasers typically produce short pulses with a repetition rate of up to 1000 pulses with a maximum power of 10-20 MW.(Bhaskar et al. 2019) 3.3. Properties of laser beam A laser is basically a light amplification by stimulated emission of radiation, a beam of high-energy electromagnetic radiation. Light moves in space like a wave, but when it collides with a substance, it behaves like an energy particle. Laser beams involved in cutting composites due to various factors and contribute to good results.(Bhaskar et al. 2019) 4. ANALYSIS 4.1. Heat-affected zone Laser cutting of composites usually leads to heat-affected areas, and subsequent experiments are performed to reduce this by optimizing cutting parameters such as laser power and cutting speed. The thermal change zone is the region around the laser-cut material, where the microstructure changes with the temperature peaks. (Bhaskar et al. 2019). Examining the three major conductivities K1, K2, and K3 along the x, y, and z axes, we came to the conclusion that the thermal damage in the z-direction is longer than in the y-direction. (Bhaskar et al. 2019).In the case of CFRP material, swelling of the fibers is seen, but in GFRP, carbonated black material called shell and glass fiber is seen in the thermal transformation zone.An equal width w is given. WhereAis the area of the entire segment and L is the length of the profile of the equation. W =A L PP has a higher HAZ. The laser power increases the HAZ and decreases with the cutting speed and gas pressure. The effect of laser power and cutting speed on the width of the HAZ is shown by the reaction surface diagram as shown in Figure 13 (Bhaskar et al. 2019)(Bhaskar et al. 2019) HAZ=PQ/V Better quality cuts obtained in GFRP by increasing the passes shown below in Figure 3. Up to 50 mm/min processing speed resolidified matrix material observed. HAZ analysed by the areas of excavated fibres oriented in the cutting direction and separated from the composite(Bhaskar et al. 2019) Figure 4.Dependence of the heat-affected zone (HAZ) (a) Processing speed and (b) Number of passes to reach a full separation cut vs. processing speed. 106 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 4.2. Taper angle The taper angle is concerned with estimating the quality of the cut based on two factors: the width of the upper cut and the width of the lower cut. The taper angle is the pulse rate and is influenced by many variables that also react to the oxygen content of the auxiliary gas. This is shown in Figure 6. The interaction between the laser and the material decreases as the pulse frequency increases. Temper angle affected by pulse energy, pulse frequency, duty cycle and assist gas pressure (Bhaskar et al. 2019) Figure 6. Influence of the assist gas pressure during pulsed laser cutting using the conventional cutting head on (a) the kerf width in the entry and exit side, (b) the taper angle and (c) the width of the HAZ. The cutting angle varies directly with the cutting speed. For fiberglass reinforced composites, both the average cutting angle and the exhaust surface angle are significantly reduced. The effect of laser power and stall spacing had a relatively greater effect on the taper angle compared to other operating input parameters such as cutting speed and cover gas pressure. 4.3. Kerf width The cuts(Kerf's) are usually not parallel from top to bottom. The deduction depends on the following factors: • Focal diameter • Material • Wavelength • Cutting procedure Kerf analysis was performed on both single and double fitting bars. For the single fitting bar, the calf width was increased according to the thickness of the material and the nozzle diameter, but was optimized by increasing the cutting speed. In the case of double pass bars, the width of the upper and lower cut varies. Therefore, ISBN: 978-0-13-601970-1 107

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) increasing the cutting speed reduces the cutting width. In the case of double pass bars, the difference between top cut and bottom cut width and top cut width was similar in case of single pass bar, but there was a tendency for width to decrease. The lower cutA, as shown in fig. The width of the cut is most affected by the translational motion, with the increase in exposure to the laser material at a slower rate.(Bhaskar et al. 2019) Some models such as ANN (artificial neural network), quadratic regression, fuzzy logic analysis, etc. to obtain results that reduce the probability of error between experimental models and theoretical models.(Bhaskar et al. 2019) The cutting width indicates the amount of additional cutting up and down and the stem of the cutting surface. At some outputs (105-107 W / cm²), a \"keyhole\" is formed that behaves like a blackbody of laser radiation. The important parameters taken into consideration were repetition rate (RR) and pulse energy.