... as truth data. A supervised regression learning multilayer perceptron (MLP) neural network engine is developed. The machine learning (ML) engine developed in the present study can compute data with LES accuracy in 95% lesser computational time than performing LES simulations. The output of the ML engine...

... conditions. Simulating this behavior using conventional finite element modeling involves detailed and time-consuming analyses for calculation of blade temperature, which can be further utilized to assess cyclic and creep life. This paper deals with developing and utilizing machine learning based surrogate...

... such as machine learning (ML) provide a valuable tool that can be utilized to predict the occurrence of cyclic failure for these conditions with minimal time and resource requirement. In this paper, a machine learning based surrogate model is developed to predict the cyclic failure of a radially cooled turbine...

... thermocouple temperature data. With this approach, user intervention is mostly eliminated. 75% of cycle time reduction is achieved. thermal data match machine learning heat transfer coefficient regression THERMAL ANALYSIS VALIDATION USING MACHINE LEARNING Krishna Nelanti 1 , Raviraj Barapu 1...