United States Department of Transportation
i
Probabilistic analysis algorithm for UA slope software program.
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2013-12-01
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[PDF-2.65 MB]
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Abstract:A reliability-based computational algorithm for using a single row and equally spaced drilled shafts to
stabilize an unstable slope has been developed in this research. The Monte-Carlo simulation (MCS)
technique was used in the previously developed deterministic computational program, in which the
limiting equilibrium method of slices was modified to incorporate the arching effects of the drilled shafts
in a slope. Uncertainties of soil parameters in the slope were considered by statistical descriptors,
including mean, coefficient of variance (c.o.v.), and distribution function. Model errors of the semiempirical predictive equation for the load transfer factor for characterizing the soil arching effects were
considered by statistics of bias. A PC-based research grade program, UA Slope 3.0, was coded to allow
for analysis of probability of failure and reliability index of a shaft/slope system. The illustrative example
demonstrated that a single value of factor of safety chosen in the deterministic approach may not yield
the desired level of reliability as uncertainties of soil parameters and model errors cannot be accounted
for systematically. As an extension of this research, importance sampling technique (IST) on drilled
shaft/slope system has been proposed to demonstrate its high efficiency, in which the importance
function and design point are determined for the ordinary method of slices (OMS) with the accompanying
load transfer factor. In addition, the design method of using multiple rows of drilled shaft was developed
to stabilize a large slope, in which the design and optimization criteria were proposed to reach the target
safety and the constructability while meeting the service limit requirement.
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