(Bhaskar et al. 2019) The motion of the workpiece with respect to fiber orientation resulted in heat buildup on the surface, due to its low thermal conductivity along the vertical direction and the spherical structure seen on the surface by the microphotograph(Bhaskar et al. 2019) 5. ARTIFICIAL NEURAL NETWORK ANN can generally be defined as a structure consisting of several interconnected units [2]. Each unit has input/output attributes (I / O) and applies local calculations or functions. The output of each unit is determined by its I / O characteristics, connections to other units, and (possibly) external inputs and their internal functions. Networks typicallydevelop overall functionalitythrough one or more types of training. The basic unit or component of an RNA is called an artificial neuron (later called a neuron). A neuron has a series of weighted inputs (Xi) before the processing element reaches the body. In addition, the bias term, the threshold that neurons need to reach or exceed to generate a signal, is the nonlinear function (Fi) acting on the generated signal (Ri) and the output (OI). The basic model of a neuron is illustrated in Fig. 2. Fig. 2. Basic model of artificial neuron. The two main categories of learning in ANN are supervised and unsupervised. In supervised learning, the outgoing response is compared to the desired target response. If the actual response differs from the target response, the network will generate an error signal. This error signal is used to calculate synaptic weight adjustment so that the actual output matches the target output. Conversely, unsupervised learning does not require target output. (El Kadi 2006, p. 2)(El Kadi 2006, p. 2) 5.1. Design of the Artificial Neural Network Neural networks are a technique inspired by the biological nervous system that aims to recreate people's learning methods to solve a variety of complex scientific problems. Neural networks consist of multiple layers of neurons connected by synaptic loads to simulate the human brain.Asimplified network consists of an input layer 108 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) with a large number of neurons, followed by one or more hidden layers, based on the input variable (4 in this case). These layers convert these variables into output layers for end use. Figure 7 shows theANN scheme used, where w231 is the weight from the third neuron in the second layer to the first neuron in the second layer to the first neuron in the third layer(Feito et al. 2019) Figure 7. Architecture of the ANN with three layers implemented. 5.2. Model prediction using artificial neural network Artificial neural networks have been developed to mimic the linear sequencing function of interconnected neural cells within the human brain structure known as biological neurons. That is, a group of specific inputs is mainly used. Each shows a different neural output. Each input is multiplied by the same weight of added synaptic force to determine the level of neuron activation. In this work, we apply an artificial neural network to propose a training model so that the set of inputs returns a set of appropriate or useful outputs. ANN uses a layered architecture consisting ofdifferent layers (input, hide, output) and a feedforward backpropagation training algorithm to solve non-linear and complex problems. Usually, in back-propagation NN, the net input is expressed as follows: Yj=∑ni=1wijxi And the network output (Zj) of each neuron is obtained by processing the net input via an activation or transfer function (here, tangent hyperbolic type) as follows: Zj= f(Yj)=1 –e-Yj/1 + e-Yj where Yjnet input is considered as linear combination of input variables in terms of weights, j number of neurons, (Dixit et al. 2019, p. 341) ISBN: 978-0-13-601970-1 109

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Table 5 Check data set for testing ANN model and comparison results of predicted and measured dimensions of microgroove Table 6 Trainingdata set for testing ANN model and comparison results of predicted and measured dimensions of microgroove 110 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) n is the input parameters, xi is the input parameter i of the network, wij represents the synaptic weight to jth neuron in the output layer from the ith neuron in the previous layer. In this study, several network architectures were tried before using the optimal neural network architecture of 5-8-8-3 (minimum MSE) shown in Figure 5. The network consists of an input layer with 5 neurons, 2 hidden layers with 8 neurons each, and an output layer with 3 neurons in each. To calculate the connection load, you need a set of required network output values, sometimes called training datasets. The desired output training dataset was prepared using the experimental dataset, as reflected in Table 3. MATLAB's TRAINGD neural network (feed-forward-back-propagation) was used for training network data to obtain closed solutions. It was widely used for predicting and optimizing various processes.TRAINGD is a network training function that uses a gradient descent method that measures output error, calculates error gradients by iterativelyadjusting and updating the weighting variable in the direction of the negative gradient of the power function, and the mean square. Reduces the error. ) Between predictive data and training data sets. The change in weight variables is given in below equation wij =-n(E /wij)Zj(Dixit et al. 2019, p. 342) Where E is the root mean square error that approximates the error gradient, and  is a learning rate parameter that typically controls the stability and convergence of the ANN model. Is assumed to be 0.0001, which is a constant value of the learning rate. The MSE