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Probabilistic analysis algorithm for UA slope software program.

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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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    urn:sha-512:0ff1cb54b38526fec7c104cf168cf644bdb5f352faf2382a572770261d3b10009617d6c7ad89f171a43461e157d840d6b44498d3929b946eaba05947ef3309d8
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