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    Reliability-Based Internal Limit State Analysis and Design of Soil Nails Using Different Load and Resistance Models

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2018:;Volume ( 144 ):;issue: 005
    Author:
    Lin Peiyuan;Bathurst Richard J.
    DOI: 10.1061/(ASCE)GT.1943-5606.0001862
    Publisher: American Society of Civil Engineers
    Abstract: A general approach for reliability-based analysis and design for pullout and tensile failure internal limit states of soil nail walls is presented. Reliability index values are computed using a closed-form solution that captures the influence of nominal load and nominal resistance model type and accuracy (method bias), bias dependencies, uncertainty in nominal load and resistance values, and possible cross-correlation (dependency) between nominal nail load and resistance terms. Maximum nail loads under operational conditions for the two limit states are calculated using the current Federal Highway Administration (FHWA) simplified method and an improved version recently published by the authors. Nail pullout capacity is calculated using the effective stress method used in Hong Kong and a modified version that has been empirically adjusted to improve model accuracy for soil nails installed in two different Hong Kong soils. Example designs with three different nail length patterns are used to illustrate the design approach and the assessment of margins of safety using factor of safety and reliability index for the pullout limit state. The results of parametric analyses and design examples demonstrate that for the same target reliability index, the combination of improved load and resistance models gave better solutions based on total length of soil nails.
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      Reliability-Based Internal Limit State Analysis and Design of Soil Nails Using Different Load and Resistance Models

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4250722
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    • Journal of Geotechnical and Geoenvironmental Engineering

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    contributor authorLin Peiyuan;Bathurst Richard J.
    date accessioned2019-02-26T07:59:32Z
    date available2019-02-26T07:59:32Z
    date issued2018
    identifier other%28ASCE%29GT.1943-5606.0001862.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4250722
    description abstractA general approach for reliability-based analysis and design for pullout and tensile failure internal limit states of soil nail walls is presented. Reliability index values are computed using a closed-form solution that captures the influence of nominal load and nominal resistance model type and accuracy (method bias), bias dependencies, uncertainty in nominal load and resistance values, and possible cross-correlation (dependency) between nominal nail load and resistance terms. Maximum nail loads under operational conditions for the two limit states are calculated using the current Federal Highway Administration (FHWA) simplified method and an improved version recently published by the authors. Nail pullout capacity is calculated using the effective stress method used in Hong Kong and a modified version that has been empirically adjusted to improve model accuracy for soil nails installed in two different Hong Kong soils. Example designs with three different nail length patterns are used to illustrate the design approach and the assessment of margins of safety using factor of safety and reliability index for the pullout limit state. The results of parametric analyses and design examples demonstrate that for the same target reliability index, the combination of improved load and resistance models gave better solutions based on total length of soil nails.
    publisherAmerican Society of Civil Engineers
    titleReliability-Based Internal Limit State Analysis and Design of Soil Nails Using Different Load and Resistance Models
    typeJournal Paper
    journal volume144
    journal issue5
    journal titleJournal of Geotechnical and Geoenvironmental Engineering
    identifier doi10.1061/(ASCE)GT.1943-5606.0001862
    page4018022
    treeJournal of Geotechnical and Geoenvironmental Engineering:;2018:;Volume ( 144 ):;issue: 005
    contenttypeFulltext
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