value calculated byANN is 0.000099. Figure 6 shows the data observed based on theANN training experiment using MATLAB. We compared the results of the data obtained from the experiment with the expected data obtained from the neural network. Of the 32 experimental data obtained according to DOE, 29 were made to train neural network models. Subsequently, the remaining three (32-29) experimental results (control data) were compared with the trained ANN model. Tables 5 and 6 show the comparison results between the experimental and ANN for 3 check data sets and 29 training sets, respectively. It can be seen that there is a close agreement between the ANN prediction and the experimental results. Figures 7, 8 and 9 compare theANN prediction results for upper width, lower width and depth with the results of experiment for training and check data sets. It is observed that the variation inANN and experimental result is under 3%, which avoids the misleading (Dixit et al. 2019, p. 343) 6. CONCLUSION The cutting quality of composites made of fiberglass reinforced polymer (GRP) using a different processing method has resulted in better results than traditional processing methods..(Bhaskar et al. 2019) Studies have shown that the heat-affected zone was the main output variable affecting the surface properties of fiberglass reinforced composites. (Bhaskar et al. 2019) A small amount of incident energy from the laser can prevent the top cut width on the surface of the material from being widened.(Bhaskar et al. 2019) The HAZ elongation of the Drilledhole can significantly affect the storage stability of the sample. Bearing resistance decreased almost linearly and HAZ increased. (Solati et al. 2019a, p. 114) ANN allows you to generate forecasts that are accurate to those obtained using traditional methods. Improve the predictive capabilities of these networks through development (El Kadi 2006, p. 21) Using less laser power with higher scan speeds will help reduce the heat-affected area. (Bhaskar et al. 2019) ISBN: 978-0-13-601970-1 111

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) REFERENCES 1. Bhaskar, Vineeta; Kumar, Dhiraj; Singh, K. K. (2019): Laser processing of glass fiber reinforced composite material: a review. InAustralian Journal of Mechanical Engineering 17 (2), pp. 95-108. DOI: 10.1080/14484846.2017.1363989. 2. Caggiano, Alessandra (2018): Machining of Fibre Reinforced Plastic Composite Materials. InMaterials (Basel, Switzerland) 11 (3). DOI: 10.3390/ma11030442. 3. Dixit, SalilaRanjan; Das, SudhansuRanjan; Dhupal, Debabrata (2019): Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach. InJ IndEngInt15 (2), pp. 333-349. DOI: 10.1007/s40092-018- 0295-1. 4. El Kadi, Hany (2006): Modeling the mechanical behavior of fiber-reinforced polymeric composite materials using artificial neural networks-Areview. InComposite Structures 73 (1), pp. 1-23. DOI: 10.1016/j.compstruct.2005.01.020. 5. Feito, Norberto; Muñoz-Sánchez, Ana; Díaz-Álvarez, Antonio; Loya, José Antonio (2019): Analysis of the Machinability of Carbon Fiber Composite Materials in Function of Tool Wear and Cutting Parameters Using the Artificial Neural Network Approach. InMaterials (Basel, Switzerland) 12 (17). DOI: 10.3390/ma12172747. 6. Rao B, Shiva Dayal; Sethi, Abhijeet; Das, Alok Kumar (2019): Fiber laser processing of GFRP composites and multi- objective optimization of the process using response surface methodology. InJournal of Composite Materials 53 (11), pp. 1459-1473. DOI: 10.1177/0021998318805139. 7. Solati, Ali; Hamedi, Mohsen; Safarabadi, Majid (2019a): Combined GA-ANN approach for prediction of HAZ and bearing strength in laser drilling of GFRP composite. In Optics & Laser Technology 113, pp. 104-115. DOI: 10.1016/ j.optlastec.2018.12.016. 8. Solati, Ali; Hamedi, Mohsen; Safarabadi, Majid (2019b): Comprehensive investigation of surface quality and mechanical properties in CO laser drilling of GFRP composites. InInt J AdvManufTechnol102 (1-4), pp. 791-808. DOI: 10.1007/s00170- 2 018-3164-6. 112 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Experimental Investigations ofAlloy Steel Under Sustainable Manufacturing Techniques A.Venkata Vishnu Assistant Professor, Department of Mechanical Engineering, Nalla Narasimha Reddy Education Society's Group of Institutions ABSTRACT Machining operation is one of the most essential processes of producing desired products from raw material, where in machining a lot of heat is generated due to the friction between work piece and tool. The lubricant/coolant plays an important role in reducing the friction between work piece and the tool. On the other hand, the cost of lubricant is also playing a vital role which is costing around 16-20% production cost in industries, to overcome with this situation the flow of lubricant is to be controlled which is done through a sustainable manufacturing technique like Cryogenic Machining, Minimum Quantity Lubrication etc. In the present work the effect of process parameters using turning of Stainless steel of grade SS 314 under different lubrication conditions with the help of vegetable based oils using taguchi design methodology is studied. Different models of minimum quantity lubrication and cryogenic systems were available in the market but they are costly, in this project a compact MQL