Advances in Theoretical & Computational Physics(ATCP)

Student Intern, USA

Publications

• Research Article   
  AI-Machine Learning Method for Design and Predictive Analysis of Wind Turbine
  Author(s): Prameet Guha, Sudipta Chakraborty and Pradip Majumdar*
  
  Wind turbines are electro-mechanical systems designed to harness kinetic energy from wind and convert it into electrical energy using rotor blades and a generator. They are considered one of the leading sources of sustainable power, offering a cleaner alternative to fossil fuels. However, the energy conversion efficiency of most commercial wind turbines remains limited, often between 25% to 40%, far below the theoretical maximum known as Betz’s limit (59.3%). This study aims to investigate design-based performance improvements to achieve a higher efficiency, employing both traditional approaches, such as Blade Element Momentum (BEM) Theory and Computational Fluid Dynamics, as well as advanced Artificial Intelligence techniques, including supervised regression-based Machine Learning (ML) algorithms. The research utilized meteorological data from 19 cities across Illinois, obtaine.. Read More»
  

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