工程岩爆灾害判别的RBF-AR耦合模型

岩爆是深部高地应力区地下岩体工程中的主要工程地质灾害之一,其发生及烈度预测是一个复杂的不确定系统问题。为了有效预测和判别深部工程岩爆灾害,在总体考虑岩爆各影响因素的基础上,选取地下工程中岩体完整性指数、岩石单轴抗压强度、岩石单轴抗拉强度、围岩最大切向应力、围岩抗压强度与其抗拉强度的比值、围岩切向应力与围岩抗压强度比值、弹性能量指数、岩爆倾向性指数作为岩爆预测的评判指标,提出了一种基于非线性参数优化的RBF-AR岩爆预测模型。在终南山隧道竖井岩爆判别中,利用RBF-AR法进行计算,计算结果与实际情况完全一致,表明该模型在岩爆预测中的可行性和有效性。     

Prediction of Uniaxial Compressive Strength,Tensile Strength and Porosity of Sedimentary Rocks Using Sound Level Produced During Rotary Drilling

The main purpose of the study is to develop a general prediction model and to investigate the relationships between sound level produced during drilling and physical properties such as uniaxial compressive strength, tensile strength and percentage porosity of sedimentary rocks. The results were evaluated using the multiple regression analysis taking into account the interaction effects of various predictor variables. Predictor variables selected for the multiple regression model are drill bit diameter, drill bit speed, penetration rate and equivalent sound level produced during rotary drilling (L _eq). The constructed models were checked using various prediction performance indices. Consequently, it is possible to say that the constructed models can be used for practical purposes.     

Relationship Between Petrographic Characteristics and the Engineering Properties of Jurassic Sandstones, Hamedan, Iran

To study the relationship between engineering properties and petrographic characteristics, 20 rock samples were collected from Jurassic sandstones in the Hamedan region, western Iran. The specimens were tested to determine uniaxial compressive strength, point load strength index, tangent modulus, porosity, and dry and saturated unit weights. Samples were also subjected to petrographic examination, which included the observation of 11 parameters and modal analysis. Based on the results of a statistical analysis, polynomial prediction equations were developed to estimate physical and mechanical properties from petrographic characteristics. The results show that textural characteristics are more important than mineral compositions for predicting engineering characteristics. The packing density, packing proximity and grain shape are the petrographic properties that significantly affect the engineering properties of samples. Multivariate linear regression analysis was performed, employing four steps comprising various combinations of petrographic characteristics for each engineering parameter. The optimal equation, along with the relevant combination of petrographic characteristics for estimating the engineering properties of the rock samples is proposed.     

Correlation of mineralogical and textural characteristics with engineering properties of selected granitic rocks from Turkey

Granitic rocks show a variety of engineering properties that may affect quarrying operations, tunneling, mining, slope stability and the use of rock as a construction material. The physical and mechanical properties are a function of the mineralogical and textural characteristics of the rock. The purpose of this study is to apply correlation analysis to investigate the relationships between petrographical and engineering properties of granitic rocks. A variety of granitic rock samples from different parts of Turkey were subjected to petrographic studies. The same samples were then tested to determine specific gravity, dry and saturated unit weight, water absorption, effective and total porosity, sonic velocity, Schmidt hardness, point load strength index, uniaxial compressive strength, tensile strength and modulus of elasticity. The relationships between these properties and the petrographical characteristics are described by simple regression analyses. The study revealed that the influence of the textural characteristics on the engineering properties appears to be more important than the mineralogy. It also determined that the types of contacts, grain (mineral) shape and size significantly influence the engineering properties of the granitic rocks.     

