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Dam and Spillway Safety: Screening Technique to Identify Risky Auxiliary Spillways at a Large Scale.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dam and Spillway Safety: Screening Technique to Identify Risky Auxiliary Spillways at a Large Scale./
作者:	Ghimire, Sanjeeta Neupane.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	214 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-10, Section: B.
Contained By:	Dissertations Abstracts International82-10B.
標題:	Geotechnology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28420564
ISBN:	9798582557975

Dam and Spillway Safety: Screening Technique to Identify Risky Auxiliary Spillways at a Large Scale.
Ghimire, Sanjeeta Neupane.

Dam and Spillway Safety: Screening Technique to Identify Risky Auxiliary Spillways at a Large Scale. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 214 p.

Source: Dissertations Abstracts International, Volume: 82-10, Section: B.

Thesis (Ph.D.)--University of Illinois at Chicago, 2020.

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

Dam operators often do not know whether the auxiliary spillway will fail until it is loaded, which can be once every ten, fifty, or a hundred years. Such failures can result in overall dam failure leading to loss of life and substantial property damage. The purpose of this dissertation is to develop a screening technique to identify potentially risky earthen auxiliary spillways. The dissertation uses the National Inventory of Dams (NID) data and analyzes a sample of 400 earthen dams and spillways. The main innovation of the dissertation is to employ a user-defined code to create multiple input files and analyze them in the Windows Dam Analysis Modules (WinDAM) C software. This technique is more efficient than the current functionality of the software that requires input information for one dam at a time. The proposed method serves as a quick screening and decision-making tool for multiple dams and spillways, especially to be prepared for extreme events like flooding, seismic activity, etc. by identifying potentially risky auxiliary spillways that may require in-depth analysis. The application of the model is tested by using various site-specific cases that have experienced past failures and the cases that are predicted to fail in the future. A sensitivity analysis is performed to identify the individual material parameter's influence on the overall spillway erosion. The most sensitive sets of variables are chosen to perform predictive analysis. A logistic regression model is applied to evaluate the erosion potential by incorporating a machine learning approach, and the usefulness of the model is verified using Bayesian inference. The dissertation also presents the impacts of climate change on dam safety by examining two recent Michigan dam failures, Edenville and Sanford, that failed in May 2020. The increasing temperature, precipitation, floods, etc. are observed, and the consequences are visualized with the help of WinDAM and Hydrologic Engineering Center - River Analysis System (HEC-RAS) simulations. Overall, besides the novelties presented in the model and various analyses, the dissertation provides useful insights into how the global climate change effects are hampering the watershed area, reservoir storage, and overall dam and spillway safety in the US.

ISBN: 9798582557975Subjects--Topical Terms:

1018558
Geotechnology.
Subjects--Index Terms:

Auxiliary Spillways

Dam and Spillway Safety: Screening Technique to Identify Risky Auxiliary Spillways at a Large Scale.
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300 $a 214 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-10, Section: B.
500 $a Advisor: Schulenberg, Joseph W.;Reddy, Krishna R.
502 $a Thesis (Ph.D.)--University of Illinois at Chicago, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Dam operators often do not know whether the auxiliary spillway will fail until it is loaded, which can be once every ten, fifty, or a hundred years. Such failures can result in overall dam failure leading to loss of life and substantial property damage. The purpose of this dissertation is to develop a screening technique to identify potentially risky earthen auxiliary spillways. The dissertation uses the National Inventory of Dams (NID) data and analyzes a sample of 400 earthen dams and spillways. The main innovation of the dissertation is to employ a user-defined code to create multiple input files and analyze them in the Windows Dam Analysis Modules (WinDAM) C software. This technique is more efficient than the current functionality of the software that requires input information for one dam at a time. The proposed method serves as a quick screening and decision-making tool for multiple dams and spillways, especially to be prepared for extreme events like flooding, seismic activity, etc. by identifying potentially risky auxiliary spillways that may require in-depth analysis. The application of the model is tested by using various site-specific cases that have experienced past failures and the cases that are predicted to fail in the future. A sensitivity analysis is performed to identify the individual material parameter's influence on the overall spillway erosion. The most sensitive sets of variables are chosen to perform predictive analysis. A logistic regression model is applied to evaluate the erosion potential by incorporating a machine learning approach, and the usefulness of the model is verified using Bayesian inference. The dissertation also presents the impacts of climate change on dam safety by examining two recent Michigan dam failures, Edenville and Sanford, that failed in May 2020. The increasing temperature, precipitation, floods, etc. are observed, and the consequences are visualized with the help of WinDAM and Hydrologic Engineering Center - River Analysis System (HEC-RAS) simulations. Overall, besides the novelties presented in the model and various analyses, the dissertation provides useful insights into how the global climate change effects are hampering the watershed area, reservoir storage, and overall dam and spillway safety in the US.
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650 4 $a Civil engineering. $3 860360
653 $a Auxiliary Spillways
653 $a Erosion
653 $a Screening Technique
653 $a WinDAM
653 $a Model Application
653 $a Sensitivity Analysis
653 $a Statistical Analysis
653 $a Machine Learning
653 $a Climate Change
653 $a Dam and Spillway Safety
690 $a 0543
690 $a 0428
710 2 $a University of Illinois at Chicago. $b Civil, Materials, and Environmental Engineering. $3 3680684
773 0 $t Dissertations Abstracts International $g 82-10B.
790 $a 0799
791 $a Ph.D.
792 $a 2020
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28420564