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Improving resolution of stiff layers...

Liu, Haiyan.

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Improving resolution of stiff layers in soil profiles through multi-step inversion of SASW data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Improving resolution of stiff layers in soil profiles through multi-step inversion of SASW data./
作者:	Liu, Haiyan.
面頁冊數:	213 p.
附註:	Source: Masters Abstracts International, Volume: 42-01, page: 0286.
Contained By:	Masters Abstracts International42-01.
標題:	Engineering, Civil. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1414534
ISBN:	0496193239

Improving resolution of stiff layers in soil profiles through multi-step inversion of SASW data.
Liu, Haiyan.

Improving resolution of stiff layers in soil profiles through multi-step inversion of SASW data. - 213 p.

Source: Masters Abstracts International, Volume: 42-01, page: 0286.

Thesis (M.S.E.)--University of Nevada, Las Vegas, 2002.

Stiff, cemented layers commonly encountered in desert soil profiles significantly affect the soil load capacity and load distribution pattern. The purpose of this research is to develop algorithms for detecting stiff layers through inversion of seismic surface wave data to generate one-dimensional shear wave velocity (VS) profiles.

ISBN: 0496193239Subjects--Topical Terms:

783781
Engineering, Civil.

Improving resolution of stiff layers in soil profiles through multi-step inversion of SASW data.
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245 1 0 $a Improving resolution of stiff layers in soil profiles through multi-step inversion of SASW data.
300 $a 213 p.
500 $a Source: Masters Abstracts International, Volume: 42-01, page: 0286.
500 $a Chair: Barbara A. Luke.
502 $a Thesis (M.S.E.)--University of Nevada, Las Vegas, 2002.
520 $a Stiff, cemented layers commonly encountered in desert soil profiles significantly affect the soil load capacity and load distribution pattern. The purpose of this research is to develop algorithms for detecting stiff layers through inversion of seismic surface wave data to generate one-dimensional shear wave velocity (VS) profiles.
520 $a The inversion algorithms begin with a starting model. Development of a high-quality starting model helps ensure good results.
520 $a Two inversion methods, simulated annealing (SA) and linearized inversion (LI), are applied to the problem. The SA method includes a general approach (SA-G) and an approach developed specifically to investigate stiff-inclusion systems (SA-I). Algorithms for applying these methods are developed and tested using two experimental datasets and two synthetic datasets, one of each pair being normally dispersive and the other having one or more stiff inclusions. For the stiff-inclusion experimental site, results are compared to a crosshole dataset. (Abstract shortened by UMI.)
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