基于岩石地质本质性的碳酸盐岩单轴抗压强度预测

充分认识岩石的地质本质性是准确描述其物理力学特性的桥梁。岩石的地质本质性涵盖了岩石的物质性、结构性和赋存状态3个方面的内容。在综合考虑岩石上述3方面特征及其与单轴试验联系的基础上,以矿物组成、密度、纵波波速和含水状态为基本指标,采用回归和BP神经网络的方法对碳酸盐岩单轴抗压强度进行预测,并采用灰色关联分析法验证本研究所选用的预测基本指标的合理性。实例应用表明：本次采用的回归方法对该类岩石强度预测的最大误差为15.3%,BP神经网络方法预测的最大误差为8.5%。预测误差出现的原因为碳酸盐岩物质组成复杂,所选预测基本指标是实际情况的简化,同时泥灰质岩石所具有的膨胀性也导致实测和预测结果具有一定的差异。     

Artificial neural network model for prediction of rock properties from sound level produced during drilling

In many rock engineering applications such as foundations, slopes and tunnels, the intact rock properties are not actually determined by laboratory tests, due to the requirements of high quality core samples and sophisticated test equipments. Thus, predicting the rock properties by using empirical equations has been an attractive research topic relating to rock engineering practice for many years. Soft computing techniques are now being used as alternative statistical tools. In this study, artificial neural network models were developed to predict the rock properties of the intact rock, by using sound level produced during rock drilling. A database of 832 datasets, including drill bit diameter, drill bit speed, penetration rate of the drill bit and equivalent sound level (L_eq) produced during drilling for input parameters, and uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density (ρ), P-wave velocity (V_p), tensile strength (TS), modulus of elasticity (E) and percentage porosity (n) of intact rock for output, was established. The constructed models were checked using various prediction performance indices. Goodness of the fit measures revealed that recommended ANN model fitted the data as accurately as experimental results, indicating the usefulness of artificial neural networks in predicting rock properties.     

多尺度节理岩体力学特性的颗粒流分析

以白云鄂博露天铁矿东矿岩质高边坡为工程背景,结合现场地质调查、室内岩石和节理力学试验等数据,采用等效岩体技术,构建能充分反映节理分布特征的实验室、现场原位试验和工程尺度等多尺度等效岩体模型。通过对各类等效岩体模型进行单轴压缩试验,研究岩体单轴抗压强度、弹性模量等力学特性的尺寸效应和各向异性。研究表明：节理的存在使岩体表现出尺寸效应和各向异性,且随着尺寸的增大,这种特性基本呈逐渐减弱的趋势;研究区域岩体的表征单元体积、单轴抗压强度和弹性模量分别为20 m×10 m×10 m、1.46 MPa和3.91 GPa;岩体单轴抗压强度、弹性模量与轴向尺寸的关系,近似符合渐进式指数函数关系,且该函数能直观地给出工程尺度岩体的力学特性。     

基于熵权正态云模型的软岩等级评价

软岩是地下工程施工中常见的复杂地质情况之一,科学准确的对其分类是进行安全施工的重要前提。针对软岩环境的复杂性和不确定性,选取单轴抗压强度σ_c、完整性系数K_v、黏聚力σ_n、软化系数K_f和软化指数f_s 5项定量化指标建立软岩评价指标体系,采用熵权法确定各指标权重,结合云理论建立熵权-正态云模型,对软岩的类型进行分级评价。以4组软岩工程实例对所建立模型进行检验,并与未确知度法、模糊评价法和BQ法的判别结果进行对比。研究结果表明,熵权-正态云模型在软岩等级判别中具有良好的实用性和可靠性,可为软岩类型预测提供一种新思路。      

基于H-B准则的公路桥梁桩基嵌岩深度计算

基于Hoek-Brown强度准则,推导了在微小转动下嵌岩段桩侧法向应力及水平摩阻力计算模型,采用静力平衡原理建立了水平荷载作用下公路桥梁桩基嵌岩深度的计算公式,提出了嵌岩深度计算的新方法。参数敏感性及影响因素分析表明： （1）水平荷载引起的力矩 、桩径d、岩层上覆压力 、岩石单轴抗压强度 、岩体类别参数 、岩体地质力学分类指标RMR均对嵌岩深度有一定影响,在 、d不变的情况下,岩体质量和岩石单轴抗压强度对嵌岩深度的确定最为敏感; （2）岩体质量越差,所需嵌岩深度越大;岩体质量越好,岩层上覆压力对嵌岩深度影响越小,反之越大。（3）嵌岩深度随岩石单轴抗压强度的提高呈非线性缓慢地减小,在相同的单轴抗压强度下,岩体质量越好,嵌岩深度越小,反之越大。     

