Browsing by Author "Rao, S.S."

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A comparative study of tensile properties of eutectic Al-Si / ZrO2 composites fabricated by spray forming and stir casting methods
(Taylor and Francis Ltd., 2022) Goudar, D.M.; Patil, I.S.; Magalad, V.T.; Rao, S.S.; Herbert, M.A.
The study aims to investigate the microstructural and mechanical properties of Al-12.5%Si matrix composites reinforced with ZrO2 were fabricated by spray forming method and stir casting (SC) technique by varying reinforcement of 2%, 6% and 10 wt.% ZrO2 powder (size 25 ?m).The spray-formed (SD) composites were subjected to hot (400°C) isostatic pressing to reduce the porosity. The microstructure of spray-formed and SC composites were examined using optical and SEM/ EDS. The microstructure of the spray-formed composites showed uniform distribution of fine Si, eutectic phase and ZrO2 particles in the equiaxed Al-matrix. In contrast, SC composites consist of a coarse Si, needle like eutectic phase and clustering of reinforcement particles at grain junctions as a continuous network along the grain boundaries. The hardness, ultimate tensile strength of both spray-formed and SC composites improved as the ZrO2 content increased, while yield strength decreased. Spray-formed composites showed better mechanical properties. This was attributed to uniform distribution fine of Si particles, reinforced particles, equiaxed matrix induced during spray deposition process. Tensile fracture surface of spray-formed composites possess ductile and cleavage fractures. SC composites showed intragranular cracks in coarse Si particles and increase in micro-cracks with increasing reinforcement. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
A comprehensive review of friction stir welding parameters on Ti-6Al-4V alloy microstructure and mechanical properties
(Taylor and Francis Ltd., 2025) Rao, R.N.; Rao, S.S.; Vijayan, V.
Ti-6AL–4 V alloy, is a widely recognised titanium alloy. It is responsible for over half of all applications involving titanium alloys, primarily due to its attractive mechanical and physical properties that make it a highly desirable material. For most applications, the vast majority of working components require permanent joining. The conventional fusion welding of titanium often leads to oxidation losses and increased brittleness. Friction stir welding improves weld quality by preventing heating the metal past its melting point. Despite the fact that Friction Stir Welding (FSW) of Ti6Al4V alloys has advantages over other welding methods, the process parameters have a major impact on the weld microstructure and mechanical properties. In most cases, a defect-free weld with the ideal microstructure can be achieved by selecting the best process parameters, such as the tool material, tool geometry, traverse speed, and rotational speed. This paper briefly reviews Ti-6Al-4 V alloy friction stir welding developments and understandings. Variation in friction stir welding process parameters like tool rotation and translation speed affects weld region microstructure constituents, defects, and mechanical properties. This paper establishes a crucial relationship between process variables, microstructure, defects, and mechanical properties. Summarising and tabulating recent developments for easy understanding and adoption is emphasised. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
A grasshopper optimization algorithm-based movie recommender system
(Springer, 2024) Ambikesh, G.; Rao, S.S.; Chandrasekaran, K.
A movie recommendation system functions as a specialized information system, providing users with personalized suggestions aligned with their movie preferences. Employing advanced algorithms and data analysis methods, these systems scrutinize variables such as users' viewing history and preferences to formulate personalized recommendations. Our proposed methodology, termed GOA-k-means, amalgamates the Grasshopper Optimization Algorithm (GOA) with k-means clustering to navigate the dynamic nature of user preferences. Facilitating real-time calibration, GOA-k-means yields recommendations that adapt to users' shifting interests. We developed our model utilizing a dataset of one million records from Movielens, pre-processed via z-score normalization and subjected to Principal Component Analysis (PCA) for feature extraction. In comparison to conventional techniques, GOA-k-means demonstrated superior performance in metrics such as precision, recall, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE), establishing itself as a valuable tool for augmenting user engagement in the entertainment industry. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.
A pressured steam JET approach to tool wear minimization in cutting of metal matrix composites
(Trans Tech Publications Ltd, 2007) Anjaiah, D.; Shetty, R.; Pai B, R.; Vijaya, M.V.; Rao, S.S.
Metal matrix composites (MMCs) have been found to possess tremendous prospective engineering applications that require materials offering a combination of lightweight with considerably enhanced mechanical and physical properties. However, the applications of MMCs are limited by their poor machinability which is a result of their highly abrasive nature that causes excessive wear to the cutting tools. In this study, an investigation into the mechanism of the tool wear in cutting of MMCs is carried out. It is found that during cutting of an MMC, the tool cutting edge will impact on the reinforcement particles. The impacted particles will then either be dislodged from the matrix, doing no harm to the tool, or be embedded into the matrix, ploughing on the tool flank and causing excessive tool flank wear. According to this tool wear mechanism, a pressured steam jet approach is developed for the minimization of the tool wear by preventing the impacted reinforcement particles from being embedded in the workpiece matrix. Experimental tests for cutting of SiC-aluminum MMC using cubic boron nitride (KB-90) and polycrystalline diamond (KP-300) tool inserts with the aid of the pressured steam jet are conducted. The results show that from full factorial design of experiments the effect of the pressured steam jet plays a significant role on the tool wear followed by tool inserts and depth of cut. The working mechanism of the pressured steam jet method and the experimental testing results are discussed in detail.
A study of microstructure and mechanical properties of friction stir welded joint of Al-Ce-Si-Mg aluminium alloy plates and optimization cum prediction techniques using Taguchi and ANN
(Elsevier Ltd, 2023) Dâ€™Souza, A.D.; Rao, S.S.; Herbert, M.A.
In the current research work, the effect of friction stir welding (FSW) on joint strength and evolution of microstructure at the weld zone of the friction stir welded of Al-Ce-Si-Mg aluminium alloy (Al10Mg8Ce3.5Si and Al5Mg8Ce3.5Si) is studied. The experimentations demonstrated that the speed of tool revolution, contour of tool pin and tool movement rate have influence on the quality of the FSW joint of the alloy. It was noticed that the size of grains at nugget zone (NZ) depends upon the speed of tool spin, speed, of tool feed, tool pin contour and composition of the aluminium alloy. The grain size at the bottom of the NZ was discovered to be reducing when compared to that at the top of the NZ. It was also noted that highest hardness was reached at NZ. Lowest hardness was found at heat affected zone (HAZ) and most of the tensile specimens fractured at HAZ. The Taguchi orthogonal array-based design has demonstrated that the tool pin contour had the greatest influence in enhancing the joint strength, followed by speed of tool feed, material composition and speed of tool spin. A speed of revolution of tool of 1000 rpm, tool movement rate of 20 mm/min, triangular contour pin (TCP) tool and Al10Mg8Ce3.5Si aluminium alloy were concluded as the optimum variables of the process. The percentage contribution of each one of these input process parameters on optimum output quality characteristics was also found out and noticed to be lying well within the confidence interval of 95% suggested by the Taguchi design. The current study has shown that the prediction results with artificial neural network (ANN) are better compared to those predicted using statistical methods like Taguchi Techniques. Â© Â© 2023 Elsevier Ltd. All rights reserved.
Achieving ultra-fine grains in Ti-6Al-4V alloy welds through pre-weld friction stir processing
(Elsevier B.V., 2024) Rao, R.N.; Rao, S.S.; Vijayan, V.
Titanium Ti-6Al-4V alloy, recognized for its exceptional strength, is extensively employed in the aerospace, biomedical, and automotive industries. Friction Stir Processing (FSP) has been found to enhance the overall performance, while friction stir welding (FSW) is recognized as the most effective technique for joining the Ti-6Al-4V alloy. This study focusses on the implementation of friction stir welding on a Ti-6Al-4V alloy that had previously undergone friction stir processing. The objective was to analyse the microstructure and mechanical characteristics. The examination using Electron Backscatter Diffraction revealed notable alterations in the microstructure, such as variations in grain size, misorientation angle, and grain boundaries. The proportion of high angle grain boundaries (HAGBs) on the advancing side and stir zone of the friction stir treated Ti-6Al-4V were 59 % and 66 %, respectively. Signifying grain refinement, grains measuring sizes between 0.83 ?m and 1.05 ?m were achieved as result of processing. Subsequent, friction stir welding resulted in about 50 % further decrease in grain size compared to base metal, with HAGBs comprising 71 % and 52 % at the advancing side and stir zone, respectively. As a result the Vickers micro hardness values increased to 397 ± 13Hv upon friction stir processing to 444 ±7Hv upon subsequent friction stir welding respectively. © 2024 The Authors
Advantages of cryogenic machining technique over without-coolant and with-coolant machining on SS316
(IOP Publishing Ltd, 2021) Karthik, M.; Malghan, R.L.; Shettigar, A.K.; Herbert, M.A.; Rao, S.S.
