ML approaches for SMM behavior characterization
Yash Chauhan
Year of Study: 4th
Contact details: 8141130114
Project type: SLP
Motivation to pursue project: After my first SLP, I wanted build on my learning from the earlier SLP as well as gain experience in developing ML model for behaviour characterization of shape memory materials.
Summary of Project: Developed hybrid machine learning model to capture non-linear hysteresis behaviour of shape memory materials.
Experience and Time commitment (1: very low, 5: very high):
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Case Study on the eect of Deep Learning in the Determination of Composite Properties
Ajith R
Year of Study: 3rd
Contact details: 180010004@iitb.ac.in
Project type: SLP.
Motivation to pursue project: Interested in a project in any of the sectors of Aerospace Engineering where I can apply artificial intelligence for analysis.
Summary of Project: The prime objective of this project is to get an overview of the application of Artificial Neural networks in the determination of mechanical properties in the composite structure through analyzing by carrying out a case study. The rst case study determines the effect of an artificial neural network in determining the mechanical properties of a composite material using a feed-forward propagation method. Furthermore, the second case study also determines the Mechanical properties of a Composite using artificial neural networks but here by Back Propagation and genetic algorithm.
Experience and Time commitment (1: very low, 5: very high):
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