Graphene-Based Surface Layer for Crystalline Deposition Control in Cryogenics
Dr.T.AMALRAJ VICTOIRE1, M.VASUKI2, E.JANANI3
1 Associate Professor, Department of MCA, Sri Manakula Vinayagar Engineering College, Puducherry-605107, India.
amalrajvictoire@gmail.com1
2 Associate Professor, Department of MCA, Sri Manakula Vinayagar Engineering College, Puducherry-605107, India.
dheshna@gmail.com2
3 Post Graduate Student, Department of MCA, Sri Manakula Vinayagar Engineering College, Puducherry-605107 India.
jananielumalai8484@gmail.com3
ABSTRACT
The system has been designed to offer a way to keep frost from forming on your plants on special types of vessels known as cryogenic tanks. There is an organized routine to how it’s run a proven system that handles all tasks in an organized way simple. It starts when an administrator takes charge. It processes registrations and sets up teams as they are being developed the process covers methods of gaining access to the system. After a team is granted access, members of the team receive email notifications with login credentials to enter the platform.
The administrator takes on the very important job of uploading critical requirements needed for the project to get started and succeed at it. The first of these requirements is a set of specifications for the tank. This is very much needed because the tank specifications provide a foundation that the system can build upon to create a necessary calculations suite. Using this, the system determines the next two big steps. Number one is calculating the surface area of the tank, which is not trivial by any means. Number two is determining the amount of graphene oxide that is required to make a coating that will stop frost from forming on the tank. The coatings production process, the system needs two essential things: number one, a suite of calculations that is very much tied to the tank specifications and number two, a very important manager (the administrator again, but now also a project owner for coatings production) who can keep the workflow going and debug problems as they arise. The system provides a sustainable and reliable way of ensuring cryogenic performance, with big implications for places like the aerospace and biomedical industries. But you can't just hope the system will not only work but also be cost-effective for big businesses.
Keywords: Graphene Coating, Cryogenic Frost Prevention, Machine Learning, Generative Adversarial Networks (GANs), K-Means Clustering, Automated Thermal Management
