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Received: 4 November 2017 Accepted: 28 August 2018 The current study highlights the application of a hybrid model in which the Jaya optimization is employed to train the artificial neural network (ANN), to model the free convection in an open round cavity. As a matter of fact, the present research attempts to demonstrate the capability of the aforementioned hybrid network to model the free convection in the cavity against the decision parameters. The decision parameters are the Rayleigh number (Ra) and ratio of the nonconductor barrier distance from the bottom of the cavity to the cavity diameter (H/D). Then, the obtained hybrid model is applied to predict the average Nusselt number in the cavity. In the next step, the experimentally obtained data by using a Mach-Zehnder interferometer is used to train the hybrid model. The accuracy of the hybrid model is evaluated through the calculation of average testing and checking errors. According to the obtained results, there is an optimum ratio (H/D), in which the heat transfer is maximum. Also, this maximum value increases by increasing the Rayleigh number (Ra).

Modeling the free convection in an open round cavity using a hybrid approach of Jaya optimization algorithm and neural network