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In this study, molecular dynamics (MD) and Monte Carlo (MC) simulations techniques were employed as well as artificial intelligence knowledge of ANFIS and GP to investigate water–acetic acid pervaporation (PV) separation through poly vinylalcohol (PVA)‑silicone based membranes under a wide range of experimental conditions. For the first time, three new optimization algorithms, namely ant colony optimization for continuous domains (ACO R ), differential evolution (DE) and genetic algorithm (GA) were employed for improving ANFIS modeling. The GP creates a mathematical function or model for the estimation of pervaporation separation index (PSI) as a function of the input variables. ACO R -ANFIS and GA-ANFIS and GP had high accuracy (R 2  = 0.9831, 0.9792 and 0.9722, respectively) but DE-ANFIS had a lower accuracy (R 2  = 0.9610) as compared to other models. On the other hand, molecular simulation methods were used and the results of all simulation models were compared fairly to each other and to the experimental results of the literature. Also, some characterizations were taking place to investigate the characteristics of the simulated membranes with MS such as WAXD, and FFV and glass transition temperature was used to estimate the thermal properties of the simulated membranes. [ABSTRACT FROM AUTHOR]

This paper numerically investigates a three-dimensional channel's thermal and hydrodynamic performance with a convergent-divergent section. The convergent-divergent part of the channel is exposed to constant heat flux, and the other walls of the channel are insulated. In particular, the effect of using the nanofluid and magnetic field on Nusselt values, coefficient of friction, and entropy have been investigated. To improve Nusselt, pressure drop, and dimensionless entropy production rate, the Taguchi and ANFIS techniques have been utilized to optimize Reynolds, Hartmann numbers, nanofluid volume fraction, and geometric parameters of the channel. The sensitivity analysis results depict that Reynolds, Hartmann dimensionless numbers, and nanofluid volume fraction play more significant roles in improving the thermal and hydrodynamic performance of the channel than geometric parameters. The results show that the increase in the nanofluid volume fraction causes the most significant increase in the Nusselt number. In this case, the pressure drop inside the channel has increased slightly, but in total, the entropy production rate decreases due to irreversibility. Compared to the base case with the Reynolds number of 100, and in the absence of a magnetic field (Hartman 0), increasing the nanofluid volume fraction to 7% causes an 80% increase in the Nusselt number and a 65% decrease in the dimensionless entropy production rate. Similarly, by increasing the Reynolds number to 500 compared to the base case, the Nusselt number increases by 60% and the dimensionless entropy production rate decreases by 60%. Also, increasing the Hartmann number to 10 compared to the base case causes a 30% increase in the dimensionless Nusselt number and a 45% decrease in the dimensionless entropy production rate. • Heat transfer of a three-dimensional channel with a convergent-divergent section was analyzed. • The impacts of efective parameters on Nusselt, pressure drop, and dimensionless entropy production rate was investigated. • The Taguchi algorithm and ANFIS technique were exploited to optimize the thermal and hydrodynamic performance of the channel. [ABSTRACT FROM AUTHOR]