Effect of Vortex Generators on NACA2412 Aerofoil at Different Angles of Attack for Aircraft Wings R. Vignesh, S. Ashish, Pranav L. Sharma, Balaji Ganesan, G. Ezhilmaran, Vijayanandh Raja, S. Sasikumar, G. Boopathy, Santhosh Kumar Ganesan International Journal of Vehicle Structures and Systems, 2026 Vortex generator and aerofoil geometry of the blade enhance the aerodynamic effectiveness of an aircraft wing. In this research work, a wind tunnel experiment was conducted to explore the impact of vortex generators on the aerodynamic characteristics of the NACA2412 airfoil. The primary goal of this study was to analyse the coefficients of lift, drag and CL/CD distributions across the NACA2412 airfoil blade at freestream velocities of 15m/s, 25m/s and 35m/s, utilizing a low-speed subsonic wind tunnel. In the wind tunnel, the impact of NACA2412 profile airfoils has been examined with the help of three component force balance instruments at various angles of attack such as 0, 4, 8, 12 and 16 deg respectively and similarly in negative angle of attack of 0, -4, -8, -12 and -16 deg. The target of the task is to find out the lift coefficient and drag coefficient at different vortex generator such as triangular vortex generator, gothic vortex generator and rectangular vortex generator and their different combination arranged over the wing of NACA2412 aerofoil at x/c of 0.25, 0.5 and 0.75. The results of the study showed that significant variations in the coefficients of lift, drag and CL/CD distributions across the airfoil blade at different freestream velocities and angles of attack.
Experimental Investigation of Aerodynamics Performance of Biomimicry Morphing Wing of NACA0012 Airfoil at Trailing Edge Deflections O.G. Ruban Raj, Narreddy Reddy Kavya Sree, S. Lokesh, Balaji Ganesan, G. Ezhilmaran, S. Sasikumar, G. Boopathy, Vijayanandh Raja, Santhoshkumar Ganesan International Journal of Vehicle Structures and Systems, 2026 Morphing wings can significantly improve aerodynamic efficiency, drag reduction, noise reduction, adaptive performance, reduce fuel consumption and increase flight range. This study aims to morph the NACA0012 airfoil trailing and leading edges using pneumatics and electronics to different angles. The pneumatics cylinder of 16mm bore 80mm stroke length with double electronic triggered 5/3-way solenoid valve, is used to control the trailing edge deflection angle of 0°, 5°, 10°, 15°, 20° and 25° morphing along with high torque standard servo motors at the tip of trailing edge to give additional morphing ability for reliability of the wings in case of safe operation during failure of pneumatics. The deflected morphing is placed in the low-speed suction types wind tunnel test section to find out the force measurement under different freestream velocities such as 5m/s, 10m/s,15m/s, 20m/s and various angle of 0°, 4°, 8°, 12° and 16°. As the trailing edge is deflecting the chord associated with it can be changed making the wing adaptive to all flight conditions. The main objective of this study is to improve the aerodynamics performance using biomimicry morphing wing with trailing edge deflection, analyse lift and drag of morphing wing at all possible deflection angles and different freestream conditions using low speed wind tunnel.
Artificial Intelligence in Lightweight Composite Materials Design and Characterization G. Boopathy, R. Sundharesan, V. Srinivasan, M. Arulmurugan Applications of AI in Materials Science, 2026 The lightweight composite materials are imperative in different sectors because they have a favorable ratio of strength to weight. Their complex microstructures, in turn, make it harder to characterize and manufacture thus contributing to higher costs and time. In this chapter, the authors present the global effects of artificial intelligence on composite engineering using sophisticated craftsmanship in design and analysis. Machine learning and digital twins are examples of AI methods that can be used to optimize designs and improve composite development as well as quality assurance. Moreover, AI and sustainability efforts go together to encourage recyclable materials and energy efficient processes. Finally, the chapter brings out new trends including physics-driven AI and ethical aspects that will shape the development of composite in the future.
