Swaminathan Ganesan

@psgitech.ac.in

Assistant Professor, Mechanical Engineering
PSG Institute of Technology and Applied Research

Swaminathan Ganesan


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https://researchid.co/swami123

EDUCATION

Ph.D. in Metallurgical and Materials Engineering
M.E. in Manufacturing Engineering
B.E. in Automobile Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Mechanical Engineering, Materials Science, Automotive Engineering
21

Scopus Publications

46

Scholar Citations

4

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Examining thermal, structural, and morphological properties of aluminium/TPU composite filaments
    Senthilkumar Krishnasamy, G. Swaminathan, Sasikumar Ramachandran, V. Parthasarathy, Jyotishkumar Parameswaranpillai, M. Chandrasekar, T. Senthil Muthu Kumar, A. Anto Dilip
    Discover Materials, 2026
    Abstract In this study, thermoplastic polyurethane (TPU)/0.25 wt% of aluminium filler was successfully fabricated using single screw extruder machine. The fabricated filaments were examined for differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), and X-ray diffraction (XRD). During filament fabrication, the parameters for pure TPU, such as die temperature (160–190 °C), screw speed (400 to 450 rpm), extruder current (2.1 to 2.2 A), were chosen. Similarly, for TPU/aluminium filaments, die temperature (190 –160 °C), screw speed (60 rpm), and extruder current (2.9 A) were chosen. Regarding the experimental results, the TGA of TPU/aluminium samples showed higher degradation than pure TPU samples at 850 °C. DSC results showed a minor effect from adding aluminium fillers in the first cycle. However, there was a significant change observed in the melting behavior in the subsequent cycles, which showed enhanced thermal stability and dimensional control at elevated temperatures. FTIR results confirmed interactions between aluminum fillers and TPU, as evidenced by the reduction in the intensity of C = O and N–H stretching bands, which indicated disrupted hydrogen bonds. SEM images showed that aluminium fillers were well embedded in the TPU matrix without any voids, which help in effective load transfer across the matrix. EDS results confirmed the presence of aluminium and oxygen and indicated the formation of Al2O3 during filament extrusion. Besides, XRD results exhibited a sharp crystalline peak and indicated improved structural stability due to adding aluminium fillers into TPU matrix.
  • Investigation of Scheil Solidification and Macrosegregation in Autogenous Gas Tungsten Arc Welded 250-Grade Maraging Steel
    V. Rajkumar, K. Krishna Kumar, G. Swaminathan
    Journal of Materials Engineering and Performance, 2026
  • Prediction of thermal cycling behaviour of Ni-rich NiTi SMA using empirical and artificial neural network modelling
    Swaminathan Ganesan, Shreyash Pandey, Senthilkumar Krishnasamy, Senthil Muthu Kumar Thiagmani
    Discover Materials, 2025
    NiTi SMAs, also known as Nitinol, are well-known and widely used due to their unique properties. This study predicts the transformation behaviour of a binary near-equiatomic shape memory alloy (SMA) during thermal cycling using empirical and ANN-based models. The input data was generated through thermal cycling tests using a differential scanning calorimeter (DSC) under a nitrogen atmosphere, wherein the maximum and minimum temperatures were varied based on the transformation temperatures of the alloy. Three different models, i.e. symmetrical, asymmetrical and artificial neural network (ANN), were developed to understand the transformation behaviour of the alloy using the same set of test data for validation. For qualitative and quantitative comparisons of the model, priority was given to the simplicity of the model (minimum variables) and the accuracy of the prediction. The results show that the ANN-based model can predict the transformation behaviour more accurately (99.81%) as compared to the conventional empirical models, i.e., symmetric (96.64%) and asymmetric models (98.14%).
  • Artificial neural network-based prediction of functional fatigue behaviour of an NiTi shape memory alloy
    G. Swaminathan, S. H. Adarsh, M. Raju, K. Senthilkumar, T. Senthil Muthu Kumar
    Discover Materials, 2025
    Shape memory alloys (SMAs), such as NiTi, exhibit phase transformations during cyclic loading, leading to degradation in functional properties like recovery strain and thermal hysteresis, known as functional fatigue. This study proposes an artificial neural network (ANN) approach to model the functional fatigue behaviour of NiTi SMA under partial thermal cycling at constant stress (100 MPa) and varying electrical current (10–17.5 A) across 1000 cycles. A feed-forward backpropagation ANN with two inputs (current, number of cycles) and four outputs (recovery strain, permanent strain, upper cycle temperature, and strain accumulation per cycle) was developed. The ANN achieved a prediction accuracy of 94.3%, indicating its reliability in capturing the complex fatigue response of SMAs.
