Catastrophe model and its experimental verification ofstatic loading rock system under impact load

According to the catastrophe model for impact buckling of static loading structures, a new catastrophe model for impact loading failure of a static loading rock system was established, and one dimension (1D) catastrophe model was analyzed. The analysis results indicate that the furcation collection where catastrophe may take place is not only decided by mechanical system itself but also relates to exterior loading, which is different from the results obtained under mono-static loading where the bifurcation collection is only determined by mechanics of the system itself and has nothing to do with exterior loading. In addition, the corresponding 1D coupled static-dynamic loading experiment is designed to verify the analysis results of catastrophe model. The test is done with Instron 1342 electro-servo controlled testing system, in which medium strain rate is caused by monotony rising dynamic load. The parameters are obtained combining theoretical model with experiment. The experimental and theoretical curves of critical dynamic load vs static load are rather coincided, thus the new model is proved to be correct.

A generic method for rock mass classification

Rock mass classification(RMC) is of critical importance in support design and applications to mining,tunneling and other underground excavations. Although a number of techniques are available, there exists an uncertainty in application to complex underground works. In the present work, a generic rock mass rating(GRMR) system is developed. The proposed GRMR system refers to as most commonly used techniques, and two rock load equations are suggested in terms of GRMR, which are based on the fact that whether all the rock parameters considered by the system have an influence or only few of them are influencing. The GRMR method has been validated with the data obtained from three underground coal mines in India. Then, a semi-empirical model is developed for the GRMR method using artificial neural network(ANN), and it is validated by a comparative analysis of ANN model results with that by analytical GRMR method.

A New System to Evaluate Comprehensive Performance of Hard-Rock Tunnel Boring Machine Cutterheads

The accurate performance evaluation of a cutterhead is essential to improving cutterhead structure design and predicting project cost. Through extensive research, this paper evaluates the performance of a tunnel boring machine(TBM) cutterhead for cutting ability and slagging ability. This paper propose cutting efficiency, stability, and continuity of slagging as the evaluation indexes of comprehensive cutterhead performance. On the basis of research of true TBM engineering applications, this paper proposes a calculation method for each index. A slagging efficiency index with a ratio of the maximum di erence between the slagging amount and average slagging is established. And a slagging stability index with a ratio of the maximum slagging fluctuation and average slagging is presented. Meanwhile, a cutting efficiency index by the weighed average value of multistage rock fragmentation of a cutter’s specific energy is established. The Robbins and China Railway Construction Corporation(CRCC) cutterheads are evaluated. The results show that under the same thrust and torque, the slagging stability of the CRCC scheme is worse, but the slagging continuity of the CRCC scheme is better. The cutting ability index shows that the CRCC cutterhead is more efficient.

Analysis profile of the fully grouted rock bolt in jointed rock using analytical and numerical methods

The purpose of this study was to investigate the effect of bolt profile on load transfer mechanism of fully grouted bolts in jointed rocks using analytical and numerical methods. Based on the analytical method with development of methods, a new model is presented. To validate the analytical model, five different profiles modeled by ANSYS software. The profile of rock bolts T3 and T4with load transfer capacity,respectively 180 and 195 kN in the jointed rocks was selected as the optimum profiles. Finally, the selected profiles were examined in Tabas Coal Mine. FLAC analysis indicates that patterns 6+7 with2 NO flexi bolt 4 m better than other patterns within the faulted zone.

