Abstract:
The global economy still relies on coal. However, coal mines at time face operational problems
such as fall of ground. Unplanned fall of ground in roadway intersections in coal mines present
a serious threat to mine safety. Despite the technological and scientific advances in ground
support, it is challenging to design the road intersections in coal mines due to variability of
rock mass properties and the difficulties of obtaining reliable input data for the design, in most
cases. Although, existing methods of design including numerical modelling or, empirical
design approaches possess merits, they cannot properly handle these aspects above mentioned.
Hence, it is essential to identify relationship between the unplanned roof falls, support methods,
presence of water and the geology to create an expert system, which will be helpful for miners
to contribute towards improving rock fall related safety in coal mines. Firstly, numerical
modelling carried out with RS2 software, is employed to characterize selected cases of FoG
in the database and to further validate an expert system. Secondly, an expert system via fuzzy
logic (fuzzy inference system) is developed to allow to objectively handle qualitative
parameters (which could be subjective) associated with the FoG in tunnel intersections. Data
pertaining to roof fall in roadway intersections are compiled from US coal mines are used to
calibrate and validate the newly proposed tools. The data include the size of the FoG, the
geology, the coal seam characteristics, the types of support and the presence water. It is
expected that the results of this study indicate good agreement with the filed. The end results
(derived empirical tools) could be helpful for mining engineers in managing FoG in tunnel
intersection in coal mine around the world