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The simplified local density (SLD) model was employed to analyze the experimental results of the adsorption of dimethyl sulfide (DMS) from a model fuel (n-hexane) on raw and modified walnut shell activated carbon (WSAC) with different impregnated amounts of silver ions (Ag-2, 4, 6, 8, and 10 mass percent). Modified Peng–Robinson equation of state was used in the liquid phase and the 6-12 Lenard Jones (LJ) potential function was implemented to represent the solid-fluid interactions. The LJ parameters for pure DMS and n-hexane were obtained from the Tsonopoulos correlation for the Second Virial coefficient data. Published experimental results of DMS and n-hexane adsorption were used for the physical properties and the molecular parameters needed in SLD model. Excess adsorption amounts of DMS were then calculated and compared with the experimental data. The average absolute deviations (AAD) between the experimental data and calculated results were 0.0072, 0.0727, 0.0377, 0.0601, 0.0605, and 0.0634 mmol/gr adsorbent for WSAC, WSAC-Ag-2, WSAC-Ag-4, WSAC-Ag-6, WSAC-Ag-8, and WSAC-Ag-10, respectively. For the same adsorbents the percent average absolute relative deviation (AARD%) were 14.11, 15.50, 7.70, 15.48, 16.16, and 29.09, respectively. The applicability of the SLD model in liquid-phase adsorption is validated. [ABSTRACT FROM AUTHOR]

• Condensation positively affects the thrust of expanding flows in thrusters. • Increasing the inlet H 2 O 2 concentration decreases the liquefaction in the nozzles. • The nozzle length affects the non-equilibrium condensation in high-speed flows. • In the thruster nozzles, the nucleation continues until the nozzle outlet. Excessive flow expansion in the thruster nozzles reduces the flow temperature and pressure. This provides conditions for the condensation phenomena in the nozzle, which can affect the thrust performance of thrusters. In this paper, the condensation effect of water components in the decomposition products of hydrogen peroxide in a typical thruster nozzle is modeled. To describe the state and properties of the real gas mixture, the Peng-Robinson equation of state is used. Moreover, the effects of H 2 O 2 concentration and nozzle profile on the condensation and nozzle performance parameters are studied. The results show that by more flow expansion and crossing the saturated state of condensable components, the thrust coefficient improves up to 6%. This improvement decreases by increasing the H 2 O 2 concentration in the reaction chamber for a fixed nozzle expansion ratio. Due to the small growth of droplets during the free molecular regime of the droplet growth in the high-speed flow, the non-equilibrium condensation continues until the nozzle outflow. In addition, although all the profiles have the same expansion ratio for nucleation start, increasing the nozzle length results in larger nano-droplets, more liquid mass fraction formation up to 4%, and moving the Wilson point to the further upstream sections in the nozzle. [ABSTRACT FROM AUTHOR]

Calculating the minimum miscibility pressure (MMP) between crude oil and carbon dioxide (CO2) is critical for optimizing injection parameters, designing schemes, and predicting production capacity in CO2 injection projects for enhancing oil recovery. However, an accurate approach for obtaining this parameter is not yet established. In order to tackle this issue, a novel approach is suggested, based on the original cell-to-cell model, to determine the MMP and the 97% oil recovery rate as the standard. Using the volume-transformed Peng-Robinson equation of state enhances the precision of fluid volume estimation, as it mainly relies on predicting fluid volume within each cell. Furthermore, to ensure a precise estimation of the ultimate oil recovery rate, it is imperative to employ a total cell count of 500 in all simulations to avoid the problem of numerical dispersion. Finally, a second-order polynomial equation more accurately predicts the infinite-cell oil recovery factor. The accuracy of the modified model is verified by comparing MMP values from five oil and gas systems in the literature. The computational results of the modified multiple-mixing-cell (MMC) approach exhibit a higher level of concordance with the MMPs in the literature. The average relative error is less than 3.96%. The improved MMC algorithm can quickly determine the miscibility mechanism and visually represent the dynamic miscibility process involving multiple oil-gas contacts in a slim tube. This study provides a theoretical and practical basis for addressing the critical scientific issues of CO2-safe storage technology. [ABSTRACT FROM AUTHOR]

A leading cause of global warming is the increase of carbon dioxide (CO2) emissions due to anthropogenic activities which prompts an urgent need for substantial reduction. Recently, CO2 absorption in deep eutectic solvents (DESs) has attracted scientific attention, because of their adaptability compared to traditional ionic liquids and aqueous amine solutions. This study employs the heating method to synthesize DESs using tetrapropylammonium bromide (TPAB) and formic acid (Fa) with molar ratios of TPAB-Fa (1:1) and TPAB-Fa (1:2). Absorption experiments by static method quantified CO2 solubility in the DESs under varied pressures and temperatures. TPAB-Fa (1:2) at 25.0 °C was the most efficient with the CO2 solubility of 0.218. Thermodynamic modeling was performed by employing the nonrandom two liquids activity coefficient model and the Peng–Robinson equation of state for the liquid and gas phases, respectively. The Henry's law constant was determined from experimental data. CO2 physical absorption was confirmed via nuclear magnetic resonance (NMR) and Fourier-transform infrared (FT-IR) analyses. TPAB-Fa (1:2), as the superior DES, exhibited regeneration efficiency of 99% after five absorption/desorption cycles. [ABSTRACT FROM AUTHOR]

Densities (ρ ) and viscosities (η ) of the binary mixtures of 2-ethyl-1-hexanol (2-EH) with ethylenediamine, 1,2-dichloroethane (DCE) and monoethanolamine (MEA) were measured at T = (298.15–318.15) K under atmospheric pressure over the entire composition range ( x 1 = 0 - 1.0 ). For these binary mixtures ultrasonic speeds (u ) and refractive indices ( n D ) were also measured at 298.15 K. With these experimental data the excess molar volumes ( V m E ), viscosity deviations ( Δ η ), excess molar refractions ( R m E ), excess isentropic compressibility ( κ S E ) and other derived properties were determined at various experimental temperatures. Such thermophysical properties were discussed in terms of molecular interactions and structural effects well corroborated with IR spectra of the mixtures. Excess molar volumes ( V m E ) of the binary mixtures were used to derive partial molar volumes ( V ¯ m,1 0 and V ¯ m, 2 0 ) and excess partial molar volumes ( V ¯ m,1 0,E and V ¯ m,2 0,E ) at infinite dilution to reveal the volume changes of the binary mixtures. Prigogine-Flory-Paterson theory (PFP), Peng-Robinson Equation of States (PR-EOS) and Bloomfield-Dewan (BF-D) model were used to predict excess molar volumes ( V m E ) and viscosities (η ) of the mixtures. Ultrasonic speeds (u ) of the binary mixtures predicted using empirical or semi-empirical theories like free length theory, Impedance dependence relation, Ideal mixture relation, Junjie's relation, collision factor theory and Nomoto's relation, etc. Computational studies have also been performed to establish the degree and nature of solvent–solvent interactions theoretically. [ABSTRACT FROM AUTHOR]

