Prediction of creep characteristic of rock under varying environment |
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| Authors: | T N Singh A K Verma |
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| Institution: | (1) Department of Earth Sciences, IIT-Bombay, Mumbai, 400076, India;(2) Institute of Technology, B.H.U, Varanasi, 221005, India |
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| Abstract: | The strain developed due to creep is mainly proportional to the logarithm of the time under load, and is mostly proportional
to the stress and temperature. At higher temperature the creep rate falls slowly with respect to time, and the creep strain
is proportional to a fractional power of time, with the exponent increasing as the temperature increases and reaching a value
approximately one-third at temperatures of about 0.5°C. At these temperatures, the creep increases with stress according to
a power greater than unity and possibly exponentially. It increases with temperature as (−U/kT), where U is an activation energy and k is Boltzman’s constant. There are different methods to determine the creep strain and the energy of Jog (B) including experimental
methods, multivariate regression analysis, and by numerical simulation. These methods are less cumbersome and time consuming.
In the present investigation, artificial neural network technique has been used for prediction of the creep strain and energy
of Jog (B). Two different networks have been tested and validated. Both the networks have four input neurons and one hidden
layer with five neurons, and one output neuron. The data for different rocks at temperatures up to 750°C under conditions
of compressive or tortional stress are taken from the literatures. The training and testing data sets used were 163 and 14,
respectively. To deal with the problem of overfitting of data, Bayesian regulation has been used and network is trained with
suitable training epochs. The coefficients of correlation among the predicted and observed values are found high and they
improve the confidence of the users. The mean absolute percentage error obtained are also very low. |
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| Keywords: | Artificial neural network Creep strain Energy of Jog (B) Rock strength |
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