Redefining DMAIC With AI and Real-Time Data G. Boopathy, G. Chandra Bose, M. Gayathri, Mohit Hemanth Kumar Transformative Lean Six Sigma Techniques for the Quality 5 0 Paradigm, 2025 The combination of Artificial Intelligence (AI) and real time data analytics with the typical Lean Six Sigma (LSS) DMAIC framework is investigated in this chapter as it includes the use of Industry 5.0 principles. As an alternative to more static data analysis, it offers more dynamic, predictive, and prescriptive decision-making procedures that allow these organizations to better optimize their operations. Machine learning and Internet of Things (IoT) are also exciting AI skills by which some problems can be proactively identified to augment operational efficiency and quality in alignment with human-centric, sustainable and resilient manufacturing paradigms. It also presents a new conceptual framework that adds to every phase of the DMAIC cycle and consequently turns this reactive system into a predictive system, supporting the continuous improvement and tackling sustainability, efficiency, and the collaboration challenges. This integration helps firms attain operational excellence in Industry 5.0 by bridge the gaps between new, technology-based methods and conventional processes.
Innovative applications of machine learning in aerospace design and manufacturing G. Boopathy, Balaji Ganesan, P. Sivaprakasam, T. Kumaran Innovative Machine Learning Applications in the Aerospace Industry, 2025 This chapter explores how machine learning (ML) is revolutionizing aerospace design and manufacturing, highlighting how it may improve operational efficiency, safety, and engineering precision. It describes how ML technologies enable smarter design, manufacturing optimization, and superior quality assurance in aerospace applications by discussing both historical and modern developments in the field. ML greatly enhances aerodynamic design, improves structural analysis, and speeds up computational fluid dynamics (CFD) simulations by using predictive algorithms and analyzing large datasets. It also explores the legal framework governing machine learning in the aerospace industry by tackling issues including data management, integration difficulties, and ethical concerns. This chapter provides a thorough review of current machine learning applications, new developments, and possible advancements in aerospace technology.
Innovative strategies in lightweight materials for high-performance defence applications G. Boopathy, V. Srinivasan, Balaji Ganesan, Mohit Hemanth Kumar Innovative Materials for Next Generation Defense Applications Cost Performance and Mass Production, 2025 Defence needs lightweight composites because of their good strength to weight ratio, corrosion resistance, and thermal stability. Then this chapter studies the design and optimization of a number of matrix composites motivated by their mechanical and thermal performance in extreme environments. This highlights the importance of multiscale modelling, simulation and advanced manufacturing in improving composite reliability. This is applied to UVAs, armoured vehicles and naval systems for enhanced mobility and efficiency. Although there have been some impediments to production, the use of AI, nanomaterials, and sustainability will lead to scalable, high-performance solutions. These materials are then substantiated empirically for such critical missions. The chapter coordinates the relationship between the research based in the academia and the requirements by the defence industry, with strategies of new generation of materials having global sustainability goals and the operational needs.
Harnessing artificial intelligence for a greener future in solar, wind, and hydrogen G. Boopathy, K. Jayakumar, C. Suresh, V. Srinivasan Leveraging AI for Innovative Sustainable Energy Solar Wind and Green Hydrogen, 2025 Renewable energy sources have been the driver of innovation, with solar, wind, and the green hydrogen close to the top of the list. The addition of Artificial Intelligence (AI) to these systems enables faster development, improved scalability, and higher reliability for these systems. AI predicts weather patterns, optimizes panel orientation and allows for predictive maintenance of solar photovoltaic (PV) systems to maximize solar energy and minimize operational downtime and inefficiencies. AI optimizes the performance of wind turbines by optimizing accurate wind pattern forecasting and energy supply stabilization through intelligent grid integration via predictive analytics. Electrolysis processes are improved with AI, its energy efficiency is increased, and the green hydrogen is distributed and stored as well as possible. While barriers still exist in issues such as data privacy and computational demand, developments in edge computing and machine learning appear to bring about encouraging opportunities for moving past these barriers.
Exploring nanomaterials for enhanced energy storage and conversion G. Boopathy, V. Srinivasan, Balaji Ganesan, Sivaprakasam Palani Innovations in Next Generation Energy Storage Solutions, 2025 Our pressing need to build better energy storage and conversion systems grows as our world develops faster. Energy storage systems perform better through nanomaterials which have unique physicochemical traits and redefine how these technologies work. This chapter evaluates how nanomaterials strengthen energy technology through product types and develops fabrication processes for particular solutions. Materials at nanoscale show better energy storage because of their huge surface area and flexible design. Nanomaterials provide multiple solutions for storing hydrogen as well as performing electro catalysis and photovoltaics. Our chapter shows that energy technology requires exact engineering along with modeling and environmental-friendly nanomaterial manufacturing to help turn scientific discoveries into real-world applications and next-level energy solutions.