  • Effects of High-Temperature Deformation and Welding on Microstructure and Thermomechanical Properties of Ti-6Al-4V
    J. Nagarjun, M. Senthil Vel, G. Swaminathan, N. Saravanakumar, J. John Rozario Jegaraj, G. Yoganand, P. Mastanaiah
    Journal of Materials Engineering and Performance, 2025
  • Hybrid glass/Kevlar fiber reinforced phenolic matrix composites: Thermal degradation and flammability studies
    Senthilkumar Krishnasamy, Sasikumar Ramachandran, G. Swaminathan, M. Thirukumaran, M. Hema, Jyotishkumar Parameswaranpillai, Senthil Muthu Kumar Thiagamani, D. Aravind, M. Chandrasekar, Varagunapandiyan Natarajan
    Polymer Composites, 2025
    In the present work, bio‐based phenolic matrix composites (PMCs) were fabricated by reinforcing them with bi‐directional glass fiber mats, bi‐directional Kevlar fiber mats, and their hybrid combinations. Both fiber mats were treated with (3‐glycidyloxypropyl) trimethoxysilane (GPTMS) to enhance fiber‐to‐matrix adhesion. Subsequently, the fibers were coated with a phenolic binder made from a mixture of phenol‐hexamine‐based novolac (N) resin and cardanol‐hexamine‐based benzoxazine (Bz) resin. Then the layers of binder‐coated fibers were compressed using a hot press molding machine at 200°C to cure the resins. The developed composites were subjected to thermogravimetric analysis (TGA) and UL‐94 V flammability test. The glass fiber (GF‐NBz) and Kevlar fiber (KF‐NBz) reinforced PMCs show an overall mass loss of ~18.5% and 66% at 850°C. Whereas the hybrid GF/KF fiber‐reinforced PMCs exhibit balanced properties of improved thermal stability and higher char yield. The flammability test results show both pure and hybrid samples exhibited a V‐0 rating. Based on these observations, the combination of glass fiber and Kevlar fiber‐reinforced PMCs may be suitable for automotive applications, such as dashboards, and door panels, with improved performance and fire safety.Highlights Glass and Kevlar/phenolic and their hybrids were developed using hot press. Fibers coated by (3‐glycidyloxypropyl) trimethoxysilane to enhance bonding. GF/KF composites exhibited balanced properties in thermal property. The pure and hybrid samples achieved a V‐0 rating under UL‐94 V test.
  • Modified Boltzmann sigmoidal model for predicting functional fatigue behaviour of NiTi shape memory alloys
    G. Swaminathan, S. H. Adarsh, M. Bharathi
    Applied Physics A Materials Science and Processing, 2025
  • Influence of applied stress on shape memory characteristics of Ni50Ti45Cu5 (at.%) alloy subjected to thermomechanical cycling
    Swaminathan Ganesan, Sampath Vedamanickam, Adarsh Sorekunte Huchappa
    Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications, 2024
    Shape memory alloys have made rapid progress in many domains, primarily biomedical (endovascular stents, orthodontic archwires), and engineering (smart actuators, robotics, hydraulic couplings). The selection of a shape memory alloy for the indented application is based on its characteristic phase transformation temperatures. These characteristic temperatures are influenced by myriad parameters, such as composition, microstructure of the alloy, defect density, etc. When an shape memory alloy under an external load is subjected to cyclic operations to perform useful work, for example, actuators, these characteristic temperatures are modified. This study, therefore, aims to understand the influence of external loading on the shape memory characteristics of a Ni50Ti45Cu5 (at.%) alloy. A wire of 1.43 mm diameter and length of 100 mm was subjected to heating and cooling between its phase transformation temperatures in a cyclic manner under constant stress (of up to 60 MPa). The maximum recovery strain, actuation/retraction rate, and the stress influence coefficient were determined and compared with those of the other Ni-Ti and Cu-based shape memory alloys. The results show that raising the load level causes an increase in the transition temperatures, especially the Ms (martensite start temperature) rather than the other phase transformation temperatures (martensite finish (Mf), austenite start (As), austenite finish (Af)). It also significantly affects the recovery strain and the rate of retraction during forward transformation and the symmetry of operation.
  • Thermal and thermomechanical cycling studies of nickel-based shape memory alloys for engineering and medical applications
    G. Swaminathan, Vedamanickam Sampath
