Properties Of Natural Gas Research Articles

Effect of pulverized anthracite coal particles injection on thermal and radiative characteristics of natural gas flame: An experimental study

Natural gas is increasingly used as a clean fuel. In many industrial combustion systems, such as industrial furnaces and boilers, a large portion of heat is transferred by radiation. The use of natural gas in such industrial systems leads to a decrease in radiative heat transfer. The addition of solid reactant particles into flame is widely proposed in the literature as a method to enhance radiation from non-luminous flames, with a preponderance of research on hydrogen flame. The present study explores how the injection of pulverized anthracite coal particles into natural gas diffusion flame, as a non-luminous one, affects the thermal and radiative properties of natural gas. A novelty of our research method is the exploitation of yellow chemiluminescence of soot particles together with infrared photography to locate radiative particles and discover their qualitative distribution. The IR filter used in our technique was tested with Thermo Nicolet Avatar 370 FTIR Spectrometer for its spectral transmittance to be determined. The results indicate that the injection of coal particles into natural gas flame leads to a rise in the soot content of flame. Having the advantage of high absorptivity and emissivity coefficients in the near IR region, the soot particles in turn increase the flame luminosity and, more importantly, its emissivity coefficient. Also, the heat released from the combustion of particles increases the average temperature of flame about 29°C. These raise the radiative heat transfer and thermal efficiency of flame as much as 43% and 21%, respectively. It is noteworthy that the average temperature difference and emissivity coefficient, respectively, account for 17% and 83% of the enhancement of the average radiation flux.

Energy markets volatility modelling using GARCH

This paper investigates the empirical properties of oil, natural gas, and electricity price volatilities using a range of univariate and multivariate GARCH models and daily data from wholesale markets in the United States for the period from 2001 to 2013. The key contribution to the literature is the estimation of trivariate BEKK and DCC models that allow us to observe spillovers and interactions among energy markets. We evaluate and compare the performance of univariate and multivariate models with a range of diagnostic and forecast performance tests, and assess forecasting performance and conditional correlation dynamics.

Numerical simulation of filling process of natural gas onboard vehicle cylinder

The accurate modeling of the filling compressed natural gas fueled vehicle storage cylinders is a complex process and should be studied deeply. The minimum filling time has positive impact on commercialization of natural gas vehicles. In other hand, very fast filling may be resulted to unexpected temperature rise and violating the safety standards. This study investigates flow and heat transfer in natural gas vehicle’s onboard cylinder during filling. The cylinder is assumed to be a type III onboard storage cylinder. An axisymmetric computational model for unsteady, compressible turbulent flow has been built. A computational fluid dynamics has been developed for predicting the temperature and pressure change during the fill based on using commercial software Fluent. The natural gas (NG) as working fluid is treated as a real gas. The Redlich–Kwong equation of state has been employed to compute the thermodynamic properties of NG. The computation results have been compared with previous measured values and show good agreement. The results show that the temperature rise for NG is about 35 K. The most of heat dissipation from the in-cylinder gas is stored in the cylinder wall during the fill and the heat lost to the ambient is small.

An intelligent approach for optimal prediction of gas deviation factor using particle swarm optimization and genetic algorithm

The measurement of PVT properties of natural gas in gas pipelines, gas storage systems, and gas reservoirs require accurate values of compressibility factor. Although equation of state and empirical correlations were utilized to estimate compressibility factor, but the demands for novel, more reliable, and easy-to-use models encouraged the researchers to introduce modern tools such as artificial intelligent systems.This paper introduces Particle swarm optimization (PSO) and Genetic algorithm (GA) as population-based stochastic search algorithms to optimize the weights and biases of networks, and to prevent trapping in local minima. Hence, in this paper, GA and PSO were used to minimize the neural network error function.A database containing 6378 data was employed to develop the models. The proposed models were compared to conventional correlations so that the model predictions indicated a good accuracy for the results in training and testing stages. The results showed that artificial neural networks (ANNs) remarkably overcame the inadequacies of the empirical models where PSO–ANN improved the performance significantly. Additionally, the regression analysis released the efficiency coefficient (R2) of 0.999 which can be considered very promising.

