Dr. A. Varun

@bvrit.ac.in

Associate Professor, Mechanical Engineering
B V Raju Institute of Technology

Dr. A. Varun


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https://researchid.co/varun.a

RESEARCH INTERESTS

Advanced Manufacturing Processes, Multi-Objective Optimization, Advanced Metrology.
11

Scopus Publications

144

Scholar Citations

6

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Microstructure and fatigue characteristics of AA6061-T6 joints with interlayer and cooling-assisted friction stir welding
    Korra Nagu, Kethavath Kranthi Kumar, K. Venkateswara Reddy, Koyilada Benarji, A. Varun, Mechiri Sandeep Kumar, A. Saravana Sundar, Adepu Kumar
    Welding International, 2026
  • Analysis of missile wing stability and weight reduction through composite materials and ply optimization
    Sandeep Kumar Mechiri, Varun Akkaldevi, Shiva Kumar Nagavelly, Sridhar Atla, Kishore Kumar Kandi
    Aip Conference Proceedings, 2025
  • SCAMPER Based Assessment Framework to Evaluate Final Year Engineering Projects in Higher Education Institutions
    , Salma Shaik, A. Varun, , Mechiri Sandeep Kumar, and
    Journal of Engineering Education Transformations, 2025
    With rapid technological advancements of the 21st century, there is a greater onus on the higher education institutions (HEIs) to innovate teaching methodologies. Especially, engineering education which is at the forefront of latest developments, needs to provide a stimulating and feedback-oriented learning environment to the students. The current paper presents a SCAMPER technique-based assessment framework embedded with Bloom's Taxonomy that can be used for assessing the technical feasibility, identification, and resolution of challenges for final year engineering projects. A case study is conducted utilizing the proposed framework to evaluate projects of final year Mechanical Engineering undergraduate students. Results highlighted that among the control group, 67% of students followed the traditional “modify” solution approach to a given problem whereas in the experimental group, the solution approaches were more diverse with only 35% of students choosing the “modify” approach. In terms of overall assessment scores, 70% of the experimental group scored in the upper quartile from 7 to 10 whereas for the control group, only 30% of students scored between 7 to 8 with 8 being the highest score. Based on these results, we can assert that the proposed framework enables students to a) think critically and be open to exploring different approaches to solve a problem b) justify the chosen solution approach and c) clearly explain the potential challenges and their feasible solutions. Hence, this research addresses the need to design robust frameworks that will a) guide students to think critically and to focus on novel idea generation b) facilitate instructors to thoroughly evaluate projects and to provide students with timely and comprehensive feedback. We believe that this framework is flexible enough that can be adapted to successfully evaluate student projects from diverse disciplines in higher education institutions globally.
  • Fatigue behavior of friction stir welded AA6061 alloy using brass insert
    Korra Nagu, A Varun, Mechiri Sandeep Kumar, Kethavath Kranthi Kumar, MVNV Satyanarayana, Adepu Kumar
    Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering, 2025
    Aluminum alloys, broadly used in aerospace and automotive, are particularly susceptible to fatigue failures. The grain refinement characteristics can improve the fatigue behavior of aluminum alloys, which can be achieved using friction stir welding (FSW). The primary aim of this study is to examine how incorporating a brass insert influences the fatigue crack growth behavior of AA6061-T6 alloy welded through FSW, comparing welds with and without the insert. Microstructural analysis showed fine recrystallized grains are obtained for both welds. However, welding with the insert exhibited smaller grains. Moreover, robust intermetallics are formed for welding with insert due to the intermixing reaction at FSW temperature, which improves mechanical properties such as hardness and tensile strength. The findings on fatigue indicate that the fatigue resistance of the weld with insert is significantly high, which can be attributed to the increased grain boundaries and development of strong intermetallic compounds, which hindered the crack propagation. Fractographic analysis of the fracture surfaces indicated the presence of striation marks in the weld with the insert, which slowed crack propagation and prolonged fatigue life. The findings suggest real-world applications in industries, where improving the fatigue life and structural reliability of welded aluminum components is critical.
  • Experimental investigation on agriculture waste residue reinforcement in Al 7075 alloy through rotary stir casting
    Murahari Kolli, Kosaraju Satyanarayana, Mechiri Sandeep Kumar, A. Varun, Solovev S. A, Oleg Igorevich Rozhdestvenskiy, Anil Kumar Saxena
    Cogent Engineering, 2024
    Aluminum metal matrix composites (MMCs) are a distinct class of materials with better performance characteristics than their equivalents made entirely of metal. The structural, maritime, aviation, defense and mining sectors all make extensive use of these composites. Many artificially produced hard ceramic reinforcements were investigated extensively to improve the properties of aluminum MMCs; however, the cost and exclusivity of the artificial reinforcements made extensive research on aluminum MMCs derived from agricultural and industrial waste possible. In this work, bamboo leaf ash (BLA), an aluminum MMC (Al 7075/ BLA) based on ceramic reinforcement produced from agricultural waste, is made utilizing the liquid metal stir casting process, with volume percentages of reinforcement in the matrix ranging from 2% to 8% by weight. To determine how much the MMC’s qualities have improved over the basic metal, mechanical and microstructural evaluation is carried out. The study’s findings verified that a sound composite with increased strength and hardness had been produced. The microstructural evaluation verified that the grain structure has undergone substantial refinement, resulting in an improvement in its properties.
