Using a Generalized Regression Neural Network Prediction Tool to Estimate Thermal Performance in A Heat Exchanger By using Triple Elliptical Leaf Angle Strips with Opposite Orientation and Same Direction
J. Bala Bhaskara Rao1, Ramachandra Raju2

1J.Bala Bhaskara Rao, Mechanical Engineering, Sri Sivani College of Engineering, Srikakulam, India.
2V. Ramachandra Raju, Mechanical Engineering, Jawaharlal Nehru Technology University, Kakinada, India.

Manuscript received on 25 August 2019. | Revised Manuscript received on 16 September 2019. | Manuscript published on 30 September 2019. | PP: 528-535 | Volume-8 Issue-11, September 2019. | Retrieval Number: K15640981119/2019©BEIESP | DOI: 10.35940/ijitee.K1564.0881119
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Abstract: In our day to day hectic schedule humans have got so adaptive to technology that tremendous pressure is built on researchers to produce better equipment with greater output & easier way of human usage. One among these is Heat exchanger which is a device for trading heat and providing comfortable environment either for humans or the equipment .This paper aims at finding a solution in improvement of the thermal performance of the heat exchanger by implementing a statistical tool derived from Artificial Neural Network. The name of the tool is GRNN. (Generalized Regression Neural Network) From a sparse data of inputs (Temperatures, Angle orientation & mass flow rates) the outputs of (outlet temperatures & drop in pressure) are found out using this tool. An experiment is also conducted to find the heat transfer rates and pressure drops. To enhance the heat transfer rate three elliptical shaped leaf strips are introduced in the tube with opposite orientation and same direction. The results obtained from both the sources are compared and the percentage of error is calculated.
Keywords: Thermal Performance, ANN, GRNN, Elliptical shaped leaf strips, percentage of error
Scope of the Article: Thermal Engineering