Formulation of Surrogate Model-Based Inverse Solution in Unsteady Conduction - Lecture 66

Learn how neural networks can be utilized as surrogate models for solving inverse problems in heat transfer through this 15-minute lecture from NPTEL's 'Inverse Methods in Heat Transfer' series. Explore the process of developing data-driven models using experimental data as alternatives to computationally intensive simulations, making parameter estimation more efficient in unsteady conduction problems. As part of NPTEL's certified curriculum, gain knowledge that can be applied toward course credits in Indian Universities under UGC and AICTE guidelines.