Modeling thermodynamic properties of natural gas mixtures using perturbed-chain statistical associating fluid theory

Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) was employed for predicting thermodynamic properties of natural gas mixture. Thermodynamic properties like density, isobaric and isochoric heat capacity, enthalpy, entropy, and internal energy were calculated with the PC-SAFT. Results are validated against experimental data for natural gas and mixtures similar to natural gas. The validation show that the Average Absolute Deviation (AAD) for density is 1.10% for binary mixture and 1.08% for mixtures similar to natural gas. Also AAD value for enthalpy is 1.42%, for internal energy, 0.77, for entropy, 0.43, for isochoric heat capacity, 1.26%, and for isobaric heat capacity, 2.66%. Results show PC-SAFT to be able to predict all the thermodynamics properties of natural gas and mixtures similar to natural gas with high accuracy in a wide range of temperature and pressure.

Measurement of the (pressure, density, temperature) relation of a (methane + nitrogen) gaseous mixture using an accurate single-sinker densimeter

A single-sinker magnetic suspension densimeter based on Archimedes’ buoyancy principle is described. Density measurements on high-purity nitrogen demonstrate the performance of the densimeter. Comprehensive (p,ρ,T) measurements at low densities on a gaseous mixture with mole fraction of (0.8977CH4+0.1023N2) were carried out on this densimeter at six temperatures from (170.586 to 270.054)K and at pressures ranging from (0.1333 to 1.5945)MPa. The overall uncertainty in density is estimated to be 0.1%. The uncertainty in temperature is estimated to be 5mK and that in pressure is 250Pa for (0 to 1.5)MPa and 390Pa for (1.5 to 3)MPa, respectively. The experimental results of the (methane+nitrogen) mixture were compared with REFPROP 9.0, which used GERG-2008 and AGA8 equations of state to predict thermophysical properties of natural gas. The absolute relative deviations of density measurements are all within 0.1%. Meanwhile the experimental results were correlated using the virial equation of state (Virial EOS) with three different mixing rules. The calculated results using the virial EOS combined with VDW mixing rule show good agreement with the experimental data.

Diversity of Hydrocarbon-Related Catabolic Genes in Oil Samples from Potiguar Basin (Rn, Brazil)

Biodegradation may result in physicochemical changes in crude oil and natural gas properties, being responsible for the decrease of saturated hydrocarbons and yielding heavy oil with low economic value. Studies on the diversity of microbial catabolic genes in oil reservoirs are scarce and could help to predict the potential of a petroleum sample to be biodegraded. The aim of this study was to evaluate the diversity of genes involved in hydrocarbon degradation in Brazilian petroleum samples (biodegraded and non-biodegraded) through the construction and analysis of gene libraries (alkane monooxygenase – alk, dioxygenase – ARHDs and 6-oxocyclohex-1-ene-1-carbonyl-CoA hydrolase - bamA). The results showed a differential distribution of catabolic genes between the sites, being the biodegraded oil more diverse for the alk and bamA genes. Sequences were similar to the alkB genes from Geobacillus thermoleovorans and several species of Acinetobacter, to ARHD genes from Pseudomonas spp. and two species of Burkholderia, and to bamA genes from deltaproteobacteria. Interestingly, most of the catabolic sequences recovered from both petroleum reservoirs grouped together forming distinct clusters in the phylogenetic tree reconstruction and may correspond to potentially new genes, possibly harbored by yet uncultivated microorganisms. This is the first report on the detection of alk, ARHD and bamA genes in petroleum reservoir environments, demonstrating the genetic potential of such microbial communities to biodegrade the oil.

The study of thermodynamic properties and transport properties of multicomponent systems with chemical reactions

In case of system with chemical reaction the most important properties are heat conductivity and heat capacity. In this work we have considered the equation for estimate the component of these properties caused by chemical reaction and ionization processes. We have evaluated the contribution of this part in heat conductivity and heat capacity too. At the high temperatures contribution in heat conductivity from ionization begins to play an important role. We have created a model, which describe partial and full ionization of gases and gas mixtures. In addition, in this work we present the comparison of our result with experimental data and data from numerical simulation. We was used the data about transport properties of middle composition of Russian coals and the data of thermophysical properties of natural gas for comparison.