The analysis concentrated towards the influence of speed of the spindle along with a cryogenic (LN2) cooling technique in treating SS316 usingCNC(Computerized numerical control) milling machine. An comparative study path was set and anlyised among three states i.e. Dry (Without coolant), wet (With coolant) and cryogenic (With liquid LN2) machining using coated carbide inserts. The coolant used in case of wet machining was water-soluble, referred to as cutting fluid. The experimental range falls in 3 different levels of spindle speed (SS), such as low level (1000 rpm), medium level (2000 rpm), and high level (3000 rpm), respectively. Meanwhile, feed rate (FR) and depth of cut (DOC) were reserved steadily with 450 mm min-1, 1 mm separately. This vital focus is towards cryogenic (LN2) machining effects and its perception of machinability on SS316, such as tool wear -TW(?m), cutting force-CF (N), cutting temperature-CT (oC) and surface roughness-Ra (?m). The experiments were conducted and documented with cryogenic (LN2) techniques to establish the fairness and practicability of the method to compare with without-coolant (dry) and with-coolant (wet) machining. The attained statistical results in comparison of LN2 method over without-coolant and with-coolant machining concerned to test cases for CF- Fx (N), CT(oC), Ra (?m) andFW(?m) are 53.21%-34.20%, 65.88%-44.51%, 75.43%-44.27%,&59.76%-23.10%, respectively. © 2021 IOP Publishing Ltd.
An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques
(Springer, 2019) Karthik, M.C.; Malghan, R.L.; Shettigar, S.; Rao, S.S.; Herbert, M.A.
The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition. © 2018, The Indian Institute of Metals - IIM.
An Experimental and Numerical Approach to Study the Performance of Modified Perforated Cutting Tools on Machining of Ti–6Al–4V Alloy
(Springer, 2020) Rao, C.M.; Rao, S.S.; Herbert, M.A.
In this research, the main aim is to reduce the unfavorable effects that occurred during machining of the Ti–6Al–4V alloy by perforating the rake face and the flank face of the cutting insert. The main novelty in this research is that machining of Ti–6Al–4V alloy with the micro-hole textured insert helps in the improvement of tribological properties and also reduces cutting temperature at chip–tool interface with proper lubricating effect. To validate the micro-hole textured tools, it is compared with conventionally available insert. The deformation of Ti–6Al–4V alloy with modified cutting inserts was simulated, considering tool as rigid body and workpiece as elasto-plastic material. DEFORM 3D software was used for the simulation of the machining process with the updated Lagrangian formulation. To predict the cutting temperature and chip morphology, the thermo-mechanical analysis was applied using Johnson–Cook material model for the machining process. The turning of the Ti–6Al–4V alloy was carried out with the modified polycrystalline diamond (PCD) cutting inserts (Design 1 and Design 2) and commercially available PCD insert (normal insert). Coconut oil was used as a micro-pool lubricant during the machining process under minimum quantity lubrication environment. In the present work, the turning performance characteristics such as cutting temperature, cutting vibration, tool wear, chip morphology and surface integrity were measured during machining of the Ti–6Al–4V alloy. The experimental results of cutting temperature and chip morphology were validated with the simulation results with better accuracy. The machining results of Design 2 cutting insert showed maximum reduction of 30%, 38%, 45% and 35% in cutting temperature, cutting vibration, tool wear and surface roughness, respectively, when compared with machining under normal insert and Design 1 cutting insert. It is also evident from the results that machining with Design 2 cutting insert significantly improved the process performance of the product quality at higher feed rates. © 2019, King Fahd University of Petroleum & Minerals.
An Industry 4.0 Approach: Data Acquisition and Machine Monitoring for Welding Machines
(Springer Nature, 2024) Narendra Reddy, T.N.; Ponnappa, N.P.; Prasad, P.; Vinod, P.; Herbert, M.A.; Rao, S.S.
