A numerical procedure for the computation of a natural gas molar heat capacity, the isentropic exponent, and the Joule–Thomson coefficient has been derived using fundamental thermodynamic equations, ...DIPPR AIChE generic ideal heat capacity equations, and AGA-8 extended virial-type equations of state. The procedure is implemented using the Object-Oriented Programming (OOP) approach. The results calculated are compared with the corresponding measurement data. The flow-rate through the orifice plate with corner taps is simulated and the corresponding error due to adiabatic expansion is calculated. The results are graphically illustrated and discussed.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
We have employed Monte Carlo simulation in the isobaric–isothermal ensemble to determine thermodynamic derivative properties of naturally occurring hydrocarbon gas mixtures. Thermal expansivity, ...isothermal compressibility, heat capacity and Joule–Thomson coefficient have been obtained from a fluctuation method detailed in our previous work Phys. Chem. Chem. Phys. 3 (2001) 4333. We have investigated two natural gases using an original method to model hydrocarbon distribution in a representative way with a limited number of linear, branched and cyclic hydrocarbon molecules. The composition used in Monte Carlo simulations was represented by 500 molecules of 20 different types with up to 35 carbon atoms. The two condensate gases are composed of rigid and flexible molecules for which intermolecular potentials have been used without fitting any parameters. Predictions are in good agreement with respect to available molar volumes at high pressure. Joule–Thomson coefficients and the other thermodynamic derivative properties have been then predicted at pressures up to 110
MPa at reservoir temperature, showing a consistent behaviour compared with light hydrocarbon gases. Inversion pressure of the Joule–Thomson effect is obtained within 1.2% compared to experimental value from volumetric measurements.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
In this paper, we present an analytical procedure to evaluate the zero-pressure Joule–Thomson coefficient using the second virial coefficient over the Lennard-Jones (12-6) potential. The analytical ...expressions are derived for the first and second derivatives of the second virial coefficient. The proposed formulae guarantee the accurate and fast calculation of the Joule–Thomson coefficient. As an example of application, the analytical expression obtained is used to calculate results for the molecules
He
,
Xe
,
N
2
,
H
2
,
O
2
,
CO
,
C
2
H
4
,
C
3
H
8
and
C
5
H
12
. The results obtained by the present analytical expression are found to be in good agreement with the data in the literature. The calculation of results will help to estimate the Joule–Thomson coefficient with sufficient reliability and to determine the interaction potentials.
Natural Gas (NG) compressibility factor as important property at any NG industrial applications determined by utilizing an intelligent approach precisely. Three thermodynamic properties include ...pressure, temperature and Joule-Thomson (JT) coefficient are selected as input parameters. These properties are chosen due to the measurement capabilities of available sensors. Unlike the traditional approaches, the current approach does not require NG compositions as input. The current intelligent approach is developed based on an Artificial Neural Network (ANN) method. Real-time measurement capability and very low cost are two main advantages of the developed approach. Big data sets of NG thermodynamic properties are created considering 30,000 random compositions for training, testing and validating the ANN. The GERG-2008 is utilized (as the most recent equation of state) to calculate thermodynamic properties to train the ANN. Validation of the developed ANN method compared to experimental data shows the Average Absolute Percent Deviation (AAPD) is about 0.33%. To show the accuracy of the developed approach, four different NG compositions are selected as case studies. The compressibility factor and JT coefficient are computed for various pressure and temperature range using the traditional approach. Then, the compressibility factor is determined using the intelligent approach when only pressure, temperature and JT coefficient are known. The AAPD of NG compressibility factor calculations for various natural gases show 0.385% for pure methane, 0.45% for the Khangiran gas, 0.58% for the Kangan gas, 0.78% for the Pars gas and is 1.12% for the Bidboland gas. The comparing results show that overall AAPD is less than 0.7% that shows the high accuracy of the intelligent approach.
