Sampath Kumar L

@sirmvit.edu

Assistant Professor Mechanical Engineering Department
Sir M Visvesvaraya Institute of Technology

Sampath Kumar L


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https://researchid.co/sampathkumar_mech

EDUCATION

1. Ph.D. Sir MVIT, Bengaluru/ VTU Oct,2023
2. M. Tech. SDMCET, Dharwad /VTU Nov, 2011
3. BE SJMIT, Chitradurga /VTU Sept, 2008

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Engineering, Mechanical Engineering, Biomaterials
5

Scopus Publications

Scopus Publications

  • Tribological properties of CNT-filled epoxy-carbon fabric composites: Optimization and modelling by machine learning
    M.D. Kiran, Lokesh Yadhav B R, Atul Babbar, Raman Kumar, Sharath Chandra H S, Rashmi P. Shetty, Sudeepa K B, Sampath Kumar L, Rupinder Kaur, Meshel Q. Alkahtani, Saiful Islam, Raman Kumar
    Journal of Materials Research and Technology, 2024
    Polymer matrix composites reinforced with fibers/fillers are extensively used in several tribological components of automotive and boating applications. The mechanical performance of polymer composites improves by incorporating nanofillers as secondary reinforcement. The present research work fabricated carbon fabric-reinforced epoxy composites using the hand layup. The carbon fabric-reinforced polymer composites were fabricated with 0.1 wt%, 0.2 wt%, and 0.5 wt% of carbon nanotubes (CNT) fillers as secondary reinforcement. Tribological properties of carbon fabric-reinforced epoxy composites filled with CNT have been carried out using a pin‐on‐disc method. Adding fillers significantly improves the tribological behaviour of the carbon fabric-reinforced epoxy composites by reducing wear rate and coefficient of friction. The large surface area of interaction due to the higher aspect ratio of CNT shows improved adhesion between epoxy matrix and carbon fabrics. It improves the various mechanical and tribological characteristics of composites—also, an analysis of worn surfaces is carried out to analyze the wear mechanisms using scanning electronic microscopy. The research employs a combination of experimental analyses and machine learning (ML) techniques to explore the wear resistance, hardness, and predictive modeling of volume loss in the composites. The hyperparameter fine-tuning of ML algorithms, including Random Forest (RF), k-Nearest Neighbors (KNN), and XGBoost, demonstrates superior predictive capabilities, particularly with RF. The study bridges material science, ML, and practical applications, contributing valuable insights for developing advanced composite materials.
  • Investigation on tensile behavior of glass-fiber reinforced polymer matrix composite with varying orientations of fibers
    Prashant S. Hatti, Sampath Kumar L., Anupama B. Somanakatti, Rakshith M.
    Materials Today Proceedings, 2022
  • Study on flexural behavior of glass-fiber reinforced polymer matrix composite
    Prashant S. Hatti, Harisha P., Sampath Kumar L., Anupama B. Somanakatti, Rakshith M.
    Materials Today Proceedings, 2022
  • Synthesis, characterization and antibacterial studies of calcite-zincite nanoparticles
    L. Sampath Kumar, V. Shantha, Chandrashekhar Naik, C. Rajendra Singh, P. Hariharan
    Materials Today Proceedings, 2021
  • Synthesis of calcite-zincite nano composite materials using sol-gel auto combustion method
    L Sampath Kumar, V. Shantha, Chandrashekhar Naik, D. N. Drakshayani, Pramodkumar S. Kataraki, Ayub Ahmed Janvekar, Aulia Ishak
    Iop Conference Series Materials Science and Engineering, 2020
    Calcite-Zincite nano particles were synthesized by Sol-Gel Auto Combustion (SGC) technique. Modifying nanoparticles promote numerous advantages, such as, simplicity of synthesis, small heat for breakdown, regulation above the compound structure, small budget, dependability, repeatability, and moderate synthesis situations. One of interesting study on Sol-Gel auto Combustion technique has proven massive advantages as compared to other traditional methods. Presented work follow synthesized of novel nanoparticles. Research work was focused on characterized UV visible absorption spectroscopy and FTIR. The UV visible absorption spectroscopy shows an absorption band at 214 nm, 234 nm and 372nm due to calcite/zincite nano composite particles. FTIR spectra establishes a particular Calcite - Zincite nano powder obtained the characteristic peak of carbonate group at 1414 cm-1, 868 cm-1 (CaCo3) and 477 cm-1 (ZnO).