The research introduces an innovative application of Industry 4.0 principles in welding by employing IIoTbased performance monitoring equipment. One the important aspect of Industry 4.0 adaption is understanding the requirement from the customer and develop/ provide the acceptable solution to them is crucial. An attempt has been made to develop a solution which can be used for any kind of welding machines including legacy welding machines. The developed solution delivers real-time updates on shop floor welding processes with the help of Operational Technology (OT) and Information technology (IT) with the help of hall effect sensors and voltage transducers by connecting them to the Programmable logic controller (PLC). Additionally, it facilitates real-time feedback, alerts, and report generation. The study comprehensively assesses the effectiveness and production capacity of an industrial welding system, presenting a detailed design overview and practical demonstration. Potential enhancements, such as integrating machine learning, emphasizing remote monitoring, evaluating energy efficiency, addressing cybersecurity, and assessing scalability, are explored. The research includes a cost–benefit analysis for the shopfloor and provides insights into the real-world effectiveness of IIoT-based welding performance monitoring in industrial contexts. The developed solution has been tested, validated, and deployed in one of the welding industries, and it has helped in real-time monitoring, scheduling the work and data analytics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Analysis of surface roughness and hardness in ball burnishing of titanium alloy
(Elsevier B.V., 2014) Revankar, G.D.; Shetty, R.; Rao, S.S.; Gaitonde, V.N.
Ball burnishing is a popular post-machining metal finishing operation. An attempt has been made in this paper to optimize the process parameters during burnishing of titanium alloy (Ti-6Al-4V). Ball burnishing process parameters such as burnishing speed, burnishing feed, burnishing force and number of passes were considered to minimize the surface roughness and maximize the hardness. The lubricated ball burnishing experiments were planned as per L25 orthogonal array and signal to noise (S/N) ratio was applied to measure the proposed performance characteristics. The validation tests with the optimal levels of parameters were performed to illustrate the effectiveness of Taguchi optimization. The optimization results revealed that burnishing feed and burnishing speed are the significant parameters for minimizing the surface roughness, whereas burnishing force and number of passes play important roles in maximizing the hardness. The optimization results showed greater improvements in surface finish (77%) and hardness (17%) when compared to pre-machined surfaces. © 2014 Elsevier Ltd. All rights reserved.
Analysis of surface roughness and hardness in titanium alloy machining with polycrystalline diamond tool under different lubricating modes
(Universidade Federal de Sao Carlos, 2014) Revankar, G.D.; Shetty, R.; Rao, S.S.; Gaitonde, V.N.
The present work deals with the investigation on machining of difficult-to-machine material titanium alloy (Ti-6Al-4V) using poly crystalline diamond (PCD) tool under different coolant strategies, namely dry, flooded and MQL. Taguchi technique has been employed and the optimization results indicated that MQL lubricating mode with cutting speed of 150 m/min, feed rate of 0.15 mm/rev, nose radius of 0.6 mm and 0.25 mm depth of cut is necessary to minimize surface roughness and dry mode with cutting speed of 150 m/min, feed rate of 0.15 mm/rev, nose radius of 0.6 mm and 0.75 mm depth of cut is necessary to maximize surface hardness. The results indicate the substantial benefit of the minimum quantity of lubrication (MQL) and justify PCD inserts to be the most functionally satisfactory commercially available cutting tool material for machining titanium alloys for better surface finish and hardness.
Application of back propagation algorithms in neural network based identification responses of AISI 316 face milling cryogenic machining technique
(Taylor and Francis Ltd., 2022) Karthik, K.R.; Malghan, R.L.; Shettigar, A.; Rao, S.S.; Herbert, M.A.
The paper explores the potential study of artificial neural network (ANN) for prediction of response surface roughness (Ra) in face milling operation with respect to cryogenic approach. The model of Ra was expressed as the main factor in face milling of spindle speed, feed rate, depth of cut and coolant type. The ANN is trained using four various back propagation algorithms (BPA). The emphasis of the paper is to investigate the performance and the accuracy of the attained results depicts the effectiveness of the trained ANN in identifying the predicted Ra. The incorporated various BPA in predicting the Ra. The performance comparative study is made among statistical (Response Surface Methodology (RSM)) and ANN (BPA–training algorithm) methods. The various incorporated BPA algorithms are Gradient Descent (GD), Scaled Conjugate Gradient Descent (SCGD), Levenberg Marquardt (LM) and Bayesian Neural Network (BNN). Afterwards the best suitable BPA is identified in predicting Ra for AISI 316 in face milling operation using liquid nitrogen (LN2) as cutting fluid. The outperformed BPA is identified based on the attained deviation percentage and time required for the training the network. © 2020 Engineers Australia.