Sustainability through digital twins optimizing energy usage and reducing waste G. Boopathy, V. Srinivasan, V. Kamalakar, G. Chandra Bose Accelerating Product Development Cycles with Digital Twins and Iot Integration, 2025 Sustainability is drastically changing in the context of digital twins and the Internet of Things (IoT) because of the capacity to do operational optimization, predictive modeling, and real-time monitoring. This chapter looks at how digital twins generate virtual representations of physical assets where its IoT sensor data is integrated to improve energy efficiency and to reduce waste. Digital twins allow organizations to run through operations via simulation and to use the data underpinning the exercise to make data-driven decisions which minimise environmental impact and help support sustainability goals. By combining its technology with IoT, they make smarter energy management, predictive maintenance, and efficient production in a circular economy, and ultimately costs. These case studies and best practice are accompanied by research and an attempt to address challenges such as the incompatibility of data, and cost of adopting them. Results show how digital twins support the achievement of the United Nations Sustainable Development Goals (SDGs) and sustain industrial practices.
Advancing green manufacturing with sustainable solutions for advanced materials G. Boopathy, V. Srinivasan, R. Bhoominathan, M. Arulmurugan Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials, 2025 This chapter touches upon the incorporation of such computational intelligence in the context of sustainable manufacturing of advanced materials from both present context and future prospect. The material creation framework depends on fundamental ideas, tools and techniques for producing sustainable materials and ecologically designed and assessed materials. The computational intelligence is studied and has shown significant importance in optimization of manufacturing process and also improvement of material properties of parts. It empirically provides pragmatic insights about the advantages and hurdle of the success of applications based on empirical studies of the success of the application on many industries. It ends by discussing economic, technologic and regulatory barriers to wide spread delivery and strategies to overcome these barriers and to continue innovation in sustainable manufacturing.
Experimental investigations of nylon 6 polymer matrix composites material for wear reduction in gears International Journal of Mechanical Engineering and Technology, 2018
Fabrication and fatigue analysis of laminated composite plates International Journal of Mechanical Engineering and Technology, 2017
Fabrication and computational analysis of cenosphere reinforced aluminum metal matrix composite disc brakes International Journal of Mechanical Engineering and Technology, 2017
Review on non-destructive testing of composite materials in aircraft applications International Journal of Mechanical Engineering and Technology, 2017
Experimental investigation of passive flow control on bluff bodies International Journal of Applied Engineering Research, 2015
RECENT SCHOLAR PUBLICATIONS
Artificial Intelligence in Lightweight Composite Materials Design and Characterization G Boopathy, R Sundharesan, V Srinivasan, M ArulMurugan Applications of AI in Materials Science, 157-190 , 2026 2026
Effect of Vortex Generators on NACA2412 Aerofoil at Different Angles of Attack for Aircraft Wings R Vignesh, S Ashish, PL Sharma, B Ganesan, G Ezhilmaran, V Raja, ... International Journal of Vehicle Structures & Systems 18 (1), 113-118 , 2026 2026
Experimental Investigation of Aerodynamics Performance of Biomimicry Morphing Wing of NACA0012 Airfoil at Trailing Edge Deflections OGR Raj, NRK Sree, S Lokesh, B Ganesan, G Ezhilmaran, S Sasikumar, ... International Journal of Vehicle Structures & Systems 18 (1), 106-112 , 2026 2026
