Science of empirical design in mining ground control

Many problems in rock engineering are limited by our imperfect knowledge of the material properties and failure mechanics of rock masses. Mining problems are somewhat unique, however, in that plenty of real world experience is generally available and can be turned into valuable experimental data. Every pillar that is developed, or stope that is mined, represents a full-scale test of a rock mechanics design. By harvesting these data, and then using the appropriate statistical techniques to interpret them, mining engineers have developed powerful design techniques that are widely used around the world. Successful empirical methods are readily accepted because they are simple, transparent, practical, and firmly tethered to reality. The author has been intimately associated with empirical design for his entire career, but his previous publications have described the application of individual techniques to specific problems. The focus of this paper is the process used to develop a successful empirical method. A six-stage process is described: identification of the problem, and of the end users of the final product; development of a conceptual rock mechanics model, and identification of the key parameters in that model; identification of measures for each of the key parameters, and the development of new measures (such as rating scales) where necessary; data sources and data collection; statistical analysis; and packaging of the final product. Each of these stages has its own potential rewards and pitfalls, which will be illustrated by incidents from the author's own experience. The ultimate goal of this paper is to provide a new and deeper appreciation for empirical techniques, as well as some guidelines and opportunities for future developers. (C) 2016 Published by Elsevier B.V. on behalf of China University of Mining & Technology.