Application of Machine Learning in Movie Recommendation using Harris Hawks Optimization and K-means (HHO-k-means) Clustering
(Ismail Saritas, 2023) Ambikesh, G.; Rao, S.S.; Chandrasekaran, K.
In this study, a novel movie recommender system with Harris Hawks Optimization— k-means (HHO-k-means) clustering is proposed. The paper presents an empirical comparison of several clustering algorithms-k-means, PCA-k-means, SOM-Cluster, PCA-SOM, and HHO-k-means-across varying numbers of clusters. The performance metrics employed are Precision, Recall, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results show that the HHO-k-means algorithm consistently outperforms the other methods in terms of these metrics across all cluster sizes. It demonstrates higher precision, higher recall, lower MAE, and lower RMSE. Conversely, the PCA-k-means method generally exhibits less favorable results as the number of clusters increases. These findings suggest that the HHO-k-means algorithm may provide a more accurate clustering approach. © 2023, Ismail Saritas. All rights reserved.
Application of neural network for the prediction of tensile properties of friction stir welded composites
(Trans Tech Publications Ltd ttp@transtec.ch, 2017) Shettigar, A.K.; Prabhu B, S.; Malghan, R.; Rao, S.S.; Herbert, M.
In this paper, an attempt has been made to apply the neural network (NN) techniques to predict the mechanical properties of friction stir welded composite materials. Nowadays, friction stri welding of composites are predominatally used in aerospace, automobile and shipbuilding applications. The welding process parameters like rotational speed, welding speed, tool pin profile and type of material play a foremost role in determining the weld strength of the base material. An error back propagation algorithm based model is developed to map the input and output relation of friction stir welded composite material. The proposed model is able to predict the joint strength with minimum error. Â© 2017 Trans Tech Publications, Switzerland.
Application of particle swarm optimization and response surface methodology for machining parameters optimization of aluminium matrix composites in milling operation
(Springer Verlag service@springer.de, 2017) Malghan, R.L.; Karthik, K.M.C.; Shettigar, A.K.; Rao, S.S.; D’Souza, R.J.
Face milling is extensively used machining operation to generate the various components. Usually the selection of the process parameters are incorporated by trial and error method, literature survey and the machining hand book. This kind of selection of process parameters turns out to be very tedious and time-consuming. In order to overcome this there is a need to develop a technique that could be able to find the optimal process parameters for the desired responses in machining. The present paper illustrates an application of response surface methodology (RSM) and particle swarm optimization (PSO) technique for optimizing the process parameters of milling and provides a comparison study among desirability and PSO techniques. The experimental investigations are carried out on metal matrix composite material AA6061-4.5%Cu-5%SiCp to study the effect of process parameters such as feed rate, spindle speed and depth of cut on the cutting force, surface roughness and power consumption. The process parameters are analyzed using RSM central composite face-centered design to study the relationship between the input and output responses. The interaction between the process parameters was identified using the multiple regression technique, which showed that spindle speed has major contribution on all the responses followed by feed rate and depth of cut. It has shown good prediction for all the responses. The optimized process parameters are acquired through multi-response optimization using the desirability approach and the PSO technique. The results obtained from PSO are closer to the values of the desirability function approach and achieved significant improvement. © 2016, The Brazilian Society of Mechanical Sciences and Engineering.
Application of response surface methodology on surface roughness in grinding of aerospace materials (6061Al-15Vol%SiC25P)
(2010) Dayananda Pai, D.; Rao, S.S.; Shetty, R.; Nayak, R.
In this paper, the effects and the optimization of machining parameters on surface roughness in the grinding of 6061Al-SiC25P (MMCs) specimen are investigated. In the grinding process, a machining parameter, such as hardness of the specimen, flow rate of the coolant and depth of cut while machining were chosen for evaluation by the response surface methodology. By response surface methodology, a complete realization of the process parameters and their effects were achieved. The variation of surface roughness with machining parameters was mathematically modeled using response surface methodology. Finally, experimentation was carried out to identify the effectiveness of the proposed method. © 2006-2010 Asian Research Publishing Network (ARPN). All rights reserved.
Applications of reinforcement particles in the fabrication of Aluminium Metal Matrix Composites by Friction Stir Processing - A Review
(EDP Sciences, 2022) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.