Emerging Trends in Self-Healing Materials for Smart and Sustainable Applications G Boopathy, V Srinivasan, C Suresh Recent Advances in Georesources, Intelligent Materials, and Environmental … , 2026 2026
Comprehensive investigation of the revolution in powder metallurgy sector through extensive modernization G Boopathy, G Balaji, N Rajamurugu, T Kumaran Powder Metallurgy, 277-294 , 2026 2026
Redefining DMAIC With AI and Real-Time Data G Boopathy, GC Bose, M Gayathri, MH Kumar Transformative Lean Six Sigma Techniques for the Quality 5.0 Paradigm, 123-150 , 2026 2026
The Essential Phases in Aircraft Component Manufacturing Using Artificial Intelligence G Boopathy, N Rajamurugu, P Siva Prakasam, JV Sai Prasanna Kumar Artificial Intelligence Applications in Aeronautical and Aerospace … , 2025 2025 Citations: 1
Mathematical perspectives on biomechanical signal processing V Srinivasan, JVSP Kumar, G Boopathy Applied Engineering Mathematics: Fluid and Solid Mechanics in Life Science … , 2025 2025
Innovative Applications of Machine Learning in Aerospace Design and Manufacturing G Boopathy, B Ganesan, P Sivaprakasam, T Kumaran Innovative Machine Learning Applications in the Aerospace Industry, 1-42 , 2025 2025 Citations: 2
Innovative Strategies in Lightweight Materials for High-Performance Defense Applications G Boopathy, V Srinivasan, B Ganesan, MH Kumar Innovative Materials for Next-Generation Defense Applications: Cost … , 2025 2025 Citations: 3
Numerical analysis of aerodynamics charateristics of different nosecone shapes at supersonic speed VR Narreddy Reddy Kavya Sree, Ruban Raj Oyyappan Ganesan, Nelluri Sri Varun ... AIP Conference Proceedings 3259 (1), 030008 , 2025 2025
Evolution of UAV Technology From Early Innovations to Future Horizons G Boopathy, R Jaganraj, V Srinivasan, T Kumaran Innovations and Developments in Unmanned Aerial Vehicles, 53-94 , 2025 2025
Evaluations of Zirconium coated surface attributes on mechanical characteristics and wear behavior of nickel based super alloy material EV Selvan, G Boopathy, L Saravanakumar, N Ramanan AIP Conference Proceedings 3162 (1), 020095 , 2025 2025 Citations: 1
CFD Analysis of Re-Entry Vehicle at Hypersonic Speed Using Ansys Fluent KD Datthathireyan, G Balaji, GS Kumar, G Boopathy, GM Pradeep, ... Innovations in Electronic Materials: Advancing Technology for a Sustainable … , 2025 2025
Fabrication of Superalloys for High-Temperature Applications Using Microwave Route V Srinivasan, G Boopathy, JVSP Kumar, V Kamalakar, PS Prakasam Microwave Processing of Metallic Materials 1, 92-126 , 2025 2025
Evolution of UAV Technology From Early Innovations to Future Horizons B Govindarajan, R Jaganraj, V Srinivasan, T Kumaran Innovations and Developments in Unmanned Aerial Vehicles, 53-94 , 2025 2025 Citations: 2
Trends and Developments in Additive Manufacturing Technologies G Boopathy, S Sathish, MV Kumar, C Suresh Modeling, Analysis, and Control of 3D Printing Processes, 489-524 , 2025 2025
Thermal and Mechanical Analysis of Materials in Additive Manufacturing G Boopathy, V Srinivasan, A Krasnikovs, B Ganesan Modeling, Analysis, and Control of 3D Printing Processes, 193-236 , 2025 2025 Citations: 2
Harnessing artificial intelligence for a greener future in solar, wind, and hydrogen G Boopathy, K Jayakumar, C Suresh, V Srinivasan Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green … , 2025 2025 Citations: 5
Exploring Nanomaterials for Enhanced Energy Storage and Conversion G Boopathy, V Srinivasan, B Ganesan, S Palani Innovations in Next-Generation Energy Storage Solutions, 193-250 , 2025 2025
MOST CITED SCHOLAR PUBLICATIONS
Optimization of tensile and impact strength for injection moulded Nylon 66/SiC/B4C Composites G Boopathy, V Vanitha, K Karthiga, B Gugulothu, A Pradeep, HP Pydi, ... Journal of Nanomaterials 2022 , 2022 2022 Citations: 36
Review on Non-Destructive Testing of Composite Materials in Aircraft Applications G Boopathy, G Surendar, A Prem, N Arun International Journal of Mechanical Engineering and Technology 8 (8), 1334-1342 , 2017 2017 Citations: 35
