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1.
Uniaxial compressive strength (UCS) of an intact rock is an important geotechnical parameter for engineering applications. Using standard laboratory tests to determine UCS is a difficult, expensive and time-consuming task. The main purpose of this study is to develop a general model for predicting UCS of limestone samples and to investigate the relationships among UCS, Schmidt hammer rebound and P-wave velocity (V P). For this reason, some samples of limestone rocks were collected from the southwestern Iran. In order to evaluate a correlation, the measured and predicted values were examined utilizing simple and multivariate regression techniques. In order to check the performance of the proposed equation, coefficient of determination (R 2), root-mean-square error, mean absolute percentage error, variance accounts for (VAF %), Akaike Information Criterion and performance index were determined. The results showed that the proposed equation by multivariate regression could be applied effectively to predict UCS from its combinations, i.e., ultrasonic pulse velocity and Schmidt hammer hardness. The results also showed that considering high prediction performance of the models developed, they can be used to perform preliminary stages of rock engineering assessments. It was evident that such prediction studies not only provide some practical tools but also contribute to better understanding of the main controlling index parameters of UCS of rocks.  相似文献   

2.
李文  谭卓英 《岩土力学》2016,37(Z2):381-387
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。  相似文献   

3.
Studying the mechanical characteristics of weak sedimentary rocks is a burning issue in civil and mining engineering designs and analysis since obtaining rock mechanical properties of these has always faced lots of problems and uncertainties due to the structural weaknesses. One of the main causes of these problems is the difficulty of preparing high-quality core specimens recommended by testing standards or suggested methods for uniaxial compressive strength (UCS). For resolving this issue, in this study, common methods for indirect estimation of UCS of weak rocks were initially studied, their merits and demerits were analyzed, and then, in light of their positive and negative points, a new modified device was designed with a different mechanical structure and force exertion system, which could be practically used to present a new method for indirect estimation of UCS. Thus, in this study, we initially had a general view of the new dynamic needle penetrometer and its modified parts and their capabilities. After introduction, as the first phase of the practical studies on this, dynamic needle penetration resistance (DNPR) was measured, as the dynamic needle penetrometer test result, from 65 specimens collected from three different projects. Then, the relationships between DNPR and UCS of the rock specimens and the regressions of correlations were statistically analyzed. Finally, a linear equation with considerable accuracy resulted from analysis, and using this led to solving the main problem of this research by proposing a developed method for indirect estimation of uniaxial compressive strength of weak rocks.  相似文献   

4.
Measuring unconfined compressive strength (UCS) using standard laboratory tests is a difficult, expensive, and time-consuming task, especially with highly fractured, highly porous, weak rock. This study aims to establish predictive models for the UCS of carbonate rocks formed in various facies and exposed in Tasonu Quarry, northeast Turkey. The objective is to effectively select the explanatory variables from among a subset of the dataset containing total porosity, effective porosity, slake durability index, and P-wave velocity in dry samples and in the solid part of samples. This was based on the adjusted determination coefficient and root-mean-square error values of different linear regression analysis combinations using all possible regression methods. A prediction model for UCS was prepared using generalized regression neural networks (GRNNs). GRNNs were preferred over feed-forward back-propagation algorithm-based neural networks because there is no problem of local minimums in GRNNs. In this study, as a result of all possible regression analyses, alternative combinations involving one, two, and three inputs were used. Through comparison of GRNN performance with that of feed-forward back-propagation algorithm-based neural networks, it is demonstrated that GRNN is a good potential candidate for prediction of the unconfined compressive strength of carbonate rocks. From an examination of other applications of UCS prediction models, it is apparent that the GRNN technique has not been used thus far in this field. This study provides a clear and practical summary of the possible impact of alternative neural network types in UCS prediction.  相似文献   

