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Abstract
Uncertainty measure theory and dependent function are combined rationally and then applied to evaluating underground cavern rock quality. According to influence factors and grading standards of underground cavern rock quality, uncertainty measure functions of evaluation indices are obtained using the uncertainty measure theory. Dependent function is used to calculate weights of the evaluation indices of underground cavern rock quality. Credible degree recognition criteria are used to evaluate underground cavern rock quality. Finally, the comparative analysis is made with examples. The results show that the uncertainty measure method is reasonable and reliable; and it is a new method for evaluating underground cavern rock quality.
... Extension theory is a widely used nonlinear method [7][8][9][10]. In addition, there unascertained measure theory [11], rough set and artificial neural network [12], reduction concept lattice, and fuzzy optimization are used [13]. The existing research methods only consider the influence of one of the factors at a time. ...
In this study, the K-means algorithm based on particle swarm optimization (K-PSO) and game theory are introduced to establish the quality evaluation model of a rock mass. Five evaluation factors were considered, i.e., uniaxial saturated compressive strength of rock, discontinuity spacing, acoustic velocity, rock quality designation (RQD), and integrity coefficient. The rock mass of an elevation adit at the abutment of Maji hydropower station was taken as a case study. The subjective weight of the evaluation factor was determined by the weighted least squares method, and the objective weight of the evaluation factor was determined by the entropy method. The combined weights of each influencing factor were determined by game theory to be 0.142, 0.179, 0.035, 0.116, and 0.108. The rock mass quality evaluation in the study area was analyzed by K-PSO algorithm. The results indicate that the K-PSO clustering results are almost the same as the evaluation results of the traditional basic quality (BQ) classification method and the widely used extension evaluation method and are consistent with the preliminary judgment of the expert field. The results are consistent with the field observation law. It is considered that the K-PSO clustering theory can reflect the engineering geological characteristics of the rock mass of the hydropower project in the rock mass quality evaluation.
... Finally, the pressure sensor in the probe converts the pressure change into electrical signal output. After passing through the preamplification circuit in the probe, it is sent to the ground electronic instrument through the cable [25][26][27][28][29]. e in situ stress test tool is shown in Figure 6. ...
With the continuous increase in the mining depth of underground mineral resources, the geological conditions encountered in mining have become more complex. The complex geological conditions have led to varying degrees of roof damage, especially the frequent occurrence of roof collapse accidents in metal mines, causing huge losses to mining enterprises. How to evaluate the risk of roof subsidence, falling, and even collapse under different geological conditions has become the primary issue. This article first selects the main evaluation indicators in the domestic and foreign roadway roof failure research literature for statistical analysis. Then, according to the statistical results, a classification approach of roof damage degree using the fuzzy comprehensive clustering method is established with roof rock strength, broken degree, roadway section size, buried depth, and roof sinking amount as evaluation indicators. The damage of the top plate is divided into five grades: minor damage, obvious damage, serious damage, extremely serious damage, and devastating damage. Finally, the established evaluation method was applied to the project site-supporting work of the 760 m main transport roadway in Yunnan Maoping Lead-Zinc Mine. The evaluation result is consistent with the actual situation on-site. The research results can provide a reference for the roof stability analysis under the background of this project and similar projects and at the same time help the next step in the classification control of different levels of roof stability and the design of the overall roadway support.
... Unascertained measurement theory, as one of the comprehensive evaluation models, has obtained great popularity with excellent adaptability for sample classification and the optimal object selection. This theory has been applied to cope with the objectives that contains unascertained information in various complex subject areas [60][61][62][63][64][65], especially, refers to the overall analysis/evaluation. Zhou et al. [66,67] evaluated the rockburst hazards and blastability of target zone, separately, based on unascertained measurement model. ...