Artificial neural networks and nonlinear regression techniques to assess the influence of slake durability cycles on the prediction of uniaxial compressive strength and modulus of elasticity for carbonate rocks

Understanding rock material characterizations and solving relevant problems are quite difficult tasks because of their complex behavior, which sometimes cannot be identified without intelligent, numerical, and analytical approaches. Because of that, some prediction techniques, like artificial neural networks (ANN) and nonlinear regression techniques, can be utilized to solve those problems. The purpose of this study is to examine the effects of the cycling integer of slake durability index test on intact rock behavior and estimate some rock properties, such as uniaxial compressive strength (UCS) and modulus of elasticity (E) from known rock index parameters using ANN and various regression techniques. Further, new performance index (PI) and degree of consistency (Cd) are introduced to examine the accuracy of generated models. For these purposes, intact rock dataset is established by performing rock tests including uniaxial compressive strength, modulus of elasticity, Schmidt hammer, effective porosity, dry unit weight, p‐wave velocity, and slake durability index tests on selected carbonate rocks. Afterward, the models are developed using ANN and nonlinear regression techniques. The concluding remark given is that four‐cycle slake durability index (I_d4) provides more accurate results to evaluate material characterization of carbonate rocks, and it is one of the reliable input variables to estimate UCS and E of carbonate rocks; introduced performance indices, both PI and Cd, may be accepted as good indicators to assess the accuracy of the complex models, and further, the ANN models have more prediction capability than the regression techniques to estimate relevant rock properties. Copyright © 2011 John Wiley & Sons, Ltd.     

基于岩爆危险性评价的川藏铁路某深埋硬岩隧道线路方案比选研究

川藏铁路穿越区域地形起伏大,区域地质构造作用强烈,隧道建设中面临的高地应力问题异常复杂,特别是深埋硬岩隧道中的岩爆灾害问题,成为制约选线、设计乃至施工建设的难题。由于隧道工程地质条件复杂,如果岩爆评价指标针对性不强,往往会造成评价结果与实际偏差较大。通过综合分析影响岩爆的关键因素,选取岩石单轴抗压强度与洞壁最大主应力比、洞壁最大切向应力与岩石单轴抗压强度比、岩石强度脆性系数、岩石弹性能指数及岩体完整性系数建立了岩爆评价指标体系。根据熵权法确定各指标权重,基于理想点的基本理论及计算规则,构建了一种岩爆危险性评价模型。通过计算各里程段与理想点的距离,对新建川藏铁路某隧道的3种线路方案进行岩爆风险评估的综合比选。研究结果表明B线路总岩爆段落占比24.9%,其中不可控岩爆段落占比13.4%,比另外两条比选方案低4%左右,综合对比B线路为最优方案。该方法可为深埋硬岩隧道地质综合选线提供必要的科学依据和技术支撑。     

Assessment of weathering processes effect on engineering properties of Alvand granitic rocks (west of Iran), based on weathering indices

The Alvand batholith is one of the largest plutonic bodies in the west of Iran. In this research, several physico-mechanical tests have been performed on granodiorite and porphiroid monzogranite consisting of five degrees of weathering in Hamedan area, west of Iran. Furthermore, weathering process of Alvand granitoid is studied by chemical analysis and petrographical studies. The results indicated that engineering properties of weathered granodiorite and monzogranite vary over the wide range depending on the degree of weathering. On the other hand, this research is focused on the assessment of relationship between weathering indices and uniaxial compressive strength. For this reason, some of the most important weathering indices are reviewed. It should be noted that, application of these chemical, engineering and petrographical indices are good quantitative indicators for describing the degree of weathering. Using these indices for the assessment of uniaxial compressive strength of granodiorite and monzogranite rocks, yields suitable and meaningful results.     

