Hybrid Reliability Analysis Method for Electromagnetic Design Problems With Non-Gaussian Probabilistic Parameters

• Published in: IEEE transactions on magnetics Vol. 53; no. 6; pp. 1 - 4
• Main Authors: Byungsu Kang, Dong-Wook Kim, Hyunkyoo Cho, Choi, K. K., Dong-Hun Kim
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Design analysis; Design parameters; Electromagnetics (EMs); Failure; Functions (mathematics); Loudspeakers; Magnetism; Mathematical model; Nonlinearity; Normal distribution; optimization; Probabilistic logic; Probabilistic methods; Probability distribution; Probability theory; Random variables; Reliability analysis; Reliability engineering; reliability theory; robustness; Stability; Transformations (mathematics)
• ISSN: 0018-9464; 1941-0069
• DOI: 10.1109/TMAG.2017.2660245

This paper proposes an efficient and stable reliability analysis method for reliability-based electromagnetic design problems with non-normal probability distributions of input parameters. The reliability analysis strongly depends on distribution types of random variables since nonlinear transformations between an original random space and a standard normal random space cause additional nonlinearity into the reliability assessment of probabilistic constraint functions. That can lead to numerical inaccuracy and instability in the reliability-based design process, or may fail to have a solution to the probabilistic constraint assessment. To overcome these difficulties, a hybrid mean-value method is introduced to seeking a most probable failure point in the performance measure approach, which is one of the first-order reliability analysis methods. The proposed method is tested with a mathematical model and a loudspeaker design, of which random variables are assumed to follow five different probability distributions case by case.