The effect of joint parameters on rock block size and key block size distributions

This thesis studies the influence of joint parameters on probabilistic rock block size distributions and probabilistic key block size distributions, and presents the use of key block size distribution graphs for quick estimation of key block size distribution in a tunnel constructed in a jointed rock mass. The matrix approach by the Discrete Region Key Block Analysis (DRKBA) program was used for all tests throughout this research.; In studying the influence of joint parameters on the rock block size and key block size distribution, three chief joint parameters, orientation (dispersion of pole vectors), length, and spacing, were used. The tests were performed by varying each parameter with the other parameters held constant. The results show that both rock block and key block size distribution shapes are fixed as a reverse J-shape Weibull distribution when the concentration factor of pole vectors (k-factor) is 200 or less. Results also show that the number of rock blocks increases exponentially when the joint length increases, whereas the number of key blocks increases linearly with increasing joint length. When joint spacing is increased, the average rock block size and key block size increase exponentially but the number of rock blocks and key blocks decrease exponentially.; The effect of joint dip angles on the occurrence of key blocks (number and size) in two 25 feet square tunnels at two different compass orientations was studied. The joint dip angle was varied in each test, and each joint dip angle was tested under two conditions: (1) varying the concentration factor of pole vectors (k-factor), and (2) using two joint spacing distributions (p:q = 0.5:1, and p:q = 1:1). It was found that the steeply dipping joints generated a greater number of large key blocks and created a larger key block size than did the shallowly dipping joints for all values of concentration factors of pole vectors, and also in both spacing distributions. The number of large key blocks was greater in the case of p:q equals 0.5:1 than p:q equals 1:1. A key finding was that the concentration factor of pole vectors and spacings are the most significant joint parameters affecting both rock block size and key block size distributions.; Model graphs for quick estimation of key block size distribution in a 25-feet diameter tunnel are proposed. These graphs were generated by varying the concentration factor for various angles between joint pole vectors (A). Each model graph of each angle (A) consists of a set of six graphs in which each graph represents one concentration factor in one direction. A comparison of the results between these simulated data and field data from the Yucca Mountain (Nevada) site was also done. The key block size distribution graphs from the field data match well with the key block size distribution graphs from simulated data. This indicates that this method has utility for predicting the location and number and size of key blocks in rock faces created in civil and mining engineering applications.