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Robust Geotechnical Design Optimizat...

Rahbari, Parishad.

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Robust Geotechnical Design Optimization of Retaining Walls and Levees.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Robust Geotechnical Design Optimization of Retaining Walls and Levees./
Author:	Rahbari, Parishad.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	164 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.
Contained By:	Dissertation Abstracts International79-04B(E).
Subject:	Geotechnology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10616570
ISBN:	9780355345469

Robust Geotechnical Design Optimization of Retaining Walls and Levees.
Rahbari, Parishad.

Robust Geotechnical Design Optimization of Retaining Walls and Levees. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 164 p.

Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.

Thesis (Ph.D.)--Clemson University, 2017.

This dissertation presents a robust geotechnical design optimization framework for retaining walls with sand backfill and lightweight shredded tire backfill subjected to earthquake load, and I-wall levee systems supported by sand foundation and clay foundation subjected to flood. The responses of retaining walls and levee systems are highly uncertain especially when subjected to natural disasters such as earthquake and flooding. The variations in the response of these systems are caused by the uncertainties associated with not only the soil properties, but also the loads induced by earthquake and flood. These critical systems must show satisfactory performance under these uncertainties because their failure may result in loss of life and property as noted in the past events. Therefore, in this study, the uncertainties in engineering properties of soils (backfill in retaining walls, levee fill and foundation in I-wall levee systems) were considered systematically along with the uncertainty in the external loads (earthquake in retaining walls and flooding in I-wall levee systems). The key design variables of these two systems were determined and based on their ranges several design cases were generated. Fully coupled finite element analyses were performed for computing responses of concern accurately, and appropriate response surfaces were developed for the respective responses of concern. Using the response surface and via a genetic algorithm code, the designs of these systems were optimized to cost and robustness while satisfying the safety constraints. Sets of preferred designs, known as Pareto fronts, were captured through the bi-objective robust optimizations that can be used as a decision-making tool for selecting the suitable design in engineering practice.

ISBN: 9780355345469Subjects--Topical Terms:

1018558
Geotechnology.

Robust Geotechnical Design Optimization of Retaining Walls and Levees.
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520 $a This dissertation presents a robust geotechnical design optimization framework for retaining walls with sand backfill and lightweight shredded tire backfill subjected to earthquake load, and I-wall levee systems supported by sand foundation and clay foundation subjected to flood. The responses of retaining walls and levee systems are highly uncertain especially when subjected to natural disasters such as earthquake and flooding. The variations in the response of these systems are caused by the uncertainties associated with not only the soil properties, but also the loads induced by earthquake and flood. These critical systems must show satisfactory performance under these uncertainties because their failure may result in loss of life and property as noted in the past events. Therefore, in this study, the uncertainties in engineering properties of soils (backfill in retaining walls, levee fill and foundation in I-wall levee systems) were considered systematically along with the uncertainty in the external loads (earthquake in retaining walls and flooding in I-wall levee systems). The key design variables of these two systems were determined and based on their ranges several design cases were generated. Fully coupled finite element analyses were performed for computing responses of concern accurately, and appropriate response surfaces were developed for the respective responses of concern. Using the response surface and via a genetic algorithm code, the designs of these systems were optimized to cost and robustness while satisfying the safety constraints. Sets of preferred designs, known as Pareto fronts, were captured through the bi-objective robust optimizations that can be used as a decision-making tool for selecting the suitable design in engineering practice.
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