Faculty Publications
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Item A comprehensive review of friction stir techniques in structural materials and alloys: challenges and trends(Elsevier Editora Ltda, 2022) Prabhakar, D.A.P.; Shettigar, A.; Herbert, M.A.; Gowdru Chandrashekarappa, M.; Pimenov, D.Y.; Giasin, K.; Prakash, C.Friction-stir techniques are the potential alternative to fusion-based systems for processing and welding metallic alloys and other materials. This review explores the advantages, applications, limitations, and future directions of seven friction-based techniques namely, Additive Friction Stir Deposition (AFSD), Friction Stir Additive Manufacturing (FSAM), Friction Stir Welding (FSW), Friction Stir Processing (FSP), Friction Surfacing (FS), Friction Stir Spot Welding (FSSW), and Friction Stir Lap Welding (FSLW). The basic underlying principle of these processes uses friction as a thermal energy source to weld/process/deposit materials. The common control parameters of all friction stir processing techniques are axial force, rotational speed, and weld or traverse speed. In addition, tool profiles and tool dimensions are known to influence the weld quality. The tool's rotational speed and axial force generate friction between the workpiece and tool material interface, which could plasticize the material. The additive powder bed friction stir process (APBFSP) is another new solid-state manufacturing technique that focus on fabricating the polymer matrix nanocomposites (PNC). In this, a hollow tool like AFSD and the fundamental principle of FSP are combined. The said parameters affect the quantity of material getting deposited/welded. However, weld speed/traverse speed alters the weld quality, and higher traverse speed results in porosity and voids in the welded/deposited/processed region. The only difference between AFSD and other friction stir techniques (FSTs) is that in the AFSD technique, the hollow rotating tool comprises two protrusions with different tool profiles (cylindrical, threaded cylindrical, and tapered cylindrical, square) used. Threaded cylindrical profile and tool steel as the tool material is the most commonly employed in FSTs. Apart from that, tungsten carbide is preferred for hard materials. The working principles and process parameters of FSTs that affect the part quality are discussed in detail. The above review gives the reader an understanding of the domain of FSTs that can be researched further. A summary of some of the potential research works with objectives, process parameters, and outcomes is highlighted. This will provide the readers with an overview of the work carried out by researchers across the globe. Finally, the potential research gaps for future directions to be explored soon across the globe are outlined. © 2022 The Author(s).Item Modelling of squeeze casting process using design of experiments and response surface methodology(Maney Publishing maney@maney.co.uk, 2015) Gowdru Chandrashekarappa, M.; Krishna, P.; Parappagoudar, M.B.The present work makes an attempt to model and analyse squeeze casting process by utilising design of experiments and response surface methodology. The input–output data for developing regression models and test cases is obtained by conducting the experiments. Surface roughness, ultimate tensile strength and yield strength have been measured for different combinations of process variables, namely, squeeze pressure, pressure duration, pouring temperature and die temperature. Two non-linear regression models based on central composite design (CCD) and Box-Behnken design (BBD) of experiments have been developed to establish the input–output relationships. The effects of process variables on the measured responses have been studied using surface plots. The performances of the two non-linear models have been tested for their prediction accuracy with the help of 15 test cases. It is observed that, both CCD and BBD, the non-linear regression models are statistically adequate and capable of making accurate predictions. © 2015 W. S. Maney & Son Ltd.Item Back propagation genetic and recurrent neural network applications in modelling and analysis of squeeze casting process(Elsevier Ltd, 2017) Gowdru Chandrashekarappa, M.; Shettigar, A.K.; Krishna, P.; Parappagoudar, M.B.Today, in competitive manufacturing environment reducing casting defects with improved mechanical properties is of industrial relevance. This led the present work to deal with developing the input-output relationship in squeeze casting process utilizing the neural network based forward and reverse mapping. Forward mapping is aimed to predict the casting quality (such as density, hardness and secondary dendrite arm spacing) for the known combination of casting variables (that is, squeeze pressure, pressure duration, die and pouring temperature). Conversely, attempt