In recent years, block caving has drawn the attention of many mine enterprises due to the admired extraction rate and lower cost, which can exploit the materials via gravity inflow. At the same time, the limitation of this advanced method cannot be underestimated easily, such as surface subsidence and boulder, usually, the latter leads to the frequent secondary blast and damage of bottom structure. Thus, it is significant and crucial to evaluate the fragmentation before the implement of this method. But, traditional fragmentation assessment model suffers from the complex process of modeling and simulation. In this study, a hybrid model consists of unascertained measurement theory and information entropy was constructed to meet the requirements of this prospective mining method. Considering the influence of various parameters on rock fragmentation at the same time, twenty-three factors (i.e., uniaxial compressive strength, modulus ratio, fracture frequency, aperture, persistence, joint orientation, roughness, infilling, weathering, in situ stresses, stress orientation, stress ratio, underground water, fine ratio, hydraulic radius, undercut height, draw column height, draw points geometry, draw rate, multiple draw interaction, air gap height, broken ore density and undercut direction) were chosen to extract the main characteristics of rock mass samples from the two different mines, namely Reserve North (Chile), Diablo Regimiento (Chile) and Kemess mine (Canada). A new membership function (logarithm curve) was added to eliminate uncertainty results from the low level of knowledge about rock mass properties. Then, information entropy was performed to quantify the impacts of individual index. A credible degree identification criterion (Rη) was also applied to review the sample attributes qualitatively. Ultimately, degree of fragmentation of the three samples was judged easily on the basis of a composite measurement vectors and Rη. The evaluation results showed that the fragmentation grades of Reserve North, Diablo Regimiento and Kemess mine, separately, were “Good”, “Medium” and “Good”. With regard to the excellent performance of this hybrid model, it can be seen as a reliable approach to describe the fragmentation potential during the ore extraction using block caving mining method.
In order to objectively obtain accurate and reliable rock quality evaluation results, a heterogeneous ensemble evaluation method based on improved D-S evidence theory is proposed for the existing individual evaluation models which are prone to misjudgment and bias. Firstly, based on determining the rock mass quality evaluation standard and data set, 6 heterogeneous base classifiers are used to train the data set, and the preliminary rock mass quality evaluation results are obtained. Then, each base classifier is taken as a piece of evidence, and the evidence is integrated through the improved D-S evidence theory to form a comprehensive evaluation result, to solve the inconsistency of the results of the existing evaluation methods. Based on 30 groups of samples, a heterogeneous ensemble evaluation model based on improved D-S evidence theory was constructed and applied to the rock mass quality evaluation of the Guangzhou Water pumping and storage power station Phase II project. The results show that the heterogeneously ensemble evaluation method based on the improved D-S evidence theory improves the accuracy and reliability of rock mass quality grade identification, avoids the subjectivity and uncertainty in the evaluation process, and has high engineering practical value. 为客观获取准确可靠的岩体质量评价结果，针对现有单个评价模型容易产生误判与偏倚现象，提出基于改进 D-S证据理论的岩体质量异质集成评价方法。首先，在确定岩体质量评价标准与数据集的基础上，采用 6 个异质基分类器对数据集进行训练，获得初步岩体质量评价结果。然后，将每个基分类器作为一条证据，经过改进 D-S 证据理论对各证据进行集成，形成综合评价结果，解决现有评价方法结果的非一致性问题。以 30 组样本构建基于改进 D-S 证据理论的异质集成评价模型，并运用于广州抽水蓄能电站二期工程岩体质量评价中。结果表明：基于改进 D-S 证据理论的异质集成评价方法提高了岩体质 量等级的识别准确性和可靠性，能够避免评价过程中的主观性与不确定性，具有较高的工程实用价值。
By studying tunnel face images collected during a highway tunnel excavation, we establish the classification system of photolithography by MATLAB programming. According to the rock mass index (rock block size index or RBI) concept, 19 virtual lines are arranged in turn to the tunnel contour line, and the difference of the brazier rock mass structure is evaluated synthetically by 19 RBs of the radial direction of the face. Based on the structure, the distribution of comprehensive index of the rock mass structure (Z-RBI) is obtained through a comprehensive evaluation of the rock surface, and the corresponding relationship between the Z-RBI and rock structure type is determined. Considering the hardening degree of rock mass, the Z-RBI, groundwater condition, and initial geostress state, we propose the BP classification method for tunnel rocks, and we evaluated the BT method by using the analytic hierarchy process standard in an actual project. The comparison of the BT classification method and traditional BQ method reveals that the result of the former is more in accordance with the actual level of the excavated rock face than that of the latter method.
Owing to multi-objectivity and uncertainty in the evaluation of rock stability, the modified analytic hierarchy process (AHP) and the entropy method are used to calculate the weights of factors. On this basis, a new combination rule is proposed to determine the weight which can help us to get a relatively objective and accurate result. According to the influence factors and grading standards of the rock stability, six qualitative indices and eight quantitative indices are selected. Based on the combined weighting-unascertained measurement theory coupled valuation model, the stabilities of 12 surrounding rocks in the study area are assessed and analyzed by using the unascertained measurement function, combination weighting and confidence criterion. The stability of each surrounding rock is obtained. Compared with the results of field evaluation and fuzzy matter-element, the evaluated results are consistent with the actual situations. Therefore, the combination weighting- unascertained measurement theory evaluation model is scientifically reasonable for the rock stability. The integrality of assessment object information is ensured, and the accuracy, objectivity and reliability of the evaluated results are guaranteed. The proposed model can be applied to the actual projects. © 2016, Editorial Office of Chinese Journal of Geotechnical Engineering. All right reserved.