The objective of this study is to assess the storage of acid gas, containing CO2 and H2S, in a depleted naturally fractured reservoir (NFR) using single matrix block (SMB) approach. The acid gas dissolution in oil is considered by Peng‐Robinson equation of state and compositional simulation. The PHREEQC package is used to determine acid gas solubility in formation brine. Three types of acid gases with different compositions are used for this study and their swelling behavior and miscibility in relation to the reservoir oil are analyzed. An SMB model, with a matrix block surrounded by fractures, is constructed, and validated for simulation of a real experiment. The simulation is conducted for synthetic and real reservoir fluids when the oil is in its residual saturation. A sensitivity analysis is performed to study the effects of key parameters, such as acid gas composition, reservoir pressure, permeability, porosity and matrix height on the storage capacity and oil recovery factor. The matrix has a volume of 27 m3 and about half of acid gas storage is achieved in the first 5 years while the simulations are run for 30 years. The results show that up to 90% of remained oil is recoverable, and more than 0.67 kmol of acid gas per cubic meter of matrix is stored whether matrix contains a real oil or a synthetic one. Higher storage is achieved for higher matrix porosities and heights and large H2S proportion in acid gas. In all cases about 10% of acid gas is trapped in water and the remaining 90% is dissolved in oil. The mineral trapping was more active in CO2‐rich acid gases. While about 10 kg of the matrix rock was dissolved in the acidic brine when the acid gas contained H2S, the amount of the dissolved minerals in acidic brine resulted from the injection of CO2‐rich acid gas was more than 16 kg. Finally, this study gives a comparative analysis of the storage performance of acid gas mixture and pure CO2. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The present study examines the effect of storage conditions on the characteristics of cryogenic hydrogen jets released into the atmosphere, relevant to an accidental leakage scenario during storage or transportation. The compressible Reynolds-Averaged Navier–Stokes equations, coupled with the Peng–Robinson equation of state for hydrogen-air mixtures, are solved for a range of operating conditions (storage pressures from 3 – 7 bar and storage temperatures of 50 – 70 K). Flow structures in the near-orifice and self-similar regions are analysed, showing that the presence of shock waves creates conditions favourable for possible condensation of hydrogen and air. In the self-similar region, decay laws based on the shock exit conditions are proposed, demonstrating a slower decay of centreline temperature in comparison to hydrogen concentration and velocity. Additionally, a universal relationship between the centreline mole fraction of hydrogen and temperature is observed, explained using an adiabatic mixing model. [Display omitted] • Numerical simulations of cryogenic hydrogen jet dispersion are performed. • Shock waves in the near-orifice region create conditions conducive to condensation of air. • Scaling of far-field flow quantities using shock exit conditions is more appropriate than using orifice exit conditions. • A universal relationship between the centreline mole fraction of hydrogen and temperature is found. • The found universal relationship can be explained by considering adiabatic mixing between hydrogen and air. [ABSTRACT FROM AUTHOR]

This work aims to provide a thermodynamic modeling to determine the high heating value (HHV) of food samples, particularly high-calorie food. The HHV is measured experimentally, and a rigorous model is constructed from these data. A bomb calorimeter under controlled conditions is used to experimentally determine the HHV of four commercial snacks (Twix, Snickers, Peanut Planters, and KitKat). The samples are characterized by ultimate analysis. The rigorous modeling is developed using a modified Peng-Robinson (PR) Equation of State (EoS) developed by Forero-Velásquez (FV). Also, mass and energy balances, vapor-liquid equilibria equations, and the reaction speed rate are stated. The results indicate that the average absolute deviation between the nutritional information label and rigorous modeling is 6.54%. Also, an equation is suggested for rapid estimation of HHV using data from rigorous modeling. The results show that the developed linear equation is simpler and provides an absolute relative deviation of 11.04% compared to other sophisticated or multiparametric reported literature models with deviations of 16.62%. [ABSTRACT FROM AUTHOR]

To investigate the self-pulsation characteristics of a liquid-centered swirl coaxial injector with liquid oxygen (LOX) and gas hydrogen (GH2) as the working mediums under supercritical condition, a numerical simulation was employed. The transient simulation of the flow and injection process of cryogenic propellant was carried out using the RNG k − ε turbulence model, VOF model, and Peng-Robinson equation of state. The frequency spectrum of calculated pressure oscillation agreed with the experimental data. The amplitude-frequency characteristics of recess region, LOX, and GH2 paths when self-pulsation occurs were analyzed. The effects of operating parameters, such as the flow rate of LOX or GH2 and the initial GH2 temperature, on the self-pulsation, were evaluated specifically. Results reveal that the self-pulsation results from the periodic variation of pressure and velocity caused by the periodic blocking of annular gas by the liquid sheet. The dominant frequencies of pressure oscillation in the recess region, upstream of LOX, or GH2 path are diverse. But for the points in each region, the dominant frequency is about the same. When the LOX/GH2 mixing ratio increases, the liquid sheet thickness and the number of liquid filaments increase. The position where filaments are massively broken into droplets moves further downstream. For the same mixing ratio, the flow rate of LOX has a greater impact on the atomization features. The pressures corresponding to low or high frequency increase when the initial GH2 temperature raises. The higher temperature would shift the dominant oscillation between the low and high regimes. [ABSTRACT FROM AUTHOR]

Multiphase flow phenomena are ubiquitous in real-life applications, and the pseudopotential-based lattice Boltzmann multiphase simulation method has gained extensive usage in fields such as fuel cells, energy storage materials, and boiling heat transfer. Over the past two decades, significant improvements have been made to the pseudopotential model. These advancements have greatly enhanced its accuracy in simulating various processes. In this paper, we employ a numerical stability-based unit conversion scheme to ensure an accurate representation of real-world material properties. Additionally, we introduce a more precise non-ideal two-parameter gas state equation Modified Peng-Robinson (MPR) that closely aligns with experimental data, surpassing the commonly used single-parameter Peng-Robinson state equations. Furthermore, we compare the accuracy of the two-state equations for polar and non-polar substances, finding improved accuracy for non-polar substances and a higher degree of fidelity for polar substances when using the MPR equation. We analyze the constant correction coefficients chosen for thermodynamic consistency regulation from the perspectives of vapor-liquid interface thickness and numerical stability, both when held constant and when employing a dynamic correction approach that balances vapor-liquid interface width, numerical stability, and thermodynamic consistency. Finally, we validate to ensure its practical applicability. [ABSTRACT FROM AUTHOR]

Machine learning based on neural networks facilitates data-driven techniques for handling large amounts of data, either obtained through experiments or simulations at multiple spatio-temporal scales, thereby finding the hidden patterns underlying these data and promoting efficient research methods. The main purpose of this paper is to extend the capabilities of a new solver called realFluidReactingNNFoam, under development at the University of Perugia, in OpenFOAM with a neural network algorithm for replacing complex real-fluid thermophysical property evaluations, using the approach of coupling OpenFOAM and Python-trained neural network models. Currently, neural network models are trained against data generated using the Peng–Robinson equation of state assuming a mixture's frozen temperature. The OpenFOAM solver, where needed, calls the neural network models in each grid cell with appropriate inputs, and the returned results are used and stored in suitable OpenFOAM data structures. Such inference for thermophysical properties is achieved via the "Neural Network Inference in C made Easy (NNICE)" library, which proved to be very efficient and robust. The overall model is validated considering a liquid-rocket benchmark comprised of liquid-oxygen (LOX) and gaseous-hydrogen (GH2) streams. The model accounts for real-fluid thermodynamics and transport properties, making use of the Peng–Robinson equation of state and the Chung transport model. First, the development of a real-fluid model with an artificial neural network is described in detail. Then, the numerical results of the transcritical mixing layer (LOX/GH2) benchmark are presented and analyzed in terms of accuracy and computational efficiency. The results of the overall implementation indicate that the combined OpenFOAM and machine learning approach provides a speed-up factor higher than seven, while preserving the original solver accuracy. [ABSTRACT FROM AUTHOR]