  • Suitability of Hybrid Aluminium Metal Matrix Composite Material to Replace Cast Iron in Automobile Components
    Mohammad Habibullah, N. V. V. Manikanta, A. Varun, M. Praveen
    Lecture Notes in Mechanical Engineering, 2022
  • Surface roughness prediction using machine learning algorithms while turning under different lubrication conditions
    A Varun, Mechiri Sandeep Kumar, Karthik Murumulla, Tatiparthi Sathvik
    Journal of Physics Conference Series, 2021
    Lathe turning is one of the manufacturing sector’s most basic and important operations. From small businesses to large corporations, optimising machining operations is a key priority. Cooling systems in machining have an important role in determining surface roughness. The machine learning model under discussion assesses the surface roughness of lathe turned surfaces for a variety of materials. To forecast surface roughness, the machine learning model is trained using machining parameters, material characteristics, tool properties, and cooling conditions such as dry, MQL, and hybrid nano particle mixed MQL. Mixing with appropriate nano particles such as copper, aluminium, etc. may significantly improve cooling system heat absorption. To create a data collection for training and testing the model, many standard journals and publications are used. Surface roughness varies with work parameter combinations. In MATLAB, a Gaussian Process Regression (GPR) method will be utilised to construct a model and predict surface roughness. To improve prediction outcomes and make the model more flexible, data from a variety of publications was included. Some characteristics were omitted in order to minimise data noise. Different statistical factors will be explored to predict surface roughness.
  • A test to assess students' conceptual understanding of engineering metallurgy subject
    A. Varun, S. Krishnan
    Journal of Engineering Education Transformations, 2021
    Engineering students have misconceptions that need to be addressed to improve their understanding of the subject especially in courses that involve several interlinked concepts. While approaches such as concept inventories and concept maps have been used in the past, the present study addresses the importance of learning assessment design with a clear understanding of the conceptual difficulties faced by students. This paper describes a series of diagnostic assessments conducted to understand the most common misconceptions encountered by the Engineering Metallurgy subject students in the 3rd semester of a B.Tech. program in Mechanical Engineering. The goal of this exploratory study was to ascertain whether this diagnostic approach could help the instructor guide the students towards correct responses through multiple interventions. The primary learning interventions included live classroom lectures, asynchronous assignments, blended mode group discussion and supplementary video lectures while secondary learning interventions included periodic postassessment reviews used for some topics. Multiplechoice questions were used for assessment and student responses were classified as correct, misconceptions or 'no basis' responses. The proposed diagnostic approach provides a framework for educators to identify best interventions suitable for specific topics and forms the basis for Outcome- Based Education. The study revealed that for 12 of the 14 topics considered in this tracking approach, a target percentage of correct responses was reached by the students while the number of 'no basis' responses were reduced significantly. The results from this study provide a basis for choosing topics where alternate learning designs could be implemented in the future.
  • Investigation on influence of Hybrid Biodegradable Nanofluids (CuO-ZnO) on Surface Roughness in Turning AISI 1018 Steel
    Mechiri Sandeep Kumar, V. Murali Krishna, A. Varun
    Materials Today Proceedings, 2020
  • Grey relational analysis coupled with firefly algorithm for multiobjective optimization of wire electric discharge machining
    A Varun, N Venkaiah
    Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, 2015
    Complex engineering problems are often required to be addressed for multiobjective optimization. Wire electric discharge machining is one such multiobjective optimization problem. Conflicting objectives such as material removal rate, surface roughness and kerf have always been research interest for optimization. In this article, a novel optimization strategy has been formulated by coupling grey relational analysis with firefly algorithm to optimize the responses. Process parameters such as pulse-on time, pulse-off time, peak current and servo voltage are studied. Response parameters such as material removal rate, surface roughness and kerf are considered. Firefly algorithm is the main technique and grey relational analysis is used to generate a grey relational grade. This grade is further used in firefly algorithm for movement of firefly to the neighboring brighter and attractive firefly. In this process of self-organization, simultaneous optimal solution for material removal rate, surface roughness and kerf is obtained. Peak current is found to be the most influencing factor affecting all the three responses. Pareto surface plot is also plotted to recommend alternate solutions for various responses based on the priorities. As the proposed strategy is generalized, it can be customized and applied for any multiobjective optimization problem.
  • Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353
    A. Varun, Nasina Venkaiah
    International Journal of Advanced Manufacturing Technology, 2015