基于量纲分析的岩石相似材料抗压强度计算模型

物理相似模型试验是复杂、难采矿技术研究的有效手段,而岩石相似材料物理力学特性的研究是试验有效进行的前提。根据相似原理和岩石的力学特性,论证了岩石相似材料单轴抗压强度的力学代表性。统计并分析了影响岩石相似材料单轴抗压强度的一系列因素,基于量纲分析的方法构建了岩石相似材料单轴抗压强度与砂粒径、配比材料总量、充填材料（砂）用量、水用量、养护方式等重要因素间的无量纲计算模型,结合岩石相似材料配比试验得到了定量关系式。选取3组具有代表性的岩石相似材料配比试验对所建立的单轴抗压强度计算关系式进行验证,其计算结果与实验室实测结果相吻合,平均误差为4.20%,定量关系式在岩石相似材料参数的研究上具有一定的合理性。研究结果可以为相似材料物理力学参数的预测及岩土工程物理模型试验相似材料的高效选取提供参考。     

Damage Constitutive and Failure Prediction of Artificial Single-Joint Sandstone Based on Acoustic Emission

The effect law of deformation and failure of a jointed rock mass is essential for underground engineering safety and stability evaluation. In order to study the evolution mechanism and precursory characteristics of instability and failure of jointed rock masses, uniaxial compression and acoustic emission (AE) tests are conducted on sandstones with different joint dip angles. To simulate the mechanical behavior of the rock, a jointed rock mass damage constitutive model with AE characteristic parameters is created based on damage mechanics theory and taking into account the effect of rock mass structure and load coupling. To quantify the mechanism of rock instability, a cusp catastrophe model with AE characteristic parameters is created based on catastrophe theory. The results indicate that when the joint dip angle increases from 0° to 90°, the failure mechanism of sandstone shifts from tensile to shear, with 45° being the critical failure mode. Sandstone's compressive strength reduces initially and subsequently increases, resulting in a U-shaped distribution. The developed damage constitutive model's theoretical curve closely matches the test curve, indicating that the model can reasonably describe the damage evolution of sandstone. The cusp catastrophe model has a high forecast accuracy, and when combined with the damage constitutive model, the prediction accuracy can be increased further. The research results can provide theoretical guidance for the safety and stability evaluation of underground engineering.

     

Prediction of hollows in abandoned underground workings at shallow depth

Composite statistical analysis of the lithological composition of the rock mass above underground workings in coal seams and experimental work (laboratory mechanical tests and boring for the determination of hollows) in Donetsk city (Ukraine) have been used to develop a method for predicting the presence of hollows. The empirical criteria K₁–K₂>0 and K₃2.5 which relate to the physical characteristics of the overlying strata were found to predict the existence of such hollows in abandoned underground workings at shallow depth. The values of K₁–K₂ and K₃ depend on the thicknesses of the different rock layers and the uniaxial compressive strength of the immediate roof over underground openings. The different layers e.g. sandstones, argillites, aleurolites and alluvium in the rock mass are shown to influence the existence of hollows in abandoned workings. Large thicknesses of sandstones in the rock mass or relatively high uniaxial compressive strength rock in the immediate roof contribute to the existence of hollows in abandoned workings. On the other hand, sandstones of small thickness, weak alluvium, argillites and aleurolites only give additional weight on immediate roof of the opening and allow collapse of the rock mass. The method of prediction for hollows was developed from the back-analysis of data from 41 boreholes which were drilled from the ground surface above underground openings.     

