A critical aspect of rock engineering modelling and rock engineering design is ensuring that all the necessary variables have been included and that the interactions between them are understood—but this is not easy to establish without a guiding methodology. For this reason, the author developed the Rock Engineering Systems (RES) approach in 1992 and, in the 20+ years since then, the RES approach has been used for a wide variety of rock engineering and other problems. As a result, there are now many case studies available which illustrate the application of RES to rock engineering problems. In this paper, the basic RES methodology is outlined and 34 case examples are referenced. The diversity of these 34 case examples illustrates the variety of applications and approaches used by different researchers and practitioners. The link between RES and ‘intelligent’ methods is emphasised.


When designing a project to be constructed on or within a rock mass for either a civil or mining engineering purpose, it is essential to have sufficient knowledge to ensure the safety of the construction and the succeeding use of the facility. In order to reduce the attendant risk to an acceptable level, it is necessary to consider the associated epistemic and aleatory uncertainties—remembering that epistemic uncertainty is concerned with lack of knowledge about a process or model, and aleatory uncertainty is concerned with the inherent randomness of a process or model. In this paper, we review how epistemic uncertainty can be significantly reduced by the use of Rock Engineering Systems (RES) originally developed by Hudson (1992).

In the following sections, the RES approach is summarised, including the interaction matrix and coding the matrix according to the significance of the interactions between the variables, together with the associated ‘Cause-Effect’ plot. Key case example applications that have been published over the last twenty years are listed via a table of the main variables used for each application. These case examples represent studies from Bangladesh, China, Greece, Iran, Italy, Korea, Spain, Sweden, Turkey, UK, and the USA.

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