Studying transmission of fuel storage bank to NGV cylinder in CNG fast filling station

The exact modeling of the fast-fill process of Compressed Natural Gas (CNG) fueled storage bank occurring to Compressed Natural Gas Vehicle (NGV) cylinders is an unintelligible process, and should be thoroughly studied. In this paper, a theoretical model based on mass balance and thermodynamic laws has been developed to study dynamic fast filling process of CNG storage bank to vehicle's (NGV) cylinder. Because Methane occupies a large percentage (between 70% to 99%) of natural gas, for the sake of simplicity it is assumed that Methane is the only substance in Natural gas and thermodynamic properties table has been employed for case of real gas model based on methane. For modeling the heat transfer, the system has been treated as an adiabatic lump one. The result shows the initial pressure of storage bank has a big effect on the storage bank volume for bringing up the NGV cylinder to its target pressure (20 MPa). The storage bank volumes required for bringing up the NGV cylinder to its final (target) pressure (20 MPa) for various initial storage bank pressure, like 20.8 MPa (RPS = 1.04), 23 MPa (RPS = 1.15) and 25 MPa (RPS = 1.25) are respectively 22, 6 and 4 times the NGV cylinder volume. It is noted that RPS is the ratio of storage bank pressure (PS) to target pressure (PT) (In this research is 20 MPa). The results also showed that ambient temperature has a big effect on refueling process, chiefly on final NGV cylinder and storage bank conditions.

The GERG-2008 Wide-Range Equation of State for Natural Gases and Other Mixtures: An Expansion of GERG-2004

A new equation of state for the thermodynamic properties of natural gases, similar gases, and other mixtures, the GERG-2008 equation of state, is presented in this work. This equation is an expanded version of the GERG-2004 equation. GERG-2008 is explicit in the Helmholtz free energy as a function of density, temperature, and composition. The equation is based on 21 natural gas components: methane, nitrogen, carbon dioxide, ethane, propane, n-butane, isobutane, n-pentane, isopentane, n-hexane, n-heptane, n-octane, n-nonane, n-decane, hydrogen, oxygen, carbon monoxide, water, hydrogen sulfide, helium, and argon. Over the entire composition range, GERG-2008 covers the gas phase, liquid phase, supercritical region, and vapor–liquid equilibrium states for mixtures of these components. The normal range of validity of GERG-2008 includes temperatures from (90 to 450) K and pressures up to 35 MPa where the most accurate experimental data of the thermal and caloric properties are represented to within their accura...

Numerical procedures for natural gas accurate thermodynamic properties calculation

Natural gas (NG) is a mixture of 21 elements and widely used in the industries and domestics. Knowledge of its thermodynamic properties is essential for designing appropriate process and equipments. In this study, the detailed numerical procedures for computing most thermodynamic properties of natural gas are discussed based on the AGA8 equation of state (EOS) and thermodynamics relationships. To validate the procedures, the numerical values are compared with available measured values. The validations show that the average absolute percent deviation (AAPD) for density calculations is 0.0831%, for heat capacity at the constant pressure is 0.87%, for heat capacity at the constant volume is 1.13%, for Joule-Thomson coefficient is 1.93%, for speed of sound is 0.133%, and for enthalpy is 1.06%. Furthermore, in this work, the new procedures are presented for computing the entropy and internal energy. Due to lack of experimental data for these properties, the validation is done for pure methane. The validation shows that AAPD is 0.078% and 0.0133% for internal energy and entropy, respectively.

Erratum to: Transport properties of natural gas through polyethylene nanocomposites at high temperature and pressure

High density polyethylene (HDPE)/clay nanocomposites containing nanoclay concentrations of 1, 2.5, and 5 wt% were prepared by a melt blending process. The effects of various types of nanoclays and their concentrations on permeability, solubility, and diffusivity of natural gas in the nanocomposites were investigated. The results were compared with HDPE typically used in the production of liners for the petroleum industry. Four different nanoclays—Cloisite 10A, 15A, 30B and Nanomer 1.44P—were studied in the presence of CH4 and a CO2/CH4 mixture in the temperature range 30–70 °C and pressure range 50–100 bar. The permeability and diffusivity of the gases were considerably reduced by the incorporation of nanoclay into the polymer matrix. Addition of 5 wt% loading of Nanomer 1.44P reduced the permeability by 46% and the diffusion coefficient by 43%. Increasing the pressure from 50 to 100 bar at constant temperature had little influence on the permeability, whereas increasing the temperature from 30 to 70 °C significantly increased the permeability of the gas. Additionally, the effect of crystallinity on permeability, solubility, and diffusivity was investigated. Thus, the permeability of the CO2/CH4 mixture in Nanomer 1.44P nanocomposite was reduced by 47% and diffusion coefficient by 35% at 5 wt% loading, 50 °C, and 100 bar, compared with pure HDPE.

