This study proposes a new topology optimization solution providing designers with choices for feasible stiffener layouts inside large-scale containers of garbage trucks. Firstly, the mathematical expressions of loadin...This study proposes a new topology optimization solution providing designers with choices for feasible stiffener layouts inside large-scale containers of garbage trucks. Firstly, the mathematical expressions of loading conditions inside garbage containers are derived. Then, a growth-based layout optimization framework is built, taking inspiration from the morphology of plant ramifications. The principles of the highly effective but individual design rules of existent leaf venation layout problems are explored and transferred into analytical laws. Based on this, an evolutionary algorithm is developed to simulate the load-adapted growth of stiffener layouts, which provides an approximately homogeneous stress distribution along the surface of self-optimizing structures, Unlike the conventional methods, the new approach needs neither the densest ground structure nor the modification of the existing finite element programs, it is fast, easy to apply and nearly constraint free. Finally, a case study is provided showing how a large-scale container structure can be designed by this extremely intelligent CAD approach.展开更多
基金Acknowledgment The work reported in this paper is supported by the National Natural Science Foundation of China （Grant No. 51405377）, and the Hi-Tech Research and Development Program of China （Grant No. 2012AA040701）.
文摘This study proposes a new topology optimization solution providing designers with choices for feasible stiffener layouts inside large-scale containers of garbage trucks. Firstly, the mathematical expressions of loading conditions inside garbage containers are derived. Then, a growth-based layout optimization framework is built, taking inspiration from the morphology of plant ramifications. The principles of the highly effective but individual design rules of existent leaf venation layout problems are explored and transferred into analytical laws. Based on this, an evolutionary algorithm is developed to simulate the load-adapted growth of stiffener layouts, which provides an approximately homogeneous stress distribution along the surface of self-optimizing structures, Unlike the conventional methods, the new approach needs neither the densest ground structure nor the modification of the existing finite element programs, it is fast, easy to apply and nearly constraint free. Finally, a case study is provided showing how a large-scale container structure can be designed by this extremely intelligent CAD approach.
