STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Polymer & Composites Original Research Special issue

Modern Heritage Restoration Using GANs: Insights into Polymer–Composite Aging

  1. Vijay Kumar Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering
  2. Apurva Jain Department of Computer Science & Engineering, Dr. Akhilesh Das Gupta Institute of Professional Studies, Guru Gobind Singh Indraprastha University
  3. Rachna Narula Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering
  4. Megha Sehgal Department of Bachelor of Computer Applications, Bharati Vidyapeeth (Deemed to be university) Institute of management and research
  5. Meena Siwach Department of Information Technology, Maharaja Surajmal Institute of Technology
  6. Tulika Bhatia Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering

Abstract

In the Era of modernization, accomplish a Net Zero goes beyond installing more solar panels and wind turbines but we also need to make sure their lifespan possibility. With the help of Polymer compound for protective coatings to find the applications in solar cells, turbine blades, batteries that degrade over the course of time causes by sun exposure, moisture, and pollution. However, due to these same types of degradation have seen in the protective varnishes and materials used in paintings and sculptures. In the context there is technology plays a main role with the machine learning plays a main role for transitioning the approach in restoration work both for artwork as well as energy infrastructure which has traditionally depended on skilled manual inspection. The modern artwork restoration methods that use the algorithms of machine learning with a specific emphasis on CNNs, GANs, and reinforcement learning techniques. But there is challenges also arise which include the problem in fetching quality training data, computation method for a power needed substantial and we have to be careful about ethical issues especially when it comes to maintaining genuineness. The scientific tools of this study examine how varnishes and coatings on artworks break down over time and how polymer composites in renewable energy devices age and wear out. The true value of this study lies in assessing ML approaches on diverse datasets ranging from centuries old painting to modern solar panels in order for us to construct more robust algorithms to minimize waste and extend equipment life, directly advancing the net-zero clean energy transition.

Keywords

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