4.6 Article

Geotechnical stability analysis considering strain softening using micro-polar continuum finite element method

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JOURNAL OF CENTRAL SOUTH UNIVERSITY
卷 28, 期 1, 页码 297-310

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JOURNAL OF CENTRAL SOUTH UNIV
DOI: 10.1007/s11771-021-4603-3

关键词

slope stability; strain localization; non-local geotechnical failure; micro-polar continuum; internal characteristic length

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The utilization of the micro-polar continuum in geotechnical stability analysis provides more accurate modeling of shear band width and capturing non-local geotechnical failure characteristics. The increase in internal characteristic length further exacerbates the issue of underestimation of factor of safety calculated from the classical continuum.
Geotechnical stability analyses based on classical continuum may lead to remarkable underestimations on geotechnical safety. To attain better estimations on geotechnical stability, the micro-polar continuum is employed so that its internal characteristic length (4) can be utilized to model the shear band width. Based on two soil slope examples, the role of internal characteristic length in modeling the shear band width of geomaterial is investigated by the second-order cone programming optimized micro-polar continuum finite element method. It is recognized that the underestimation on factor of safety (FOS) calculated from the classical continuum tends to be more pronounced with the increase of 4. When the micro-polar continuum is applied, the shear band dominated by 4 is almost kept unaffected as long as the adopted meshes are fine enough, but it does not generally present a slip surface like in the cases from the classical continuum, indicating that the micro-polar continuum is capable of capturing the non-local geotechnical failure characteristic. Due to the coupling effects of 4 and strain softening, softening behavior of geomaterial tends to be postponed. Additionally, the bearing capacity of a geotechnical system may be significantly underestimated, if the effects of 4 are not modeled or considered in numerical analyses.

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