A new practical method for prediction of geomechanical failure-time

Abstract

Can we predict failure-time of geo-hazards? This question, poses a traditional rock mechanics problem. It is a challenge to date in the rock mechanics field to precisely predict failure-time of geo-hazards, and geo-hazards still pose major threat to life and major loss in terms of economics. The focal point of our research is to predict failure-time of geo-hazards. Firstly, we evaluated the validity of the INVerse-velocity (INV) method to predict failure-time of rock mass and landslides. And as a merit, the method utilizes rates of displacement (du/dt) or strain (d /dt) to predict the actual failure-time (T f ), so the value of total displacement or strain before "failure" is not crucial. Secondly, we developed a new method for computing failure-time predictions based on the SLOpe (gradient) to predict T f , termed the SLO method, which will be described in detail in the paper. And in tally, a simple conceptualised model representing "safe" and "unsafe" predictions was proposed.To validate these hypotheses, prediction of rock mass failure, Asamushi and Vaiont landslides (in situ studies) was conducted.Furthermore, laboratory conditions were incorporated into the research, which are: (i) predictions using circumferential strain c and axial strain a from uniaxial compression creep test on Shikotsu welded tuff (SWT); and (ii) predictions of failure-time for Inada granite under Brazilian creep tests. It was realized that SLO method is better than the INV method; SLO gave safe predictions in all the cases. In contrast, INV tends to give unsafe predictions (predicted failure-time T fp > T f ). Our findings reveal that predictions using c are better than using a for SWT, and notably, given failure with very short tertiary creep, the methods tend to show limited reliability. However, SLO method could find extensive application in predicting failure-time of geo-hazards, for instance, roof wall failure in mines etc.; this method is promising in reducing fatalities and damage to property which industry and society still face at present.

Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

“…In Fig. 3c, predictions approach the actual values already on late October but finally diverge towards significantly negative ΔT f , which is something to avoid in risk management of geological hazards (concept of Bsafe^and Bunsafep redictions, Mufundirwa et al 2010). Exponential smoothing produces a reliable T f in correspondence of the last measurement, but the predicted time to failure line does not have a regular pattern, if compared to the others.…”

“…3a. Life expectancy plots are very useful tools to examine the course with time of the T f predictions, updated on an on-going basis each time a new measurement is available (Mufundirwa et al 2010;Dick et al 2014).…”

“…These are usually based on the recurrent observation before failure of certain relationships in the strain or displacement data, eventually linked to some intrinsic properties of the rock mass (Ventura et al 2009). For example, Mufundirwa et al (2010) evaluated T f as the slope of the t(du/dt)-du/dt curve, where du/dt is the displacement rate. Newcomen and Dick (2015) recently reported the Bboundary conditions^for different failure mechanisms based on the correlation between the Rock Quality Mass (RMR) index and the observed highwall strain percentage.…”

“…Nevertheless, INV has some important limitations and its application requires experienced users. In particular, INV can be used only for slopes which fail in accordance to the accelerating creep theory, excluding, for example, cases of structural (Mufundirwa et al 2010) or brittle (Rose and Hungr 2007) failure. Rose and Hungr (2007) provided a list of elements that can cause variation of displacement rates and thus hamper the performances of INV.…”

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

“…In particular, a slope might incur in a hyperbolic acceleration, called tertiary creep, that typically precedes collapse and from which a time of failure can be forecasted (Saito 1969;Fukuzono 1985;Rose and Hungr 2007;Mufundirwa et al 2010;Carlà et al 2017); the most popular method to achieve this prediction has been developed by Fukuzono (1985) and consists in plotting the inverse of the slope velocity against time: the point where the extrapolation of this plot intersects the time axis (corresponding to a theoretical infinite velocity) is an estimation of the time of failure.…”