5.
The uniaxial compressive strength of intact rock is the main parameter used in almost all engineering projects. The uniaxial compressive strength test requires high quality core samples of regular geometry. The standard cores cannot always be extracted from weak, highly fractured, thinly bedded, foliated and/or block-in-matrix rocks. For this reason, the simple prediction models become attractive for engineering geologists. Although, the sandstone is one of the most abundant rock type, a general prediction model for the uniaxial compressive strength of sandstones does not exist in the literature. The main purposes of the study are to investigate the relationships between strength and petrographical properties of sandstones, to construct a database as large as possible, to perform a logical parameter selection routine, to discuss the key petrographical parameters governing the uniaxial compressive strength of sandstones and to develop a general prediction model for the uniaxial compressive strength of sandstones. During the analyses, a total of 138 cases including uniaxial compressive strength and petrographic properties were employed. Independent variables for the multiple prediction model were selected as quartz content, packing density and concavo–convex type grain contact. Using these independent variables, two different prediction models such as multiple regression and ANN were developed. Also, a routine for the selection of the best prediction model was proposed in the study. The constructed models were checked by using various prediction performance indices. Consequently, it is possible to say that the constructed models can be used for practical purposes.  相似文献   

6.
Estimation of uniaxial compressive strength (UCS) by P-wave velocity (VP) is of great interest to geotechnical engineers in various design projects. The specimen diameter size is one of the main factors that influence rock parameters such as UCS and VP. In this study, the diameter size of specimens that effect UCS and VP is investigated. Moreover, the correlation between UCS and VP are examined via empirical analysis. For this purpose, 15 travertine samples were collected and core specimens with a diameters size of 38, 44, 54, 64 and 74 mm were prepared. Then, uniaxial compressive strength and P-wave velocity tests were conducted according to the procedure suggested by ISRM (1981). It is concluded that the diameter size of the specimen has a significant effect on UCS and VP. Moreover, it was found that the best correlation between relevant parameters obtained for the specimen diameter of 38 mm.  相似文献   

7.
Elastic properties of rocks play a major and crucial role for the design of any engineering structure. Determination of elastic properties in laboratory is tedious, laborious, very time consuming, as well as expertise is required, whereas determination of uniaxial compressive strength (UCS) and tensile strength in laboratory is simple, easy, and less expertise is required. Here, an attempt has been made to predict the elastic properties (Poisson’s ratio and Young’s modulus) of the schistose rocks from unconfined strength (UCS and tensile strength) using artificial neural network (ANN). A three-layer feed-forward back propagation neural network with 2-5-2 architecture was trained up to 855 epochs to predict the elastic properties of rock mass. The network was trained and tested by 120 data sets, and validation of the network was done by 20 new randomly selected data sets of UCS and tensile strength. The samples were collected from the schistose rocks of Nathpa-Jhakri hydropower project site, SJVNL, Himachal Pradesh, India. To check the validity and suitability of the artificial neural network technique, multivariate regression analysis (MVRA) is also performed, and comparison has been made. It was found that ANN gives closer values of predicted Poisson’s ratio and Young’s modulus as compared to MVRA. The coefficient of determination for Poisson’s ratio was 0.9809 and 0.843 by ANN and MVRA, respectively, whereas 0.9922 and 0.9362 for Young’s modulus by ANN and MVRA, respectively. The mean absolute percentage error (MAPE) for Young’s modulus is 11.13 and 28.21 by ANN and MVRA, respectively; whereas MAPE for Poisson’s ratio is 3.64 and 9.23 by ANN and MVRA, respectively.  相似文献   

8.
Accurate laboratory measurement of geo-engineering properties of intact rock including uniaxial compressive strength (UCS) and modulus of elasticity (E) involves high costs and a substantial amount of time. For this reason, it is of great necessity to develop some relationships and models for estimating these parameters in rock engineering. The present study was conducted to forecast UCS and E in the sedimentary rocks using artificial neural networks (ANNs) and multivariable regression analysis (MLR). For this purpose, a total of 196 rock samples from four rock types (i.e., sandstone, conglomerate, limestone, and marl) were cored and subjected to comprehensive laboratory tests. To develop the predictive models, physical properties of studied rocks such as P wave velocity (Vp), dry density (γd), porosity, and water absorption (Ab) were considered as model inputs, while UCS and E were the output parameters. We evaluated the performance of MLR and ANN models by calculating correlation coefficient (R), mean absolute error (MAE), and root-mean-square error (RMSE) indices. The comparison of the obtained results revealed that ANN outperforms MLR when predicting the UCS and E.  相似文献   

