Abstract
Augmenting the thermal conductivity (TC) of fluids makes them more favorable for thermal applications. In this regard, nanofluids are suggested for achieving improved heat transfer owing to their modified TC. The TC of the base fluid, the volume fraction and mean diameter of particles, and the temperature are the main elements influencing the TC of nanofluids. In this article, two approaches, namely multivariate adaptive regression splines (MARS) and group method of data handling (GMDH), are applied for forecasting the TC of ethylene glycol-based nanofluids containing SiC, Ag, CuO, , and MgO particles. Comparison of the data forecast by the models with experimental values shows a higher level of confidence in GMDH for modeling the TC of these nanofluids. The values determined using MARS and GMDH for modeling are 0.9745 and 0.9332, respectively. Moreover, the importance of the inputs is ranked as volume fraction, TC of the solid phase, temperature and particle dimensions.
Highlights
A nanofluid is a colloidal suspension composed of a base fluid and particles with sizes in the range of 1–100 nm
The results showed that enhancement of the thermal conductivity (TC) was dependent on the type of base fluid in a constant fraction of the solid phase
This goal is achieved by appointing the gain data to piecewise linear regression functions. Another advantage of the multivariate adaptive regression splines (MARS) method is that it does not demand a priori presumptions regarding elemental correlations among dependent and independent factors. This correlation is revealed by a group of coefficients and the order of q polynomials as the basis functions, which are completely acquired from the regression data
Summary
A nanofluid is a colloidal suspension composed of a base fluid and particles with sizes in the range of 1–100 nm. The suspension of solid particles leads to augmented thermal conductivity (TC) (Jiang, Zhang, & Shi, 2015); the heat transfer features are improved. Owing to their enhanced thermal properties, nanofluids are promising options for utilization in heat exchangers, thermal media and energy systems to improve the heat transfer rate and modify the thermal management of devices with high heat flux (Gandomkar, Saidi, Shafii, Vandadi, & Kalan, 2017; Ramezanizadeh, Nazari, Ahmadi, & Açıkkalp, 2018; Ramezanizadeh, Nazari, Ahmadi, & Chen, 2019). Heat transfer augmentation of thermal media achieved by employing nanofluids is mainly attributed to their modified TC (Nazari, Ghasempour, Ahmadi, Heydarian, & Shafii, 2018).
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