Open Access
ARTICLE
A NEURAL NETWORK BASED METHOD FOR ESTIMATION OF HEAT GENERATION FROM A TEFLON CYLINDER
Sharath Kumar, Harsha Kumar, N. Gnanasekaran*
Department of Mechanical Engineering, National Institute of Technology, Karnataka, Mangalore, India
* Corresponding Author: Email:
Frontiers in Heat and Mass Transfer 2016, 7, 1-7. https://doi.org/10.5098/hmt.7.15
Abstract
The paper reports the estimation of volumetric heat generation (qv) from a Teflon cylinder. An aluminum heater, which acts as a heat source, is
placed at the center of the Teflon cylinder. The problem under consideration is modeled as a three dimensional steady state conjugate heat
transfer from the Teflon cylinder. The model is created and simulations are performed using ANSYS FLUENT to obtain temperature data for the
known heat generation qv. The numerical model developed using ANSYS acts as a forward model. The inverse model used in this work is
Artificial Neural Network (ANN). Estimation of heat generation is carried out by minimizing the error between the simulated temperature and
the experimental/surrogated temperature. The efficacy of the ANN method is explored for the estimation of unknown heat generation as both
forward model and inverse model. The concept of Asymptotic Computational Fluid Dynamics (ACFD) is introduced as a fast forward model
which is obtained by performing CFD simulations. The unknown heat generation is estimated for the surrogated data using ANN. In order to
mimic experiments, noise is added to the surrogated data and estimation of heat generation is also carried out for the perturbed/noise added
temperature data.
Keywords
Cite This Article
Kumar, S., Kumar, H., Gnanasekaran, N. (2016). A NEURAL NETWORK BASED METHOD FOR ESTIMATION OF HEAT GENERATION FROM A TEFLON CYLINDER.
Frontiers in Heat and Mass Transfer, 7(1), 1–7.