9.
针对金属矿山接触带复合岩体非协调变形现象,开展物理相似试样单轴压缩试验,结合理论分析,研究不同介质力学性质的差异对复合试样力学特性及破坏形式的影响。试验结果表明:复合试样的单轴抗压强度和弹性模量相对两种介质中较大的单轴抗压强度和弹性模量减小,减小幅度随介质力学性质差异程度（λ）的增大而增大,同时,随着差异程度（λ）的增大,复合试样逐渐由单斜面剪切破坏变为复杂的横向拉伸破坏。理论分析表明,不同介质泊松比的差异（Δv）导致接触面处产生非协调变形,形成的侧向约束应力弱化了复合试样的力学性能,通过引入非协调变形系数α量化了非协调变形程度与泊松比的差异（Δv）之间的相关性;构建了由两种介质力学参数确定的复合试样弹性模量的表达式和轴向应力-应变本构关系式。研究结果可为接触带复合岩体非协调变形破坏的进一步分析提供理论基础。  相似文献   

10.
The unconfined compressive strength (UCS) of intact rocks is an important geotechnical parameter for engineering applications. Determining UCS using standard laboratory tests is a difficult, expensive and time consuming task. This is particularly true for thinly bedded, highly fractured, foliated, highly porous and weak rocks. Consequently, prediction models become an attractive alternative for engineering geologists. The objective of study is to select the explanatory variables (predictors) from a subset of mineralogical and index properties of the samples, based on all possible regression technique, and to prepare a prediction model of UCS using artificial neural networks (ANN). As a result of all possible regression, the total porosity and P-wave velocity in the solid part of the sample were determined as the inputs for the Levenberg–Marquardt algorithm based ANN (LM-ANN). The performance of the LM-ANN model was compared with the multiple linear regression (REG) model. When training and testing results of the outputs of the LM-ANN and REG models were examined in terms of the favorite statistical criteria, which are the determination coefficient, adjusted determination coefficient, root mean square error and variance account factor, the results of LM-ANN model were more accurate. In addition to these statistical criteria, the non-parametric Mann–Whitney U test, as an alternative to the Student’s t test, was used for comparing the homogeneities of predicted values. When all the statistics had been investigated, it was seen that the LM-ANN that has been developed, was a successful tool which was capable of UCS prediction.  相似文献   

11.
花岗岩体是很多重要工程地基或围岩的首选。选取高放废物地质处置阿拉善预选区巴彦诺日公花岗岩样品,开展薄片鉴定,获得各花岗岩样品的矿物含量和粒径;通过单轴压缩试验,获得花岗岩的单轴抗压强度。通过对比各组样品矿物含量和粒径与单轴抗压强度,研究二者之间的关系。结果表明:对花岗岩单轴抗压强度影响最大的矿物是钾长石和黑云母,斜长石和石英的影响不明显;矿物粒径与单轴抗压强度的相关性不明显,但与某一结构岩石单轴抗压强度的相关性明显;花岗岩的强度不仅仅取决于组成矿物含量和粒径,对于其内部结构的细节（如微裂隙、矿物排列、胶结等）非常敏感。  相似文献   

12.
Many surface and underground structures are constructed in heterogeneous rock formations. These formations have a combination of weak and strong rock layers. Due to the alternation of the weak and strong layers, selecting the equivalent and appropriate geomechanical parameters for these formations is challenging. One of these problems is choosing the equivalent strength (i.e., uniaxial compressive strength) of intact rock for a group of rocks. Based on the volume of weak and strong parts and their strength, the equivalent strength of heterogeneous rocks changes. Marinos and Hoek (Bull Eng Geol Environ 60(2):85–92, 2001) presented the “weighted average method” for defining the uniaxial compressive strength (UCS) of heterogeneous rock masses based on the volume of weak and strong parts. Laubscher (1977) used the volume ratio of the strength of a weak part to a strong part (UCS weak/UCS strong) to determine the equivalent strength. In this study, the two methods are compared and their validity is evaluated by experimental data and numerical analyses. The geomechanical parameters of two heterogeneous formations (Aghajari and Lahbari) in the west of Iran were estimated using these methods. The results of the present study obtained through numerical analyses using particle flow code are compared with those of previous studies and discussed. Laboratory and numerical results show UCS decrease and approach to weak strength with an increasing in volume of weak part. When strength ratio of strong to weak rock increase, equivalent strength decrease more severely. The findings show that Laubscher’s method gives more appropriate results than the weighted average method.  相似文献   