A micromachined thermoelectric sensor for natural gas analysis: Multivariate calibration results

The potential use of a micromachined thermopile based sensor device for analyzing natural gas is explored. The sensor consists of a thermally isolated hotplate, which is heated by the application of a sequence of programmed voltages to an integrated heater. Once the hotplate reaches a stationary temperature, the thermopile provides a signal proportional to the hotplate temperature. These signals are processed in order to determine different natural gas properties. Sensor response is mainly dependent on the thermal conductivity of the surrounding gas at different temperatures. Seven predicted properties (normal density, superior heating value, Wobbe index and the concentrations of methane, ethane, carbon dioxide and nitrogen) are calibrated against sensor signals by using multivariate regression, in particular partial least squares. Experimental data have been used for calibration and validation. Results show property prediction capability with reasonable accuracy except for prediction of carbon dioxide concentration. A detailed uncertainty analysis is provided to better understand the metrological limits of the system. These results imply for the first time the possibility of designing unprecedented low-cost natural gas analyzers. The concept may be extended to other constrained gas mixtures (e.g. of a known number of components) to enable low-cost multicomponent gas analyzers.

Transport properties of natural gas through polyethylene nanocomposites at high temperature and pressure

Transport properties of natural gas through polyethylene nanocomposites at high temperature and pressure

Structures of Hydrocarbon Hydrates during Formation with and without Inhibitors

The formation of hydrates from a methane-ethane-propane mixture is more complex than with single gases. Using nuclear magnetic resonance (NMR) and high-pressure powder X-ray diffraction (PXRD), we have investigated the structural properties of natural gas hydrates crystallized in the presence of kinetic hydrate inhibitors (KHIs), two commercial inhibitors and two biological ice inhibitors, or antifreeze proteins (AFPs). NMR analyses indicated that hydrate cage occupancy was at near saturation for controls and most inhibitor types. Some exceptions were found in systems containing a new commercial KHI (HIW85281) and a recombinant plant AFP, suggesting that these two inhibitors could impact the kinetics of cavity formation. NMR analysis confirmed that the hydrate composition varies during crystal growth by kinetic effects. Strikingly, the coexistence of both structures I (sI) and II (sII) were observed in NMR spectra and PXRD profiles. It is suggested that sI phases may form more readily from liquid water. Real time PXRD monitoring showed that sI hydrates were less stable than sII crystals, and there was a conversion to the stable phase over time. Both commercial KHIs and AFPs had an impact on hydrate metastability, but transient sI PXRD intensity profiles indicated significantly different modes of interaction with the various inhibitors and the natural gas hydrate system.

Method to Predict Proppant flowback in Fractured Gas well

Abstract It has influences on the production of gas well and the effects of fracture when proppant flowback in the fractured gas well and the loss of the proppant from the fracture will corrupt the equipment above and below ground. For the problem of proppant flowback in fractured gas well, the purpose of this paper is to building a model of predict the proppant flowback in fractured gas well.With this model, the necessary control measures can provided to the designers during fracturing design stage, and Provide the basis for the rational allocation of production after the fracture. The prediction model includes both critical rate model of fracture and fracture shunt model. The critical gas rate at which depends on the moment balance of the proppant cracks can find out the critical velocity of gas. Then, Correct the critical velocity based on the formation closure stress, proppant size and strength, natural gas properties and gas seepage law. Last, the critical gas rate of fracture is computed using the gas velocity at borehole wall. Shunt a model of gas distribution between fracture and matrix depends on the numerical simulation. Demonstrate the usefulness of the model because the prediction results of the model agree with production data.

