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Modeling the likelihood of extreme e...

Tufts University., Civil Engineering.

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Modeling the likelihood of extreme earthquakes, the spatial variability of seismic properties, and the site response transfer function.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Modeling the likelihood of extreme earthquakes, the spatial variability of seismic properties, and the site response transfer function./
Author:	Thompson, Eric M.
Description:	201 p.
Notes:	Adviser: Laurie G. Baise.
Contained By:	Dissertation Abstracts International70-01B.
Subject:	Engineering, Civil. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3344054

Modeling the likelihood of extreme earthquakes, the spatial variability of seismic properties, and the site response transfer function.
Thompson, Eric M.

Modeling the likelihood of extreme earthquakes, the spatial variability of seismic properties, and the site response transfer function. - 201 p.

Adviser: Laurie G. Baise.

Thesis (Ph.D.)--Tufts University, 2009.

This dissertation addresses three different earthquake engineering prediction problems and draws heavily from other fields, especially statistics. The great uncertainty associated with each prediction requires statistics to rigorously address the problem. Conventional wisdom within the geotechnical engineering field often assumes that there is too much uncertainty in the material property estimates to use statistics. This assumption reflects a limited understanding of the role and value of statistics: if there was no uncertainty then we would not need statistics. In fact, statistics provides a quantitative framework for analyzing and understanding the uncertainty that is so prevalent in the natural world. This dissertation focuses on (i) the likelihood of large earthquakes, (ii) spatial interpolation of seismic properties, and (iii) the theoretical formulation of site response prediction. The accuracy of the predictions in each problem is limited for fundamentally different reasons. By properly accounting for the unique limitations in each situation, I hope to improve our understanding of the problem and help the field develop more accurate models.Subjects--Topical Terms:

783781
Engineering, Civil.

Modeling the likelihood of extreme earthquakes, the spatial variability of seismic properties, and the site response transfer function.
LDR:02193nam 2200301 a 45 001 854269
005 20100702
008 100702s2009 ||||||||||||||||| ||eng d
035 $a (UMI)AAI3344054
035 $a AAI3344054
040 $a UMI $c UMI
100 1 $a Thompson, Eric M. $3 1020595
245 1 0 $a Modeling the likelihood of extreme earthquakes, the spatial variability of seismic properties, and the site response transfer function.
300 $a 201 p.
500 $a Adviser: Laurie G. Baise.
500 $a Source: Dissertation Abstracts International, Volume: 70-01, Section: B, page: 0514.
502 $a Thesis (Ph.D.)--Tufts University, 2009.
520 $a This dissertation addresses three different earthquake engineering prediction problems and draws heavily from other fields, especially statistics. The great uncertainty associated with each prediction requires statistics to rigorously address the problem. Conventional wisdom within the geotechnical engineering field often assumes that there is too much uncertainty in the material property estimates to use statistics. This assumption reflects a limited understanding of the role and value of statistics: if there was no uncertainty then we would not need statistics. In fact, statistics provides a quantitative framework for analyzing and understanding the uncertainty that is so prevalent in the natural world. This dissertation focuses on (i) the likelihood of large earthquakes, (ii) spatial interpolation of seismic properties, and (iii) the theoretical formulation of site response prediction. The accuracy of the predictions in each problem is limited for fundamentally different reasons. By properly accounting for the unique limitations in each situation, I hope to improve our understanding of the problem and help the field develop more accurate models.
590 $a School code: 0234.
650 4 $a Engineering, Civil. $3 783781
650 4 $a Geophysics. $3 535228
650 4 $a Statistics. $3 517247
690 $a 0373
690 $a 0463
690 $a 0543
710 2 $a Tufts University. $b Civil Engineering. $3 1020594
773 0 $t Dissertation Abstracts International $g 70-01B.
790 $a 0234
790 1 0 $a Baise, Laurie G., $e advisor
790 1 0 $a Kayen, Robert E. $e committee member
790 1 0 $a Vogel, Richard M. $e committee member
791 $a Ph.D.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3344054