Engineers need the equation of states to simulate refinery processes in order to respond to their needs. In the present study the Perturbed-chain Statistical associating fluid theory (PC-SAFT) Equation of State are used to predict thermodynamic properties of hydrocarbon fluids. PC-SAFT is able to predict the thermodynamic properties of associating fluids such as hydrocarbons. The thermodynamic relationships are derived analytically with MATLAB. The numerical values of the thermodynamic properties of hydrocarbons, such as density, entropy, enthalpy, in thermal energy, heat capacity of hydrocarbons are obtained by MATLAB as well. By comparing the results with experimental results, the author found that PC-SAFT entails accurate predictions about the properties of hydrocarbons and also can predict thermodynamic properties of hydrocarbons at high pressures and low temperature. The calculated results from PC-SAFT minimum error for pure hydrocarbon and the maximum error for mixed hydrocarbons. Furthermore, the maximum calculated average absolute are 1.18% for density, 2.5% for enthalpy, 0.77% for internal energy, 3.33% for constant volume heat capacity and 4% for constant pressure heat capacity. Therefore, very low level of errors indicates the appropriateness of PC-SAFT performance to predict thermodynamic properties of materials.

In this paper, we have used a simple equation of state to predict the volumetric and thermodynamic properties of liquid refrigerants. The thermodynamic properties such as density ρ, isobaric expansion coefficient α, and isothermal compressibility κ, for some refrigerants e.g. R236ea, R245ca, and R245fa, based on GMA EOS have been calculated and a wide comparison with experimental data was made. This article is devoted to the theoretical study of some thermodynamic properties of the liquid refrigerants over the temperature range between 240K and 440K and pressures up to 580 atm to indicate that the GMA EoS has an acceptable performance for property predictions of pure liquid refrigerants. Our calculated results on the density, isobaric expansion coefficient and isothermal compressibility for the liquid refrigerants are in good agreement with the experimental data. The accuracy of the equation of state is determined by a statistical parameter; Absolute Average Deviation ( AAD). The AAD values show that the GMA equation of state can predict the thermodynamic properties of the refrigerants in the range of temperature and pressure with high precision.

Thermodynamic properties of sugar solutions have important roles and uses in different industries such as food production, food preservation industries, while there is not enough experimental data for all of the properties of sugar solutions. Therefore, representing a method for prediction and calculation of the thermodynamic properties of these solutions might be helpful in food industries. In this study thermodynamic properties of important aqueous sugar solutions in food industries containing glucose, sucrose, fructose, maltose, manose,maltotriose, xylose and galactose have been studied using a developed thermodynamics model based on Gibbs free energy. Different properties including water activity, sugar solubility, density, vapor pressure and boiling temperature of aqueous sugar solutions have been calculated using the Gibbs free energy based thermodynamic model proposed by Pazuki et.al. According to the number of experimental data used for different sugar solutions in this study for prediction of the solutions thermodynamic properties, it can be concluded that the model has a good ability to predict sugar solution's solubility, density and water activity. The comparison between the results proposed model results and the UNIQUAC model shows that the proposed model has a better agreement with the experimental data. It might be concluded that this model can be used for sugar solutions in food industries.

In this study, Artificial Neural Networks (ANNs) technique is applied for the determination of thermodynamic properties of the Lithium Bromide-Water solution, which is widely used in the thermodynamic simulations. For training of the ANNs the simulation results of a thermodynamic analysis are used. The presented ANN model provides simpler and faster results comparing to complex differential equations and exsiting limited experimental data. Using the ANN technique, the thermodynamic properties of LiBr-Water solution are derived as the mathematical relations. Simulation results show the effectiveness of ANN in identification of LiBr-Water solution thermodynamic properties.

