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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Main Authors: Lehman Will, Hasanzadeh Nafari R.
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:E3S Web of Conferences
Online Access:http://dx.doi.org/10.1051/e3sconf/20160705002
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spelling 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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