2 publications

• Published Subscription Original Research 15 Oct 2024

  An Innovative AI-Integrated Approach for Identifying the Tensile Robustness of Polymeric Materials

  By M.V. Kulkarni, P. William, Pravin B Khatkale, Sandip R. Thorat, Santosh Kumar Sharma, Apurv Verma

  Abstract: Polymeric materials have so many applications and character similar to flexibility, robustness and lightweight nature they are essential to a large variety of industries. Though, it is difficult to establish their tensile robustness appropriately, particularly in a variety of environmental situation. Provide a recommended Artificial Intelligence (AI)-integrated method to decide the issues of rapidly ascertaining the tensile robustness of the polymeric material. Using machine learning (ML), this study, predicted and …

  Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 90–97 Read article →

• Published Subscription Original Research 30 Jul 2024

  Developing an AI-Based Novel Forecasting Framework for Surface Irregularity in Metal Matrix Materials

  By M.V. Kulkarni1, P. William, Pravin B Khatkale, Harshal P. Varade, Sandip R. Thorat

  Abstract: Surface irregularity in metal matrix materials (MMM) signifies the deviations from smoothness, influencing structural integrity and performance frequently arising from the manufacturing process along with intrinsic material characteristics that influence effectiveness. Limitations in data, model interpretability and complexity are the difficulties that impede artificial intelligence (AI) based surface irregularity in MMM. In this study, we suggested a novel framework of Gaussian regression fused multi-strategy adaptive boosting classifier (GR-MABC) for the …

  Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 48–56 Read article →