A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
In a probabilistic slope stability analysis, the input parameters are considered as random variables that must be statistically described. The descriptive process relies on statistical analyses of discontinuity data collected by field mapping and of laboratory and field test results. Sound geologic and engineering judgment should be used in conjunction with these analyses. The probability of stability for a given slope failure mode is estimated by combining the probability of sliding and the probability that the potential sliding surface is long enough to allow failure. The probability of sliding is calculated from a safety factor distribution which can be estimated by Monte Carlo simulation or by numerical convolution performed by discrete Fourier procedures. The probability of sifficient length is estimated from discontinuity length data obtained by structure mapping. Multiple occurrences of the same failures mode in a slope can be analyzed after they have been simulated by generating spatially correlated properties of discontinuities responsible for the failure mode. A probabilistic analysis also allows for the effects of different failure modes in the same slope to be combined into a probabilistic estimate of overall slope stability. Thus, rock slope engineering can be enhanced by probabilistic methods that allow for a realistic treatment of parameter variabilities and multiple failure modes and that also produce useful probabilistic slope design criteria.
In a probabilistic slope stability analysis, the input parameters are considered as random variables that must be statistically described. The descriptive process relies on statistical analyses of discontinuity data collected by field mapping and of laboratory and field test results. Sound geologic and engineering judgment should be used in conjunction with these analyses. The probability of stability for a given slope failure mode is estimated by combining the probability of sliding and the probability that the potential sliding surface is long enough to allow failure. The probability of sliding is calculated from a safety factor distribution which can be estimated by Monte Carlo simulation or by numerical convolution performed by discrete Fourier procedures. The probability of sifficient length is estimated from discontinuity length data obtained by structure mapping. Multiple occurrences of the same failures mode in a slope can be analyzed after they have been simulated by generating spatially correlated properties of discontinuities responsible for the failure mode. A probabilistic analysis also allows for the effects of different failure modes in the same slope to be combined into a probabilistic estimate of overall slope stability. Thus, rock slope engineering can be enhanced by probabilistic methods that allow for a realistic treatment of parameter variabilities and multiple failure modes and that also produce useful probabilistic slope design criteria.
Probabilistic Rock Slope Engineering
S. M. Miller (author)
1984
80 pages
Report
No indication
English
| TIBKAT | 1974
| TIBKAT | 1981
| Elsevier | 1975
| UB Braunschweig | 1974
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