In this study, the phase diagram and thermodynamic properties of Ti-O system up to 30 mole percent of oxygen was calculated with Calphad method. In this range of oxygen, Ti-O system includes αTi, βTi and liquid phases. αTi and βTi were modeled by “sublattice” model and the model of liquid phase was modeled by “ionic liquid”. Gibbs energy parameters of each phase was optimized by Thermo-Calc software and their phase and thermodynamic diagrams were drawn using this software. The obtained results were compared with experimental and other calculated results. A good accordance was observed between calculated and experimental results. In calculation of phase diagram, with increasing temperature and mole fraction of oxygen, the use of “ionic liquid” model instead of “sublattice” model in thermodynamic description of liquid phase showed better accordance with experimental data.

Molecular dynamics simulation is an appropriate method for microscpoic modeling of materials and is widely used in several fields of science and technology. Experimental measurement of thermodynamic properties of many materials is not economic due to time consuming and high cost of instruments. Using simulation methods such as molecular dynamics, thermodynamic properties of these materials can be computed and compared with experimental data. One of the important arguments in molecular dynamics simulation is application of appropriate combination ruls for dissimilar pair interactions. In this study, volumetric properties of 1-butyl-3-methylimidazolium hexafluorophosphate inonic liquid, acetonitrile, and their mixture are studied by molecular dynamics simulation and using three different combination rules for dissimilar pair interactions. Then the results are compared with experimental data inorder to evaluate validity of the applied combination rules.

In this study various empirical، theoritical and semi-theoritical equations of state for different optional fluids، have been investigated and the accuracy of these equations for thermodynamic properties estimation of these fluids in comparison with experimental data، was evaluated. Also a new equation of state has been derived from Mohammadikhah-Abolqasemi-Mohebbi semi-theoretical equation and has been introduced. The results of this research have showed that assumed equations of state have good accuracy in predicting the enthalpy and entropy for pure fluids in atmospheric pressures and slightly higher، except for n-butane which the error was high. Also، results of this research have showed good agreement between calculated data from these equations for compressibility factor prediction of optional fluids with experimental data. Also soave-redlich-kwong equation of state has been recommended for calculating thermodynamic properties including enthalpy and entropy at low pressures، because it has showed minimum errors.

In recent decades, there have been great eorts to simulate ow in hydrocarbon reservoirs and oil recovery processes. Compositional model is one of the most advanced models for this purpose. In this model, nonlinear mass conservation equations for multicomponent ow have to be solved along with thermodynamic equilibrium constraints. In most compositional simulators, an equation of state is used to determine phase behavior of hydrocarbon mixtures. In this article, an ecient two-phase compositional model for both immiscible and miscible uid ows in porous media is presented. In this model, the mass conservation equations are discretized using a cell-centered control volume method. The solution algorithm employs the so-called Implicit Pressure Explicit Saturation (IMPES) method. To determine the thermodynamic state of the mixture, the equation of state must be solved at each time step for each computational cell. These computations consume considerable time in a compositional simulation. Compositional space is parameterized with tie-line variables, and this parameterized space is used to reduce the number of times the equation of state must be solved. To parameterize compositional space, a few supporting tie-lines are needed, which were obtained adaptively during simulation process. The tie-line space is discretized using these supporting tie-lines and a Delaunay triangulation procedure. In the rest of discretized tie-line space, thermodynamic properties are calculated using linear interpolation. It is important to note that the equation of state is solved only at the supporting points used to discretize the tie-line space. Since tie-lines do not exist in the super-critical region, the space is represented based on overall compositions and equation of state. In this work, the used method keeps continuity of tie-line variables and overall compositions with respect to the change of the mixture state from sub-critical to super-critical space, and vice versa. The performance of the proposed approach is assessed using a number of homogeneous one-dimensional multicomponent problems. Numerical results show200e that the proposed method has acceptable accuracy and signi cantly reduces the total number of ash calculations needed in a compositional simulator.

In this paper, we have been used energy spectrum of ideal single layer graphene to investigate thermodynamic properties of this material. We have used Shannon and Tsallis entropies for investigating the entropy, internal energy and specific heat of this system. We plot these properties versus temperature. The obtained results show that the entropy and internal energy increase with enhancing the temperature and then these reach to a constant values. Also, the specific heat increases until it reaches a maximum and then reduces with increasing the temperature.