Composite materials possess advantages like high strength and stiffness with low density and prove their essentiality in the aviation sector. Aluminium metal matrix composites (AMMC) find applications in automotive, aircraft, and marine industries due to their high specific strength, superior wear resistance, and lower thermal expansion. The fabrication of composites using the liquid phase at high temperature leads to the formation of intermetallics and unwanted phases. Friction Stir Processing (FSP) is a novel technique of composite fabrication, with temperature below the melting point of the matrix, achieving good grain refinement. Many researchers reported enhancement of mechanical, microstructure, and tribological properties of AMMC produced by the FSP route. The FSP parameters such as tool rotational speed, tool traverse speeds are found to be having greater impact on uniform dispersion of particles. It is observed that the properties such as tensile strength, hardness, wear and corrosion resistance, are altered by the FSP processes, and the scale of the alterations is influenced significantly by the processing and tool parameters. The strengthening mechanisms responsible for such alterations are discussed in this paper. Advanced engineering materials like shape memory alloys, high entropy alloys, MAX phase materials and intermetallics as reinforcement material are also discussed. Challenges and opportunities in FSP to manufacture AMMC are summarized, providing great benefit to researchers working on FSP technique. ©
Assessment of influence of process parameters on properties of friction stir welded Al-Ce-Si-Mg aluminium alloy
(Institute of Physics Publishing helen.craven@iop.org, 2019) D’Souza, A.D.; Rao, S.S.; Herbert, M.A.
The research on friction stir welding is mainly focused on welding of aluminium alloys. The material of interest in this research is an aluminium alloy known as Al-Ce-Si-Mg aluminium alloy. The FSW of this alloy finds applications in aerospace industry like joining of aircraft structure parts such as fuselage, cladding and engine components and in automotive industry for welding of parts of body structure and engine. The quality of the weld produced by FSW such as macrostructure defects, average grain size, ultimate tensile stress and weld zone hardness etc are dependent on input parameters like tool revolution, tool feed rate and tool pin profile. The weld defects like tunnel hole, worm hole and pin holes were not predominant in the tool revolution range of 800 to 1200 rpm and tool feed rate range of 10 to 20 mm min-1. The maximum ultimate stress was found to be lesser in the low and high tool revolution and tool feed rates compared to the medium speeds. The maximum value of UTS noted was 102.55 MPa for the weld at a tool revolution of 800 rpm and tool feed rate of 20 mm min-1 with a triangular pin profile tool, giving a joint efficiency of 67%. The Vickers hardness values were less at lower and higher speed ranges of tool revolution and tool feed rates for all the tool pin profiles used. The maximum value of Vickers hardness was noted for a tool revolution of 1000 rpm and tool feed rate of 20 mm min-1 with a triangular pin profile tool. The lowest grain size was observed for the tool revolution of 1000 rpm and tool feed rate of 20 mm min-1 with a triangular pin profile tool, indicating the inverse relation between hardness and grain size. In all the experiments it was observed that the triangular pin profile tool gives the best results at medium tool revolution and tool feed rate ranges. © 2019 IOP Publishing Ltd.
Behavioral study of alumina nanoparticles in pool boiling heat transfer on a vertical surface
(2011) Hegde, R.N.; Reddy, R.P.; Rao, S.S.
Experiments were carried out to investigate the pool boiling of alumina-water nanofluid at 0.1 g/l to 0.5 g/l of distilled water, and the nucleate pool boiling heat transfer of pure water and nanofluid at different mass concentrations were compared at and above the atmospheric pressure. At atmospheric pressure, different concentrations of nanofluids display different degrees of deterioration in boiling heat transfer. The effect of pressure and concentration of nanoparticles revealed significant enhancement in heat flux and deterioration in pool boiling. The heat transfer coefficient of 0.5 g/l alumina-water nanofluid was compared with pure water and clearly indicates deterioration. At all pressures the heat transfer coefficients of the nanofluid were lower than those of pure water. Experimental observation revealed particles coating over the heater surface and subsequent SEM inspection of the heater surface showed nanoparticles coating on the surface forming a porous layer. To substantiate the nanoparticle deposition and its effect on heat flux, investigation was done by measuring the surface roughness of the heater surface before and after the experiment. While SEM images of the heater surface revealed nanoparticle deposition, surface roughness of the heater surface confirmed it. Based on the experimental investigations it can be concluded that an optimum thickness of nanoparticles coating favors an increase in heat flux. Higher surface temperature due to the presence of nanoparticles coating results in the deterioration of boiling heat transfer. © 2011 Wiley Periodicals, Inc.