Risk assessment of water inrush to coal seams from underlying aquifer by an innovative combination of the TFN-AHP and TOPSIS techniques

Shi, Longqing; Qiu, Mei; Teng, Chao; Wang, Ying; Liu, Tianhao; Qu, Xingyue

doi:10.1007/s12517-020-05588-0

Cited by 16 publications

(9 citation statements)

References 41 publications

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“…The calculation process can be divided into six steps: constructing the initial matrix, constructing the normalization matrix, constructing the weighted gauge matrix, determining the positive ideal solution and negative ideal solution, determining the distance from each scheme to the ideal solution, and calculating the relative proximity between each scheme and the ideal solution. These six steps are described below Constructing (same trend/same direction) the initial matrix: …”

Section: Geological Model and Mathematical Methodsmentioning

confidence: 96%

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Numerical Simulation of the Temperature Distribution and Evolution Law of Underground Lignite Gasification

Zhou

Chen

et al. 2022

ACS Omega

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To study the temperature distribution characteristics and evolution law of underground lignite gasifiers, a three-dimensional heat conduction model of underground lignite gasification was constructed. Moreover, the effects of different coal thicknesses, advance speeds of the flame working face, and surrounding rock types on the gasifier were analyzed. The results show that with the increase in the coal thickness, the transfer range and distance of temperature in the roof, floor, and coal seam gradually increase, as does the coal quantity in the three zones. The heat loss rate of the gasifier decreased gradually with the coal seam thickness. When the advance speed of the flame working face is 0.5 m/d, the ideal gasification coal thickness range of lignite is 2.5–17.5 m. With the increase in the gasification rate, the maximum transfer distance of temperature to the roof and floor, the average temperature of the gasifier, and the coal quantity of the three zones gradually increase. Conversely, the coal thickness corresponding to the intersection of the coal quantity of the oxidation and reduction zones and the heat loss rate of the gasifier gradually decrease. When the coal seam below 2.5 m is gasified, the gasification rate can be increased appropriately. When the coal seam is above 13 m, increasing the gasification rate will make the coal quantity in the oxidation zone close to or even higher than that in the reduction zone. Regarding the surrounding rock types comprising a combination of siltstone, mudstone, sandy mudstone, and fine sandstone, the most favorable roof and floor type for underground coal gasification is the combination of fine sandstone and sandy mudstone (without considering the sealing and mechanical properties). These results provide important theoretical support for the industrialization of underground coal gasification.

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Section: Geological Model and Mathematical Methodsmentioning

confidence: 96%

“…These six steps are described below. 42 Constructing (same trend/same direction) the initial matrix: …”

Section: Geological Model and Mathematical Methodsmentioning

confidence: 99%

Numerical Simulation of the Temperature Distribution and Evolution Law of Underground Lignite Gasification

Zhou

Chen

et al. 2022

ACS Omega

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“…The basic principle is to decompose the decision goal according to different standard, then calculate the weight each element to a specific element in the above layer through calculating the matrix and eigenvector, finally conclude the weight of every element in this system [16]. The specific procedure includes 5 necessary steps [6][7][8]11,16]: clarify the decision goal, build hierarchical structure, construct judgment matrix, check consistency and make judgment. The finally goal of AHP method is to determine the relative weight every element in the system.…”

Section: Ahp Methodsmentioning

confidence: 99%

“…Vulnerability evaluation is derived from natural disaster risk assessment, which is widely used in assessing the loss caused by earthquake, debris flow, landslip and rainstorm [5][6][7][8]. Currently, the research on risk management in cultural heritage is still in the exploratory stage.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation System Based on AHP Method for Preserve Situation in Guangyuan Thousand-Buddha Grotto of Tang Dynasty in Sichuan, China

Yao¹,

Zhao²

2021

Preprint

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Guangyuan thousand-buddha grotto is of great value in researching Buddhism spread in China. By joint effect of various factors, the grottos have developed serious diseases, which threaten the long-term preservation. To date, the existing study can neither reveal the contribution each disease makes to nor the grottos’ preserve situation in a quantized way. Therefore, establishing a scientific evaluation system to explore the effection of each disease and assess grottos’ preserve situation degree has been a significant topic for grotto’s conservation. In this research, the authors selected 11 grottos of middle Tang dynasty in Guangyuan thousand-buddha grotto as survey objects, traditional diseases investigation was taken and analytic hierarchy process (AHP method) was applied to build a system to calculate weight of 15 diseases and evaluate grottos’ preserve situation. The result shows, 15 diseases can be classified as two risk categories, and every disease has its own weight on effecting grotto’s preserve situation. AHP method is suitable for heritage assessment with complex structure.

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“…In applications, the TFN-AHP used triangular fuzzy numbers instead of the crisp numbers in the judgment structure matrix to express the importance degree between factors [68]. The triangular fuzzy number is defined as P = (l, m, u), where the l and u represent the minimum and maximum possible values, while m is the most promising value [69]. The membership function of the P = (l, m, u) is expressed as follows [70]:…”

Section: Triangular Fuzzy Number-based Ahp (Tfn-ahp)mentioning

confidence: 99%

Dynamic Assessment of the Flood Risk at Basin Scale under Simulation of Land-Use Scenarios and Spatialization Technology of Factor

Liu

Wang

Xiong

et al. 2021

Water

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Climate change, population increase, and urban expansion have increased the risk of flooding. Therefore, accurately identifying future changing patterns in the flood risk is essential. For this purpose, this study elaborated a new framework for a basin scale that employs a future land-use simulation model, a factor spatialization technique, and a novel hybrid model for scenario-based flood risk assessment in 2030 and 2050. Three land-use scenarios (i.e., natural growth scenario, cropland protection scenario, and ecological protection scenario) were set and applied in Jinjiang Basin to explore the changes in future flood risk under these scenarios. The results indicate the different degrees of increase in flood risk that will occur in the three scenarios. Under the natural growth (NG) scenario, the city will expand rapidly with the growth of population and economy, and the total area with high and very high flood risk will increase by 371.30 km2 by 2050, as compared to 2020. However, under the ecological protection (EP) scenario, woodlands will be protected, and the growth in population, economy, and built-up lands will slow down with slightly increased risk of flooding. In this scenario, the total area with high and very high flood risk will increase by 113.75 km2 by 2050. Under the cropland protection (CP) scenario, the loss of croplands will have been effectively stopped, and the flood risk will not show a significant increase under this scenario, with an increase by only 90.96 km2 by 2050, similar to the EP scenario. Spatially, these increased flood risks mainly locate at the periphery of existing built-up lands, and the high-flood-risk zones are mainly distributed in the southeast of the Jinjiang Basin. The information about increasing flood risk determined by the framework provides insight into the spatio-temporal characteristics of future flood-prone areas, which facilitates reasonable flood mitigation measures to be developed at the most critical locations in the region.

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Risk assessment of water inrush to coal seams from underlying aquifer by an innovative combination of the TFN-AHP and TOPSIS techniques

Cited by 16 publications

References 41 publications

Numerical Simulation of the Temperature Distribution and Evolution Law of Underground Lignite Gasification

Numerical Simulation of the Temperature Distribution and Evolution Law of Underground Lignite Gasification

An Evaluation System Based on AHP Method for Preserve Situation in Guangyuan Thousand-Buddha Grotto of Tang Dynasty in Sichuan, China

Dynamic Assessment of the Flood Risk at Basin Scale under Simulation of Land-Use Scenarios and Spatialization Technology of Factor

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