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http://dx.doi.org/10.3795/KSME-A.2017.41.11.1099

Statistical Effective Interval Determination and Reliability Assessment of Input Variables Under Aleatory Uncertainties  

Joo, Minho (School of Mechanical Engineering College, Yonsei Univ.)
Doh, Jaehyeok (School of Mechanical Engineering College, Yonsei Univ.)
Choi, Sukyo (Research & development division, Hyndai Motor)
Lee, Jongsoo (School of Mechanical Engineering College, Yonsei Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.41, no.11, 2017 , pp. 1099-1108 More about this Journal
Abstract
Data points obtained by conducting repetitive experiments under identical environmental conditions are, theoretically, required to correspond. However, experimental data often display variations due to generated errors or noise resulting from various factors and inherent uncertainties. In this study, an algorithm aiming to determine valid bounds of input variables, representing uncertainties, was developed using probabilistic and statistical methods. Furthermore, a reliability assessment was performed to verify and validate applications of this algorithm using bolt-fastening friction coefficient data in a sample application.
Keywords
Sequential Statistical Modeling; Statistical Area Metric; Monte-Carlo Simulation; Confidence Interval; Inverse Cumulative Distribution Function;
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Times Cited By KSCI : 1  (Citation Analysis)
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