A major concern in the design of foundations is
to achieve a precise estimation of bearing capacity of the
underlying soil or rock mass. The present study proposes a
new design equation for the prediction of the bearing
capacity of shallow foundations on rock masses utilizing
artificial neural network (ANN). The bearing capacity is
formulated in terms of rock mass rating, unconfined compressive
strength of rock, ratio of joint spacing to foundation
width, and angle of internal friction for the rock mass.
Further, a conventional calculation procedure is proposed
based on the fixed connection weights and bias factors of
the best ANN structure. A comprehensive database of rock
socket, centrifuge rock socket, plate load, and large-scaled
footing load test results is used for the model development.
Sensitivity and parametric analyses are conducted and
discussed. The results clearly demonstrate the acceptable
performance of the derived model for estimating the
bearing capacity of shallow foundations. The proposed
prediction equation has a notably better performance than
the traditional equations.
کلید واژگان :
Bearing capacity Shallow foundation Rock mass Artificial neural network Tractable design equation
