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ANN vs. MARS modeling: Experimental performance enhancement of MgO-TiO2/water binary and TiO2/water mono nanofluids in a plate-fin heat exchanger
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DOI：10.1016/j.ijheatfluidflow.2025.110022.png)
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Abstract
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• The overall performance of OSFPHE is constrained by a certain concentration threshold. • Heat transfer, effectiveness, and UA product increase up to certain nanofluid concentration. • The performance of the heat exchanger increases with the decrease in flow rate. • Both ANN and MARS provide reliable predicted effectiveness.
Keywords:
nanofluid concentration
heat transfer performance
effectiveness
UA product
artificial neural network
multivariate adaptive regression splines
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