RECENT SCHOLAR PUBLICATIONS

  • Microstructure and fatigue characteristics of AA6061-T6 joints with interlayer and cooling-assisted friction stir welding
    K Nagu, K Kranthi Kumar, KV Reddy, K Benarji, A Varun, ...
    Welding International, 1-16 , 2026
    2026
  • Analysis of a novel composite bullet-proof vest
    MS Kumar, A Varun, PS Kumar, NS Kumar
    Applications of AI in Smart Technologies and Manufacturing, 41-51 , 2025
    2025
  • Analysis of missile wing stability and weight reduction through composite materials and ply optimization
    SKMC Author, V Akkaldevi, SK Nagavelly, S Atla, KK Kandi
    AIP Conference Proceedings 3363 (1), 1-14 , 2025
    2025
  • SCAMPER Based Assessment Framework to Evaluate Final Year Engineering Projects in Higher Education Institutions
    MSK Salma Shaik, A. Varun
    Journal of Engineering Education Transformations 39 (1), 152-165 , 2025
    2025
  • Fatigue behavior of friction stir welded AA6061 alloy using brass insert
    KA Nagu K, Varun A, Kumar MS, Kumar KK, Satyanarayana M
    Proceedings of the Institution of Mechanical Engineers, Part E: Journal of … , 2025
    2025
    Citations: 6
  • Experimental investigation on agriculture waste residue reinforcement in Al 7075 alloy through rotary stir casting
    M Kolli, K Satyanarayana, M Sandeep Kumar, A Varun, S S. A, ...
    Cogent Engineering 11 (1), 2410307 , 2024
    2024
    Citations: 1
  • An Overview of Nature-Inspired and Swarm Intelligence Algorithms
    MSKSBS Saniya Chheda, Varun A
    4th Indian International Conference on Industrial Engineering and Operations … , 2024
    2024
  • Sustainability Consciousness and Awareness of Sustainable Development Goals among Future Engineers
    S Shaik, A Varun
    Preprints , 2024
    2024
    Citations: 1
  • Suitability of Hybrid Aluminium Metal Matrix Composite Material to Replace Cast Iron in Automobile Components
    M Habibullah, NVV Manikanta, A Varun, M Praveen
    Applications of Computational Methods in Manufacturing and Product Design … , 2022
    2022
  • Surface Roughness Prediction using Machine Learning Algorithms while Turning under Different Lubrication Conditions
    KMTS A Varun, Mechiri Sandeep Kumar
    Journal of Physics: Conference Series 2070 , 2021
    2021
    Citations: 7
  • A Test to Assess Students' Conceptual Understanding of Engineering Metallurgy Subject
    SK A. Varun
    Journal of Engineering Education Transformations 34 (4), 22-29 , 2021
    2021
    Citations: 5
  • COST EFFECTIVE SETUP TO MEASURE THERMAL CONDUCTIVITY OF FLUIDS WITH VARYING TEMPERATURES
    DMK Dr. MECHIRI SANDEEP KUMAR VENUGOPAL, Dr. A. VARUN
    IN Patent App. 202,041,055,473 , 2021
    2021
  • Investigation on influence of hybrid biodegradable nanofluids (CuO-ZnO) on surface roughness in turning AISI 1018 steel
    MS Kumar, VM Krishna, A Varun
    Materials Today: Proceedings 24, 1570-1576 , 2020
    2020
    Citations: 15
  • A Comprehensive Review of the Pigeon-Inspired Optimization Algorithm
    MSK A. Varun
    International Journal of Engineering & Technology 7 (29), 758- , 2018
    2018
    Citations: 9
  • Grey relational analysis coupled with firefly algorithm for multiobjective optimization of wire electric discharge machining
    A Varun, N Venkaiah
    Proceedings of the Institution of Mechanical Engineers, Part B: Journal of … , 2015
    2015
    Citations: 15
  • Single-Discharge Analysis and Multi Objective Optimization of Wire-EDM using Grey Relational Analysis coupled with Genetic and Firefly Algorithms
    A Varun
    2015
  • Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353
    A Varun, N Venkaiah
    The International Journal of Advanced Manufacturing Technology 76 (1-4), 675-690 , 2015
    2015
    Citations: 81
  • Multi–objective optimization of powder mixed EDM
    A Varun, N Venkaiah, B Kotiveerachari
    4th International & 25th All India Manufacturing Technology, Design and … , 2012
    2012
    Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

  • Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353
    A Varun, N Venkaiah
    The International Journal of Advanced Manufacturing Technology 76 (1-4), 675-690 , 2015
    2015
    Citations: 81
  • Investigation on influence of hybrid biodegradable nanofluids (CuO-ZnO) on surface roughness in turning AISI 1018 steel
    MS Kumar, VM Krishna, A Varun
    Materials Today: Proceedings 24, 1570-1576 , 2020
    2020
    Citations: 15
  • Grey relational analysis coupled with firefly algorithm for multiobjective optimization of wire electric discharge machining
    A Varun, N Venkaiah
    Proceedings of the Institution of Mechanical Engineers, Part B: Journal of … , 2015
    2015
    Citations: 15
  • A Comprehensive Review of the Pigeon-Inspired Optimization Algorithm
    MSK A. Varun
    International Journal of Engineering & Technology 7 (29), 758- , 2018
    2018
    Citations: 9
  • Surface Roughness Prediction using Machine Learning Algorithms while Turning under Different Lubrication Conditions
    KMTS A Varun, Mechiri Sandeep Kumar
    Journal of Physics: Conference Series 2070 , 2021
    2021
    Citations: 7
  • Fatigue behavior of friction stir welded AA6061 alloy using brass insert
    KA Nagu K, Varun A, Kumar MS, Kumar KK, Satyanarayana M
    Proceedings of the Institution of Mechanical Engineers, Part E: Journal of … , 2025
    2025
    Citations: 6
  • A Test to Assess Students' Conceptual Understanding of Engineering Metallurgy Subject
    SK A. Varun
    Journal of Engineering Education Transformations 34 (4), 22-29 , 2021
    2021
    Citations: 5
  • Multi–objective optimization of powder mixed EDM
    A Varun, N Venkaiah, B Kotiveerachari
    4th International & 25th All India Manufacturing Technology, Design and … , 2012
    2012
    Citations: 4
  • Experimental investigation on agriculture waste residue reinforcement in Al 7075 alloy through rotary stir casting
    M Kolli, K Satyanarayana, M Sandeep Kumar, A Varun, S S. A, ...
    Cogent Engineering 11 (1), 2410307 , 2024
    2024
    Citations: 1
  • Sustainability Consciousness and Awareness of Sustainable Development Goals among Future Engineers
    S Shaik, A Varun
    Preprints , 2024
    2024
    Citations: 1
  • Microstructure and fatigue characteristics of AA6061-T6 joints with interlayer and cooling-assisted friction stir welding
    K Nagu, K Kranthi Kumar, KV Reddy, K Benarji, A Varun, ...
    Welding International, 1-16 , 2026
    2026
  • Analysis of a novel composite bullet-proof vest
    MS Kumar, A Varun, PS Kumar, NS Kumar
    Applications of AI in Smart Technologies and Manufacturing, 41-51 , 2025
    2025
  • Analysis of missile wing stability and weight reduction through composite materials and ply optimization
    SKMC Author, V Akkaldevi, SK Nagavelly, S Atla, KK Kandi
    AIP Conference Proceedings 3363 (1), 1-14 , 2025
    2025
  • SCAMPER Based Assessment Framework to Evaluate Final Year Engineering Projects in Higher Education Institutions
    MSK Salma Shaik, A. Varun
    Journal of Engineering Education Transformations 39 (1), 152-165 , 2025
    2025
  • An Overview of Nature-Inspired and Swarm Intelligence Algorithms
    MSKSBS Saniya Chheda, Varun A
    4th Indian International Conference on Industrial Engineering and Operations … , 2024
    2024
  • Suitability of Hybrid Aluminium Metal Matrix Composite Material to Replace Cast Iron in Automobile Components
    M Habibullah, NVV Manikanta, A Varun, M Praveen
    Applications of Computational Methods in Manufacturing and Product Design … , 2022
    2022
  • COST EFFECTIVE SETUP TO MEASURE THERMAL CONDUCTIVITY OF FLUIDS WITH VARYING TEMPERATURES
    DMK Dr. MECHIRI SANDEEP KUMAR VENUGOPAL, Dr. A. VARUN
    IN Patent App. 202,041,055,473 , 2021
    2021
  • Single-Discharge Analysis and Multi Objective Optimization of Wire-EDM using Grey Relational Analysis coupled with Genetic and Firefly Algorithms
    A Varun
    2015