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Finite Element Modeling for Assessing Flood Barrier Risks and Failures Due to Storm Surges and Waves.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Finite Element Modeling for Assessing Flood Barrier Risks and Failures Due to Storm Surges and Waves./
作者:	Wood, Dylan.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	198 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-01, Section: B.
Contained By:	Dissertations Abstracts International83-01B.
標題:	Physics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28642434
ISBN:	9798516074738

Finite Element Modeling for Assessing Flood Barrier Risks and Failures Due to Storm Surges and Waves.
Wood, Dylan.

Finite Element Modeling for Assessing Flood Barrier Risks and Failures Due to Storm Surges and Waves. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 198 p.

Source: Dissertations Abstracts International, Volume: 83-01, Section: B.

Thesis (Ph.D.)--The Ohio State University, 2020.

This item must not be sold to any third party vendors.

Storms often severely impact coastal areas, posing risks to life, infrastructure and the economy. In major coastal centers of population and commerce, extensive flood protection systems are implemented to mitigate storm impacts and reduce risks. If the flood barriers that comprise these systems fail, e.g., by erosion, excess capacity, or some design flaw, then extensive losses can be incurred to protected areas. Finite element models for solutions to the shallow water equations are frequently used to project risks to coastal areas due to impacts of storm surge; however, despite the significant risks posed by flood barrier failures, the models in use typically are limited in regard to modeling these risks, only considering one of the many different modes in which these systems may potentially fail, overtopping. Additionally, the finite element models exert considerable computational demand, often constraining their applications to high performance parallel computing environments. In this study, we seek to enhance the flood barrier modeling capabilities of current finite element modeling frameworks designed for projecting risks due to storm surge, by seeking cost effective solutions that minimize additional computational demands as well as by optimizing the currently existing techniques. Discussion of these developments primarily is in the context of a discontinuous Galerkin (DG) based framework for modeling of shallow water flow. We demonstrate improvements on the efficiency of this approach by implementing DG-optimized strong stability-persevering Runge--Kutta (RK) time stepping, which optimizes for the stability region of the RK method, and can reduce the computational demand by at least 5% for low-order approximations. Additional consideration is owed to quadrilateral based finite element meshes, which can nearly half the computational demand exerted by more commonly used triangular meshes. Finally, we demonstrate fast and effective approximations of storm surge by parametric wind modeling, in lieu of processing large data sets of atmospheric measurements. Approaches for modeling the interaction of flow with flood barriers are also refined, by first introducing corrections for piping flows, i.e., flows which may occur through a barrier structure at localized points either due to design or by internal erosion, and then by coupling with a parametric model for waves. The parametric wave model is shown to provide reliable approximations of wave heights and overtopping rates for barrier structures, as compared to a commonly used spectral wave model, despite its significantly reduced computational demand and description of the wave field. Finally, we demonstrate a framework for interfacing these finite element modeling capabilities with those for continuum analysis and geotechnical modeling to realize the full extent of risks posed to a barrier structure by storm impact, and study a case involving failure due to a flood wall and embedded sheet pile instability in a levee in New Orleans, Louisiana. By the model optimizations and refinements shown here, researchers can be prepared to more thoroughly and efficiently assess risks posed to flood barrier structures by storms as well as the flooding risks posed by the potential failures of these structures, especially in the context of forecasting risks for hurricanes and tropical storms.

ISBN: 9798516074738Subjects--Topical Terms:

516296
Physics.
Subjects--Index Terms:

Finite element

Finite Element Modeling for Assessing Flood Barrier Risks and Failures Due to Storm Surges and Waves.
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500 $a Source: Dissertations Abstracts International, Volume: 83-01, Section: B.
500 $a Advisor: Kubatko, Ethan.
502 $a Thesis (Ph.D.)--The Ohio State University, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Storms often severely impact coastal areas, posing risks to life, infrastructure and the economy. In major coastal centers of population and commerce, extensive flood protection systems are implemented to mitigate storm impacts and reduce risks. If the flood barriers that comprise these systems fail, e.g., by erosion, excess capacity, or some design flaw, then extensive losses can be incurred to protected areas. Finite element models for solutions to the shallow water equations are frequently used to project risks to coastal areas due to impacts of storm surge; however, despite the significant risks posed by flood barrier failures, the models in use typically are limited in regard to modeling these risks, only considering one of the many different modes in which these systems may potentially fail, overtopping. Additionally, the finite element models exert considerable computational demand, often constraining their applications to high performance parallel computing environments. In this study, we seek to enhance the flood barrier modeling capabilities of current finite element modeling frameworks designed for projecting risks due to storm surge, by seeking cost effective solutions that minimize additional computational demands as well as by optimizing the currently existing techniques. Discussion of these developments primarily is in the context of a discontinuous Galerkin (DG) based framework for modeling of shallow water flow. We demonstrate improvements on the efficiency of this approach by implementing DG-optimized strong stability-persevering Runge--Kutta (RK) time stepping, which optimizes for the stability region of the RK method, and can reduce the computational demand by at least 5% for low-order approximations. Additional consideration is owed to quadrilateral based finite element meshes, which can nearly half the computational demand exerted by more commonly used triangular meshes. Finally, we demonstrate fast and effective approximations of storm surge by parametric wind modeling, in lieu of processing large data sets of atmospheric measurements. Approaches for modeling the interaction of flow with flood barriers are also refined, by first introducing corrections for piping flows, i.e., flows which may occur through a barrier structure at localized points either due to design or by internal erosion, and then by coupling with a parametric model for waves. The parametric wave model is shown to provide reliable approximations of wave heights and overtopping rates for barrier structures, as compared to a commonly used spectral wave model, despite its significantly reduced computational demand and description of the wave field. Finally, we demonstrate a framework for interfacing these finite element modeling capabilities with those for continuum analysis and geotechnical modeling to realize the full extent of risks posed to a barrier structure by storm impact, and study a case involving failure due to a flood wall and embedded sheet pile instability in a levee in New Orleans, Louisiana. By the model optimizations and refinements shown here, researchers can be prepared to more thoroughly and efficiently assess risks posed to flood barrier structures by storms as well as the flooding risks posed by the potential failures of these structures, especially in the context of forecasting risks for hurricanes and tropical storms.
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650 4 $a Geotechnology. $3 1018558
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