Investigation on process parameters for injection moulding of nylon 6/SiC and nylon 6/B4C composites G Boopathy, JU Prakash, K Gurusami, JVSP Kumar Materials Today: Proceedings 52, 1676-1681 , 2022 2022 Citations: 16
Development and Experimental Characterization of Fibre Metal Laminates to Predict the Fatigue Life G Boopathy, KR Vijayakumar, M Chinnapandian, K Gurusami International Journal of Innovative Technology and Exploring Engineering 8 … , 2019 2019 Citations: 15
Fabrication and Fatigue Analysis of Laminated Composite Plates KRVMC G.Boopathy International Journal of Mechanical Engineering and Technology 8 (7), 388-396 , 2017 2017 Citations: 13
Enhancing Mechanical Characteristics and Cost-Efficiency of Composite Materials Through Hybridization and Nanoparticle Incorporation. G Boopathy, G Balaji, R Bhoominathan, ABH Bejaxhin International Conference on Smart Sustainable Materials and Technologies, 83-89 , 2023 2023 Citations: 12
Optimization of Process Parameters for Injection Moulding of Nylon6/SiC and Nylon6/B4C Polymer Matrix Composites. G Boopathy, K Gurusami, M Chinnapandian, KR VijayaKumar FDMP-Fluid Dynamics & Materials Processing 18 (2), 223–232 , 2021 2021 Citations: 12
Fabrication and Computational Analysis of Cenosphere Reinforced Aluminum Metal Matrix Composite Disc Brakes RK Kumaar, G Kannan, G Boopathy, G Surendar Technology 8 (6), 553-563 , 2017 2017 Citations: 12
Experimental investigation of double delta wings with different angles of attack at subsonic speeds G Balaji, A Bharath Kumar, R Divya, G Boopathy, N Seenu, ... International conference on smart sustainable materials and technologies … , 2023 2023 Citations: 8
Numerical investigations of aerodynamics performance of blunt nose cone with aerodisk at hypersonic flow J Chauhan, G Balaji, M Swastikar, G Boopathy, S Sangeetha, ... International Conference on smart sustainable materials and technologies … , 2023 2023 Citations: 8
Harnessing artificial intelligence for a greener future in solar, wind, and hydrogen G Boopathy, K Jayakumar, C Suresh, V Srinivasan Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green … , 2025 2025 Citations: 5
Sustainability through digital twins optimizing energy usage and reducing waste G Boopathy, V Srinivasan, V Kamalakar, GC Bose Accelerating product development cycles with digital twins and IoT … , 2025 2025 Citations: 5
Experimental investigation of passive flow control on bluff bodies R Jaganraj, G Boopathy, V Varun International Journal of Applied Engineering Research: IJAER 10 (8), 19793-19798 , 2015 2015 Citations: 5
Aluminum agglomerate size measurements in composite propellant combustion BG Jayaraman K Lecture Notes in Mechanical Engineering, pp. 437-445 , 2017 2017 Citations: 4
Innovative Strategies in Lightweight Materials for High-Performance Defense Applications G Boopathy, V Srinivasan, B Ganesan, MH Kumar Innovative Materials for Next-Generation Defense Applications: Cost … , 2025 2025 Citations: 3
Feasibility and Insights into the Optimization and Characterization of Friction Welded Aluminum–Steel Dissimilar Joints SHK Raj, G Boopathy, S Vijayananth, G Balaji, N Ramanan International Conference on Smart Sustainable Materials and Technologies … , 2023 2023 Citations: 3
Application of six sigma practice for quality improvement in textile industry MS Kumaravel, G Boopathy, S Mohamed International Journal of ChemTech Research 10 (5), 817-823 , 2017 2017 Citations: 3
Innovative Applications of Machine Learning in Aerospace Design and Manufacturing G Boopathy, B Ganesan, P Sivaprakasam, T Kumaran Innovative Machine Learning Applications in the Aerospace Industry, 1-42 , 2025 2025 Citations: 2
Evolution of UAV Technology From Early Innovations to Future Horizons B Govindarajan, R Jaganraj, V Srinivasan, T Kumaran Innovations and Developments in Unmanned Aerial Vehicles, 53-94 , 2025 2025 Citations: 2
Thermal and Mechanical Analysis of Materials in Additive Manufacturing G Boopathy, V Srinivasan, A Krasnikovs, B Ganesan Modeling, Analysis, and Control of 3D Printing Processes, 193-236 , 2025 2025 Citations: 2