Hydrogen-fueled, fuel-cell-powered cars offer environmentally friendly alternative for near future. One of the critical part of this technology is to store hydrogen efficiently and securely. Many different methods have been developed to store hydrogen. The most popular storage method for hydrogen storage in vehicles is compressible hydrogen storage tanks due to their lightweight and efficiency. One of the most important factors during filling is the filling time. During rapid filling, the tank temperature rises significantly, which can cause damage to the tank and create a dangerous situation. In this research, CFD simulation has been made for fast filling condition for compressible hydrogen storage tanks. It was decided to use the k- ε turbulence model and different real gas equations for numerical simulation. The effects of four different real gas equations and also ideal gas equation on the temperature, the pressure, and filling times are investigated numerically. As a result of the simulation, it was concluded that the use of different real gas equations does not have a significant effect on the temperature and the pressure of the storage tank. However, the filling duration of storage tank is slightly affected by usage of different real gas equations. Filling durations of hydrogen according to Redlich-Kwong equation of state increased for Soave-Redlich-Kwong equation 1.3 %, for Aungier Redlich-Kwong equation 1.5 %, for Peng-Robinson's equation of state 5.85 %, for ideal gas equation of state 24.2 %. • Effects of different real gas equations on the filling time of type-III hydrogen storage tank is considered. • The filling duration of storage tank is slightly affected by usage of different real gas equations. • Maximum pressure, maximum temperature and maximum velocity values were solved for certain filling time intervals. • Ideal gas assumption over estimates the filling time of hydrogen compared to different real gas equations. [ABSTRACT FROM AUTHOR]

The energy production potential of some common food waste, including cooked rice, “eba,” orange, yam, and potato peels, has been studied through thermodynamic modeling and simulation. The key gasification processes were modeled individually in ASPEN PLUS. The component properties were calculated with Peng-Robinson’s equation of state. The effect of the equivalence ratio (ER), steam-to-biomass ratio (STBR), and gasifier operating temperature on the composition, cold gas efficiency (CGE), and higher heating value (HHV) of the syngas was studied. Results revealed that the production of H2 and CO2 reduces with the increase in ER and increases with STBR. The molar fraction of CO is inversely proportional to that of CO2. Increasing ER causes an increase in oxidizer within the gasifier and a corresponding increase in the molar fraction of N2. Reduction in STBR reduces both the N2 content and heating value of syngas. Syngas from both feedstocks has heating values ranging from 18.48 to 11.04 MJ/kg, with food waste yielding higher HHV than hardwood. The CGE for hardwood ranges from 55.6% to 74.95%, while for food waste, it ranges from 49.3% to 57%. This study demonstrates the production of high-quality syngas from locally sourced food waste. [ABSTRACT FROM AUTHOR]

Modeling droplet dynamics on solid surfaces with rough or chemically heterogeneous walls is crucial in various industrial applications. In such cases, the downstream and upstream contact lines of the droplet usually move incongruously, leading to droplet deformation known as the contact angle hysteresis (CAH) phenomenon. In this work, we developed a cascaded multicomponent Shan–Chen lattice Boltzmann method to simulate droplet dynamics considering the CAH. Specifically, the Peng–Robinson equation of state is added to one component to improve the density ratio of the model. By modifying the fluid–fluid interaction force scheme, we achieve thermodynamic consistency and independent adjustment of the surface tension. We also implement the modeling of CAH by applying geometric wetting boundaries with a hysteresis window. Based on this model, we first simulated pinned droplets in inclined channels with different hysteresis windows. We obtain the critical tilt angle of the droplet at the onset of sliding, which agrees with the theoretical result. For sliding droplets in the inclined channel, our results reveal that a slight tilt angle is unfavorable for the upstream portion of the droplet sliding, while a large tilt angle is favorable for the entire droplet sliding. A small receding angle results in a large droplet deformation at the quasi-steady state. Finally, by periodically transitioning between different hysteresis windows, enabling exclusive sliding of the upstream contact line during the first half period and subsequent sliding of the downstream contact line during the second half period, we successfully observed the stick-slip phenomenon of the droplet. [ABSTRACT FROM AUTHOR]

Mixtures containing isobutane, carbon dioxide, and/or hydrogen are found in various industrial processes, green refrigerant systems, and the growing hydrogen industry. Understanding the thermophysical properties of these mixtures is essential for these processes, and depends on reliable experimental data. Making use of an automated static-analytical apparatus, measurements were made of the phase behavior of binary mixtures of isobutane with CO2 and with H2, extending the range of available data for both mixtures. Measurements of the system isobutane + CO2 were carried out along three isotherms at temperatures of (240, 280, and 310) K with pressures from the lower limit of the sampling system (~ 0.5 MPa) to the mixture critical pressure. The results exhibit good agreement with literature data. Measurements on isobutane + H2 were carried out along nine isotherms at temperatures of (190, 240, 280, 311, 339, 363, 375, 390, and 400) K with pressures up to 20 MPa, covering a much broader range of conditions than the one prior investigation. The results have been used to optimize temperature-dependent binary parameters in the Peng–Robinson equation of state with two different mixing rules. This approach was found to perform well in comparison to alternative models. [ABSTRACT FROM AUTHOR]

The phase equilibrium of the propane–butane–sulfur system is studied using a high-pressure optical cell in the temperature range 403–443 K and pressure from 5.3 to 24.5 MPa, and the phase behavior is found to be of type V. The solubility of sulfur in a supercritical propane–butane mixture is estimated from the characteristics of the vapor branch of the phase equilibrium of the propane–butane–sulfur system and described by the Peng–Robinson equation of state in combination with the Mukhopadhyay–Rao mixing rule. It is determined that the propane–butane mixture in the supercritical fluid (SCF) state not only has good extraction properties but also allows us to desulfurize commercial hydrocarbons. For example, reducing the pressure from 25 to 7 MPa makes it possible to decrease the sulfur content in the product by 50% in the 413 K isotherm and by a factor of 10 in the 443 K isotherm. [ABSTRACT FROM AUTHOR]

Type II phase behavior is determined in the study of the phase equilibrium of the decalin–carbon dioxide binary system in the 313 and 333 K isotherms in the pressure range of 2–15 MPa using a high-pressure optical cell. The experimental results are described using the Peng–Robinson equation of state. [ABSTRACT FROM AUTHOR]

