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    Source: International Journal of Geomechanics:;2018:;Volume ( 018 ):;issue: 005
    Author:
    Bathurst Richard J.;Yu Yan
    DOI: 10.1061/(ASCE)GM.1943-5622.0001120
    Publisher: American Society of Civil Engineers
    Abstract: The response surface method (RSM) with a quadratic polynomial was used to formulate three equations for the calculation of the maximum reinforcement loads in steel-reinforced mechanically stabilized earth (MSE) walls under operational (working stress) conditions. The RSM models were formulated using control variables found in the simplified stiffness method. The model coefficients were back-calculated from a large database of measured steel-reinforcement loads from full-scale instrumented walls using a least-squares solution. Model uncertainty was quantified using bias statistics for which model bias is defined as the ratio of measured to calculated reinforcement load. The simplest of the three RSM models has only three empirical constants and has the advantage that reinforcement stiffness and soil friction angle are not required as input parameters. The same model was shown to give a predicted load accuracy that exceeds that of the simplified method that is used in current U.S. design specifications and has the same practical accuracy as the simplified stiffness method used for steel MSE walls constructed with frictional soils. The paper shows how the three models can be used in Monte Carlo simulations to compute probabilities of load exceedance at the time of design.
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    contributor authorBathurst Richard J.;Yu Yan
    date accessioned2019-02-26T07:58:43Z
    date available2019-02-26T07:58:43Z
    date issued2018
    identifier other%28ASCE%29GM.1943-5622.0001120.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4250642
    description abstractThe response surface method (RSM) with a quadratic polynomial was used to formulate three equations for the calculation of the maximum reinforcement loads in steel-reinforced mechanically stabilized earth (MSE) walls under operational (working stress) conditions. The RSM models were formulated using control variables found in the simplified stiffness method. The model coefficients were back-calculated from a large database of measured steel-reinforcement loads from full-scale instrumented walls using a least-squares solution. Model uncertainty was quantified using bias statistics for which model bias is defined as the ratio of measured to calculated reinforcement load. The simplest of the three RSM models has only three empirical constants and has the advantage that reinforcement stiffness and soil friction angle are not required as input parameters. The same model was shown to give a predicted load accuracy that exceeds that of the simplified method that is used in current U.S. design specifications and has the same practical accuracy as the simplified stiffness method used for steel MSE walls constructed with frictional soils. The paper shows how the three models can be used in Monte Carlo simulations to compute probabilities of load exceedance at the time of design.
    publisherAmerican Society of Civil Engineers
    typeJournal Paper
    journal volume18
    journal issue5
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/(ASCE)GM.1943-5622.0001120
    page4018027
    treeInternational Journal of Geomechanics:;2018:;Volume ( 018 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian