An Application of Fuzzy Sets to the Blastability Index (BI) Used in Rock Engineering

Alipour, Aref; Mokharian, Mojtaba; Chehreghani, Sajjad

doi:10.3311/ppci.11276

Cited by 9 publications

(2 citation statements)

References 27 publications

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“…erefore, the effect of this single index evaluation method is not ideal. e second category uses soft mathematical calculation methods such as set pair analysis, neural network, cluster analysis, matter element extension method, and gray correlation analysis for comprehensive blastability classification [11][12][13][14][15][16]. Zhou et al [17] proposed a multifactor index system of rock mass blastability consisting of density, wave impedance, uniaxial compressive strength, and uniaxial tensile strength.…”

Section: Introductionmentioning

confidence: 99%

Classification Method and Application of Rock Fracture Ability by Supercritical CO2 Blasting

Zhu

Jia²,

Cai³

2022

Shock and Vibration

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In order to study the fracture ability classification of rock mass under the cracking action of supercritical CO2 phase transition, based on the classification theory of rock mass in blasting engineering, an analytic hierarchy process (AHP)-entropy weight method (EWM) and the cloud model classification method for rock mass cracking under CO2 phase transformation are proposed. In this method, rock density, rock tensile strength, rock wave impedance, and rock mass integrity coefficient are used as the factors to determine the level of rock mass fracturing, and the evaluation index system of rock mass fracturing is established. Through this evaluation method, the rock mass in a reconstruction project section of Nyingchi, Tibet, is classified and evaluated. The results present that this new classification method of rock mass fracture ability uses AHP–EWM to carry out the weight distribution of the classification index. In addition, it is combined with the cloud model for the classification division, overcoming the traditional classification method fixed with appraisal pattern flaw. Therefore, it has validity and feasibility. According to the characteristics of fracture ability, the rock masses in the area to be rebuilt on the Tibet Highway are divided into grade II, grade III, and grade IV, which provides scientific guidance for the construction of the project.

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Section: Introductionmentioning

confidence: 99%

Classification Method and Application of Rock Fracture Ability by Supercritical CO2 Blasting

Zhu

Jia²,

Cai³

2022

Shock and Vibration

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“…In Aref's study, the fuzzy algorithm was used to express the blastability index by employing fuzzy sets. Fuzzy BIs have more adjustment than conventional BI models [11]. Esmaeili et al analyzed the factors affecting rock fragmentation by Principal Component Analysis (PCA) and established a prediction model based on Support Vector Regression (SVR) and Adaptive Networkbased Fuzzy Inference System (ANFIS).…”

Section: Introductionmentioning

confidence: 99%

Improved Rock Engineering System (RES)- Multidimensional Cloud Evaluation Model and Its Application to the Rock Mass Blastability

Zhou

Kuang

et al. 2019

IEEE Access

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The blastability grading of a rock mass is an important parameter for the blasting design in metal mines. Appropriate blastability grading results guide the production to increase the efficiency and reduce the costs. In this paper, the multi-factors index system of the rock mass blastability consisting of the density, the p-wave velocity, the wave impedance, the uniaxial compressive strength, the rock elasticity, and the uniaxial tensile strength is determined for the Tongkeng ore in Guangxi, China. The determination of such indicator system is based on the multi-factors interaction, ambiguity, and randomness of the rock engineering system (RES). Based on the system engineering theory, a new improved RES-multidimensional cloud rock mass blastability classification model is established. The results show that the cloud-inference expert semi-quantitative (CESQ) can effectively obtain the expert experience and decrease the subjectivity of the traditional RES methods, and based on the improved fuzzy RES, the interaction factors among the factors and the systems affecting the blasting morphology of the rock mass are analyzed. Moreover, the importance of in situ testing of mechanical parameters of different rock masses is determined; finally, the five 6-D cloud models for the rock mass blastability grade are generated via the multidimensional cloud theory. The program is designed to support the engineering case analysis and is consistent with the results of the sample blasting experiment. A biased evaluation of the edge results is carried out, and this improved the actual usability of the evaluation model. INDEX TERMSAdvantage parameter, blastability, improve RES, multidimensional cloud model, rock mechanics.

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Fuzzy classification of rock engineering indices using rock texture characteristics

Mikaeil

Bakhtavar

Hosseini

et al. 2022

Bull Eng Geol Environ

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An Application of Fuzzy Sets to the Blastability Index (BI) Used in Rock Engineering

Cited by 9 publications

References 27 publications

Classification Method and Application of Rock Fracture Ability by Supercritical CO2 Blasting

Classification Method and Application of Rock Fracture Ability by Supercritical CO2 Blasting

Improved Rock Engineering System (RES)- Multidimensional Cloud Evaluation Model and Its Application to the Rock Mass Blastability

Fuzzy classification of rock engineering indices using rock texture characteristics

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