    Advanced Materials for Emerging Applications Innovations Improvements Inclusion and Impact, 2024
    Shape memory alloys (SMAs) are those that can return to their initial shape after deformation under a stimulus, such as temperature or stress. They are capable of recovering deformations of up to 8%. Generally, the martensitic transformation is reversible in nature and the shape memory alloys exhibit two unique characteristics, super-elasticity effect (SE) and shape memory effect (SME), depending on whether these properties/responses are brought on by stress and temperature, respectively. Since the shape memory alloys undergo full cycling, they transform from austenite to martensite at temperatures between martensite finish and austenite finish. However, partial cycling refers to heating above the austenite start temperature but below the austenite finish temperature followed by cooling to below the martensite finish temperature. The phase transformation is partial before it is complete, consequently, only smaller amounts of the phases undergo a phase transition. Based on the operating temperature window and the transformation temperatures of the alloy, partial cycling can be divided into three categories. This chapter discusses the various types of cycling, i.e., thermomechanical, thermal, and partial cycling behavior of nickel-titanium-based shape memory alloys.
  • Effect of cobalt addition on thermal cycling behaviour of Ti50Ni(50−x)cox shape memory alloys
    G Swaminathan, V Sampath, S Santosh
    Physica Scripta, 2024
    The effect of adding Co on the temperature cycling behaviour of ternary Ti50Ni(50−x)Cox (x = 1, 2, 3) alloys was experimentally studied in this work. The alloys were prepared using a vacuum induction furnace, followed by subjecting them to homogenization, hot-rolling and annealing processes. The alloys were subjected to thermal cycling experiments in a nitrogen atmosphere by differential scanning calorimetry under stress-free conditions between their transformation temperatures. The results indicate that adding Co to NiTi alloys decreases their transition temperatures, improves the thermal cycling stability apart from suppressing the R-phase formation on cooling during cycling. The changes are due to the addition of Co introducing solid solution strengthening and generation of dislocations during cyclic phase transformations, as confirmed by the hardness test results and TEM micrographs, respectively.
  • Prediction of transformation temperatures of NiTiZr shape memory alloys using artificial neural network
    Sampath Vedamanickam, Poojalakshmi Vageeswaran, Bharathy Jacob, Swaminathan Ganesan, Khadambari Bhaskaran
    Materials Today Communications, 2023
  • Transformation Behavior of a Shape Memory Ni50.7Ti49.3 (at.%) Alloy during Partial Thermal Cycling
    Swaminathan Ganesan, Sampath Vedamanickam
    Journal of Materials Engineering and Performance, 2023
  • Effect of operating parameters on functional fatigue characteristics of an Ni-Ti shape memory alloy on partial thermomechanical cycling
    Swaminathan Ganesan, Sampath Vedamanickam
    Journal of Intelligent Material Systems and Structures, 2022
  • Effect of Mode of Heating on Cyclic Temperature Range during Partial Thermal Cycling under Constant Stress of a Near-Equiatomic Ni-Ti Shape Memory Alloy
    G. Swaminathan, V. Sampath
    Journal of Materials Engineering and Performance, 2022
  • Influence of Aging Temperature on Functional Fatigue Behavior of a Ti50Ni45Cu5 Shape Memory Alloy
    G. Swaminathan, V. Sampath, S. H. Adarsh
    Transactions of the Indian Institute of Metals, 2021
  • Observation of Transformation Strain Arrest During Partial Thermomechanical Cycling of an NiTi Shape Memory Alloy
    G. Swaminathan, V. Sampath
    Metallurgical and Materials Transactions A Physical Metallurgy and Materials Science, 2021
  • Studies on thermomechanical cycling characteristics of an Ni-Ti-Cu shape memory alloy
    Ganesan Swaminathan, Vedamanickam Sampath
    Materials Science Forum, 2021
  • Experimental Investigation on Hardness and Thermal Conductivity of D2 Steel Alloyed with Copper
    N. Ajay Guru, G. Swaminathan, P.R. Prasanna Venkatesh, P. Aravind
    Materials Today Proceedings, 2018
  • Rapid heat treatment process using microwaves - A novel approach
    Materials Science and Technology Conference and Exhibition 2016 MS and T 2016, 2016
  • Evaluation of mechanical properties and analysis of rapidly heat treated M-42 high speed steels
    ASM International 28th Heat Treating Society Conference Heat Treating 2015, 2015
  • Evaluation of mechanical properties and analysis of rapidly heat treated T-1 high speed steels
    International Journal of Applied Engineering Research, 2015

