An Empirical, Functional approach to Depth Damages
In order to compute direct damages to structures and contents, the United States Army Corps of Engineers (USACE) has traditionally relied on relationships that define damage for a given depth. These relationships are described using paired data relationships of depth and damage. Generally, the curve...
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2016-01-01
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Series: | E3S Web of Conferences |
Online Access: | http://dx.doi.org/10.1051/e3sconf/20160705002 |
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doaj-78e1af9e998d449185e04547cf2a50742021-02-02T08:12:25ZengEDP SciencesE3S Web of Conferences2267-12422016-01-0170500210.1051/e3sconf/20160705002e3sconf_flood2016_05002An Empirical, Functional approach to Depth DamagesLehman Will0Hasanzadeh Nafari R.1USACECDMPS, Deparment of Infrastructure Engineering, The University of MelbourneIn order to compute direct damages to structures and contents, the United States Army Corps of Engineers (USACE) has traditionally relied on relationships that define damage for a given depth. These relationships are described using paired data relationships of depth and damage. Generally, the curves utilized are based on an Elicitation of Experts (EoE). This paper will present an alternative methodology which takes empirical data of damage and depth, stratified by building classifications, and use Non Linear Least Squares Estimation to fit a parameterized function to compute depth-damage estimates. The general function will be described, and the parameters will be discussed. Parameters include foundation height, ground elevation, percent damages below ground, number of stories, height of stories, maximum damage as a percent, and the beginning elevation for damage. The advantages of this approach include the ability to utilize empirical data, and the ability to change parameters based on building practices across the world. Additionally, the paper will illustrate a bootstrapping approach to the empirical data to assist in describing confidence limits around the parameterized functional depth damage relationship. A Figure (Figure 1) is provided to illustrate the output of the process.http://dx.doi.org/10.1051/e3sconf/20160705002 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lehman Will Hasanzadeh Nafari R. |
spellingShingle |
Lehman Will Hasanzadeh Nafari R. An Empirical, Functional approach to Depth Damages E3S Web of Conferences |
author_facet |
Lehman Will Hasanzadeh Nafari R. |
author_sort |
Lehman Will |
title |
An Empirical, Functional approach to Depth Damages |
title_short |
An Empirical, Functional approach to Depth Damages |
title_full |
An Empirical, Functional approach to Depth Damages |
title_fullStr |
An Empirical, Functional approach to Depth Damages |
title_full_unstemmed |
An Empirical, Functional approach to Depth Damages |
title_sort |
empirical, functional approach to depth damages |
publisher |
EDP Sciences |
series |
E3S Web of Conferences |
issn |
2267-1242 |
publishDate |
2016-01-01 |
description |
In order to compute direct damages to structures and contents, the United States Army Corps of Engineers (USACE) has traditionally relied on relationships that define damage for a given depth. These relationships are described using paired data relationships of depth and damage. Generally, the curves utilized are based on an Elicitation of Experts (EoE). This paper will present an alternative methodology which takes empirical data of damage and depth, stratified by building classifications, and use Non Linear Least Squares Estimation to fit a parameterized function to compute depth-damage estimates. The general function will be described, and the parameters will be discussed. Parameters include foundation height, ground elevation, percent damages below ground, number of stories, height of stories, maximum damage as a percent, and the beginning elevation for damage. The advantages of this approach include the ability to utilize empirical data, and the ability to change parameters based on building practices across the world. Additionally, the paper will illustrate a bootstrapping approach to the empirical data to assist in describing confidence limits around the parameterized functional depth damage relationship. A Figure (Figure 1) is provided to illustrate the output of the process. |
url |
http://dx.doi.org/10.1051/e3sconf/20160705002 |
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