•An intelligent approach for determining the NG compressibility factor is developed.•The approach needs only pressure, temperature, and JT coefficient as input.•Artificial Neural Network (ANN) is employed to develop the approach.•The ANN is trained with the 30,000 random datasets of NG compositions.•The GERG-2008 is employed to determine NG properties and produces the dataset.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The predictive power of a set of molecular models, which have been adjusted to vapor–liquid equilibria only, is validated. For that purpose, Joule–Thomson inversion curves were determined by ...molecular simulation for 15 pure fluids, i.e. argon, methane, oxygen, nitrogen, carbon dioxide, ethylene, carbon monoxide, R11, R23, R41, R124, R125, R134a, R143a, R152a, and for air. Comparison of the simulation results with reference equations of state shows an excellent agreement.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The analytical expressions of the Joule–Thomson coefficient (JTC) for an imperfect Fermi gas and a Bose gas are derived by means of thermodynamic theory and “pseudopotential” method, respectively. It ...is discussed that the influence of the Joule–Thomson effect by repulsive interacting and attractive interacting. We find the following results: (1) For an ideal Fermi gas, the JTC is lower than zero owing to the equivalent repulsive potential arising from the quantum degeneracy at sufficiently low temperature; for repulsive interaction Fermi gases, the JTC is lower than zero at sufficiently low temperature; for attractive interaction Fermi gases, there is an inversion particle density at sufficiently low temperature, when the particle density is not only higher than the inversion density, but also lower than the boundary particle density of the criterion of the stability of the Fermi system, the JTC is higher than zero; when the particle density is lower than the inversion density, the JTC is lower than zero. (2) The JTC for an ideal Bose gas is the limit of the JTC of an imperfect Bose gas when
S wave scattering length is zero; for repulsive interaction Bose gases, there is an inversion particle density at certain temperature, when the particle density is lower (higher) than the inversion density, the JTC is positive (negative); for attractive interaction Bose gases, the JTC is always positive.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Models of mercury were constructed by molecular dynamics using the interparticle potential of the embedded atom model (EAM) at temperatures below 10 000 K and pressures below 2.5 GPa. The ...thermodynamic properties of the models were presented on the isobars of 0.5, 1.0, 1.5, 2.0, and 2.5 GPa. The compressibility factors
Z
=
pV
/(
RT
) were calculated; the coordinates of the inversion points of the Joule–Thomson coefficient below 5600 K were found from the positions of minima on the
Z
(
p
,
T
) isobars. At densities above 8–9 g/cm
3
, the results of simulation agreed well with experiment; at lower densities there were discrepancies associated with a loss of metal properties by real mercury. The behavior of the models was analyzed in the region of the van der Waals loop. The calculated critical temperature of mercury was found to be significantly overestimated relative to the experiment. Modeling the “meta-mercury” with the EAM potential with excluded embedded potential contribution gave better agreement with the equation of state of mercury at lower densities. The states with
Z
= 1 can be observed below 1.0 GPa. The calculated temperature of the inversion of the Joule–Thomson coefficient increased monotonically to 5600 K as the pressure increased to 2.5 GPa.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In this study, three equations of state (EOS) in conjunction with computational fluid dynamics (CFD) modeling were used to predict the Joule – Thomson (JT) process behavior for natural gas and ...various pure gases. The JT effect is encountered in several industrial applications. The experimental determination of the JT coefficient (JTC) is complicated, and there is little gas pressure-volume-temperature (PVT) data available for estimating these JTC. Thus, the development of an efficient model to predict the JT effect in industrial processes is necessary. This study was carried out to attain a clear view of the single phase-flow of hydrocarbons and nitrogen in the JT process with CFD modeling. The JT valve was modeled in a pipe so as to predict the JTC, inversion curve (IC) and the isenthalpic curve of nitrogen, methane, ethane, propane and their mixtures in a wide range of temperature and pressure. Generally, the low-temperature branch of IC was predicted accurately by most of EOSs. Among the considered EOSs, Soave-Redlich-Kwong (SRK) EOS is able to predict more accurately the Joule – Thomson inversion curve (JTIC) in comparison with the other EOS. The validation of this CFD modeling was conducted using the experimental data from the literature and the industrial data of natural gas from an Iranian Gas Dehydration unit. The outlet temperature obtained from the CFD model agreed well with the industrial data of the JT process. The proposed CFD model accurately predicts the experimental and the industrial data of the JT process.
•Derivation of new relations for calculation of JTC and JTIC using three cubic EOSs.•Development of the CFD model for prediction of JT process.•Comparing and selecting the most accurate equation of state for predicting of natural gas behaviors.•Investigating the behavior of gases in throttling process using developed model, in a wide range of temperature and pressure.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Densities (ρ) and speed of sound (SOS) of a synthetic natural gas (∼88 mol% methane) were determined simultaneously at temperatures between 323 and 415 K and pressure up to 58 MPa. Densities and ...speed of sound were measured using a high pressure and high temperature Vibrating Tube densitometer (VTD) and an in-house acoustic cell, respectively. Moreover, to extend the PρT measurements to a wider range of temperature, isochoric measurements were conducted in a temperature range of 210–270 K.
The AGA8-DC92, GERG-2008, SBWR and PR-78 equations of state (EoS) were used to evaluate the experimental data. Finally, the SBWR EoS was tuned on the experimentally measured density to determine other thermodynamic properties such as isobaric heat capacity (Cp), isochoric heat capacity (Cv) and Joule-Thomson coefficients (μJT).
Display omitted
•New experimental setup was designed to measure speed of sound for natural gas.•Density and speed of sound of natural gas were measured simultaneously.•The SBWR EoS was tuned on the experimentally measured density.•Derived calorific and thermal properties were calculated using tuned SBWR EoS.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
An experiment has been built to study heat transfer in forced flow of He II at flow velocities up to 22
m/s. The main part of this experiment is a 10
mm ID, 0.86
m long straight test section ...instrumented with a heater, thermometers and pressure transducers. The high flow velocities allow clear observation of the effects of the forced convection, counterflow heat transfer and the Joule–Thomson effect. A numerical model based on the He II energy conservation equation and including pressure effects has been developed to compare with the experimental results. The model works well for low flow velocities where the heat flux is primarily driven by the temperature gradient and for high flow velocities where the heat flux is primarily driven by the pressure gradients. In the intermediate velocity region, discrepancies between the model and experiment may result from an inappropriate representation of the heat flux by counterflow when the temperature and pressure gradients have an effect of similar magnitude on the heat flux.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