RECENT SCHOLAR PUBLICATIONS

  • Investigation of Scheil Solidification and Macrosegregation in Autogenous Gas Tungsten Arc Welded 250-Grade Maraging Steel
    V Rajkumar, KK Kumar, G Swaminathan
    Journal of Materials Engineering and Performance, 1-12 , 2026
    2026
  • Examining thermal, structural, and morphological properties of aluminium/ TPU composite filaments
    TSMKAAD Senthilkumar Krishnasamy, G. Swaminathan, Sasikumar Ramachandran, V ...
    Discover Materials 6 , 2026
    2026
  • Artificial neural network-based prediction of functional fatigue behaviour of an NiTi shape memory alloy
    G Swaminathan, SH Adarsh, M Raju, K Senthilkumar, TS Muthu Kumar
    Discover Materials 5 (1), 196 , 2025
    2025
    Citations: 1
  • Effects of High-Temperature Deformation and Welding on Microstructure and Thermomechanical Properties of Ti-6Al-4V
    J Nagarjun, M Senthil Vel, G Swaminathan, N Saravanakumar, ...
    Journal of Materials Engineering and Performance 34 (20), 23010-23018 , 2025
    2025
    Citations: 1
  • Modified Boltzmann sigmoidal model for predicting functional fatigue behaviour of NiTi shape memory alloys
    G Swaminathan, SH Adarsh, M Bharathi
    Applied Physics A 131 (6), 475 , 2025
    2025
  • Prediction of thermal cycling behaviour of Ni-rich NiTi SMA using empirical and artificial neural network modelling
    S Ganesan, S Pandey, S Krishnasamy, SMK Thiagmani
    Discover Materials 5 (1), 48 , 2025
    2025
    Citations: 2
  • Hybrid glass/Kevlar fiber reinforced phenolic matrix composites: Thermal degradation and flammability studies
    S Krishnasamy, S Ramachandran, G Swaminathan, M Thirukumaran, ...
    Polymer Composites , 2025
    2025
    Citations: 11
  • Influence of applied stress on shape memory characteristics of Ni 50 Ti 45 Cu 5 (at.%) alloy subjected to thermomechanical cycling
    S Ganesan, S Vedamanickam, AS Huchappa
    Proceedings of the Institution of Mechanical Engineers, Part L: Journal of … , 2024
    2024
    Citations: 1
  • Effect of Cobalt Addition on Thermal Cycling Behaviour of Ti50Ni(50-x)Cox Shape Memory Alloys
    S Ganesan, V Sampath, S Santosh
    Physica Scripta , 2024
    2024
    Citations: 3
  • Prediction of transformation temperatures of NiTiZr shape memory alloys using artificial neural network
    S Vedamanickam, P Vageeswaran, B Jacob, S Ganesan, K Bhaskaran
    Materials Today Communications 36, 106712 , 2023
    2023
    Citations: 8
  • Transformation Behavior of a Shape Memory Ni 50.7 Ti 49.3 (at.%) Alloy during Partial Thermal Cycling
    S Ganesan, S Vedamanickam
    Journal of Materials Engineering and Performance 32 (5), 2501-2508 , 2023
    2023
    Citations: 6
  • Effect of operating parameters on functional fatigue characteristics of an Ni-Ti shape memory alloy on partial thermomechanical cycling
    S Ganesan, S Vedamanickam
    Journal of Intelligent Material Systems and Structures 33 (14), 1834-1845 , 2022
    2022
    Citations: 7
  • Effect of Mode of Heating on Cyclic Temperature Range during Partial Thermal Cycling under Constant Stress of a Near-Equiatomic Ni-Ti Shape Memory Alloy
    G Swaminathan, V Sampath
    Journal of Materials Engineering and Performance 31 (4), 3120–3126 , 2022
    2022
  • Observation of Transformation Strain Arrest During Partial Thermomechanical Cycling of an NiTi Shape Memory Alloy
    G Swaminathan, V Sampath
    Metallurgical and Materials Transactions A 52 (7), 3182-3189 , 2021
    2021
    Citations: 3
  • Influence of Aging Temperature on Functional Fatigue Behavior of a Ti50Ni45Cu5 Shape Memory Alloy
    G Swaminathan, V Sampath, SH Adarsh
    Transactions of the Indian Institute of Metals 74 (10), 2435-2446 , 2021
    2021