13.
Adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) models have been extensively used to predict different soil properties in geotechnical applications. In this study, it was aimed to develop ANFIS and ANN models to predict the unconfined compressive strength (UCS) of compacted soils. For this purpose, 84 soil samples with different grain-size distribution compacted at optimum water content were subjected to the unconfined compressive tests to determine their UCS values. Many of the test results (for 64 samples) were used to train the ANFIS and the ANN models, and the rest of the experimental results (for 20 samples) were used to predict the UCS of compacted samples. To train these models, the clay content, fine silt content, coarse silt content, fine sand content, middle sand content, coarse sand content, and gravel content of the total soil mass were used as input data for these models. The UCS values of compacted soils were output data in these models. The ANFIS model results were compared with those of the ANN model and it was seen that the ANFIS model results were very encouraging. Consequently, the results of this study have important findings indicating reliable and simple prediction tools for the UCS of compacted soils.  相似文献   

14.
In this paper, first, the needle penetrometer test is briefly presented and experience gained, mainly in Japan and Turkey, with a model manufactured in Japan is reviewed. Second, the needle penetrometer test is used successfully to distinguish qualitatively carbonate sands from very weak and weak calcarenites in borehole cores recovered for cut-and-cover tunnel projects in Maastricht. Third, the relation between UCS and needle penetration resistance (NPR) for the Maastrichtian limestones is further analyzed. Needle penetration tests are conducted with the help of a loading frame. Results suggest that there is a statistically significant relationship between the UCS and NPR, that leaves however to high predictive uncertainty. During testing, very high compressive and shear stresses develop under the needle and stresses normal to the needle shaft increase. Microscopic observations show the extent of grain crushing and compaction ahead and around the needle. Nevertheless, resistance to needle penetration and UCS values are somehow related. The needle penetrometer is recommended as an index test rather than a way to determine accurately the UCS of the Maastrichtian limestones.  相似文献   

15.
乐慧琳  孙少锐 《岩土力学》2018,39(Z1):211-219
选用环氧树脂和纯水泥浆作为注浆材料,对含不同角度和不同注浆材料裂隙试样进行单轴压缩试验。试验结果表明,注浆材料和裂纹缺陷角度对类岩石试件单轴抗压强度及破坏模式具有重要影响;环氧树脂加固效果优于纯水泥浆,环氧树脂可以有效地消除预制裂纹尖端的应力集中;在裂纹缺陷角度很小( <30°)和角度很大( =90°)的情况下无论裂隙是注环氧树脂还是纯水泥浆,注浆效果都不明显,当 =60°时两种注浆材料的加固效果都很好。提出滑动裂纹模型,对注浆裂隙进行力学分析发现,含注浆裂隙试样的抗压强度随着注浆材料和完整材料胶结面摩擦系数和黏聚力的增大而增大,不同注浆材料和完整材料胶结面的摩擦系数和黏聚力不同,解释了为什么不同的注浆材料对注浆试样强度提升作用不同。研究成果为分析工程中注浆材料和裂纹缺陷角度对岩体强度的影响提供了一定的理论基础。  相似文献   

16.
重庆沙溪庙组地层岩石单轴抗压强度研究   总被引：6，自引：0，他引：6  
陈小平 《岩土力学》2014,35(10):2994-2999
岩石单轴抗压强度是工程勘察中最基本的岩体力学参数之一,已广泛应用于岩石地基设计、隧洞围岩分类、岩体质量分级、土石开挖分级和岩石地基验收中。重庆市区约70%面积坐落于侏罗系中统沙溪庙组地层之上,研究沙溪庙组地层岩石单轴抗压强度具有十分重要的意义。从工程勘察的实践出发,通过对重庆市沙溪庙组岩石抗压强度的统计和对软化系数的研究,建立了饱和抗压强度与天然抗压强度之间的经验公式。通过对计算值和试验值的大量对比,结果显示,计算值的可靠性高,可替代试验值,应用前景广阔。  相似文献   