and Cryogenic setup is been developed for machining SS314 steel alloy. Keywords: Machining, Cryogenic Machining, Minimum Quantity Lubrication, SS314 steel alloy, Taguchi design methodology etc. 1. INTRODUCTION Turning is the machining operation that produces cylindrical parts. It can be defined as machining of an external surface such that, there is a relative movement between work piece and single- point cutting tool. Cutting tool is being fed parallel to the axis of the work piece. In the present work a set of experiments are conducted on the work piece SS-314 with CVD coated carbide cutting tools to evaluate the effect of machining parameters such as cutting conditions, speed, feed and depth of cut on cutting temperature. Taguchi approach is used to obtain the optimal settings of these process parameters. The objective of this work is to find out the set of optimum values for the selected control factors in order to reduce the cutting temperature using Taguchi's robust design methodology, considering the control factors. In the present work, Taguchi method is used to determine the optimum cutting parameters more efficiently. Four control factors viz. cutting conditions, speed, feed rate and depth of cut are investigated at three different levels. The work piece material used is SS 314. Taguchi method is used to optimize the process parameters using signal-to-noise ratio for turning process. Experiments are carried out using L9(34) orthogonal array. 1.1 Minimum Quantity Lubrication setup: Minimum quantity lubrication eliminates large number of water and oil based coolants and replaces them with a small quantity of lubricant mixed with air. The air-oil stream is precisely metered and delivered to the cutting tool's edge. The philosophy behind mql is based on simple principle-more is not always better; use only what's needed for the application, because enough is as good as a feast.This MQL also goes with many names. It has been referred as \"Minimum Quantity Lubrication\", \"Near-Dry Machining\" or \"NDM\", \"Micro-Lubrication\" ISBN: 978-0-13-601970-1 113

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) \"Microlubrification\", \"Micro-Dosing\" and sometimes as \"Mist coolant\". Fig 1 Lathe Machine Fig 2 MQL Setup Fig 3 Lubricant Fig 4 Block Diagram of a compact MQL setup 1.2 Cryogenic Machining Setup Cryogenic machining is a material removal process where the conventional cutting fluids are replaced with cryogenics such as liquid nitrogen and CO2 etc., in this method usually liquefied gases, is directed into the cutting zone temperature and cool down the tool and/or work piece. The cryogenic medium absorbs the heat from the cutting zone and evaporates into the atmosphere. Cryogenic Coolants are used in conventional machining in material removing process can increase tool life, better surface finish, dimensional accuracy, and reduce the cutting temperature. Cryogenic coolant used in this process is DRY ICE+ACETONE mixture. Dry ice, carbon dioxide in its solid form, a dense, snowlike substance that sublimes (passes directly into the vapour without melting) at -78.5 °C (-109.3°F), used as a refrigerant, especially during shipping of perishable products such as meats or ice cream. Dry Ice-Ethanol baths are used to rapidly cool solutions to below freezing temperatures. Since dry ice will sublime at -78 °C, a mixture such as acetone/dry ice will maintain -78 °C.Also, the solution will not freeze because acetone requires a temperature of about -93 °C to begin freezing. 114 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Fig 5 Cryogenic Setup 2. EXPERIMENTATION AND DATA ANALYSIS The objective of this project work is to find out the set of optimum values for the selected control factors in order to reduce the cutting temperature and using Taguchi's robust design methodology, considering the control factors. In the present work, Taguchi method is used to determine the optimum cutting parameters more efficiently. Four control factors viz. cutting conditions, cutting speed, feed rate and depth of cut are investigated at three different levels. The work piece material used is SS 314. Taguchi method is used to optimize the process parameters using signal-to-noise ratio for turning process. Experiments are carried out using L (34) orthogonal array. 9 The work material selected is SS 314. The dimensions of the SS 314, selected are of 30mm diameter X 150mm length. The experiments are conducted using L9 (34) orthogonal array. This chapter contains the machining aspects and robust design implementation procedure in Turning of SS 314. The turning operations are carried out on Lathe machine. The experiments are conducted in VRR ENGINEERING WORKS, Kukatpally shown in fig 1. 2.1. Work piece Material: SS 314 steel has a carbon content of 0.25% and probably the most usual form of steel, because of the Chromium content the material becomes corrosion resistance .generallyavailable with a maximum brinell hardness of 230, charecterised by high core strength, excellent toughness and fatigue resistance in relatively large sections with case hardness upto RC43 when carburized, hardened and tempered. TABLE 1 COMPOSTION OF SS-314 Element Weight percentage (%) C 0.20-0.26 Cr 23-26 Ni 19-22 Mn 2 Mo 0.80-0.15 Si 0.35 S 0.03 P 0.045 ISBN: 978-0-13-601970-1 115