Developing an ANFIS-based swarm concept model for estimating the relative viscosity of nanofluids

Abstract

Nanofluid viscosity is an important physical property in convective heat transfer phenomena. However, the current theoretical models for nanofluid viscosity prediction are only applicable across a limited range. In this study, 1277 experimental data points of distinct nanofluid relative viscosity (NF-RV) were gathered from a plenary literature review. In order to create a general model, adaptive network-based fuzzy inference system (ANFIS) code was expanded based on the independent variables of temperature, nanoparticle diameter, nanofluid density, volumetric fraction, and viscosity of the base fluid. A statistical analysis of the data for training and testing (with R 2 = .99997) demonstrates the accuracy of the model. In addition, the results obtained from ANFIS are compared to similar experimental data and show absolute and maximum average relative deviations of about 0.42 and 6.45%, respectively. Comparisons with other theoretical models from previous research is used to verify the model and prove the prediction capabilities of ANFIS. Consequently, this tool can be of huge value in helping chemists and mechanical and chemical engineers -especially those who are dealing with heat transfer applications by nanofluids -by providing highly accurate predictions of NF-RVs.

Synthesis and application of Fe 3 O 4 @nanocellulose/TiCl as a nanofiller for high performance of quasisolid‐based dye‐sensitized solar cells

“…Nanofluids are defined as a fluid that contains nanometer‐sized particles (nanofibers, nanorods, nanotubes, nanoparticles, nanowires, and nanosheets) . The viscosity, thermal conductivity, and specific heat and density are the important parameters influencing the transfer of heat in the devices . Because of the importance of increasing and decreasing the temperature in industrial applications, temperature conductivity has found many applications.…”

“…30 The viscosity, thermal conductivity, and specific heat and density are the important parameters influencing the transfer of heat in the devices. 31,32 Because of the importance of increasing and decreasing the temperature in industrial applications, temperature conductivity has found many applications. In high-speed performance, it results in an increase in the amount of temperature that results in the operation at high power and high energy consumption.…”

Fully-automatic natural plant recognition system using deep neural network for dynamic outdoor environments

“…In order to do the experiment and the evaluation, the proposed model was applied in a tropical environment and several metrics such as the coefficient of determination (r), Nash-Sutcliffe efficiency (Ens), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) were computed [29]. Recently in 2019, Baghban et al [30] proposed a new approach to develop a general model for predicting nanofluid relative viscosity (NF-RV) [30]. To achieve the goal, expansion of an adaptive network-based fuzzy inference system (ANFIS) was performed [30].…”

“…Recently in 2019, Baghban et al [30] proposed a new approach to develop a general model for predicting nanofluid relative viscosity (NF-RV) [30]. To achieve the goal, expansion of an adaptive network-based fuzzy inference system (ANFIS) was performed [30]. The proposed model can be used as a tool for helping chemists and engineers who are involved with nanofluids in their works [30].…”

Soft Computing Approaches for Thermal Conductivity Estimation of CNT/Water Nanofluid

“…A few relationships were derived by Alimoradi et al [40], to estimate the Nusselt number of these sort of heat exchanger. According to the literature review, by using size and volume fraction of solid phase in addition to temperature accurate predictive models are achievable for a single nanofluid [41][42][43][44][45]. In this article, the data were gathered from different studies [46][47][48][49][50] to achieve a comprehensive model applicable in various operating conditions.…”