ASCE GSP 121-2003 PROBABILISTIC SITE CHARACTERIZATION AT THE NATIONAL GEOTECHNICAL EXPERIMENTATION SITES.pdf

1、GEOTECHNICAL SPECIAL PUBLICATION NO. 121 PROBABILISTIC SITE CHARACTERIZATION AT THE NATIONAL GEOTECHNICAL EXPERIMENTATION SITES SPONSORED BY The Geo-Institute of the American Society of Civil Engineers EDITED BY Erik V anmarcke Gordon A. Fenton ASC II/! American Society 5 of Civil Engineers 1801 ALE

2、XANDERBELLDRIVE RESTON, VIRGINIA 20191-4400 Abstract: 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

3、the NGES locations at Texas A no. 121) Includes bibliographical references and index. ISBN 0-7844-0669-3 I. Soils-United States-Testing. 2. Engineering geology-United States. I. Vanmarcke, Erik. II. Fenton, Gordon, A. III. American Society of Civil Engineers. IV. Series. TA710.5.P76 2003 624.1 51 02

4、8-dc2 I 2003040326 Any statements expressed in these materials are those of the individual authors and do not necessarily represent the views of ASCE, which takes no responsibility for any statement made herein. No reference made in this publication to any specific method, product, process, or servi

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9、ance Center (CCC) Transactional Reporting Service, provided that the base fee of $18.00 per article is paid directly to CCC, 222 Rosewood Drive, Danvers, MA 01923. The identification for ASCE Books is 0-7844-0669-3/03/ $18.00. Requests for special permission or bulk copying should be addressed to Pe

10、rmissions Akkaya and Vanmarcke), two different fractal representations of spatial variation in soil deposits (Kulatilake and Um; Fenton and Vanmarcke), a neural network model (Juang and Jiang), and a new approach to correlating CPT data with soil type and engineering properties based on the concept

11、of fuzzy subsets (Zhang and Tumay). There are results for both horizontal and vertical variation of measured soil properties - most often CPT data - under various assumptions about trends-in-the-mean and layering by soil type, or about the validity of combining, for statistical analysis purposes, da

12、ta from similar non-contiguous soil deposits (e.g., data on variation-with-depth of CPT tip resistance from different clay layers at one site or from all layers at all five sites). Useful perspectives on the different sources of uncertainty of soil properties is offered, in this volume, by Kulatilak

13、e the sampling interval and the size of the domain sampled or analyzed also affect the parameter estimates. Transformation of the raw data prior to statistical analysis, for example by first calculating the logarithms of the measured CPT tip resistance values (Fenton and Vanmarcke), further v compli

14、cates interpretation of the results. The paper by Akkay and Vanmarcke reports estimated coefficients of variation and scales of fluctuation for many different soil properties at the Texas A&M NOES sand and clay sites. Kulatilake and Um concentrate on statistical analyses of cone tip resistance data

15、from the Texas A&M NOES clay site, while Fenton and Vanmarcke aggregate all the CPT data from the five NOES, disregarding trends and other site-specific information. Only Zhang and Tumays paper deals explicitly with cross correlation between measured values, focusing on how CPT data inform about soi

16、l type and engineering properties. Knowledge about the inherent variability of soil properties is of critical importance in reliability analysis of geotechnical facilities, risk assessment for decision support or regulatory control, and planning and optimization of site-specific exploration and test

17、ing. The dual aim of this publication is to present an overview of traditional and novel statistical methods of soil profile modeling and provide a set baseline statistics, representing the well documented NOES, that can serve as a priori information, in a Bayesian sense, about pattern of spatial va

18、riation of soil properties in probabilistic site characterization worldwide. The papers in this volume, having been accepted for publication by the editors based on a process of peer review in accordance with the standards of ASCE and the Geo-Institute, are eligible for discussion in the Journal of

19、Geotechnical and Geo-Environmental Engineering and for ASCE awards. Early versions of most of the papers were presented, discussed and criticized at a workshop held in conjunction with the Geo-Institute Conference in Seattle, WA (1998) and sponsored by the G-I Committee on Risk Assessment and Manage

20、ment. The Federal Highway Administration (FHWA) and the National Science Foundation (NSF) provided funding for the NOES program during the 1990s. Support for the project on probabilistic site characterization at the NOES, conducted by the G-I Committee on Risk Assessment and Management, and for rela

21、ted research by Dr. Akkaya and co-editor Dr. Fenton during extended visits to Princeton University, came from FHWA through the Geo Institute of ASCE. Special thanks are due to Albert F. DiMillio of FHW A for his leadership in the NOES program and to Carol Bowers of the Geo-Institute for critical pro

22、ject management support. Erik Vanmarcke, Princeton University and Gordon Fenton, Dalhousie University vi Contents Spatial Variability of Cone Penetrometer Test (CPT) Parameters at University of Houston National Geotechnical Experimentation Site (NGES) . 1 Michael W. ONeill and Gil Lim Yoon Variation

23、s in Clay Deposits of Chicago 13 TienH. Wu Estimation of Spatial Correlation of Soil Parameters Based on Data from the Texas A&M University National Geotechnical Experimentation Site (NGES) 29 Aysen (Dener) Akkaya and Erik H. Vanmarcke Spatial Variation of Cone Tip Resistance for the Clay Site at Te

24、xas A&M University 41 P.H.S.W. Kulatilake and Jeong-gi Um Random Field Characterization of National Geotechnical Experimentation Sites (NGES) Data 61 Gordon A. Fenton and Erik H. Vanmarcke A New Approach to Site Characterization Using Generalized Regression Neural Networks . 79 C.H. Juang and T. Jia

25、ng Non-Traditional Approaches in Soil Classification Derived from the Cone Penetration Test (CPT) 101 Zhongjie Zhang and Mehmet T. Tumay Subject lndex . 151 Author Index 153 vii Spatial Variability of CPT Parameters at University of Houston NGES Michael W. ONeill 1 and Gil Lim Yoon 2 Abstract Cone p

26、enetrometer test (CPT) records for the University of Houston National Geotechnical Experimentation Site were analyzed for variability using simple statistical methods. The site, which comprised approximately 4000 m 2 in area, consisted of generally insensitive clays interbedded with seams and layers

27、 of fine sand and clayey silt that were overconsolidated in Pleistocene times by desiccation. CPT records were examined by (a) simple direct comparison, (b) computation of depthwise means and coefficients of variation, (c) estimation of the probability distribution model, (d) determination of vertic

28、al and horizontal variograms and correlation distances, and (e) development of Kriging surfaces for the CPT tip and sleeve resistance values across the site. Together, these results constitute an appropriate, practical geostatistical characterization of the CPT test results at the site. Introduction

29、 The University of Houston National Geotechnical Experimentation Site (NGES-UH) was operated from 1979 - 2000 by the senior author. Its primary use was the testing of full-scale shallow and deep foundations - particularly the effects of construction methods and technologies on the geotechnical and s

30、tructural performance of foundations. However, during the course of its operation many in situ soil tests were performed on the site, including a large number of cone penetrometer tests (CPTs). Selected CPT records from two series of tests are considered herein to document the general statistical ch

31、aracteristics of the soil at the site, which is geologically typical of many Pleistocene terrace sites in the southeastern United States. The NGES-UH consisted of soils from two Pleistocene terrace (sedimentary) deposits, as indicated in Fig. 1. The older and deeper deposit, termed locally the 1 Cullen Dist. Prof., Dept. of Civil and Env. Engrg., University of Houston, Houston, TX 77204-4791 2 Sr. Researcher, Korea Ocean Res. and Devel. Inst., Ansan, Seoul 425-600 Korea