Landslide susceptibility assessment and prediction are the important contents of the first solution for the decision-making of prevention and mitigation of disaster. Starting from the geological environmental conditions within Longzi county in Tibet, the 13 influencing factors are selected, including elevation, slope and so on. According to landslide risk classification standards established, landslide risk rating is divided into high, moderate and low. Based on combination weighting-unascertained measure theory coupled evaluation model, 20 landslides' risks in study area are assessed and analyzed by unascertained measure function, combination weighting and confidence criterion. Each landslide risk is obtained. Compared with evaluation results of fuzzy matter-element and catastrophe theory, the evaluation results are consistent with actual situation and reasonable. Therefore, the model can provide a new idea for landslide risk prediction.
Combined with the uncertainty measurement theory and analytic hierarchy process (AHP), a mining method optimization model was established. During this process, variable uncertainty factors which influenced mining method were taken into account, and some appropriate factors were selected as evaluation index. According to the classification standards of each index, a single index measure function was constructed, the uncertainty measurement of each index was calculated, and the weights of the influence factors matrix were established according to the AHP method. The evaluating grade was determined with credible degree recognition criterion, superior degrees were measured and finally the optimization results were obtained. Taking Yaogangxian Wolfram Mine for example, the results show that the three methods' evaluation levels are III, I and II, and superior degrees are 1.480 0, 2.501 6 and 1.973 6, indicating that the second method is the optimal. ©, 2014, Central South University of Technology. All right reserved.
For the purpose of legitimately determining each major factor weight and objectively analyzing debris flow susceptibility, a model for analyzing debris flow susceptibility is established based on minimum entropy analysis and uncertainty measurement theory. Nine major factors of 26 typical debris flows along Jinsha River are selected. By utilizing the minimum entropy analysis, the contribution rate to debris flow system and weight of each major factor are obtained. And then, the multi-index comprehensive evaluation measure vector of each debris flow catchment is determined based on the uncertainty measurement theory. The final susceptibility degree is acquired by credible degree recognition criteria. By comparing the debris-flow susceptibility results with reference [11], we find that only seven debris flow catchments are different. Comparing the susceptibility results with field observations, 22 of 26 debris flow catchments agrees very well with real status of debris flow; and the susceptibilities of four debris flow catchments are conservative. Thus, the proposed model is shown to be quite effective in predicting debris flow susceptibility, which can be applied to actual engineering; and the analyzing results can provide rational suggestion for debris flow prevention.
In order to effectively solve the problems of fuzziness and randomness existing in the process of rock quality evaluation of dam foundation, a new approach of comprehensive evaluation on rock quality of dam foundation is proposed based on cloud model after analyzing the influence factors and grading standards. First, by means of constructing the antecedent and consequent cloud models and the uncertainty reasoning of cloud, the qualitative comment of each evaluation index is quantified into specific score value. Then, combined with the weight coefficient of each evaluation index, the total scores of dam foundation rock needed to be evaluated are obtained, which are helpful to determine the quality level. The results of case analysis and contrastive study indicate that this approach is feasible, moreover, the calculation steps are simple and the method can be easily realized by programming, which provides new ideas and means for the evaluation on rock quality of dam foundation.
It's a top priority to estimate risk of landslides for landslide disaster prevention and disaster reduction. In this paper, taking Xiaojiang ravine, a frequent debris flow occurring area as the study area, a classification assessment system of landslide risk is built by selecting 3 evaluation indexes including slope, cohesive force and internal friction angle based on the geographic information system support. Moreover, the projection pursuit technique is applied to evaluate landslide risk classification. According to linear projection of index factors of evaluation samples, the projection pursuit model to classification evaluation of landslide risk is built and the classification map of landslide risk zoning is drawn by the optimal projection direction of the projection characteristic value. The results show that the area ratio of extremely high risk zone, high risk zone, medium risk zone, low risk zone, extremely low risk zone in the study area is 14.28:9.41:69.12:7.00:0.19. A total of 60 landslides were verified in the study area according to the established evaluation index system of level 5. The high and extremly high risk zones cover 23.69% of the study area, but the actual number of soil landslides is 45, and the number of soil landslides in those risk zones is 75.00% of the total. The number of soil landslides in medium risk level and above risk zones is 96.67% of the total. The statistical results of landslide risk point density in the classification map of landslide risk zoning show that the density of landslides' volume increases rapidly with the increase of risk level. The evaluation results are relatively more consistent with actual situation and more reasonable compared with the measured results. The model proves to be a new perspective for landslide risk prediction.