An investigation of the relationship between uniaxial compressive strength and degradation for selected rock types

The relationship between uniaxial compressive strength and degradation was investigated for selected rock types, by using regression analyses to determine whether degradation was a useful predictor of compressive strength. In addition, the effects of aggregate particle size, number of hammer blows during the degradation test, engineering index properties, petrographic characteristics, and water saturation on the compressive strength-degradation relationship were evaluated. The results show that strong inverse relationships exist between compressive strength and degradation (measured on a 9.5-4.75-mm size aggregate) for sandstones and igneous/metamorphic rocks, but that no significant relationship exists for limestones/dolomites. The results also indicate a strong positive correlation between degradation and L.A. abrasion loss and can be used to establish a limit of allowable degradation for practical applications. Engineering index properties do not significantly affect the relationship between compressive strength and degradation but petrographic characteristics are important in explaining the strength and degradation behavior of the rocks studied. Water saturation decreases compressive strength and increases degradation to varying degrees.     

A new rock mass classification for Coal Measures Rocks

This paper examines a new rock mass classification system (RMCR) for Coal Measures Rocks which is based on extensive laboratory testing results. The new system has been developed using 12 parameters which consist of mineral content index, uniaxial compressive strength, uniaxial tensile strength, Young's modulus of elasticity, shear strength, cohesion of rocks, angle of internal friction, point load index, cone indenter index, Cerchar index, Shore schleroscope hardness and specific energy index. The RMCR value was obtained by a number of laboratory and in situ testing results which were obtained from the coal site. The objective of the RMCR is to estimate the rock mass properties for engineering purposes.     

基于人工神经网络模型的岩石特性预测

近年来,软计算技术被用作替代的统计工具。如人工神经网络（ANN）被用于开发预测模型来估计所需的参数。在本研究中,通过利用冲击钻进过程中的一些钻进参数（气压、推力、钻头直径、穿透率）和所产生的声级,建立了预测岩石性质的神经网络模型。在实验室中所产生的数据,用于开发预测岩石特性（如单轴抗压强度、耐磨性、抗拉强度和施密特回弹数）的神经网络模型,并使用各种预测性能指标对所建模型进行检验,结果表明人工神经网络模型适用于岩石性质的预测。     

基于P波模量的岩石单轴抗压强度预测

传统获取岩石单轴抗压强度参数需要钻进取样、加工制作等严格的试验步骤,需要建立一种参数易于获取且准确的岩石单轴抗压强度预测公式。基于岩石物理力学参数的内在联系,建立了岩石单轴抗压强度与岩石P波模量的关系式。根据英安斑岩和页岩两种岩石的干密度、P波速度及单轴抗压强度的测试数据,采用线性拟合的方法建立了岩石基于P波模量的单轴抗压强度预测公式,并采用统计检验的方法对上述预测公式与传统基于P波速度的预测公式进行了对比分析。结果表明,所建立的强度预测通式简单、精度高,模量容易获取,具有很强的实用性。     

Effects of Rock Properties on Specific Cutting Energy in Linear Cutting of Sandstones by Picks

Summary. Specific cutting energy (SE) has been widely used to assess the rock cuttability for mechanical excavation purposes. Some prediction models were developed for SE through correlating rock properties with SE values. However, some of the textural and compositional rock parameters i.e. texture coefficient and feldspar, mafic, and felsic mineral contents were not considered. The present study is to investigate the effects of previously ignored rock parameters along with engineering rock properties on SE. Mineralogical and petrographic analyses, rock mechanics, and linear rock cutting tests were performed on sandstone samples taken from sites around Ankara, Turkey. Relationships between SE and rock properties were evaluated using bivariate correlation and linear regression analyses. The tests and subsequent analyses revealed that the texture coefficient and feldspar content of sandstones affected rock cuttability, evidenced by significant correlations between these parameters and SE at a 90% confidence level. Felsic and mafic mineral contents of sandstones did not exhibit any statistically significant correlation against SE. Cementation coefficient, effective porosity, and pore volume had good correlations against SE. Poisson’s ratio, Brazilian tensile strength, Shore scleroscope hardness, Schmidt hammer hardness, dry density, and point load strength index showed very strong linear correlations against SE at confidence levels of 95% and above, all of which were also found suitable to be used in predicting SE individually, depending on the results of regression analysis, ANOVA, Student’s t-tests, and R² values. Poisson’s ratio exhibited the highest correlation with SE and seemed to be the most reliable SE prediction tool in sandstones.