YangBo Yu, YuLei Ji, YanRen Chen, Kun Xu, QingZhen Bi
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A novel domain decomposition-based model for efficient dynamic predictions of large composite machine tools
We propose a large combined moving component composed of carbon fiber reinforced polymer (CFRP) laminates for making lightweight machine tools with high dynamic performance. The accurate dynamic prediction of composite machine tools is essential for the new generation machine tool. This paper aims to address two challenges in numerical dynamic modeling and the design of composite machine tools to enhance development efficiency. (1) Anisotropic composite laminates, which form the composite machine tool, exhibit coupling in various directions. We propose the generalized continuity condition of the boundary to tackle this dynamic modeling challenge. (2) Composite machine tools feature numerous composite-metal coupled structures. The mechanical model correction of isotropic metals is performed to address their dynamics. We take the example of a five-axis gantry machine tool with composite moving parts, establish a dynamic model for efficient prediction, and verify it through simulation and experimentation. The proposed method yields remarkable results, with an average relative error of only 3.85% in modal frequency prediction and a staggering 99.7% reduction in solution time compared to finite element analysis. We further discuss the dynamic performance of the machine tool under varied stacking angles and layer numbers of the composite machine tool. We propose general design criteria for composite machine tools to consider the modal frequency and manufacturing cost of machine tools.
期刊介绍:
Science China Technological Sciences, an academic journal cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China, and published by Science China Press, is committed to publishing high-quality, original results in both basic and applied research.
Science China Technological Sciences is published in both print and electronic forms. It is indexed by Science Citation Index.
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Reviews summarize representative results and achievements in a particular topic or an area, comment on the current state of research, and advise on the research directions. The author’s own opinion and related discussion is requested.
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