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Three-dimensional site characterizat...

Jiang, Tao.

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Three-dimensional site characterization with artificial neural networks.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Three-dimensional site characterization with artificial neural networks./
Author:	Jiang, Tao.
Description:	176 p.
Notes:	Co-Advisers: C. Hsein Juang; Raymond A. Christopher.
Contained By:	Dissertation Abstracts International63-03B.
Subject:	Engineering, Civil. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3045211
ISBN:	0493590528

Three-dimensional site characterization with artificial neural networks.
Jiang, Tao.

Three-dimensional site characterization with artificial neural networks. - 176 p.

Co-Advisers: C. Hsein Juang; Raymond A. Christopher.

Thesis (Ph.D.)--Clemson University, 2002.

This research is designed to develop a new technique for site characterization in a three-dimensional domain. Site characterization is a fundamental task in geotechnical engineering practice, as well as a very challenging process, with the ultimate goal of estimating soil properties based on limited tests at any half-space subsurface point in a site.

ISBN: 0493590528Subjects--Topical Terms:

783781
Engineering, Civil.

Three-dimensional site characterization with artificial neural networks.
LDR:02602nam 2200301 a 45 001 926887
005 20110422
008 110422s2002 eng d
020 $a 0493590528
035 $a (UnM)AAI3045211
035 $a AAI3045211
040 $a UnM $c UnM
100 1 $a Jiang, Tao. $3 1023418
245 1 0 $a Three-dimensional site characterization with artificial neural networks.
300 $a 176 p.
500 $a Co-Advisers: C. Hsein Juang; Raymond A. Christopher.
500 $a Source: Dissertation Abstracts International, Volume: 63-03, Section: B, page: 1471.
502 $a Thesis (Ph.D.)--Clemson University, 2002.
520 $a This research is designed to develop a new technique for site characterization in a three-dimensional domain. Site characterization is a fundamental task in geotechnical engineering practice, as well as a very challenging process, with the ultimate goal of estimating soil properties based on limited tests at any half-space subsurface point in a site.
520 $a In this research, the sandy site at the Texas A&M University's National Geotechnical Experimentation Site is selected as an example to develop the new technique for site characterization, which is based on Artificial Neural Networks (ANN) technology. In this study, a sequential approach is used to demonstrate the applicability of ANN to site characterization. To verify its robustness, the proposed new technique is compared with other commonly used approaches for site characterization. In addition, an artificial site is created, wherein soil property values at any half-space point are assumed, and thus the predicted values can compare directly with their corresponding actual values, as a means of validation.
520 $a Since the three-dimensional model has the capability of estimating the soil property at any location in a site, it could have many potential applications, especially in such case, wherein the soil properties within a zone are of interest rather than at a single point. Examples of soil properties of zonal interest include soil type classification and liquefaction potential evaluation. In this regard, the present study also addresses this type of applications based on a site located in Taiwan, which experienced liquefaction during the 1999 Chi-Chi, Taiwan, Earthquake.
590 $a School code: 0050.
650 4 $a Engineering, Civil. $3 783781
690 $a 0543
710 2 0 $a Clemson University. $3 997173
773 0 $t Dissertation Abstracts International $g 63-03B.
790 $a 0050
790 1 0 $a Christopher, Raymond A., $e advisor
790 1 0 $a Juang, C. Hsein, $e advisor
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3045211