Staszak Natalia, Garbowski Tomasz, Ksit Barbara
Doctoral School, Department of Biosystems Engineering, Poznan University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland.
Department of Biosystems Engineering, Poznan University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland.
Materials (Basel). 2023 Mar 14;16(6):2320. doi: 10.3390/ma16062320.
The use of layered or hollow floors in the construction of buildings obviously reduces the self-weight of the slab, and their design requires some expertise. In the present work, a sensitivity analysis and numerical homogenization were used to select the most important characteristics of bubble deck floors that have a direct or indirect impact on their load capacity. From the extensive case study, conclusions were drawn regarding the optimal selection of geometry, materials, and the arrangement and size of air voids in such a way as to ensure high stiffness of the cross-section and at the same time maximally reduce the self-weight of the slabs. The conducted analyses showed that the height of the slab and the geometry of the voids had the greatest impact on the load-bearing capacity. The concrete class and reinforcement used are of secondary importance in the context of changes in load-bearing capacity. Both the type of steel and the amount of reinforcement has a rather small or negligible influence on the bubble deck stab stiffness. Of course, the geometry of the voids and their arrangement and shape have the greatest influence on the drop in the self-weight of the floor slabs. Based on the presented results of the sensitivity analysis combined with numerical homogenization, a set of the most important design parameters was ordered and selected for use in the optimization procedure.
在建筑物施工中使用分层或空心楼板显然会降低楼板的自重，并且其设计需要一定的专业知识。在本研究中，通过敏感性分析和数值均匀化来选择对气泡楼盖楼板承载能力有直接或间接影响的最重要特征。从广泛的案例研究中得出了关于几何形状、材料以及气孔的布置和尺寸的最佳选择的结论，以便确保横截面具有高刚度，同时最大程度地降低楼板的自重。所进行的分析表明，楼板高度和气孔几何形状对承载能力影响最大。在承载能力变化方面，所使用的混凝土等级和钢筋的重要性次之。钢材类型和钢筋用量对气泡楼盖楼板刚度的影响相当小或可忽略不计。当然，气孔的几何形状及其布置和形状对楼板自重的降低影响最大。基于敏感性分析结果与数值均匀化相结合，整理并选择了一组最重要的设计参数用于优化过程。
