Modeling the relationship between the influencing factors and the multiple responses of coal‐like materials using Taguchi‐Gray correlation analysis for their utilization in gas seepage studies

Li, Qingmiao; Zou, Quanle

doi:10.1002/ese3.313

Cited by 6 publications

(6 citation statements)

References 30 publications

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“…The water storage capacity depends on the porosity of the coal specimens, while water adsorption is an external manifestation of the size and distribution of cracks in the coal, and micro‐pore structure also has a certain effect on seepage and water drive . An increase in the water adsorption of coal specimens indicates an increase and extension of cracks within the structure and an increase in fluid permeability in the coal . The curve of water adsorption under cyclic wetting‐drying is shown in Figure .…”

Section: Results and Analysismentioning

confidence: 99%

Influence of cyclic wetting‐drying on the mechanical strength characteristics of coal samples: A laboratory‐scale study

Chen

Jiang

Wang³

et al. 2019

Energy Science & Engineering

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Water‐coal interactions have gained much recent attention, although few studies focus on the strength of coal under wetting‐drying cycles. This study investigates changes in the microstructure and mechanical strength of coal that are induced by water‐coal interactions, at the macroscale and microscale. Fourteen specimens after continuous wetting and fourteen specimens after wetting‐drying cycles were tested, indicating that peak stress and elastic modulus decrease with increasing continuous wetting time and number of wetting‐drying cycles, while peak strain increases. We analyzed changes in the coal microstructure using a scanning electron microscope (SEM) and the Image Pro Plus 6.0 (IPP 6.0) software. The regression model for cyclic wetting‐drying reveals that porosity and pore circularity are the main correlation indicators associated with uniaxial compressive strength. Therefore, different numbers of wetting‐drying cycles could induce different degrees of damage to coal, which increases progressively through gradual changes to its microstructure. These findings indicate that wetting‐drying cycles have a more significant impact on the stability of coal mass than continuous wetting. Our results are of use in determining the size of coal pillars, and expanding the knowledge base related to the mechanical properties of coal mass, water bursting, water recharge channels, and the stress‐crack‐permeability evolution law in mines.

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Section: Results and Analysismentioning

confidence: 99%

Influence of cyclic wetting‐drying on the mechanical strength characteristics of coal samples: A laboratory‐scale study

Chen

Jiang

Wang³

et al. 2019

Energy Science & Engineering

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“…Gypsum (main ingredients: gypsum, sand, calcium carbonate, and additives), cement (32.5# ordinary Portland pozzolana cement), pulverized coal (lignite from the Dongsheng Coalmine, China), and sand were selected as similar materials to make coal-like samples (Figure ). ,− The testing results of the proximate analysis, mechanics, and porosity of lignite are presented in Table . Based on a pilot experiment in the laboratory, we concluded that the mechanical properties of the coal-like samples were similar to those of low-rank coal when the weight ratio of pulverized coal (0–1 mm):cement:gypsum:sand (0.25–0.5 mm):water was 1:3:1:1:2 (Figure ).…”

Section: Methodsmentioning

confidence: 99%

“…It was also found that the coal particle sizes had a significant effect on the strength and permeability of the coal-like briquettes. − Zhong et al found that the compressive strength and Young’s modulus of German brown coal particles significantly increased as the specimen size (diameter range of 0.8–6.3 mm) decreased. Dong et al concluded that the effective elastic moduli and tensile strengths were related to tectonic coal particles (size range of 0.2–4.0 mm) as a power function.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Effect of Coal Particle Size on the Mechanics, Pore Structure, and Permeability of Coal-like Materials for Low-Rank Coalbed Methane Reservoir Simulation

Zheng

Zhai

et al. 2021

Energy Fuels

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Coal-like materials have been widely used to simulate low-rank coalbed methane (CBM) reservoirs to develop fracturing stimulation technology since the transportation and preparation of low-rank coal produce easily secondary damages, causing large dispersion of test results. However, the coal particle sizes have a significant effect on the performance of coal-like materials among many factors. Hence, to accurately simulate lowrank CBM reservoirs for promoting the development of reservoir stimulation technologies, cement, gypsum, pulverized coal, and sand were selected as similar materials to make coal-like samples with different coal particle sizes to study the influence law of coal particle size on the mechanics, pore structure, and permeability of samples. The ultrasonic wave velocity, dynamic parameters, uniaxial compressive strength, elastic modulus, and uniaxial tensile strength of samples increased with increasing coal particle size in the range of 0−2 mm. However, these parameters suddenly decreased when the coal particle size increased to 2−3 mm. The porosity and permeability of the samples exhibited an opposite trend compared to the above parameters. The fracture occurred in cementing materials, and the crack extension direction was affected by the coal particle sizes. The fracture complexity of the coal-like samples decreased with increasing particle size under uniaxial compressive testing. The failure mode was mainly a tensile failure, supplemented by shear failure. The coal-like materials can well meet the performance requirements of low-rank CBM reservoirs.

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“…Although the method will improve the prediction accuracy, the time cost will be relatively high. At present, the most common feature selection method applied in industrial production processes is the filter methods, such as correlation-based analysis methods [6]- [8]; wrapper methods, such as variable pruning methods [9], [10], genetic algorithm-based methods [11].…”

Section: A Feature Extractionmentioning

confidence: 99%

Smart Online Fuel Sulfur Prediction in Diesel Hydrodesulfurization Process

Huang

et al. 2020

IEEE Access

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In the process industry, online operators usually adjust the entire production process in time according to changes in certain key indicators. However, it is difficult to directly obtain the value of key indicators due to the complex structure and the numerous processes of the process industry. This paper proposes a method to achieve high precision on-line prediction of key indicators in the process industry. The method first performs data preprocessing of multi-source heterogeneous time series data involved in industrial processes based on the professional knowledge, which not only keeps the prediction error within 10%, but also reduces the prediction time. Then a model framework is constructed based on LSTM neural network and the error correction algorithm is proposed to improve prediction accuracy based on real-time error, which directly causes the error to drop by 3%-5%. At the end, a set of multi-mode online training strategies and related trigger conditions are designed to perform predicting online. Diesel hydrodesulfurization is a typical case in the process industry. The effectiveness of the proposed method is empirically studied by applying its actual data sets. Through the comparison with other traditional wellknown forecasting models, and models optimized by adjusting parameters, the experimental results demonstrate that the method can achieve the great prediction performance in terms of both accuracy and stability.

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Modeling the relationship between the influencing factors and the multiple responses of coal‐like materials using Taguchi‐Gray correlation analysis for their utilization in gas seepage studies

Cited by 6 publications

References 30 publications

Influence of cyclic wetting‐drying on the mechanical strength characteristics of coal samples: A laboratory‐scale study

Influence of cyclic wetting‐drying on the mechanical strength characteristics of coal samples: A laboratory‐scale study

Experimental Study on the Effect of Coal Particle Size on the Mechanics, Pore Structure, and Permeability of Coal-like Materials for Low-Rank Coalbed Methane Reservoir Simulation

Smart Online Fuel Sulfur Prediction in Diesel Hydrodesulfurization Process

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