17.
The Cerchar abrasivity index (CAI) is one of the most widely known index method for identification of rock abrasivity. It is a simple and fast testing method providing reliable information on rock abrasiveness. In this study, the relationships between the CAI and some rock properties such as uniaxial compressive strength (UCS), point load strength, Brazilian tensile strength and Schmidt rebound hardness, and equivalent quartz content (EQC) are examined. The relationships between the CAI and drill bit lifetime is also investigated and the type of drill bit wear observed is mentioned. Additionally, the CAI is modeled using simple and multiple linear regression analysis based on the rock properties. Drill bit lifetime is also modeled based on the CAI. The results show that the CAI increases with the increase of the UCS, point load strength, Brazilian tensile strength, L-type and N-type Schmidt rebound hardness, and the EQC. It is concluded that the higher and the lower bit lifetime are obtained for marl and andesitic-basaltic formation, respectively. Moreover, flushing holes, inserted button, button removal, and failures of button on the bits are determined as the type of drill bit wear. The modeling results show that the models based on the UCS and the EQC give the better forecasting performances for the CAI.  相似文献   

18.
This study aims to express the relationships between Schmidt rebound number (N) with unconfined compressive strength (UCS) and Young's modulus (Et) of the gypsum by empirical equations. As known, the Schmidt hammer has been used worldwide as an index test for a quick rock strength and deformability characterisation due to its rapidity and easiness in execution, simplicity, portability, low cost and nondestructiveness. In this study, gypsum samples have been collected from various locations in the Miocene-aged gypsum of Sivas Basin and tested. The tests include the determination of Schmidt hammer rebound number (N), tangent Young's modulus (Et) and unconfined compressive strength. Finally, obtained parameters were correlated and regression equations were established among Schmidt hammer rebound hardness, tangent Young's modulus and unconfined compressive strength, presenting high coefficients of correlation. It appears that there is a possibility of estimating unconfined compressive strength and Young's modulus of gypsum, from their Schmidt hammer rebound number by using the proposed empirical relationships of UCS=exp(0.818+0.059N) and Et=exp(1.146+0.054N). However, the equations must be used only for the gypsum with an acceptable accuracy, especially at the preliminary stage of designing a structure. Finally, by using the obtained Schmidt hammer rebound number from this study, unconfined compressive strength was calculated and compared with the calculated value from different empirical equations proposed by different authors. It can be said that it is impossible to obtain only one relation for all types of the rocks.  相似文献   

19.
通过振动及单轴压缩试验,研究了受振动荷载扰动裂隙性黄土的单轴压缩力学行为。结果表明：裂隙性黄土的单轴压缩破坏模式表现为压裂破坏、滑移破坏、滑移-压裂复合破坏以及压剪破坏4种类型;振动扰动对单轴压缩条件下裂隙性黄土的破坏模式无显著影响,其破坏模式主要由初始裂隙的倾角控制。振动幅值和频率对裂隙性黄土应力-应变曲线的类型及特征无显著影响,不同振动参数条件下试样的应力-应变曲线均表现为应变软化型,且45°倾角试样的应力-应变曲线呈现出第二峰值强度高于第一峰值强度的“双峰”变化特征。单轴抗压强度随振动幅值和频率的增大均呈现出近似线性减小的变化规律;不同振动参数条件下试样单轴抗压强度随裂隙倾角增大近似呈现出“双V”变化特征。构建了受振动荷载扰动裂隙性黄土的二元介质本构模型,可较好预测其单轴压缩过程的应力-应变关系及单轴抗压强度。  相似文献   

20.
Uniaxial Compressive Strength (UCS) is considered as one of the most important parameters in designing rock structures. Determination of this parameter requires preparation of rock samples which is costly and time consuming. Moreover discrepancy of laboratory test results is often observed. To overcome the drawbacks of traditional method of UCS measurement, in this paper, predictive models based on neuro-genetic approach and multivariable regression analysis have been developed for predicting compressive strength of different type of rocks. Coefficient of determinatoin (R2) and the Mean Square Error (MSE) were calculated for comparison of the models’ efficiency. It was observed that accuracy of the neuro-genetic model is significantly better than regression model. For the neuro-genetic and regression models, R2 and MSE were equal to 95.89 % and 0.0045 and 77.4 % and 1.61, respectively. According to sensitivity analysis for neuro-genetic model, Schmidt rebound number is the most effective parameter in predicting UCS.  相似文献   

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