An improved pseudopotential lattice–Boltzmann model was proposed for simulating multiphase flow dynamics to describe fuel droplets, and its thermodynamic consistency was tested against the Peng–Robinson equation of state. The studied liquid fuels included paraffinic hydrocarbons with a different number of carbon atoms (C 1 –C 10), methanol (CH 3 OH), hydrogen (H 2), ammonia (NH 3), and water (H 2 O). To improve accuracy and reduce the magnitude of the spurious currents, the multi-relaxation times collision operator was implemented and the forcing term was computed using the hybrid pseudopotential interaction force with an eighth-order isotropic degree. The pseudopotential lattice–Boltzmann model accurately predicted the equilibrium densities and captured satisfactorily the thermodynamic vapor-liquid coexistence curve given by the analytical solution of the Peng–Robinson equation of state for acentric factors ranging from − 0.22 to 0.56, keeping the maximum average error for the liquid and vapor branches below 0.8% and 3.7%, respectively. Nevertheless, Peng–Robinson was found to be insufficiently accurate to replicate the actual thermodynamic state, especially for H 2 O and CH 3 OH, for which the results strongly deviated from the experimental vapor-liquid equilibrium densities and reached average errors for the vapor phase of nearly 28%. Furthermore, the surface tension (γ) was retrieved using the multiphase pseudopotential lattice–Boltzmann results and served to verify the thermodynamic consistency of the pseudopotential lattice–Boltzmann with respect to the parachor model. Lastly, the pseudopotential lattice–Boltzmann model was also shown to predict accurately the transient behavior of oscillating droplets. Overall, the enhanced model satisfactorily predicted the properties and behavior of the substances for a wide range of conditions. [ABSTRACT FROM AUTHOR]

Many difficulties and challenges have been encountered during the exploration and development of shale gas, among which high flexibility of the reservoir structure and low permeability have been the most notable problems that have restricted the efficient development of shale gas. In this paper, we have developed a fractal apparent permeability model for shale based on fractal theory that has taken into account the confinement effects. Also considering the effect of pore deformation on porosity, the defining equation of pore size under the combined effect of multiple factors is obtained, which, in turn, leads to the defining equation of dynamic fractal dimension. Due to the significant confinement effect due to the development of nanopores in shale reservoirs, the Peng–Robinson equation of state is modified using the adsorption effect, and the influence of the confinement effect on the critical properties and each permeability parameter is considered. Based on this, a shale fractal apparent permeability model coupled with slip flow, Knudsen diffusion, and surface diffusion was developed, and the model was validated with experimental data. The results revealed that the developed model was in relatively better agreement with the measured data. Furthermore, the confinement effect performed a positive role in shale's apparent permeability, with the calculated values of model permeability that considered the confinement effect was greater than the calculated values of model permeability, without the confinement effects being considered. [ABSTRACT FROM AUTHOR]

Pure components exhibit different phase behavior and critical properties shift when confined, primarily due to increased molecules-pore wall interactions. While extensive research has focused on modeling this behavior for pure components, there is a need to extend these models to hydrocarbon gas mixtures in tight and shale reservoirs to understand the deviation of gas properties from bulk behavior. The study utilizes the Peng–Robinson equation of state to calculate gas properties, considering the shift in critical properties of pure components due to confinement in EOS parameter calculations. Trend analysis investigates the effect of pore size reduction on gas properties, introducing the concepts of the confinement impact factor and specific pore radius. Correlation analysis explores the relationships between variables. Nonlinear regression analysis leads to the development of a new correlation that accounts for confinement effects on gas properties. The findings reveal that the deviation from bulk properties depends on the pore radius, pressure, temperature, and gas composition. The magnitude of deviation ranges from negligible to exceeding 15% under specific conditions of high pressure, low temperature, small pore radius, and rich gas composition. Gas viscosity experiences the most significant alteration, followed by density, while the gas compressibility factor also displays a noticeable impact. The isothermal gas compressibility coefficient demonstrates minimal to no response to confinement. Decreasing pore radius increases the gas compressibility factor, while gas viscosity and density decrease. The obtained results are crucial for shale and tight reservoir engineering calculations, particularly in adjusting gas properties in reservoir simulation and production modeling software. [ABSTRACT FROM AUTHOR]

In this study, a new method for the LNG has been proposed based on the SMR process. In the proposed process, an ORC is added to the conventional SMR process and the BOG is used as a coolant in the main heat exchanger. ASPEN HYSYS software utilizing the Peng–Robinson equation of state is used to simulate the SMR and SMR-ORC. The specific energy consumption, total exergy efficiency, and carbon dioxide emissions of the proposed method are compared with the conventional SMR process. Finally, an economic evaluation was performed on both processes. The simulation results showed that in the conventional process the total exergy efficiency and specific energy consumption are 34% and 647 kWh ton , respectively, while in the proposed process the total exergy efficiency has reached 39% and the energy consumption is reduced to 472 kWh ton . Also, the environmental assessment of carbon dioxide emissions from the production of electrical energy required by pumps and compressors showed that the proposed process has 28.51% less carbon dioxide emissions than the conventional SMR method. [ABSTRACT FROM AUTHOR]

Critical temperature, critical pressure and P–T–ρ–X data of acetone–water solutions with water mole fractions in a range of 0–60% were measured to provide fundamental data for CFD simulations. Critical temperatures were determined via observing critical opalescence in fused quartz capillary tubes. Meanwhile, critical pressures were measured by heating acetone–water solutions to its critical temperature in an autoclave. The standard deviations of critical temperature and critical pressure were 0.55 K and 0.029 MPa, respectively. The results indicate that only one phase exists during mixing of acetone with water. Moreover, P–T–ρ–X data under 15 and 20 MPa in the temperature range of 460–550 K were measured in the autoclave. The relative deviation of density was 0.32%. Volume-translated Peng-Robinson and Soave–Redlich–Kwong state equations were used to illustrate the P–V–T–X relationship of acetone–water solutions, and the Peng–Robinson state equation with an average absolute relative deviation of 1.19% between fitting and experimental densities was found more accurate. [ABSTRACT FROM AUTHOR]

The influence of a capillary pressure jump in a porous medium on the equilibrium between its liquid and gas phases, defined by the Peng–Robinson equation of state, was investigated. A numerical analysis of the phase diagrams of a gas–condensate mixture, constructed in gas-pressure and liquid-pressure coordinates for different capillary pressure jumps in the mixture, has been performed. The boundary of the two-phase region of such a mixture was determined as a domain of its existence in the two-phase state. The calculations were not associated with a concrete porous medium, and they were based on the condition of phase equilibrium of such a medium at different capillary pressure jumps in it. [ABSTRACT FROM AUTHOR]

