Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
19 results
Search Results
Item Examining the Influence of StackinSequence on the Mechanical Properties of Hybrid Abaca-Jute Vinyl Ester Composites(Springer Nature, 2024) Ramesh, S.; Maruthi Prashanth, B.H.; Anne, G.; Naik, G.M.; Reddy, R.; Jagadeesh, C.; Sharma, P.; Prashanth Pai, M.This research looked on the impacts of layer arrange-ment on inter-laminar shear strength (ILSS), tensile, flexural, and impact capabilities of hybrid composite developed from 25% abaca and 25% jute fabrics reinforced 50% vinyl ester. Furthermore, the samples frac-tured under the tensile load were examined using SEM images. Utilizing a hot press process, these hybrid laminates were fabricated and sample preparation and testing were done as per ASTM criteria. The findings demonstrate that among Abaca-Jute-Abaca-Jute (AJAJ), Abaca-Jute-Abaca (AJJA), and Jute-Abaca-Abaca-Jute (JAAJ) vinyl ester composites, the Abaca-Jute-Jute-Abaca (AJJA) composites showed higher tensile modulus and strength by 23–33%, the flexural modulus and strength by 3–22%, the impact behavior, and ILSS strength by 11–33%. These benefits could be attributed to the presence of abaca fiber on the exterior of lami-nates. Fractography studies revealed that the fiber-resin bonding was superior. AJJA composites were found to be stronger than commonly used plastics in automobile interiors, making them a promising alternative. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Item Climatic effects on sugarcane productivity in India: A stochastic production function application(Inderscience Publishers, 2015) Singh, A.; Sharma, P.; Ambrammal, S.K.The present study estimates the influence of climatic and non-climatic factors on mean yield and yield variability of sugarcane crop in different weather seasons (e.g., rainy, winter and summer) in India. Sugarcane mean-yield for fourteen major sugarcane growing states from different agro-ecological zones are delimitated in panel data during 1971-2009. Regression coefficient for mean yield and yield variability production function (i.e. risk increasing or decreasing inputs) has been estimated through log-linear regression model with the help of Just and Pope (stochastic) production function specification. Empirical results based on feasible generalise least square (FGLS) estimations shows a significant effect of rainfall, maximum and minimum temperatures on sugarcane mean yield and yield variability. Whereas, average maximum temperature in summer and average minimum temperature in rainy season have a negative and statistically significant impact on sugarcane mean yield. Sugarcane mean yield positively gets affected with average maximum temperature during rainy and winter season. © © 2015 Inderscience Enterprises Ltd.Item Energy efficient quality of service aware virtual machine migration in cloud computing(Institute of Electrical and Electronics Engineers Inc., 2018) Sharma, N.; Sharma, P.; Guddeti, R.M.This paper deals with mulit-objective (network aware, energy efficient, and Service Level Agreement (SLA) aware) Virtual Machines (VMs) migration at the cloud data center. The proposed VMs migration technique migrate the VMs from the underutilized PMs to the energy efficient Physical Machines (PMs) at the cloud data center. Further, the multi-objective VMs migration technique not only reduces the power consumption of PMs and switches but also guarantees the quality of service by maintaining the SLA at the cloud data center. Our proposed VMs migration approach can find the good balance between three conflict objectives as compared to other algorithms. Further, the cloudsim based experimental results demonstrate the superiority of our proposed multi-objective VMs migration technique in terms of energy efficiency and also reduces the SLA violation over state-of-the-art VMs migration techniques such as Interquartile Range (IQR), and Random VMs migration techniques at the cloud data center. © 2018 IEEE.Item Machine Learning Solutions for Predicting Bankruptcy in Indian Firms(Springer Science and Business Media Deutschland GmbH, 2025) Chaithra; Sharma, P.; Mohan, R.The growing demand to identify potential bankrupt companies has prompted more research into bankruptcy prediction, assisting stakeholders in determining the worthiness of an investment. The Indian stock market offers investment opportunities, but it also involves risk. As a result, it is critical to invest in fundamentally sound companies for long-term investment. To address this need, we created a machine learning-based model for identifying a healthy and distressed firm in the Indian scenario. We created a dataset consisting of 118 bankrupt and 310 healthy firms. The dataset contains three labels: bankrupt, healthy, and financial distress. The addition of the financial distress category improves our ability to recognize and identify firms that are more likely to declare