Determining diffusion coefficients of coal particles by solving the inverse problem based on the data of methane desorption measurements

Fuel ◽  
2022 ◽  
Vol 308 ◽  
pp. 122045
Author(s):  
Qingquan Liu ◽  
Jing Wang ◽  
Jingjing Liu ◽  
Qiquan Yang ◽  
Wenyi Huang ◽  
...  
Holzforschung ◽  
2003 ◽  
Vol 57 (5) ◽  
pp. 533-538 ◽  
Author(s):  
P. Koc ◽  
M. Houka ◽  
B. Štok

Summary An inverse identification method for characterization of wood sorptive properties is presented. The method relies on a computer simulation of a real experiment, in our case a desorption experiment, where spruce heartwood samples were dried from 27% to 8% moisture content. Three samples, distinguished by the respective moisture flow pattern through the specimen, were investigated. A computer aided material characterization using the so-called inverse problem identification method was performed on the measurements. The solution of the specified inverse problem enabled us to estimate the moisture diffusion coefficients of wood and to determine the moisture content field in the sample simultaneously. The method is first verified on two simple cases of uniaxial moisture flow, and then is used to characterize the diffusion coefficients on a biaxial moisture flow sample. In the latter case some salient features of the proposed method are exhibited.


2012 ◽  
Vol 54 (12) ◽  
pp. 124025 ◽  
Author(s):  
F Sattin ◽  
D F Escande ◽  
Y Camenen ◽  
A T Salmi ◽  
T Tala ◽  
...  

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yongjiang Hao ◽  
Xiaofeng Ji ◽  
Jiewen Pang

In order to research on the law of methane released through the pore in coal particles, the methane desorption experiments were conducted, respectively, on four types of particle size of coal samples under three different initial adsorption pressures. The cumulative methane desorption quantity (CMDQ) with time increasing was obtained to show that the reciprocal of CMDQ was in linear relation with the reciprocal of the square root of time, and the correlation coefficients were all above 0.99, on basis of which an empirical formula of CMDQ was established. Then, according to Fick diffusion law and Darcy percolation law, the mathematical models of methane emission from the spherical coal particles were created, respectively, and the corresponding calculating software was programmed by the finite difference method to obtain the simulated CMDQ of each sample under different conditions. The methane emission rate functions (MERF) of the simulation and the experiment were also calculated, respectively. Comparative analysis between the numerically simulated outcomes and the assay results reveals that the simulation outcomes as per Darcy’s law match the experimental data better, while the simulated results by Fick’s law deviate greatly, which indicates that the methane flowing through coal particles is more in accordance with Darcy’s law.


2009 ◽  
Vol 111 (2) ◽  
pp. 129-147 ◽  
Author(s):  
K. Sakthivel ◽  
N. Baranibalan ◽  
J.-H. Kim ◽  
K. Balachandran

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1695
Author(s):  
Tzitlali Gasca-Ortiz ◽  
Francisco J. Domínguez-Mota ◽  
Diego A. Pantoja

In this study, optimal diffusion coefficients for Lake Zirahuén, Mexico, were found under particular conditions based on images taken with a drone of a dye release experiment. First, the dye patch concentration was discretized using image processing tools, and it was then approximated by an ellipse, finding the optimal major and minor axes. The inverse problem was implemented by comparing these observational data with the concentration obtained numerically from the 2D advection–diffusion equation, varying the diffusion tensor. When the tensor was isotropic, values of K11=K22≈0.003 m2/s were found; when nonequal coefficients were considered, it was found that K11≈0.005 m2/s and K22≈0.002 m2/s, and the cross-term K12 influenced the results of the orientation of the ellipse. It is important to mention that, with this simple technique, the parameter estimation had consequences of great importance as the value for the diffusion coefficient was bounded significantly under particular conditions for this site of study.


2010 ◽  
Vol 111 (2) ◽  
pp. 149-152 ◽  
Author(s):  
K. Sakthivel ◽  
N. Baranibalan ◽  
J.-H. Kim ◽  
K. Balachandran

Processes ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 219 ◽  
Author(s):  
Yang ◽  
Wang ◽  
Zhang ◽  
Ren

Gas pressure changes during the process of coal mine gas drainage and CBM recovery. It is of great importance to understand the influence of sorption pressure on gas diffusion; however, the topic remains controversial in past studies. In this study, four samples with different coal ranks were collected and diffusion experiments were conducted under different pressures through the adsorption and desorption processes. Three widely used models, i.e., the unipore diffusion (UD) model, the bidisperse diffusion (BD) model and the dispersive diffusion (DD) model, were adopted to compare the applicability and to calculate the diffusion coefficients. Results show that for all coal ranks, the BD model and DD model can match the experimental results better than the UD model. Concerning the fast diffusion coefficient Dae of the BD model, three samples display a decreasing trend with increasing gas pressure while the other sample shows a V-type trend. The slow diffusion coefficient Die of BD model increases with gas pressure for all samples, while the ratio β is an intrinsic character of coal and remains constant. For the DD model, the characteristic rate parameter kΦ does not change sharply and the stretching parameter α increases with gas pressure. Both Dae and Die are in proportion to kΦ, which reflect the diffusion rate of gas in the coal. The impacts of pore characteristic on gas diffusion were also analyzed. Although pore size distributions and specific surface areas are different in the four coal samples, correlations are not apparent between pore characteristic and diffusion coefficients.


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