The concentration of ethylene and 1-butene in n-hexane as polymerization media was calculated at five different pressure levels (4, 6, 8, 10, and 12 bar) and four different 1-butene concentrations (0.13, 0.26, 0.39, and 0.52 mol/L) in n-hexane at T= 80°C using the Peng-Robinson thermodynamic equation of state. Some combinations of conditions were selected to perform the copolymerization reaction in the presence of an industrial TiCl4/MgCl2 Ziegler-Natta catalyst. The forms of the synthesized products were visually and qualitatively classified as either powder or sticky. The percentage of incorporated 1-butene comonomer into the polyethylene chains was analyzed using calibrated FTIR tests. It was shown that for ethylene/1-butene concentration ratios (ß) in n-hexane above approximately 1.80, the product forms as a powder. For values below 1.30 threshold, the product was sticky. Thus, this ratio could be used as a criterion for selecting the proper combination of copolymerization pressure and 1-butene concentration when aiming to achieve a powdered form of the product. It was shown that ß has a strong correlation with the weight percentage of 1-butene in the final LLDPE polymer. Therefore it can be used as an accurate prediction for wt.% of incorporated 1-butene into the LLDPE chain within the studied concentration ranges with the specific catalyst system utilized. [ABSTRACT FROM AUTHOR]

Among the essential thermodynamic parameters of behavior, analysis (PVT) in natural gas engineering is the gas compressibility factor (Z). In this work, we improve the results of the compressibility factor (Z) prediction accurately after modifying the cubic equation coefficients for different gas types; the cubic equation of state (EOS) prediction model was tested using 149 experimental data under different conditions. In this study, the gas compressibility factor is calculated by Peng Robinson's equation of state (PR EOS). Additionally, the coefficients were updated to reflect a better representation of natural gas. The results are compared to the predictions of the original PR EOS and other equations of state in the literature. The statistical analysis shows an average absolute deviation percentage (AAD %) of 0,99% and a coefficient of determination (R²) of 0,9968 at pressure and temperature up to 16632,93 PSI (114,68 MPa) and 426,74K, respectively. The proposed model can effectively calculate (Z) for any type of gas, including condensate gas. [ABSTRACT FROM AUTHOR]

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Reduction in energy consumption of industrial plants is always an essential need due to high cost, CO 2 emissions and global warming caused by energy supply from fossil fuels for boilers and electricity consumers. Iran has been struggling to compensate the lack of gas supply for domestic and industrial demands in winter within the past decade despite of having large natural gas resources. One of the most economical methods to decrease energy requirements in hydrocarbon plants is process improvement and revamping by changing existing solvents. There are already 44 identical acid gas removal units under operation in the South Pars Gas Complex (located in Iran) with the same feed composition. The gas-sweetening unit in the Phase 12, operating with the solution of 45.5 wt% methyldiethanolamine (MDEA), was modeled by Aspen Plus for acid gas removal (CO 2 and H 2 S) as a rate-based model with the application of electrolyte non–random two–liquid (E-NRTL) activity model and Peng–Robinson equation of state in addition to the actual characteristics of the absorber and regenerator, and the operational conditions of the gas and liquid streams. After validation of the model by the real data from the plant, the incumbent amine solution was replaced with five proposed amine solutions – one single and four blended amine mixtures – in the same mass concentration to select the most efficient alternative from the aspects of outlet acid gas concentration, H 2 S content in the treated flash gas, required total power, reboiler power supply, and regeneration heat duty. The simulation results revealed that H 2 S was sharply absorbed on the top of the column, while CO 2 was smoothly removed from the gas phase to the MDEA and blended solutions along the absorber and it occurred at the bottom of the column for the DEA solution. The blended amine solution of 1.5 wt% sulfolane + 44 wt% MDEA (Sulfinol-M) has shown to be the most appropriate option instead of the solution of MDEA compared to other suggested absorbents, with several advantages such as higher selectivity of H 2 S over CO 2 , low temperature bulge, highest H 2 S loading, and outlet sweet gas flow rate while required total power, reboiler power supply, and regeneration heat duty were reduced by 21.19%, 21.26%, and 23.54% respectively. The operational conditions of the unit with the application of the Sulfinol-M solution were optimized to achieve three specifications (constraints) and the minimum required total power (objective function) through a sensitivity analysis and optimization using a genetic algorithm to assure the reliability of values for three independent parameters, namely, amine solution temperature, amine solution flow rate, and gas temperature. The optimum limits and values of these parameters were 47–50 °C, 220 – 240 ton/h, and 34 °C respectively. [ABSTRACT FROM AUTHOR]

Prediction of critical point is of great interest for CO:based binary mixlure being the working fluid of power cycle. Compared with empirical correlation. the critical point of mixture can be calculated based on its rigorous thermodynamic criteria. with limited binary interaction parameters and consistency on vapor-liquid equilibrium and other thermodynatnic properties. In this study. the critical points of CO:based binary mixture. applicable for being working fluid of power cycle. including hydrocarbons. fluorocarbons. diniethyl ether, methanol, water and xenon, were studied ba;ed on the Peng-Robinson equation of state (PR EOS) with van der Waals (vdW) mixing rule, according to the Heidemann-Khalil approach. By comparing the predicted results with the experimentai data in the literature, the applicability of this method to various mixtures is discussed. The characteristics of critical lines, type of phase diagram, and binary interaction parameters of each mixture were analyzed and discusxed, and the results show that the Heidemann-Khalil approach is efficient fur critical point calculation and prediction of COi-based hillary mixture. [ABSTRACT FROM AUTHOR]

Accurate phase equilibrium data for mixtures of eco-friendly but mildly-flammable refrigerants with inert components like CO2 will help the refrigeration industry safely employ working fluids with 80 % less global warming potential than those of many widely-used refrigerants. In this work, a visual high-pressure measurement setup was used to measure solid–fluid equilibrium (SFE) of HFC-32 + CO2 binary systems at temperatures between (132 and 217) K. The experimental data show a eutectic composition of around 11 mol % CO2 with a eutectic temperature of 131.9 K at solid–liquid–vapour (SLVE) condition. Measured SLVE and solid–liquid equilibrium data were used to tune a thermodynamic model implemented in the ThermoFAST software package by adjusting the binary interaction parameter (BIP) in the Peng–Robinson equation of state. The tuned model represents the measured melting points for binary mixtures with a root mean square deviation (RMSD) of 3.2 K, which is 60 % less than achieved with the default BIP. An RMSD of 0.5 K was obtained using the tuned model for the mixtures with CO2 fractions over 28 mol % relative to an RMSD of 3.4 K obtained with the default model. The new property data and improved model presented in this work will help avoid solid deposition risk in cryogenic applications of the HFC-32 + CO2 binary system and promote wider applications of more environmentally-friendly refrigerant mixtures. [ABSTRACT FROM AUTHOR]

Nilotinib hydrochloride monohydrate (NHM) is an anti-cancer drug whose solubility was statically determined in supercritical carbon dioxide (SC-CO2) for the first time at various temperatures (308–338 K) and pressures (120–270 bar). The mole fraction of the drug dissolved in SC-CO2 ranged from 0.1 × 10–5 to 0.59 × 10–5, corresponding to the solubility range of 0.016–0.094 g/L. Four sets of models were employed to evaluate the correlation of experimental data; (1) ten empirical and semi-empirical models with three to six adjustable parameters, such as Chrastil, Bartle, Sparks, Sodeifian, Mendez-Santiago and Teja (MST), Bian, Jouyban, Garlapati-Madras, Gordillo, and Jafari-Nejad; (2) Peng-Robinson equation of state (Van der Waals mixing rule, had an AARD% of 10.73); (3) expanded liquid theory (modified Wilson model, on average, the AARD of this model was 11.28%); and (4) machine learning (ML) algorithms (random forest, decision trees, multilayer perceptron, and deep neural network with respective R2 values of 0.9933, 0.9799, 0.9724 and 0.9701). All the models showed an acceptable agreement with the experimental data, among them, the Bian model exhibited excellent performance with an AARD% of 8.11. Finally, the vaporization (73.49 kJ/mol) and solvation (− 21.14 kJ/mol) enthalpies were also calculated for the first time. [ABSTRACT FROM AUTHOR]

