Elnaz Siami-Irdemoosa

arXiv2016

A modified model of a single rock joint shear behavior in limestone specimens

The shear behavior of a single rock joint in limestone specimens, under a constant normal load (CNL), was analyzed in this study. Test specimens with different asperity roughness were prepared and tested. The Goodman model of a rock joint shear behavior, under CNL, was modified to render a better representation of the data obtained. The model applicability was validated. The proposed model shows better correlation with experimental data. It also, requires fewer variables. The steps to calculate all the necessary variables for the model are discussed.

physics.geo-ph↗

arXiv2016

Estimating the unconfined compressive strength of carbonate rocks using gene expression programming

Conventionally, many researchers have used both regression and black box techniques to estimate the unconfined compressive strength (UCS) of different rocks. The advantage of the regression approach is that it can be used to render a functional relationship between the predictive rock indices and its UCS. The advantage of the black box techniques is in rendering more accurate predictions. Gene expression programming (GEP) is proposed, in this study, as a robust mathematical alternative for predicting the UCS of carbonate rocks. The two parameters of total porosity and P-wave speed were selected as predictive indices. The proposed GEP model had the advantage of the both traditionally used approaches by proposing a mathematical model, similar to a regression, while keeping the prediction errors as low as the black box methods. The GEP outperformed both artificial neural networks and support vector machines in terms of yielding more accurate estimates of UCS. Both the porosity and the P-wave velocity were sufficient predictive indices for estimating the UCS of the carbonate rocks in this study. Nearly, 95% of the observed variation in the UCS values was explained by these two parameters (i.e., R2 =95%).

cs.CE↗