Based on contrast analysis of tunnel surrounding rock classification method, five basic indicators were selected as evaluation factors. Evaluation matrix was constructed by uncertainty measurement theory. Weight was established by introducing drifting degree concept. The principle of maximum membership degree was choosed as evaluation criterion.Then a tunnel surrounding rock classification model was built.This comprehensive evaluation method made full use of its own parameters and evaluation standard to completely avoid the subjective influence of traditional weights determination and the sample set, making itself more objectivity and accuracy, having a strong operability. The practical engineering showed that this model applied to tunnel surrounding rock classification was feasible and had certain superiority, providing a new way for tunnel surrounding rock classification.
In order to describe quantitatively the degree of possessing the unascertained nature or the degree of being in the unascertained state, a concept of unascertained measure satisfying measure criteria in the measurable space is defined. Then it is used as a membership function, and based on it, the concept of unascertained set in domain is introduced, the operations of the unascertained set are defined. The usefulness of the new uncertainty set is illustrated via discussing the relationship and essential difference between the unascertained set and the fuzzy set. On the basis of unascertained set, an unascertained logic system is set up, and it can be used to deal with the uncertain information. A new concept, weight of index classification, is defined, its calculation method is given, and is applied to the reasoning algorithm in the unascertained logic system, which makes the complex reliability well explicable. Finally, an example in fault diagnosis is presented to show the effectiveness of the proposed unascertained logic system.
The extension engineering method is combined with tunnel rock evaluation. In view of the variety and complexity of the factors influencing rock quality, the parameters reflecting the general rock engineering are taken into account for evaluation. On the basis of matter-element theory, extension set theory and dependent function calculation, a matter-element model calculating procedure is proposed. By practical calculation of the dependent degree to the quality classification of the tunnel rock, the Shibeiling tunnel rock is evaluated by extenics. Compared with the evaluation results by the former RMR method, the rock quality evaluation results obtained by the extenics method can more precisely reflect the engineering characteristics of tunnel rock.
The method of fuzzy synthetical assessment applied to rock mass classification results in losing information of judgment, then influences veracity and reliability of the result. In allusion to the limitation, the theory of barycentei of fuzzy set is imported. Because weights of some factors is relative small, if using usual fuzzy synthetical assessment method, it will result in phenomenon of submerge. However, this problem does not exist now. Based on this theory, the six more important influential factors for rock mass classification such as index of rocky quality, uniaxial strength of renitency, integrated modulus of rock mass, soft modulus of rock, maximal seismic intensity and osmotic quantity of groundwater, are chosen; then the normal distribution as its membership function and the theory of the mean are used based on proportion to conform weights of the whole factors. Thus the method of rock mass fuzzy synthetical classification based on the theory of fuzzy set has been established. The calculational method of barycenter of fuzzy set of the whole factors is clarified combining a material project example. Finally, the method of rock mass fuzzy classification based on the theory of barycenter of fuzzy set is used to research the steady classification of a certain underground wall rock. Compared to the result of the method of fuzzy synthetical assessment and the actual steady instance of the wall rock, the veracity and the applicability of the textual method are validated.
The matter element model of cavern rock quality evaluation is established using matter element model theory based on extension engineering method. The stratification analysis method used to calculate weight aggregation of evaluating factors is proposed. Through calculating the relational degree of the actual cavern rock quality grades, the rock quality of Shuibuya Waterpower Station cavern is evaluated by extenics, and the conclusion has good relation with the facts. It is shown that stratification analysis method is feasible to calculate the weight aggregation of evaluating factors. The extenics evaluation of cavern rock quality with high applicability can more precisely reflect the quality classification of the cavern rock.
The role of rock mass classifications in site characterization and project planning is critically reviewed, and their advantages as well as common pitfalls are identified. In particular, the Rock Mass Rating system (Geomechanics Classification) described in detail together with the scope of its applications and the database on which it was developed. It is concluded that the RMR system has established itself as a versatile method for assessing rock mass conditions on engineering projects. The system has withstood the test of time and is backed by 351 case histories, demonstrating its reliability and ease of use. -from Author
A result of safety evaluation was educed according to the rules of credible recognition after a index system in colliery ventilation safety evaluation was established. An unascertained measure model was constructed and the unascertained measure values of all evaluation indexes were calculated. This method can solve a lot of unascertained problems in ventilation system evaluation, and also can analyze the ventilation system quantitatively. Exemplification indicates that the evaluation result is consistent with actual instance if the method of unascertained measure evaluation is applied in colliery ventilation safety evaluation.