Failure mechanism and stability control of a large section of very soft roadway surrounding rock shear slip

The measured data and simulation test phenomenon of surrounding rock deformation and failure at the project site indicate that shear failure which firstly occurs in surrounding rock, block slip and second shear failure are the root cause of deformation and damage of supporting structure of the surrounding rock at a large scale. We derived limit load of surrounding rock shear slip failure and reasonable support resistance of given load by means of shear slip line field theory, discussed the main factors which influence the limit load of surrounding rock. Shear slip line field and limit load of circular tunnel surrounding rock were obtained by means of physical simulation test, which agreed well with the theoretical analysis results. Based on the theoretical analysis and physical simulation test, the cause deformation and failure at large scale of Xinshanghai No. 1 coal mine big section ingate was analyzed, and the shear failure resistance and block slip in surrounding rock were proposed as the core technical supporting ideas. Proper range of supporting resistance which came from calculation was suggested. The support scheme which is mainly composed of large grouting anchor, sprayed anchor net support technique and full-face grille concrete finally ended the dilemma of repeated failure and mending of ingate and created critical conditions for smooth production in the coal mine.

New artificial neural networks for true triaxial stress state analysis and demonstration of intermediate principal stress effects on intact rock strength

Simulations are conducted using five new artificial neural networks developed herein to demonstrate and investigate the behavior of rock material under polyaxial loading. The effects of the intermediate principal stress on the intact rock strength are investigated and compared with laboratory results from the literature. To normalize differences in laboratory testing conditions, the stress state is used as the objective parameter in the artificial neural network model predictions. The variations of major principal stress of rock material with intermediate principal stress, minor principal stress and stress state are investigated. The artificial neural network simulations show that for the rock types examined, none were independent of intermediate principal stress effects. In addition, the results of the artificial neural network models, in general agreement with observations made by others, show （a） a general trend of strength increasing and reaching a peak at some intermediate stress state factor, followed by a decline in strength for most rock types; （b） a post-peak strength behavior dependent on the minor principal stress, with respect to rock type; （c） sensitivity to the stress state, and to the interaction between the stress state and uniaxial compressive strength of the test data by the artificial neural networks models （two-way analysis of variance; 95% confidence interval）. Artificial neural network modeling, a self-learning approach to polyaxial stress simulation, can thus complement the commonly observed difficult task of conducting true triaxial laboratory tests, and/or other methods that attempt to improve two-dimensional （2D） failure criteria by incorporating intermediate principal stress effects.

Discussion on bearing capacity of soft rock ground based on in-situ load test

The suitability of five methods was discussed here,taking the typical results from in-situ load test of Renshou Mansion and Caifu Plaza in Yueyang City for example.It shows that bearing capacity can be obtained by the proportion load and limit load from p-s curve with the first and the second point of contraflexure easily.It is recommended that the accurate value of bearing capacity can be obtained by hyperbola fitting method and minimum curvature radius method theoretically.The rebound method is clear in principle,in which the elastoplasticity characteristic is thought about.Out of consideration for the unsteadiness and unobviousness of bearing capacity from relative settlement method,it can be only adopted as reference.So bearing capacity of soft rock ground should be determined by weathering condition of soft rock and curve type.

The use of point load test for Dubai weak calcareous sandstones

Intact rock is typically described according to its uniaxial compressive strength （UCS）. The UCS is needed in the design of geotechnical engineering problems including stability of rock slopes and design of shallow and deep foundations resting on and/or in rocks. Accordingly, a correct measure-ment/evaluation of the UCS is essential to a safe and economic design. Typically, the UCS is measured using the unconfined compression tests performed on cylindrical intact specimens with a minimum length to width ratio of 2. In several cases, especially for weak and very weak rocks, it is not possible to extract intact specimens with the needed minimum dimensions. Thus, alternative tests （e.g. point load test, Schmidt hammer） are used to measure rock strength. The UCS is computed based on the results of these tests through empirical correlations. The literature includes a plethora of these correlations that vary widely in estimating rock strength. Thus, it is paramount to validate these correlations to check their suitability for estimating rock strength for a specific location and geology. A review of the available correlations used to estimate the UCS from the point load test results is performed and summarized herein. Results of UCS, point load strength index and Young＇s modulus are gathered for calcareous sandstone specimens extracted from the Dubai area. A correlation for estimating the UCS from the point load strength index is proposed. Furthermore, the Young＇s modulus is correlated to the UCS.