scholarly journals Large Scale Experimental Evaluation to Methane Hydrate Dissociation below Quadruple Point by Depressurization Assisted with Heat Stimulation

2017 ◽  
Vol 142 ◽  
pp. 4117-4123 ◽  
Author(s):  
Jing-Chun Feng ◽  
Yi Wang ◽  
Xiao-Sen Li
2021 ◽  
Vol 304 ◽  
pp. 117750
Author(s):  
Jing-Chun Feng ◽  
Bo Li ◽  
Xiao-Sen Li ◽  
Yi Wang

2002 ◽  
Vol 80 (4) ◽  
pp. 418-439 ◽  
Author(s):  
David N Glew

Literature data for the saturation pressure P(hl1g) of methane hydrate with water, at 102 temperatures between –0.29 and 46.87°C, are properly represented by two distinct equations, with a quadruple point Q(h1h2l1g) transition temperature at 26.7°C with standard error (SE) 0.9°C and 55.5 MPa with SE 5.3 MPa. The structure I type methane hydrate phase h1 is stable below 26.7°C and the structure II type methane hydrate phase h2 is stable above 26.7°C. Between –0.29 and 25.54°C, 85 equilibrium pressures of methane hydrate with water are best represented, with SE 1.33% on a single pressure measurement, by a four-parameter thermodynamic equation. The corresponding equilibrium methane fugacities are represented, with SE 0.94% on a fugacity determination, by a five-parameter equation. Between 26.98 and 46.87°C, 17 equilibrium methane hydrate pressures with water are best represented, with SE 2.22% on a pressure measurement, by a three-parameter equation. Composition of the equilibrium aqueous phase is evaluated using methane fugacity with the solubility equation including a Poynting correction. Literature data between –2.22 and –14.10°C, for the saturation pressure P(h1s1g) of structure I methane hydrate with ice, are properly represented by a two-parameter equation, with SE 1.1% on a single pressure measurement. Standard enthalpy change for structure I methane hydrate dissociation into ice and methane gas is found to be ΔHot(h1[Formula: see text] s1g) = 18058 J mol–1 with SE 608 J mol–1 at -8.28°C. The quadruple point Q(h1s1l1g) is estimated at –0.290°C with SE 0.0064°C and at 2.527 MPa with SE 0.053 MPa. Using the classical thermodynamic method, as described for deuterium sulfide D-hydrate, methane hydrate equilibrium fugacities define 85 equilibrium constants Kp(h1[Formula: see text]l1g) between –0.29 and 25.54°C for dissociation of structure I hydrate h1 into liquid water l1 and methane gas. Temperature dependence of ln Kp(h1[Formula: see text]l1g) is well-represented by a three-parameter thermodynamic equation that gives both estimates and their standard errors for (i) ΔHot(h1[Formula: see text]l1g) and ΔCpot(h1[Formula: see text]l1g), the standard enthalpy and heat capacity changes, respectively, for hydrate h1 dissociation, and for (ii) n = r, the approximate formula number of the hydrate CH4·nH2O at each experimental temperature. The formula CH4·6.205H2O with SE 0.066H2O is found for the structure I methane hydrate h1 with water at quadruple point Q(h1s1l1g) –0.29°C; an approximate formula CH4·5.759H2O with SE 0.077H2O is found at quadruple point Q(h1h2l1g) 26.7°C. Between 26.98 and 46.87°C, the 17-equilibrium constants Kp(h2[Formula: see text]l1g) for dissociation of structure II methane hydrate h2 into liquid water l1 and methane gas are represented by a constrained three-parameter thermodynamic equation. For structure II methane hydrate the formula CH4·5.822H2O with SE 0.064H2O is found at quadruple point Q(h1h2l1g) 26.7°C and the formula CH4·5.699H2O with SE 0.064H2O at 46.87°C. Molar volumes and cohesive energy densities of the methane hydrates are compared with equilibrium compressed water.Key words: clathrate hydrates of methane, two methane gas hydrates, formula of structure I methane hydrate, thermodynamics of clathrate hydrate dissociation, dissociation equilibrium constants of structure I methane hydrate, standard enthalpy and heat capacity changes for dissociation of structure I methane hydrate, methane hydrates' transition temperature, formula of structure II methane hydrate, dissociation equilibrium constants of structure II methane hydrate, standard enthalpy change for dissociation of structure II methane hydrate, methane hydrates' cohesive energy density.


2018 ◽  
Author(s):  
Mingjun Yang ◽  
Yi Gao ◽  
Hang Zhou ◽  
Bingbing Chen ◽  
Yongchen Song

Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 590
Author(s):  
Lihua Wan ◽  
Xiaoya Zang ◽  
Juan Fu ◽  
Xuebing Zhou ◽  
Jingsheng Lu ◽  
...  

The large amounts of natural gas in a dense solid phase stored in the confined environment of porous materials have become a new, potential method for storing and transporting natural gas. However, there is no experimental evidence to accurately determine the phase state of water during nanoscale gas hydrate dissociation. The results on the dissociation behavior of methane hydrates confined in a nanosilica gel and the contained water phase state during hydrate dissociation at temperatures below the ice point and under atmospheric pressure are presented. Fourier transform infrared spectroscopy (FTIR) and powder X-ray diffraction (PXRD) were used to trace the dissociation of confined methane hydrate synthesized from pore water confined inside the nanosilica gel. The characterization of the confined methane hydrate was also analyzed by PXRD. It was found that the confined methane hydrates dissociated into ultra viscous low-density liquid water (LDL) and methane gas. The results showed that the mechanism of confined methane hydrate dissociation at temperatures below the ice point depended on the phase state of water during hydrate dissociation.


Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.


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