Machine Learning in Engineering: A Necessity for Viksit Bharat
Abstract
In the present era of Artificial Intelligence (AI) and Machine Learning (ML), it is very evident for everyone to think of Natural Language Processing (NLP) or Robotics as the innovations of AI/ML that has revolutionized the world. Machine Learning can play a vital role in predicting important parameters in new and existing Engineering Applications if trained well by data. ML models can save time and computational power upto 10 times the conventional models. The data can be generated via experiments or via Computational fluid Dynamics (CFD) simulation-based analysis. The present article presents the opportunities that lie in building machine learning models in industries including Chemical processes, Mechanical Equipments, Nuclear Reactors etc. The procedure is substantiated with a case study to show the power of a Machine Learning Model to reduce time and computational power. A transient CFD simulation for a rectangular tank heated with water filled in it is performed and the data generated is used to train a Machine Learning model. The predictions match the actual data to 98% accuracy.
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References
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