Developing novel correlations for calculating natural gas thermodynamic properties

Developing novel correlations for calculating natural gas thermodynamic properties Natural gas is a mixture of 21 components and it is widely used in industries and homes. Knowledge of its thermodynamic properties is essential for designing appropriate processes and equipment. This paper presents simple but precise correlations of how to compute important thermodynamic properties of natural gas. As measuring natural gas composition is costly and may not be effective for real time process, the correlations are developed based on measurable real time properties. The real time properties are temperature, pressure and specific gravity of the natural gas. Calculations with these correlations are compared with measured values. The validations show that the average absolute percent deviation (AAPD) for compressibility factor calculations is 0.674%, for density is 2.55%, for Joule-Thomson coefficient is 4.16%. Furthermore, in this work, new correlations are presented for computing thermal properties of natural gas such as enthalpy, internal energy and entropy. Due to the lack of experimental data for these properties, the validation is done for pure methane. The validation shows that AAPD is 1.31%, 1.56% and 0.4% for enthalpy, internal energy and entropy respectively. The comparisons show that the correlations could predict natural gas properties with an error that is acceptable for most engineering applications.

OPTIMIZATION OF THE C3MR CYCLE WITH GENETIC ALGORITHM

The aim of this paper is thermodynamic simulation and optimization of the C3MR system with Genetic Algorithm. For this purpose, in the first step, the Peng Robinson equation of state is simulated with a code in MATLAB and then used for simulating thermodynamic properties of natural gas and refrigerants that are used in the cycle. Following that the cycle is thermodynamically simulated and composite curves for subcooling and liquefaction heat exchangers are plotted. If composite curves in heat exchangers approach, the total power will decrease. Then, the total power used by the compressors is calculated. In the next step, the thermodynamic modeling is linked with Genetic Algorithm and the total power consumed by compressors is defined as objective function. The best value resulted from optimization has 23% lower power than the base design. In addition, heat exchange curves closed together.

A Model To Calculate the Theoretical Critical Flow Rate Through Venturi Gas Lift Valves

Summary A model to calculate the theoretical critical flow rate of nitrogen (N2) or natural gas through a Venturi gas lift valve is described herein. This new model considers real-gas effects not only in density calculations but also in other thermodynamic properties that are relevant during gas isentropic evolution. For the properties of N2, the Bennedict, Webb, and Rubin (BWR) equation of state and an accurate correlation for the ideal-gas isobaric heat capacity were used. For natural gas, the Dranchuk and Abou-Kassem equation, which reproduces the well-known Standing and Katz chart, was used, and, for the ideal-gas isobaric heat capacity, it was assumed that the natural gas was a mixture of methane and ethane only, their individual ideal-gas heat capacity being calculated by updated correlations. To validate the use of the proposed equations of state, a comparison of calculated with experimental or reference data on properties of N2 and natural gas (including pure methane and some relevant mixtures) was performed with very good results for N2 and for natural-gas compositions usual in gas lift operations (dry gas with very small amounts of contaminants). For natural gas with moderate amounts of N2 and carbon dioxide (CO2), accurate results were obtained after correction of critical conditions and of ideal heat capacity. The model was also compared with other theoretical models found in the literature, which use compositional approaches for natural gas, with excellent results. Some experimental results obtained with commercial Venturi valves manufactured in Brazil are also presented.

Compensation for Joule–Thomson effect in flowrate measurements by GMDH polynomial

The international standard for flowrate measurements ISO-5167 recommends the temperature sensor to be located downstream of the differential device what may cause a significant error in the measurement of the flowrate of natural gas, especially at high differential pressure, low temperature and low diameter ratio. The flowrate generally needs to be compensated for the temperature change due to the Joule–Thomson effect caused by the constriction of the metering device. The accurate compensation involves double calculation of both the natural gas properties and the flowrate. To decrease the computational load, an automatic correction of the flowrate by the GMDH polynomial surrogate is proposed. By using the compound measure of the approximation error and the execution time for model selection, the modified GMDH algorithm searches for the satisfactory model fulfilling the constraints of real-time application. The automatic correction of the flowrate measurements of a natural gas is simulated and the corresponding results are discussed. The derived model can be equally used for a natural gas specified by composition or by physical properties.