Probabilistic analysis algorithm for UA slope software program.
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2013-12-01
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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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Main Document Checksum:urn:sha-512:0ff1cb54b38526fec7c104cf168cf644bdb5f352faf2382a572770261d3b10009617d6c7ad89f171a43461e157d840d6b44498d3929b946eaba05947ef3309d8