Efficient Robust Geotechnical Design of Drilled Shafts in Clay Using a Spreadsheet
This article has been corrected.
VIEW CORRECTIONPublication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 141, Issue 2
Abstract
This paper presents an efficient robust geotechnical design (RGD) approach that considers performance requirements, design robustness, and cost efficiency simultaneously. In this paper, design robustness is measured via the variation in the performance function of concern that can be evaluated using reliability analysis. Furthermore, the performance requirements of the system are also evaluated using reliability analysis. Thus, the evaluation of design robustness and the evaluation of performance requirements share common computational steps, referred to herein as computational coupling. This coupling for computational efficiency is a significant feature of the proposed RGD approach. Within the framework of the proposed RGD approach, design robustness, cost efficiency, and performance requirements can be considered simultaneously by means of multiobjective optimization. Furthermore, a practical and efficient procedure is developed for such optimization using a feature resident in a popular spreadsheet program. Through an example of the design of a drilled shaft in clay, the effectiveness of this new RGD approach is demonstrated. The results show that the hard-to-control variability resulting from construction variation, variable loading conditions, model errors, and uncertain geotechnical parameters in the design of drilled shafts in clay can be effectively considered with the proposed RGD approach.
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Acknowledgments
The study on which this paper is based was supported in part by the National Science Foundation (Grant No. CMMI-1200117, “Transforming Robust Design Concept into a Novel Geotechnical Design Tool”) and the Glenn Department of Civil Engineering, Clemson University. The results and opinions expressed in this paper do not necessarily reflect the views and policies of the National Science Foundation.
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© 2014 American Society of Civil Engineers.
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Received: Dec 27, 2013
Accepted: Sep 9, 2014
Published online: Oct 6, 2014
Published in print: Feb 1, 2015
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