Probabilistic site characterization at the national geotechnical experimentation sites
Author(s)
Bibliographic Information
Probabilistic site characterization at the national geotechnical experimentation sites
(Geotechnical special publication, no. 121)
American Society of Civil Engineers, c2003
- : pbk
Available at 1 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references and index
Description and Table of Contents
Description
The papers in this Geotechnical Special Publication explain and demonstrate a broad range of methods of probabilistic site characterization using soil data obtained at one or more National Geotechnical Experimentation Sites (NGES), in particular the NGES locations at Texas A&M University, Treasure Island Naval Station, University of Massachusetts at Amherst, University of Houston, and Northwestern University. Among the topics covered are statistical estimation procedures based on homogenous random field theory, with as parameters the mean, coefficient of variation and scale of fluctuation, as well as two alternate fractal representations of spatial variation in soil deposits, a neural network model, and an approach to correlating soil properties based on the concept of fuzzy subsets. The aim of this publication is to provide both a state-of-the-art assessment of statistical methods of soil profile modeling and a set of baseline statistics, representative of the well-documented NGES, intended to serve as a priori information for probabilistic site characterization.
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