期刊
COMPOSITE STRUCTURES
卷 323, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compstruct.2023.117495
关键词
Sandwich FGM plates and shells; Similitude method; Distorted similitude; Natural frequency; High-temperature environments
This study investigates the similitude distortion of sandwich FGM plates and shells in high-temperature environments for the first time. The Energy Similitude Correction Method proposed by the author is used to solve the distortion caused by non-scalability of material properties and thermal effects. The method is extended to various shapes of shells and considers the impact of heat conduction, thermal expansion, and temperature-dependent material properties. Numerical examples show that the prediction approach is accurate and widely applicable.
Limit to the size of the experimental platform, scaled-down model test is a reliable mean to study the dynamic of sandwich functionally graded material (FGM) structures in high-temperature environments. However, due to the complexity of material composition and impact of high-temperature environments, relevant parameters cannot be scaled with traditional similitude methods, resulting in the similitude distortion. For the first time, the present work studies the distorted dynamic similitude of sandwich FGM plates and shells in high-temperature environments. Based on the Energy Similitude Correction Method proposed by the author in recent years, the similitude distortion derived from the non-scalability of material properties and thermal effects is solved. More importantly, the application object of this method is extended for the first time from plates to shells of various shapes, including cylindrical shells, conical shells and double curved shells. Meanwhile, heat conduction, thermal expansion and temperature-dependent material properties are taken into account for the impact of high temperature environments. Various numerical examples are verified with different gradient coefficients, thicknesses, temperature conditions and shapes of shells. The results of high-precision similitude show that the prediction approach is correct and widely applicable.
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