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • Hybrid glass/Kevlar fiber reinforced phenolic matrix composites: Thermal degradation and flammability studies
    S Krishnasamy, S Ramachandran, G Swaminathan, M Thirukumaran, ...
    Polymer Composites , 2025
    2025
    Citations: 11
  • Prediction of transformation temperatures of NiTiZr shape memory alloys using artificial neural network
    S Vedamanickam, P Vageeswaran, B Jacob, S Ganesan, K Bhaskaran
    Materials Today Communications 36, 106712 , 2023
    2023
    Citations: 8
  • Effect of operating parameters on functional fatigue characteristics of an Ni-Ti shape memory alloy on partial thermomechanical cycling
    S Ganesan, S Vedamanickam
    Journal of Intelligent Material Systems and Structures 33 (14), 1834-1845 , 2022
    2022
    Citations: 7
  • Transformation Behavior of a Shape Memory Ni 50.7 Ti 49.3 (at.%) Alloy during Partial Thermal Cycling
    S Ganesan, S Vedamanickam
    Journal of Materials Engineering and Performance 32 (5), 2501-2508 , 2023
    2023
    Citations: 6
  • Effect of Cobalt Addition on Thermal Cycling Behaviour of Ti50Ni(50-x)Cox Shape Memory Alloys
    S Ganesan, V Sampath, S Santosh
    Physica Scripta , 2024
    2024
    Citations: 3
  • Observation of Transformation Strain Arrest During Partial Thermomechanical Cycling of an NiTi Shape Memory Alloy
    G Swaminathan, V Sampath
    Metallurgical and Materials Transactions A 52 (7), 3182-3189 , 2021
    2021
    Citations: 3
  • Influence of Aging Temperature on Functional Fatigue Behavior of a Ti50Ni45Cu5 Shape Memory Alloy
    G Swaminathan, V Sampath, SH Adarsh
    Transactions of the Indian Institute of Metals 74 (10), 2435-2446 , 2021
    2021
    Citations: 3
  • Prediction of thermal cycling behaviour of Ni-rich NiTi SMA using empirical and artificial neural network modelling
    S Ganesan, S Pandey, S Krishnasamy, SMK Thiagmani
    Discover Materials 5 (1), 48 , 2025
    2025
    Citations: 2
  • Artificial neural network-based prediction of functional fatigue behaviour of an NiTi shape memory alloy
    G Swaminathan, SH Adarsh, M Raju, K Senthilkumar, TS Muthu Kumar
    Discover Materials 5 (1), 196 , 2025
    2025
    Citations: 1
  • Effects of High-Temperature Deformation and Welding on Microstructure and Thermomechanical Properties of Ti-6Al-4V
    J Nagarjun, M Senthil Vel, G Swaminathan, N Saravanakumar, ...
    Journal of Materials Engineering and Performance 34 (20), 23010-23018 , 2025
    2025
    Citations: 1
  • Influence of applied stress on shape memory characteristics of Ni 50 Ti 45 Cu 5 (at.%) alloy subjected to thermomechanical cycling
    S Ganesan, S Vedamanickam, AS Huchappa
    Proceedings of the Institution of Mechanical Engineers, Part L: Journal of … , 2024
    2024
    Citations: 1
  • Investigation of Scheil Solidification and Macrosegregation in Autogenous Gas Tungsten Arc Welded 250-Grade Maraging Steel
    V Rajkumar, KK Kumar, G Swaminathan
    Journal of Materials Engineering and Performance, 1-12 , 2026
    2026
  • Examining thermal, structural, and morphological properties of aluminium/ TPU composite filaments
    TSMKAAD Senthilkumar Krishnasamy, G. Swaminathan, Sasikumar Ramachandran, V ...
    Discover Materials 6 , 2026
    2026
  • Modified Boltzmann sigmoidal model for predicting functional fatigue behaviour of NiTi shape memory alloys
    G Swaminathan, SH Adarsh, M Bharathi
    Applied Physics A 131 (6), 475 , 2025
    2025
  • Effect of Mode of Heating on Cyclic Temperature Range during Partial Thermal Cycling under Constant Stress of a Near-Equiatomic Ni-Ti Shape Memory Alloy
    G Swaminathan, V Sampath
    Journal of Materials Engineering and Performance 31 (4), 3120–3126 , 2022
    2022