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- W4225548395 abstract "In this work, we present an adaptive feature-driven topology optimization method with the adaptability realized by using the well-known SIMP method. The proposed new method inherits the merits of both the feature-driven approach and SIMP method, and optimized results with clear and smooth boundaries can therefore be obtained without initial layout dependence. Specifically, in the early stage of optimization design, engineer features (i.e. design primitives) are systematically introduced into the design domain according to the sensitivity analysis result of the SIMP method, in view of its high numerical stability and strong versatility; and in the final stage, the topology optimization is implemented based solely on the feature-driven method, so that the high-quality design result can be achieved with very few variables. The transition between the two methods is carried out automatically by a novel volume restriction scheme, in which the structural volume obtained by the SIMP approach is limited to the difference between the prescribed maximum volume and the features’ total volume. It should be noted that the number and volume of engineer features are quite small at first several iterations, hence the effective force transferring path could not be formed just by using these features. But benefiting from the proposed volume restriction scheme, the connection between the load application and the displacement constraint positions can always be guaranteed because the optimization design is dominated by the SIMP method at initial iterations. The superiority and universality are demonstrated by typical numerical examples including the topology optimization design of the stiffest structure and compliant mechanism." @default.
- W4225548395 created "2022-05-05" @default.
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- W4225548395 date "2022-01-01" @default.
- W4225548395 modified "2023-09-27" @default.
- W4225548395 title "An Adaptive Feature-Driven Method for Structural Topology Optimization" @default.
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- W4225548395 doi "https://doi.org/10.1007/978-981-16-7381-8_137" @default.
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