Mine Water and the Environment

, Volume 37, Issue 3, pp 636–648 | Cite as

Sensitivity Analysis of the Main Factors Controlling Floor Failure Depth and a Risk Evaluation of Floor Water Inrush for an Inclined Coal Seam

  • Weitao Liu
  • Dianrui MuEmail author
  • Xiangxiang Xie
  • Li Yang
  • Donghui Wang
Technical Communication


The main factors controlling floor failure depth are highly consistent with those of floor water inrush. In this paper, a mechanical model was developed to calculate the maximum failure depth of the upper and lower sides of a mining working face floor along the coal seam’s inclination. The results indicated that the main factors controlling floor failure depth are mining thickness, working face slanting length, coal seam dip angle, mining depth, water pressure, cohesion, and internal friction angle. The floor failure depth of the 3303 working face in the Yangcheng coal mine was calculated using FLAC3D numerical simulation software. Based on matrix and variance analyses, the sensitivity of each of these factors with respect to floor failure depth followed the order: working face slanting length (extremely significant) > mining depth (highly significant) > cohesion (significant) > mining thickness (not significant) > coal seam dip angle (not significant) > water pressure (not significant) > internal friction angle (not significant). Also, the optimal plan for orthogonal simulation is A1 B1 C1 D1 E2 F1 G1, in which the floor failure depth is minimized. Finally, the average accuracy of logistic regression analysis of the principal component was up to 90.4% accurate, about 10% better than conventional logistic regression analysis.


Floor aquiclude Variance analysis Principal component Logistic regression analysis 

Sensitivitätsanalyse der Haupteinflussfaktoren für die Grenzteufe von Sohlaufbrüchen und Risikoanalyse für Liegendwassereinbrüche eines geneigten Kohleflözes


Die für die Grenzteufe von Sohlaufbrüchen bestimmenden Haupteinflussfaktoren stimmen in hohem Maße mit den für Liegendwassereinbrüche verantwortlichen überein. In der vorliegenden Arbeit wird ein mechanisches Modell für die Berechnung der maximalen Versagensteufe für die obere und untere Begrenzung der Verhiebsfront im Einfallen eines Kohleflözes in geneigter Lagerung entwickelt. Die Ergebnisse weisen als Haupteinflussfaktoren für die Grenzversagensteufe aus: gebaute Mächtigkeit, Länge der Arbeitsfront, Einfallswinkel des Kohleflözes, Abbauteufe, Wasserdruck, Kohäsion und innerer Reibungswinkel. Die Sohlbruchgrenzteufe von Streb 3303 in der Kohlengrube Yangcheng wurde mit FLAC3D numerisch simuliert. Auf Basis von Matrix- und Varianzanalysen ergab sich für die Sensitivität jedes einzelnen Faktors in Bezug auf die Grenztiefe folgende Reihenfolge: Länge der Arbeitsfront (äußerst signifikant) > Abbauteufe (hochsignifikant) > Kohäsion (signifikant) > gebaute Mächtigkeit (unbedeutend) > Einfallswinkel des Kohleflözes (unbedeutend) > Wasserdruck (unbedeutend) > innerer Reibungswinkel (unbedeutend). Die optimale Vorgehensweise für die orthogonale Simulation ist A1 B1 C1 D1 E2 F1 G1, wobei die Grenzbruchteufe minimiert wird. Schließlich betrug die durchschnittliche Genauigkeit der logistischen Regressionsanalyse der Hauptkomponente bis zu 90,4% und war damit etwa 10% genauer als die konventionelle logistische Regressionsanalyse.

Análisis de sensibilidad de los principales factores de control de la profundidad de la falla del suelo y de una evaluación de riesgo de irrupción de agua a través del piso para una veta de carbón inclinada


Los principales factores que controlan la profundidad de una falla en el piso son altamente consistentes con aquellos que controlan la irrupción de agua a través del piso. En este trabajo, se desarrolló un modelo mecánico para calcular la máxima profundidad de falla en los lados superior e inferior de una cara de trabajo minero a lo largo de la una veta de carbón inclinada. Los resultados indicaron que los principales factores controlando la profundidad de la falla son el grosor de la minería, la longitud de inclinación de la cara de trabajo, el ángulo de inmersión de la capa de carbón, la profundidad de la mina, la presión del agua, la cohesión y el ángulo de fricción interno. La profundidad de la falla en el piso de la cara de trabajo 3303 en la mina de carbón Yangcheng se calculó usando el software de simulación numérica FLAC3D. Basado en análisis de matriz y varianza, la sensibilidad de cada uno de estos factores con respecto a la profundidad de la falla del piso siguió el orden: longitud de la inclinación de la cara de trabajo (extremadamente significativo) > profundidad de la minería (altamente significativo) > cohesión (significativo) > grosor de la minería (no significativo) > ángulo de inmersión de la capa de carbón (no significativo) > presión del agua (no significativo) > ángulo interno de fricción (no significativo). Además, el plan óptimo para simulación ortogonal es A1 B1 C1 D1 E2 F1 G1, en el cual se minimiza la profundidad de la falla del piso. Finalmente, la exactitud media del análisis logístico de regresión del componente principal fue hasta 90,4%, que es aproximadamente 10% mejor que el análisis logístico de regresión convencional.



底板破坏深度主控主因素与底板突水主控因素高度一致。本文建立力学模型计算工作面底板沿煤层倾向上、下两侧的最大破坏深度。结果表明,底板破坏深度主控因素包括采厚、工作面斜长、煤层倾角、水压、内聚力和内摩擦角。利用FLC3D数值模拟软件计算了阳城煤矿3303工作面的底板破坏深度。基于矩阵分析和方差分析,可得各主控因素对底板破坏深度的敏感性顺序为:工作面斜长(高度显著)>采深(较为显著)>内聚力(显著)>采厚(不显著)>煤层倾角(不显著)>水压(不显著)>内摩擦角(不显著)。正交模拟优化方案为A1 B1 C1 D1 E2 F1 G1,此时底板破坏深度最小。最终,主成分logistic回归分析平均精度达90.4%,比传统logistic回归分析精度高10%。



This work was supported by these projects of the National Natural Science Foundation of China (Grant 51274135), the National High Technology Research and Development Program (863 Program) of China (Grant 2015AA016404-4), and the State Key Research and Development Program of China (Grant 2017YFC0804108). This study used the free software SPSS, and the authors are grateful for the support of the SPSS development community. The authors sincerely appreciate the valuable comments from the journal’s reviewers.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Weitao Liu
    • 1
  • Dianrui Mu
    • 1
    Email author
  • Xiangxiang Xie
    • 1
  • Li Yang
    • 2
  • Donghui Wang
    • 1
  1. 1.College of Mining and Safety EngineeringShandong University of Science and TechnologyQingdaoChina
  2. 2.College of Foreign LanguagesShandong University of Science and TechnologyQingdaoChina

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