Rock bolting is one of the most important support systems used for rock structures. Rock bolts are widely used in underground excavations as they are suitable for a wide range of geological conditions and allow using progressive design methods; besides, they help economising in the use of materials and manpower. Thus, to provide the most effective support at minimum cost by means of rock bolting, it is essential to optimise the elements contributing to bolt design, including their length, as well as bolt density and tension during installation. This paper considers the length of bolts for optimisation of the design phase, which is one of the most important parameters impacting the entire design procedure. Presenting and comparing results of some statistical models, neural network modeling is introduced as powerful means in prediction of the optimal length of rock bolts. Subsequent to training and testing of a large number of 1-layer and 2-layer backpropagation neural networks, it was reported that the optimal model was the network with the architecture of 6-18-3-1 as it demonstrated the minimum RMSE and MAE as well as the maximum R 2 . In comparison to statistical models (0.7182 for the value of R 2 in the multiple linear regression model, 0.68 in the polynomial model and 0.7 in the dimensionless model), the results obtained by the neural network modeling − i.e. the coefficient of determination R 2 of 0.9259, the value of mean absolute error MAE of 0.068, and the root mean squared error RMSE of 0.078 − not only proved their superiority but also introduced the neural network modelling as a highly capable prediction tool in forecasting the optimal length of rock bolts. Furthermore, sensitivity analysis was used to obtain parameters that have the greatest and the least impact on the optimal bolt length: the effect of the overburden thickness, tensile strength, cohesion and Poisson's ratio on the optimal bolt length was almost the same while the friction angle had the least influence.Keywords: optimal length of rock bolts, artificial neural networks, statistical methods, sensitivity analysis.
In this paper, stress-strain behaviour of sand-clay mixture stabilised with different cement and rice husk ash percentages, and reinforced with different polypropylene fibre lengths are evaluated. Mixtures are widely used in road construction for soil stabilisation. It is observed that replacing half of the cement percentage (in high cement contents) with rice husk ash will result in a higher unconfined compressive strength. In addition, the presence of 6 mm polypropylene fibres will help to increase the unconfined compressive strength of stabilised samples, while larger fibres cause reverse behaviour. In addition, introducing a new index for assessing the effect of curing days. Curing Improvement Index it is obtained that larger fibres show higher Curing Improvement Index values. Results gained for the THE BALTIC JOURNAL OF ROAD AND BRIDGE ENGINEERING 2 0 1 8/ 1 3 (4) effects of curing days, and fibre lengths are further discussed and interpreted using Scanning Electron Microscopy photos. Based on the conducted Unconfined Compressive Strength, Indirect Tensile Strength, and Flexural Strength tests and using evolutionary polynomial regression modelling, some simple relations for prediction of unconfined compressive strength, indirect tensile strength, and flexural strength of cement-rice husk ash stabilised, and fibre reinforced samples are presented. High coefficients of determination of developed equations with experimental data show the accuracy of proposed relationships. Moreover, using a sensitivity analysis based on Cosine Amplitude Method, cement percentage and the length of polypropylene fibres used to reinforce the stabilised samples are respectively reported as the most and the least effective parameters on the unconfined compressive strength of specimens.
As a matter of fact, the failure criteria only predict failure's initiation in materials. And, in order to predict post-yield behaviour of materials, a much complicated formulation for stress-strain relationship is required, which we know as plasticity theory. For instance, these formulations are developed based on Mohr-Coulomb criterion for soils and Drucker-Prager criterion for concrete. According to a majority of rock mechanics researchers, the empirical and experimental Hoek-Brown failure criterion is one of the well-progressed and suitable criteria, which can efficiently predict the rock failure initiation under different stress states for various types of intact rocks and rock masses. In this article, according to the suggestion by Heok explained in his paper of 1997, this rugged mentioned criterion is considered as a yield criterion and the elastic-perfect plastic behaviour of rock masses is determined using calculating material constitutive matrix's arrays in terms of Hoek-Brown's material constants and mechanical characteristics of rock materials in the general stress space, considering associated flow rule.
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