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Mixing Regression-Global Sensitivity analysis of concrete arch dam system safety considering foundation and abutment uncertainties
Abstract A mixing-locally polynomial Regression method and Global Sensitivity analysis – (MRGS) procedure is used in assessing foundation and abutment uncertainties of concrete arch dams. Latin hypercube sampling is employed for generating samples in the sensitivity analysis. The model consists of a typical 80 m high arch dam along with its foundation and abutments. A potentially movable rock wedge confined by three discontinuities located in the Karun IV dam’s abutment is incorporated in the model. The random variables include (a) variables related to the geometry of foundation discontinuities, (b) variables associated with the strength of discontinuities, and (c) rock mass properties. The response parameter (Damage Parameter (DP)) is the maximum displacement of the foundation in contact with the dam body. Sobol indices as a measure of sensitivity to response change are computed for each random variable, and the most important random variables affecting the dam's stability are identified. Results show that compared with the first-order polynomial, the second-order functions lead to a more efficient sample size. The proposed methodology can be used practically in the reliability analysis of not only any existing concrete arch dam but also for similar civil engineering systems.
Mixing Regression-Global Sensitivity analysis of concrete arch dam system safety considering foundation and abutment uncertainties
Abstract A mixing-locally polynomial Regression method and Global Sensitivity analysis – (MRGS) procedure is used in assessing foundation and abutment uncertainties of concrete arch dams. Latin hypercube sampling is employed for generating samples in the sensitivity analysis. The model consists of a typical 80 m high arch dam along with its foundation and abutments. A potentially movable rock wedge confined by three discontinuities located in the Karun IV dam’s abutment is incorporated in the model. The random variables include (a) variables related to the geometry of foundation discontinuities, (b) variables associated with the strength of discontinuities, and (c) rock mass properties. The response parameter (Damage Parameter (DP)) is the maximum displacement of the foundation in contact with the dam body. Sobol indices as a measure of sensitivity to response change are computed for each random variable, and the most important random variables affecting the dam's stability are identified. Results show that compared with the first-order polynomial, the second-order functions lead to a more efficient sample size. The proposed methodology can be used practically in the reliability analysis of not only any existing concrete arch dam but also for similar civil engineering systems.
Mixing Regression-Global Sensitivity analysis of concrete arch dam system safety considering foundation and abutment uncertainties
Ahmadi, Mohammad T. (author) / Soltani, Narjes (author)
2021-07-15
Article (Journal)
Electronic Resource
English
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