is also made to determine the appropriate set of casting variables for the required casting quality (that is, reverse mapping). Forward and reverse mapping tasks are carried out utilizing back propagation, recurrent and genetic algorithm tuned neural networks. Parameter study has been conducted to adjust and optimize the neural network parameters utilizing the batch mode of training. Since, batch mode of training requires huge data, the training data is generated artificially using response equations. Furthermore, neural network prediction performances are compared among themselves (reverse mapping) and with those of statistical regression models (forward mapping) with the help of test cases. The results shown all developed neural network models in both forward and reverse mappings are capable of making effective predictions. The results obtained will help the foundry personnel to automate and précised control of squeeze casting process. © 2017Item Experimental analysis and optimization of plasma spray parameters on microhardness and wear loss of Mo-Ni-Cr coated super duplex stainless steel(Taylor and Francis Ltd., 2022) Gowdru Chandrashekarappa, M.; Pradeep, N.B.; Girisha, L.; Harsha, H.M.; Shettigar, A.Plasma spray coatings are one among the economic path to offer quick solutions for preventing the part (substrate) failures due to rapid wear. In the present work, Mo-Ni-Cr powder is used as a coating material on super duplex stainless steel to minimise the wear loss. The microhardness of the coating is affected by the factors (current, powder feed rate and standoff distance) of the plasma spray coating process. Taguchi method is followed for preliminary experimental plan, analysis, and to perform optimisation for maximum microhardness. The results showed that the current being the dominant effect followed by powder feed rate and standoff distance on the microhardness of coated samples. The optimised plasma spray condition resulted in the highest coating microhardness (i.e., 764.33 HV), which is 2.78 times higher than that of super duplex stainless steel (i.e., 275 HV). Taguchi experiments are conducted to know the factors (load, sliding speed and sliding distance) influence the wear loss of coated samples prepared for optimised plasma spray conditions. The applied load and sliding speed are found statistically significant, whereas the sliding distance is insignificant towards wear loss. The results of wear loss of the substrate (uncoated sample) and optimised condition of the coated sample are found equal to 18 mg, and 2.8 mg, respectively. © 2020 Engineers Australia.Item Influence of process variables on joint attributes of friction stir welded aluminium matrix composite(Taylor and Francis Ltd., 2022) Prabhu B, S.R.; Shettigar, A.; Gowdru Chandrashekarappa, M.; Herbert, M.A.; Rao, S.S.The microstructure and mechanical attributes of the friction stir welded aluminium metal matrix composites (AMCs) are reported in this paper. Impacts of friction stir welding (FSW) process variables on the mechanical properties are evaluated. Metallographic studies showed that variation in welding process variables’ plays a vital role in obtaining recrystallised equiaxed fine-grain structures. The formed joint region indicates a gradual reduction in grain size as it moves from top to bottom of the weld region due to variation in the heat generation. Process variables like tool movement along the joint direction and tool revolution speed govern the joint strength of AMCs. Beyond the optimum values of process variables, the weld quality and joint strength of the welded part deteriorate due to the inappropriate stirring of the material at the weld region. The highest joint strength obtained for tool movement along the direction was 80 mm/min, and the revolution of the tool was 1000 rpm. © 2020 Informa UK Limited, trading as Taylor & Francis Group.Item Development of a Convolutional Neural Network Model to Predict Coronary Artery Disease Based on Single-Lead and Twelve-Lead ECG Signals(MDPI, 2022) Vasudeva, S.T.; Rao, S.S.; Karanth P, N.; Shettigar, A.; Mahabala, C.; Kamath, P.; Gowdru Chandrashekarappa, M.; Linul, E.Coronary artery disease (CAD) is one of the most common causes of heart ailments; many patients with CAD do not exhibit initial symptoms. An electrocardiogram (ECG) is a diagnostic tool widely used to capture the abnormal activity of the heart and help with diagnoses. Assessing ECG signals may be challenging and time-consuming. Identifying abnormal ECG morphologies, especially in low amplitude curves, may be prone to error. Hence, a system that can automatically detect and assess the ECG and treadmill test ECG (TMT-ECG) signals will be helpful to the medical industry in detecting CAD. In the present work, we developed an intelligent system that can predict CAD, based on ECG and TMT signals more