Nilotinib hydrochloride monohydrate (NHM) is an anti-cancer drug whose solubility was statically determined in supercritical carbon dioxide (SC-CO2) for the first time at various temperatures (308–338 K) and pressures (120–270 bar). The mole fraction of the drug dissolved in SC-CO2 ranged from 0.1 × 10–5 to 0.59 × 10–5, corresponding to the solubility range of 0.016–0.094 g/L. Four sets of models were employed to evaluate the correlation of experimental data; (1) ten empirical and semi-empirical models with three to six adjustable parameters, such as Chrastil, Bartle, Sparks, Sodeifian, Mendez-Santiago and Teja (MST), Bian, Jouyban, Garlapati-Madras, Gordillo, and Jafari-Nejad; (2) Peng-Robinson equation of state (Van der Waals mixing rule, had an AARD% of 10.73); (3) expanded liquid theory (modified Wilson model, on average, the AARD of this model was 11.28%); and (4) machine learning (ML) algorithms (random forest, decision trees, multilayer perceptron, and deep neural network with respective R2 values of 0.9933, 0.9799, 0.9724 and 0.9701). All the models showed an acceptable agreement with the experimental data, among them, the Bian model exhibited excellent performance with an AARD% of 8.11. Finally, the vaporization (73.49 kJ/mol) and solvation (− 21.14 kJ/mol) enthalpies were also calculated for the first time. [ABSTRACT FROM AUTHOR]

This paper proposes simulation protocols in terms of an auto-calibration strategy for the parameterisation of Gibbs ensemble Monte Carlo simulations for Lennard–Jones fluids. The proposed simulation protocols have been deduced from various approaches proposed in literature and have been tested against pure LJ fluids and their mixtures. These simulation protocols are intended to reduce or avoid time-consuming pre-simulations by adjusting the trial move limits, the number of attempted transfers, or the probability of attempted transfer during the equilibration phase, and can serve as a starting point for simulating more complex molecules, beyond LJ-fluids. This new approach aims to adjust simulation parameters to ensure a sufficient amount of successful trial moves as suggested in literature. It is similar to a previously proposed trial move adjustment and can easily be implemented in existing simulation code. Abbreviations: BWR EoS: Benedict–Webb–Rubin equation of state; CBMC: Configurational-bias Monte Carlo; EoS: Equation of state; GEMC: Gibbs ensemble Monte Carlo; LJ: Lennard–Jones; M1; M2; M3: Abbreviations for the three simulated mixtures; MC: Monte Carlo; PAT: Probability of attempted transfer; TL: Translation within a box (GEMC move); TR: Transfer to the other box (GEMC move); t-PR EoS: Volume-translated Peng-Robinson equation of state [ABSTRACT FROM AUTHOR]

Studies of phase transition kinetics are important for such supercritical processes as supercritical drying, adsorption, micronization, etc. In supercritical technologies, "organic solvent—CO2" systems are often formed, the properties of which strongly depend on the system parameters. In this article, the kinetic curves of phase transitions in the "2-propanol—CO2" system were investigated experimentally and theoretically. Experimental studies were carried out in a 250 mL high-pressure apparatus at temperatures of 313 and 333 K and pressures of 6.3 and 7.8 MPa with and without the addition of alginate porous gel. Theoretical studies were carried out using the mass transfer equation, the Peng-Robinson equation of state, and the Van der Waals mixing rules, with Python being used for the calculations. The mass transfer coefficients and equilibrium concentrations of CO2 in the liquid phase were determined using the BFGS optimization method. [ABSTRACT FROM AUTHOR]

The cavitation dynamics of an air-vapor mixture bubble with ultrasonic excitation can be greatly affected by the equation of state (EOS) for the interior gases. To simulate the cavitation dynamics, the Gilmore-Akulichev equation was coupled with the Peng–Robinson (PR) EOS or the Van der Waals (vdW) EOS. In this study, the thermodynamic properties of air and water vapor predicted by the PR and vdW EOS were first compared, and the results showed that the PR EOS gives a more accurate estimation of the gases within the bubble due to the less deviation from the experimental values. Moreover, the acoustic cavitation characteristics predicted by the Gilmore-PR model were compared to the Gilmore-vdW model, including the bubble collapse strength, the temperature, pressure and number of water molecules within the bubble. The results indicated that a stronger bubble collapse was predicted by the Gilmore-PR model rather than the Gilmore-vdW model, with higher temperature and pressure, as well as more water molecules within the collapsing bubble. More importantly, it was found that the differences between both models increase at higher ultrasound amplitudes or lower ultrasound frequencies while decreasing as the initial bubble radius and the liquid parameters (e.g., surface tension, viscosity and temperature of the surrounding liquid) increase. This study might offer important insights into the effects of the EOS for interior gases on the cavitation bubble dynamics and the resultant acoustic cavitation-associated effects, contributing to further optimization of its applications in sonochemistry and biomedicine.

The increasingly serious global warming problem has accelerated the elimination of traditional hydrofluorocarbon (HFC) refrigerants. R1234ze(E) + R290 binary mixture as a potential alternative refrigerant are expected to overcome the deficiencies of R1234ze(E) (low volumetric refrigeration capacity) and R290 (flammability and explosiveness). In this paper, the 38 density and 119 isochoric specific heat capacity data of R1234ze(E)+R290 mixtures were measured at temperatures from (285.45 to 349.71) K using an adiabatic batch calorimeter with intermittent heating. Uncertainties of temperature, pressure, density and isochoric heat capacity were estimated to be less than 12 mK, 5 kPa, 0.30% and 1.0%. The density data were correlated using the Tait equation, and good regression results were obtained, with the AARD of 0.19% and MARD of 0.83%. A comparison was conducted between the Tait equation and REFPROP 10 and Peng-Robinson equation of state (PR EoS), the Tait equation gives the best prediction performance. In addition, the isochoric specific heat capacity data were compared with the values calculated by four models (PR model, Zhong model, Sheng model and REFPROP 10). Among them, the three models, the Zhong model, Sheng model and REFPROP 10, give the same prediction performance, with AARD of 2.88%, 2.47% and 2.51%, respectively. But for the PR model, the density data has a significant impact on the result, especially for the low-temperature region. When the density data were calculated by the Tait equation, the PR model presents the best prediction performance for the heat capacity of R1234ze(E) + R290 mixtures with the AARD of 2.00%, nevertheless, when the density data were calculated from the PR EoS, the PR model showed a large deviation in the prediction of isochoric heat capacity with the AARD and MARD of 3.74% and 11.11%. An empirical equation was correlated to represent the experimental heat capacity data with the MARD of 3.07% and the AARD of 1.15%. [ABSTRACT FROM AUTHOR]

