R-LRFD: Load and resistance factor design considering robustness

被引:41
作者
Gong, Wenping [1 ]
Juang, C. Hsein [1 ,2 ]
Khoshnevisan, Sara [1 ]
Phoon, Kok-Kwang [3 ]
机构
[1] Clemson Univ, Glenn Dept Civil Engn, Clemson, SC 29634 USA
[2] Natl Cent Univ, Dept Civil Engn, Taoyuan 320, Taiwan
[3] Natl Univ Singapore, Dept Civil & Environm Engn, Singapore 117576, Singapore
基金
美国国家科学基金会;
关键词
LRFD; Robust design; Sensitivity; Pareto front; Knee point; Drilled shaft; RELIABILITY-BASED DESIGN; GEOTECHNICAL DESIGN; FACTORS CALIBRATION; DRILLED SHAFTS; OPTIMIZATION; ALGORITHM; FRAMEWORK;
D O I
10.1016/j.compgeo.2015.12.017
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
LRFD (Load and Resistance Factor Design) is becoming a design method of choice in geotechnical practice, in lieu of the factor of safety (FS)-based design approach. However, even with LRFD, the need to reduce the variation in the predicted performance of a geotechnical system (or a geotechnical structure), referred to herein as the system response under applied loads, is still apparent. This paper presents a novel approach for applying existing LRFD codes, with explicit consideration of design robustness, safety, and cost efficiency. The recently developed reliability-based robust geotechnical design (RGD) approach is modified such that it can be integrated with the standard LRFD approach. This modified RGD approach is termed R-LRFD, which stands for Robust Load and Resistance Factor Design. In R-LRFD, the robustness of the system response against the variation in uncertain parameters is explicitly considered. Unlike the reliability-based design (RBD), the user is not required to conduct a full statistical characterization of uncertain parameters. With R-LRFD, the gain in the robustness, as reflected by the reduction in the sensitivity of the system response to the recognized but unquantified uncertainty of input parameters, is accompanied by an increase in cost. Thus, the concepts of Pareto front and knee point are introduced to aid in making an informed design decision. Further, a simplified procedure is developed to identify the most preferred design (knee point) in the design space, which is generally solved with multi objective optimization algorithms. The effectiveness and significance of the proposed R-LRFD approach are demonstrated with two examples: one is the design of drilled shaft in sand (illustrated with a discrete design space) and the other is the design of drilled shaft in clay (illustrated with a continuous design space). (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:74 / 87
页数:14
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