bankruptcy. Recognizing the shortcomings of limited data in the Indian scenario in previous research, our study aimed to include more data instances for training. The dataset included widely recognized financial ratios and macroeconomic data that recognize the interconnectedness of broader economic trends with the company’s financial health. Advanced machine learning algorithms, namely Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), Categorical Boosting (CatBoost), Gradient Boost (GB), and K-Nearest Neighbors (KNN) were applied. The XGBoost and LGBM demonstrated the highest level of classification accuracy and also performed well on real-world data, demonstrating their potential use in supporting investors with decision-making processes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Item Evaluation of WEDM performance characteristics of Inconel 706 for turbine disk application(Elsevier Ltd, 2015) Sharma, P.; Dupadu, D.; Narendranath, S.Inconel 706 is a newly developed superalloy, which offers high mechanical strength alongwith easy fabricability thus making it suitable for turbine disk applications. Although Inconel 706 exhibits a substantial increase in stress rupture and tensile yield strength compared to other superalloys, its conventional machining yields poor surface finish and low dimensional accuracy of the machined components. Hence, wire electrical discharge machining (WEDM) of Inconel 706 has been performed and various performance attributes such as material removal rate (MRR), surface roughness (SR), recast surface, topography, microhardness, microstructural and metallurgical changes of the machined components have been evaluated. The experimental results revealed that servo voltage, pulse on time, and pulse off time greatly influence the MRR and SR. Due to high toughness of Inconel 706, no micro cracks were observed on the machined surface. Micro voids and micro globules are significantly reduced at low pulse on time and high servo voltage. But, there is a propensity of thick recast layer formation at high pulse on time and low servo voltage. EDAX analysis of recast surface exposed the existence of Cu and Zn which have migrated from the brass wire. The subsurface microhardness was changed to 80. ?m due to significant thermal degradation. © 2015 Elsevier Ltd.Item Effect of Wire Material on Productivity and Surface Integrity of WEDM-Processed Inconel 706 for Aircraft Application(Springer New York LLC barbara.b.bertram@gsk.com, 2016) Sharma, P.; Dupadu, D.; Narendranath, S.Inconel 706 is a recently developed superalloy for aircraft application, particularly in turbine disk which is among the most critical components in the gas turbine engines. Recently, wire electrical discharge machining (WEDM) attained success in machining of gas turbine components which require complex shape profiles with high precision. To achieve the feasibility in machining of these components, the research work has been conducted on Inconel 706 superalloy using WEDM process. And, the effect of different wire materials (i.e., hard brass wire, diffused wire, and zinc-coated wire) on WEDM performance characteristics such as cutting speed, surface topography, surface roughness, recast layer formation, residual stresses, and microstructural and metallurgical alterations have been investigated. Even though, zinc-coated wire exhibits improved productivity, hard brass wire was found to be beneficial in terms of improved surface quality of the machined parts. Additionally, lower tensile residual stresses were obtained with hard brass wire. However, diffused wire has a moderate effect on productivity and surface quality. Under high discharge energy, higher elemental changes were observed and also the white layer was detected. © 2016, ASM International.Item Effect of wire diameter on surface integrity of wire electrical discharge machined Inconel 706 for gas turbine application(Elsevier Ltd, 2016) Sharma, P.; Dupadu, D.; Narendranath, S.Inconel 706 superalloy has established itself in the field of gas turbine industry because of its easy fabricability combined with high mechanical strength. Due to its high stress rupture and tensile yield strength, conventional machining of this superalloy exhibits poor surface and low dimensional accuracy of the machined components. It is well known that most of the gas turbine components include complex shaped profile with high precision and hence, wire electrical discharge machining (WEDM) of Inconel 706 has been performed to achieve the feasibility in manufacturing of complex shaped components for gas turbine application. In the current investigation, the effect of wire diameter on WEDM performance characteristics such as cutting speed, surface roughness, surface topography, recast layer formation, microhardness, microstructural and metallurgical changes have been evaluated. It was investigated that smaller diameter wire is advantageous over the larger diameter wire since it improves productivity as well as surface quality of the machined components under the same settings of control parameters. In addition, smaller diameter wire has shown comparatively lower recast layer thickness, minimum hardness alteration and shorter manufacturing time. The XRD result has confirmed the presence of residual stress within WED machined component. © 2016 The Society of Manufacturing EngineersItem Analysis and Optimization of WEDM Performance Characteristics of Inconel 706 for Aerospace Application(Springer Netherlands rbk@louisiana.edu, 2018) Sharma, P.; Dupadu, D.; Narendranath, S.Wire Electrical Discharge Machining (WEDM) has established itself for manufacturing of precise and complex shape components for aerospace application due to the high quality requirement of aerospace components such as normal residual stress, no cracks, no recast layer, no porosity; still there is a need to optimize the control parameter settings and evaluate the performance characteristics of the WEDM process. The experiments have been conducted on Inconel 706 which is a newly-developed superalloy specially for aircraft application. A hybrid approach has been used to optimize the material removal rate (MRR) as well as surface roughness (SR) and significant control parameters have been identified using analysis of variance (ANOVA). Microstructure analysis revealed the formation of microglobules, melted debris and microholes on the machined surface, but no microcrack was detected due to the high toughness of the alloy. Energy dispersive X-ray spectroscopy (EDAX) has been carried out to study the metallurgical changes in the WED machined surface. The topography analysis of the curved surface revealed the best surface quality of the machined component at low pulse on time and high pulse off time. A thick recast layer of 39.6 µm was observed at high pulse on time and low servo voltage. Microhardness of the machined surface was changed up to a depth of 70 µm due to cyclic thermal loading during the WEDM process. © 2017, Springer Science+Business Media Dordrecht.Item Design, fabrication and testing of a 2 DOF compliant flexural microgripper(Springer Verlag service@springer.de, 2018) Dsouza, R.D.; Karanth P, K.P.; Theodoridis, T.; Sharma, P.This paper presents the development of a monolithic two degrees of freedom (2 DOF), piezoelectric actuated microgripper for the manipulation of micro-objects. Micromanipulation and microassembly are the major subjects of interest in recent times and are becoming increasingly important in many domains. An effort is being made to develop a novel 2 DOF microgripper, each jaw being able to move independently to grasp and rotate objects of micro sizes. Microgripper is developed based on the compliant mechanism. The designed 2 DOF compliant microgripper is modeled using FEM and PRBM approach further validated experimentally. The microgripper is actuated using APA 120-S piezoelectric stack actuators. The displacement of the microgripper and the gripping force is measured by image processing technique using LabVIEW tools. The microgripper is subjected to various tests to measure the displacement amplification ratio and micromanipulation experiments. Wire of various sizes are used to test the grasping and rotating sequence of the microgripper. The theoretical, simulation and experimental results reveal the good performance of the microgripper. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.Item Response surface methodology and artificial neural network-based models for predicting performance of wire electrical discharge machining of inconel 718 alloy(MDPI Multidisciplinary Digital Publishing Institute rasetti@mdpi.com, 2020) Lalwani, V.; Sharma, P.; Pruncu, C.I.; Unune, D.R.This paper deals with the development and comparison of prediction models established using response surface methodology (RSM) and artificial neural network (ANN) for a wire electrical discharge machining (WEDM) process. The WEDM experiments were designed using central composite design (CCD) for machining of Inconel 718 superalloy. During experimentation, the pulse-on-time (TON), pulse-off-time (TOFF), servo-voltage (SV), peak current (IP), and wire tension (WT) were chosen as control factors, whereas, the kerf width (Kf), surface roughness (Ra), and materials removal rate (MRR) were selected as performance attributes. The analysis of variance tests was performed to identify the control factors that significantly affect the performance attributes. The double hidden layer ANN model was developed using a back-propagation ANN algorithm, trained by the experimental results. The prediction accuracy of the established ANN model was found to be superior to the RSM model. Finally, the Non-Dominated Sorting Genetic Algorithm-II (NSGA- II) was implemented to determine the optimum WEDM conditions from multiple objectives. © 2020 by the authors.