과제정보
The work described in this paper was fully funded by the National Science Foundation of China (Grant No. 51508182) and the Natural Science Foundation of Hunan Province, China (Grant No. 2021JJ30270).
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By presetting various reinforcement diameters in topology optimization with the discrete model finite element analysis, an algorithm of bidirectional evolutionary structural optimization of multi-level reinforcement diameter is presented to obtain the optimal reinforcement topologies which describe the degree of stress of different parts. The results of a comparative study on different reinforcement feasible domain demonstrate that the more angle types of reinforcement are arranged in the initial domain, the higher utilization rate of reinforcement of the optimal topology becomes. According to the nonlinear finite element analysis of some deep beam examples, the ones designed with the optimization results have a certain advantage in ultimate bearing capacity, although their failure modes are greatly affected by the reinforcement feasible domain. Furthermore, the bearing capacity can be improved when constructional reinforcements are added in the subsequent design. However the adding would change the relative magnitude of the bearing capacity between the normal and inclined section, or the relative magnitude between the flexural and shear capacity within the inclined section, which affects the failure modes of components. Meanwhile, the adding would reduce the deformation capacity of the components as well. It is suggested that the inclined reinforcement and the constructional reinforcement should be added properly to ensure a desired ductile failure mode for components.
The work described in this paper was fully funded by the National Science Foundation of China (Grant No. 51508182) and the Natural Science Foundation of Hunan Province, China (Grant No. 2021JJ30270).