Study To Improve The Predicted Response Of Floor Systems Due To Walking
Boice, Michael DeLancey
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STUDY TO IMPROVE THE PREDICTED RESPONSE OF FLOOR SYSTEMS DUE TO WALKING By Michael DeLancey Boice Dr. Thomas M. Murray, Chairman Department of Civil and Environmental Engineering (ABSTRACT) The scope of this study is divided into three topics. To begin, more accurate methods for estimating the fundamental natural frequencies of floors were explored. Improvements for predicting the behavior of floor systems using several criteria were also investigated. The final topic compared the AISC and SCI methods for analyzing vibrations acceptability. Natural frequency prediction was studied by examining 103 case studies involving floor systems of various framing occupied or being constructed in the United States and Europe. Based on the results from these comparisons, it was reasonably concluded that the predicted bay frequency using Dunkerlyâ s estimate (fn2) is not the most accurate method for predicting the system frequency using the AISC Design Guide for all types of framing analyzed. The predicted beam frequency using AISC methods provided sound correlations with the measured bay frequencies. On the other hand, with the exception of floor systems with joist girders and joists, the results showed that the SCI methods provided more accurate predictions of bay frequency despite a fair amount of data scatter. Evaluations based on the AISC Design Guide 11, the SCI criteria Murray Criterion, and Modified Reiher-Meister scale were compared with subjective field analyses for each case study in the second part of this study. The AISC Design Guide criterion is the most consistent method for predicting floor behavior. The SCI criterion is the next most consistent method for floor acceptability, followed by the Murray Criterion then the Modified Reiher-Meister scale. In the final part of this study, predicted accelerations and floor behavior tolerability for 78 case studies were evaluated using the AISC and the SCI criteria. The two prediction methods are in agreement for 82 % (64 of 78) of the case studies, and strongly disagree for only 12 % (9 of 78) of the case studies.
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