Statistical analysis of rock-burst events in underground mines and excavations to present reasonable data-driven predictors

Afraei, Sajjad; Shahriar, K.; Madani, Sayyed Hasan

doi:10.1080/00949655.2017.1367000

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…The relevant equation is shown below: Doerffel's test is useful in civil and mining engineering across numerous applications. Afraei et al [62] utilized the technique to treat their rockburst database with confidence in two different scenarios. Moreover, the test has provided a reliable method for determining uncertainty and correcting soil parameters [34].…”

Section: Peirce's Testmentioning

confidence: 99%

Review of Applicable Outlier Detection Methods to Treat Geomechanical Data

2023

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The reliability of geomechanical models and engineering designs depend heavily on high-quality data. In geomechanical projects, collecting and analyzing laboratory data is crucial in characterizing the mechanical properties of soils and rocks. However, insufficient lab data or underestimating data treatment can lead to unreliable data being used in the design stage, causing safety hazards, delays, or failures. Hence, detecting outliers or extreme values is significant for ensuring accurate geomechanical analysis. This study reviews and categorizes applicable outlier detection methods for geomechanical data into fence labeling methods and statistical tests. Using real geomechanical data, the applicability of these methods was examined based on four elements: data distribution, sensitivity to extreme values, sample size, and data skewness. The results indicated that statistical tests were less effective than fence labeling methods in detecting outliers in geomechanical data due to limitations in handling skewed data and small sample sizes. Thus, the best outlier detection method should consider this matter. Fence labeling methods, specifically, the medcouple boxplot and semi-interquartile range rule, were identified as the most accurate outlier detection methods for geomechanical data but may necessitate more advanced statistical techniques. Moreover, Tukey’s boxplot was found unsuitable for geomechanical data due to negative confidence intervals that conflicted with geomechanical principles.

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Section: Peirce's Testmentioning

confidence: 99%

Review of Applicable Outlier Detection Methods to Treat Geomechanical Data

2023

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“…Rock burst control around the roadway has become a difficult problem since the 20th century. Many scholars have proposed that the layout of the working face and the recovery roadway is an important condition influencing the extent of damage to the roadway in the case of rock burst [11,12]. However, coal and rock in the field are anisotropic in nature, unlike laboratory models.…”

Section: Introductionmentioning

confidence: 99%

Mechanisms and Models of Attenuation of Shock Waves through Rock Formations

Zhao

Gao

et al. 2023

Applied Sciences

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Rock bursts have become one of the worst disasters in deep mines, and the safety of roadways is affected by stress waves generated when hard roofs fracture. Pictures of a mine site were collected using the Hujiahe mine as a case study. The damage characteristics of the roadway were analyzed and the damage process was reproduced using numerical simulation software. The attenuation characteristics of the strength of the shock wave as it passes from the impact shock source to the roadway are summarized. Based on the stress wave transmission mechanism and geological characteristics, a “shock wave attenuation model through rock formations“ was established to analyze the transmission characteristics of impact stress under the composite roof structure. The strength criterion and energy balance equation for roadway damage under the action of shock waves are derived. This work provides a reference for roadway support under similar conditions and can be generalized and applied elsewhere.

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