Modeling the outlet temperature in heat exchangers: Case study
| Autor: | Alina Barbulescu, Lucica Barbes |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
outlet temperature
Artificial neural network Renewable Energy Sustainability and the Environment lcsh:Mechanical engineering and machinery Computer Science::Neural and Evolutionary Computation Reynolds number Mechanics Perceptron neural networks Volumetric flow rate Physics::Fluid Dynamics symbols.namesake Multilayer perceptron Heat transfer Heat exchanger heat transfer symbols Environmental science Working fluid lcsh:TJ1-1570 reynolds number |
| Zdroj: | Thermal Science, Vol 25, Iss 1 Part B, Pp 591-602 (2021) |
| ISSN: | 2334-7163 0354-9836 |
| Popis: | This article presents the results of the study of the heat transfer in a heat ex-changer where the working fluid is the crude oil prepared for desalination, and the thermic agent is the re-circulating heavy gasoline fraction. Firstly, the Reynolds numbers have been computed using the temperatures and flow rates of the fluids as input variables. Then, general regression neural network and multi-layer perceptron were used for the outlet temperatures estimation using the inlet temperatures and the Reynolds numbers as input variables. The best models on the training dataset were obtained utilizing a multilayer perceptron with one hidden layer, while the best performance on the validation dataset was obtained using a multilayer perceptron network with two hidden layers. |
| Databáze: | OpenAIRE |
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