Process monitoring and forecasting are essential to ensure the efficiency of industrial processes. Although it is possible to model processes using phenomenological approaches, these are not always easy to apply and generalize due to the complexity of the processes and the high number of unknown parameters. This work aims to present a hybrid modeling architecture that combines a phenomenological model with machine learning models. The proposal is to enable the use of simplified phenomenological models to explain the basic principles behind a phenomenon. Next, the data-oriented model corrects deviations from the simplified model predictions. The research hypothesis consists of showing the benefits of integrating prior knowledge of chemical engineering in simplifying data-based models, enhancing their generalization and improving their interpretability. The gasification process of lignin biomass with supercritical water was used as a case study for this methodology and the variable to be observed was the production of hydrogen. The real experimental data of this process were augmented using Gibbs energy minimization with the Peng–Robinson equation of state, thus generating a more voluminous database that was considered as real process data. The ideal gas model was used as a simplified model, producing significant deviations in predictions (relative deviations greater than 20%). Deviations (∆H2 = H 2 r e a l − H 2 p r e d i c t ) were used as the target variable for the machine learning model. Linear regression models (LASSO and simple linear regression) were used to predict ∆H2 and this variable was added to the simplified forecast model. This consisted of the hybrid prediction of the resulting hydrogen formation ( H 2 p r e d i c t ). Among the verified models, the simple linear regression adjusted better to the values of ∆H2 (R2 = 0.985) and MAE smaller than 0.1. Thus, the proposed hybrid architecture allowed for the prediction of the formation of hydrogen during the gasification process of lignin biomass, despite the thermodynamic limitations of the ideal gas model. Hybridization proved to be robust as a process monitoring tool, providing the abstraction of non-idealities of industrial processes through simple, data-oriented models, without losing predictive power. The objective of the work was fulfilled, presenting a new possibility for the monitoring of real industrial processes. [ABSTRACT FROM AUTHOR]

Phase equilibrium data (p , T , y ) for the binary systems of carbon dioxide + dimethyl carbonate and carbon dioxide + ethyl methyl carbonate were obtained. All systems were measured for isotherms ranging from 298.2 K to 328.2 K with pressure ranging between 0.13 MPa and 10.6 MPa. A static equilibrium technique was established with samples quantified using an offline method. The results were modeled using the Peng–Robinson equation of state with van der Waals one-fluid mixing rules. [ABSTRACT FROM AUTHOR]

R-1132a is increasingly being considered as a low global warming potential component in alternative mixtures to R-23 in specialized low temperature and ultra-low temperature refrigeration systems. Though the thermodynamic properties of R-1132a were investigated in several studies up to 2018, reinvestigations have been carried out in recent years. In order to contribute toward these renewed measurements, the critical parameters of R-1132a were experimentally re-determined. Thirty-two vapor pressures from 240 K to the critical temperature, fifteen saturated vapor and six saturated liquid densities above 254 K and the PvT properties in both the vapor phase (98 points) and liquid phase (34 points) from densities of 50 kg·m−3 to 760 kg·m−3 were also measured. Specific correlations for each of these properties were optimized and compared to previously available data from the literature. Additionally, the Peng–Robinson equation of state was used to represent the aforementioned properties and further utilized to determine the enthalpy and entropy of R-1132a. [ABSTRACT FROM AUTHOR]

Gas injection can increase oil recovery because the gas–oil interfacial tension is less than the water–oil interfacial tension (IFT) and tends to zero in the miscibility state. However, little information has been provided on the gas–oil movement and penetration mechanisms in the fracture system at the porosity scale. The IFT of oil and gas in the porous medium changes and can control oil recovery. In this study, the IFT and the minimum miscibility pressure (MMP) are calculated using the cubic Peng-Robinson equation of state that has been modified using the mean pore radius and capillary pressure. The calculated IFT and MMP change with the pore radius and capillary pressure. To investigate the effect of a porous medium on the IFT during the injection of CH4, CO2, and N2 in the presence of n-alkanes and for validation, measured experimental values in references have been used. According to the results of this paper, changes in IFT vary in terms of pressure in the presence of different gases and, the proposed model has good accuracy for measuring the IFT and the MMP during the injection of hydrocarbon gases and CO2. In addition, as the average radius of the pores gets smaller, the interfacial tension tends to lower values. This effect is different with increasing the mean size of interstice in two different intervals. In the first interval, i.e. the Rp from 10 to 5000 nm, the IFT changes from 3 to 10.78 mN/m and in the second interval, i.e. the Rp from 5000 nm to infinity, the IFT changes from 10.78 to 10.85 mN/m. In other words, increasing the diameter of the porous medium to a certain threshold (i.e. 5000 nm) increases the IFT. As a rule, changes in IFT affected by exposure to a porous medium affect the values of the MMP. In general, IFT decreases in very fine porous media, causing miscibility at lower pressures. [ABSTRACT FROM AUTHOR]

CO2 flooding is recognized as an efficient method for enhancing shale oil recovery, while CO2-oil MMP (minimum miscibility pressure) in the micro-nanoscale is a crucial parameter. This paper presents a method for calculating the MMPs of pure hydrocarbons (C4H10, C6H14, C8H18, and C10H22) and CO2 systems in nanopores (3 nm to 10 nm) with temperature ranging from 290.15 K to 373.15 K. Firstly, we modify the Peng-Robinson equation of state (PR-EOS) by considering the influence of confinement effect and capillary pressure in nanopores. Secondly, the flash calculation algorithm is employed to determine whether the oil and gas phases in nanopores have reached an equilibrium state according to the equality of the fugacity of the two phases. Thirdly, we calculate the interfacial tension (IFT) between the two phases using the Macleod-Sugden equation. When the extrapolated IFT is zero, we treat the corresponding pressure as the MMP of the CO2-oil system in nanopores. Simulation results indicate that the calculated MMP using this method has a relative error of about 0.62% compared to the MMP calculated using the multiple mixing cell (MMC) method, indicating high reliability for MMP prediction. Moreover, the measured MMP at the nanoscale is generally smaller than that in the bulk phase due to the influence of the confinement effect. The MMP is positively correlated with the reservoir temperature, the carbon atom number in alkanes, and the nanopore radius. [ABSTRACT FROM AUTHOR]

Thermodynamic models have been developed for isobaric and isothermal ternary system acetone-ethanol-hexane vapor liquid equilibria (VLE) data. The boiling point, melting point, and heat capacity of the system were estimated through Group Contribution Methods (GCMs) and the application of summability relations. The Peng-Robinson Equation of State (PREOS), Redlich Kwong (RKEOS), and Soave-Redlich Kwong (SRKEOS) were utilized in the calculations of fugacity and fugacity coefficients of the components in the system. The Non-Random Two-Liquid (NRTL), Wilson, Universal Quasi-Chemical (UNIQUAC), and UNIQUAC Functional-Group Activity Coefficients (UNIFAC) models were used in predicting the activity coefficients and in the determination of the bubble point and dew point pressures and temperatures. All the models used in comparing the experimental and calculated activity coefficients appeared to be satisfactory and in good agreement for all the data but among these models UNIFAC and Wilson models exhibited the best fit for 42 total data points based on the regression analyses used namely R2, adjusted R2, SSE, and RMSE. The UNIFAC model also performed exceptionally well when it comes to calculating bubble point and dew point temperatures and pressures. A modified activity coefficient model (MACM) was also formulated and applied to various ternary systems where the results exhibited comparable results to the existing models. [ABSTRACT FROM AUTHOR]

