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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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