钢筋混凝土深梁的拓扑优化模型的获取是一个既有理论意义又有工程背景的设计问题。由于钢筋混凝土材料的特殊性,特别是混凝土拉压性能极端差异的特点以及变量的离散性使得问题复杂化。介绍了一种基于演化原理的结构优化算法——演化结构优化算法(GESO算法),这种算法通过以一定的概率淘汰构件中利用率不高的材料获取构件的优化桁架模型。在计算中考虑钢筋混凝土构件的受力特点,充分发挥钢筋受拉和混凝土受压的优势,给出能反映钢筋混凝土深梁工作机理的拓扑优化桁架模型。给出的钢筋混凝土简支梁和开孔深梁的计算实例,说明了方法的有效性和可行性。
An appropriate strut-and-tie model of deep reinforced concrete beams is essential to engineering designs. But the issue is complicated by the fact that concrete strength of a compressive member is different from that of a tensile one and the design valuables are discrete. This paper focuses on automatic generation of optimal strut-and-tie models in deep reinforced concrete beams by the newly proposed genetic evolutionary structural optimization algorithm. The proposed algorithm acquires an optimal truss model by eventually deleting the elements with low sensitivity number. The finite element models are developed with two different elements--reinforcement elements and concrete elements. The approach is proved to be effective in the application to simply supported beams with or without openings.