The use of the group contribution concept in the design of refrigerants for a single effect absorption refrigeration machine is presented. Chosen functional groups were combined according to the known chemistry rules to generate refrigerant candidates. The prediction of vapor-liquid phase equilibria data using the UNIFAC (Universal Functional Activity Coefficient) model and the Peng-Robinson equation of state and the resolution of heat and mass balances over different compartments led to the coefficient of performance (COP). An exergy analysis was carried out in order to assess the performance of the machine by calculating the exergy efficiency, the second law efficiency and the exergy destruction ratio. The design strategy was tested with chosen groups such as Fluor (F) and Methyl (CH3), Carbon (C), Methine (CH) and Methylene (CH2) and with N, N Dimethylformamide (DMF) as the absorbent. The results showed Interesting refrigerant-absorbent pairs with reasonably high COP values. [ABSTRACT FROM AUTHOR]

Two eminent molecular type composition methods (paraffins, naphthenes, and aromatics [PNA] and saturates, aromatics, and polynuclear aromatics [SAP]) are employed to construct new characterization procedures for predicting the phase behaviour of petroleum fluids using a modified Peng–Robinson equation of state. The PNA and SAP methods divide a petroleum fraction into (PNA) and (SAP) homologous groups, respectively. Two generalized models are developed to predict the physical properties (Mw,SG,Tb) and equation of state (EOS) parameters (Tc,Pc,ω) for both PNA and SAP sub‐fractions. Each generalized model covers 18 different correlations in a single mathematical form that enables the model to return 18 outputs for PNA and SAP sub‐fraction parameters. A new lumping method is also developed to convert triple PNA or SAP pseudo‐components into single characterized fractions. Accordingly, seven different characterization procedures are introduced and compared with one another. The first two procedures are completely constructed based on the proposed models, and the other procedures encompass the models already developed. The results obtained from the simulation of the differential liberation test for 12 diverse reservoir fluids and bubble pressure prediction for 40 oil samples revealed that the first two methods (1 and 2) could enhance the abilities of the traditional characterization procedures for reservoir fluid modelling. The mean value of average absolute relative deviations (AARDs) over a total of 52 oil samples is about 6.5% for the proposed methods and is about 13.2% for the best previously existing methods. Moreover, an efficient workflow is provided for the parameter tuning process, which is notably capable of reducing the level of prediction errors using only three adjustable parameters. [ABSTRACT FROM AUTHOR]

Surface tension is one of the most important thermodynamic properties of the working fluids for the design of heat pumps, refrigerators and air conditioners. The Linear Gradient Theory have been widely used for the prediction of surface tension. Based on this theory and combining with the Peng-Robinson Equation of State, a novel model for surface tension calculation is proposed in this work. In this model, new correlation of pure substance influence parameter (PSIP) with temperature and correlation of binary interaction parameters for influence parameter (BIPc) with temperature and with composition, alongside with the adjustment method for these two parameters are proposed in order to optimize the model. The PSIPs of several common refrigerants and the BIPc of several binary mixtures are adjusted, while the new predictions with these adjusted parameters are done. Results with the adjusted parameters show a great consistency with the experimental data and a great improvement compare to the result obtained with the unadjusted parameters. The adjusted parameters can also be used to predict other mixtures with the same components but with different compositions. [ABSTRACT FROM AUTHOR]

The extreme conditions at the surface of Venus pose a challenge for monitoring the planet's seismic activity using long-duration landed probes. One alternative is using balloon-based sensors to detect venusquakes from the atmosphere. This study aims to assess the efficiency with which seismic motion is coupled as atmospheric acoustic waves across Venus's surface. It is, therefore, restricted to the immediate neighborhood of the crust-atmosphere interface. In order to account for supercritical conditions near the surface, the Peng-Robinson equation of state is used to obtain the acoustic sound speed and attenuation coefficient in the lower atmosphere. The energy transported across the surface from deep and shallow sources is shown to be a few orders of magnitude larger than on Earth, pointing to a better seismo-acoustic coupling. For a more realistic scenario, simulations were made of the acoustic field generated in the lower atmosphere by the ground motion arising from a vertical array of subsurface point-force sources. The resulting transmission loss maps show a strong epicentral cone accompanied by contributions from leaky surface waves. Results at 0.1 Hz and 1 Hz confirm that the width of the epicentral cone is larger at lower frequencies. [ABSTRACT FROM AUTHOR]

The article focuses on inferential models using vapor-liquid equilibrium equations of state, which can be used to create models for estimating real-time operating conditions in a system. It mentions the examples of inferential models and explains how these models can provide useful information about the state of the operating plant.

The thermodynamic behaviors of the two-phase systems of 3,5,5-trimethylhexyl acrylate (355-TMHA) and 3,3,5-trimethylcyclohexyl methacrylate (335-TMCHMA) in high-pressure CO2 are reported. The thermodynamic data were determined with the aid of a synthetic approach at temperature (T) = (313.2–393.2 K) and pressure (p) = (3.84–20.80 MPa). The acquired findings revealed that the miscibility of CO2 was observed to raise monotonically and the augmented of model Ts and mole fraction of (355-TMHA and 335-TMCHMA) in two-component (solvent + solute) mixtures. The miscibility curves of 355-TMHA and 335-TMCHMA in the 355-TMHA + Sc-CO2 and 335-TMCHMA + Sc-CO2 systems increased with the temperature at a fixed pressure. The 355-TMHA + Sc-CO2 and 335-TMCHMA + Sc-CO2 systems exhibited type-I phase behavior. Besides, the lab-based investigational solubility was adequately compared with the value obtained using the Peng–Robinson equation of state (P–R E–S). Both the model mixtures (355-TMHA + Sc-CO2 and 335-TMCHMA + Sc-CO2) did not reveal 3 phases (liquid + vapor + liquid) at any of the five analyzed temperatures. The P–R E–S comparatively provided the phase behavior (PB) of the (355-TMHA + Sc-CO2 and 335-TMCHMA + Sc-CO2) models utilizing two T-independent mixture interaction factors. The mixture critical curves (MCC) obtained using the computational data and lab-based results had a relatively good match when the two adjustable factors of the P–R E–S were applied. The root means square deviation (RMSD) percentage (%) for the 355-TMHA + Sc-CO2 [κij = 0.040, ηij = −0.040] and 335-TMCHMA + Sc-CO2 [κij = 0.035, ηij = −0.040] systems ascertained at 353.2 K utilizing the two factors were 6.67% and 7.57%, correspondingly. Then, the RMSD (%) of the 335-TMCHMA + Sc-CO2 system predicted using the adjusted values at every temperature was noted as 4.56%. [ABSTRACT FROM AUTHOR]