ACI Structural Journal/May-June 2006 399 ACI Structural Journal, V. 103, No. 3, May-June 2006. MS No. 04-306 received September 27, 2004, and reviewed under Institute publication policies. Copyright © 2006, American Concrete Institute. All rights reserved, including the making of copies unless permission is obtained from the copyright proprietors. Pertinent discussion including author’s closure, if any, will be published in the March-April 2007 ACI Structural Journal if the discussion is received by November 1, 2006. ACI STRUCTURAL JOURNAL TECHNICAL PAPER Large structures present numerous possible test locations for a nondestructive evaluation. Challenges lie in selecting test locations, managing data collected, and stating testing results. This research evaluated the feasibility of using sampling methods to assist in these tasks. To assess the methods’ applicability, sampling was applied to data from actual structures that had previously been extensively tested. The researchers could then compare their predictions based on sampling to actual results from comprehensive testing. These studies demonstrated that sampling methods are useful at determining the number of samples and their locations. The results can effectively be stated as a confidence interval, presenting a range for the prediction based on an acceptable uncertainty. In Part I, a brief description of some sampling methods is given and the procedure (including simple random, stratified, and adaptive sampling) is applied to a post-tensioned bridge, which was nondestructively tested to locate air voids within grouted tendon ducts. Keywords: post-tensioned; sampling; test. INTRODUCTION In recent years, the development of a wide variety of nondestructive testing methods for concrete structures has provided engineers with numerous possibilities for evaluating structures. 1 While greatly expanding an engineer’s capabilities, this availability of testing techniques has also introduced its own set of challenges, particularly when evaluating a large structure. The engineer faces the challenge of dealing with hundreds to many thousands of possible test locations. Time and cost constraints work to limit the test number to a minimum while the desire to accurately assess the state of the structure argues for the maximum number of tests. This paper and its companion, “Sampling Techniques for Evaluating Large Concrete Structures, Part II,” which will appear in the July-August issue of the ACI Structural Journal, present research aimed at examining the use of sampling techniques to assist the engineer in making choices concerning the number and location of tests and in stating the extent of knowledge gained from the testing. Two case studies are presented. The nondestructive test data for the structures highlighted in the case studies were initially collected for all possible test locations in structural investigations; therefore, the authors had the unique opportunity to compare sampling predictions to the actual state of the structures to evaluate the accuracy of various sampling approaches. The structures examined include a post-tensioned bridge, 2,3 on which nondestructive testing was performed to locate air voids within grouted tendon ducts, and a 7.5 mi (12 km) long, reinforced concrete seawall, 4 where the aim was to locate delaminations caused by corrosion of the reinforcing bars. In the first case, sampling methods, including simple random, stratified, and adaptive sampling, were used to determine the number and location of test points along the bridge. The information collected from these tests was used to estimate the level of damage in the entire bridge within a given confidence; these results were then compared with actual damage statistics. In the second case, sampling methods, including simple random, systematic, and adaptive sampling, were employed to make predictions about the state of the walls based on tests on only a fraction of the wall panels. Again, the results were compared to the actual results from testing the entire structure. In addition, the seawall data was also used to construct probabilistic models to examine patterns in the damage. Subsequently, repair options were incorporated into these models to determine their reliability. The results of these studies were stated in terms of the cost of repair versus the predicted cost of failure. This work is summarized in Reference 5. This paper provides background information on sampling methods and focuses on the case study of the post-tensioned bridge. In the companion paper, the case study of the reinforced concrete seawall is presented and key conclusions are given based on the results of both case studies. For a more in depth discussion of sampling concepts and their application in the case studies, the reader is referred to Reference 6. RESEARCH SIGNIFICANCE This research has led to the development of a method for determining the number and locations of tests in nondestructive assessment of large concrete structures. The method shows how the information obtained from these tests can then be used to make a prediction about the state of the entire structure using confidence intervals. This is the first time that sampling techniques were used to establish the damage state in concrete structures. The results of the studies presented indicate that sampling techniques are very useful in making the collection and analysis of data from nondestructive tests more efficient and cost effective. BACKGROUND ON SAMPLING Sampling methods, which allow statements to be made about an entire group based on data collected for only a certain portion, were applied to the nondestructive testing of structures for flaw detection. The inspection schemes that are the focus of the research are those in which the data taken at each test point is in the form of a Binomial variable (a yes/ no answer) such as flaw/no flaw information. For example, tests may be performed at locations on the surface of a Title no. 103-S42 Sampling Techniques for Evaluating Large Concrete Structures: Part I by Tamara Jadik Williams, Linda K. Nozick, Mary J. Sansalone, and Randall W. Poston