To Develop the model for heat transfer coefficient with Machine Learning Techniques.

2022-26-1235

05/26/2022

Event
AeroCON 2022
Authors Abstract
Content
Being the Need of Increasing the heat transfer for domain which under heat stress index,key parameter is heat transfer coefficient, Which majorly depends upon the float rate of the context, the input of the heating element which ultimately decide the the time of contact of fluid which raise the concern about heat transfer. The Main goal of the presented study is to Investigate and develope model for the heat transfer coefficient in forced convection.The study comprising two section as conduction the experiment by considering the parameters like air flow, heater input, varying one at a time, which will creat the dataset, with dependent label as heat transfer coefficient using empirical relation. Three Machine learning algorithm i.e is Support Vector Machines, Decision Tree and XG boost are tested over the dataset. The metrics like Root mean squre error and Mean absolute error is plooed with the doamin, All algorithm implemented with the Python.
Meta TagsDetails
Citation
Dorwat, A., Dhotre, S., Biradar, A., and Lokhande, P., "To Develop the model for heat transfer coefficient with Machine Learning Techniques.," SAE Technical Paper 2022-26-1235, 2022, .
Additional Details
Publisher
Published
May 26, 2022
Product Code
2022-26-1235
Content Type
Technical Paper
Language
English