accurately than any other system developed thus far. The distinct convolutional neural network (CNN) architecture deals with single-lead and multi-lead (12-lead) ECG and TMT-ECG data effectively. While most artificial intelligence-based systems rely on the universal dataset, the current work used clinical lab data collected from a renowned hospital in the neighborhood. ECG and TMT-ECG graphs of normal and CAD patients were collected in the form of scanned reports. One-dimensional ECG data with all possible features were extracted from the scanned report with the help of a modified image processing method. This feature extraction procedure was integrated with the optimized architecture of the CNN model leading to a novel prediction system for CAD. The automated computer-assisted system helps in the detection and medication of CAD with a high prediction accuracy of 99%. © 2022 by the authors.Item Fretting wear behavior on LPBF processed AlSi10Mg alloy for different heat treatment conditions(Elsevier Editora Ltda, 2024) Nanjundaiah, R.S.; Rao, S.S.; Praveenkumar, K.; Prabhu, T.R.; Shettigar, A.K.; Gowdru Chandrashekarappa, M.; Linul, E.To widen the industrial application of additively manufactured (AM) parts, the study of fretting wear behavior is essential, as it ensures the safety and reliability that drive innovation in design and materials. This study explores the fretting wear behavior of the as-built and heat-treated state of AlSi10Mg alloy fabricated, viz., laser powder bed fusion (LPBF). Initially, the as-built and T5, T6, and stress-relieved (SR) heat-treated samples were examined using scanning electron microscopy (SEM) to gain insights into the microstructural changes. The as-built samples exhibited a higher hardness level (135 HV) primarily due to the presence of very fine microstructure of the α-Al cellular matrix with embedded Si. The α-Al cellular structure dissolved with various heat treatments, and Si particles coarsened. The hardness decreased to 85, 79, and 67 HV for the T5, T6, and SR conditions, respectively. Subsequently, fretting tests were conducted on the samples, applying various normal loads of 10, 50, and 100 N. Further, the samples were characterized by the coefficient of friction (COF), worn surface morphology, and wear volume loss. The investigation showed that the as-built material showed less wear volume loss under all loading conditions than the heat-treated conditions. Furthermore, the T5 heat treated sample had a lower wear volume when compared to the T6 and SR heat-treated samples. The heat-treated sample exhibits compressive stress, whereas the LPBF processed, the as-built sample shows tensile stress. © 2024 The AuthorsItem Estimation of Monsoon Seasonal Precipitation Teleconnection with El Niño-Southern Oscillation Sea Surface Temperature Indices over the Western Ghats of Karnataka(Korean Meteorological Society, 2024) Doranalu Chandrashekar, V.; Shetty, A.; Gowdru Chandrashekarappa, M.The Western Ghats (WG) of India are basically north-to-south oriented mountains with three distinct meteorological divisions. These mountains exhibit the characteristic features of precipitation and distribution during the summer monsoon season and possess latitudinal variations. It is a well-known fact that sea surface temperature (SST) combined with the El Niño-Southern Oscillation (ENSO) enacts a predominant role in the precipitation over the entire Western Ghats during the summer monsoon season. Whereas the Niño regions affect the variability of the Western Ghats’ precipitation in an asymmetric relationship. Nevertheless, the simulation of precipitation has been evidenced to be difficult. The current study attempts to predict the seasonal precipitation over the coastal region and the Western Ghats of Karnataka. The relationship between summer monsoon precipitation (SMP) and SST is examined up to eight seasons by conducting the correlation analysis with three seasons that lag before the onset of the monsoon season. The significant and positively correlated lagged Niño indices with the SMP index are identified as the predictors. The selected predictors are used for predicting the SMP by using statistical models, the multiple linear regression model and the artificial neural network (ANN) model. The statistical models are based on the combined lagged indices and the principle component as the predictor. The results of the statistical models on comparison suggest that neural network models have a better predictive skill than the linear regression models. Neural network models with combined lagged indices being used as predictors are slightly better, but a few more climatic parameters must be verified and the usage of this method on other meteorological divisions of the West Coast of India needs to be further investigated. © Korean Meteorological Society and Springer Nature B.V. 2019.