Sharif Digital Repository

In this study, the liquid-liquid phase behavior of aromatic compound. +. aliphatic compound. +. ionic liquid (IL) ternary systems was estimated by using two artificial neural networks (ANN) developed based on back propagation (BP) and hybrid group method of data handling (GMDH). Molar ratio of aliphatic compound, aromatic compound, and IL as well as temperature, molecular weight ratio of aliphatic compound to IL, and molecular weight ratio of aromatic compound to IL were chosen as the inputs to the networks. Additionally, the mole fraction of components in final alkane-rich phase and IL-rich phase was considered as desired outputs. The best topology of the BP-ANN model was found as (6-8-4).... 

Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif... 

Thermal conductivity of nanofluids plays key rol in heat transfer capacity of fluids. adding nanoparticles to a base fluid can lead to enhancement in thermal conductivty ratio. CuO/Ethyle Glycol (EG) is one of the most applicable nanofluids for heat transfer purposes. In the present study, thermal conductivty ratio of CuO/EG nanofluid is modeled by applying Group Method of Data Hnadling and Least Square Support Vector Machine – Gentic Algorithm approaches. Results indicated that the utilized model are very accurate in predicting thermal conductivty ratio of the nanofluid. The R-squared values for the proposed model are equal to 0.994 and 0.991 by applying Group Method of Data Handling and... 

The main focus of this paper is to present thermodynamic and economic analyses and multi-objective optimization of a novel geothermal-solar multigeneration system. The system aims to produce hydrogen, freshwater, electricity, cooling load, and hot water and designed based on geothermal and solar energy. After modeling and thermodynamic and economic analysis, exergy destruction rate, exergy efficiency and, cost rate were calculated for each component of the system. The results showed that the highest amount of exergy destruction was related to parabolic trough collectors (PTCs) and absorption chillers. To select the geothermal fluid of the organic Rankine cycle (ORC), several different fluids... 

In the last years, an appreciable effort has been directed toward developing empirical models to link the relative permeability of gas condensate reservoirs to the interfacial tension and velocity as well as saturation. However, these models suffer from non-universality and uncertainties in setting the tuning parameters. In order to alleviate the aforesaid infirmities in this study, comprehensive modeling was carried out by employing numerous smart computer-aided algorithms including Support Vector Regression (SVR), Least Square Support Vector Machine (LSSVM), Extreme Learning Machine (ELM), Multilayer Perceptron (MLP), Group Method of Data Handling (GMDH), and Gene Expression Programming...