Non-probabilistic interval model-based system reliability assessment for composite laminates
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Composite materials have been widely applied to engineering fields by virtue of its superior mechanical properties. Therefore, the problem of composite laminates safety assessment has also been discussed. This paper develops the non-probabilistic interval model-based system reliability evaluation strategy based on the last ply failure criterion (LPF), which improves the rough reliability solution based on first ply failure criterion (FPF) for composite laminates, and overcomes the shortage of traditional LPF method based on the probabilistic reliability theory. Obviously, the probability density function (PDF) is difficult to be calculated due to the experimental cost and time. In the proposed method, considering the fiber failure and matrix failure (limit state functions) for composite laminates, the failure possibility of every single ply is evaluated by the non-probabilistic interval model method. Subsequently, the progressive damage method is combined with the branch-bound method (B&B) to search the significant failure paths of composite laminates, and then the whole system analysis process is completed based on LPF criterion. Finally, the system reliability model of composite laminates can be constructed by introducing non-probabilistic interval model. Furthermore, the correlation description for the non-probabilistic interval model among is applied to the failure modes, and the Cornell first-order bound theory is applied to achieve the system reliability of composite laminates. After the detailed analysis steps, the numerical example of laminated plate is presented to demonstrate the validity and reasonability of the developed methodology.
KeywordsNon-probabilistic interval model System reliability Last ply failure criterion Composite laminates Progressive damage analysis Failure sequence
The authors would like to thank the National Key Research and Development Program (No. 2016YFB0200700), the National Nature Science Foundation of the P.R. China (No. 11872089, No. 11572024, No. 11432002), Defense Industrial Technology Development Programs (No. JCKY2016601B001, No. JCKY2016204B101, No. JCKY2017601B001), and the postgraduate innovation practice fund of Beihang University (No. YCSJ-01-2018-07) for the financial supports. Besides, the authors wish to express their many thanks to the reviewers for their useful and constructive comments.
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