Optimize The Design Study, Based On Orthogonal Experiment Ribbed Composite Wall

ABSTRACT: Multi-ribbed slab structure (MRSS) is a new energy-saving structure system, which has a widely application prospect. The main staged achievements have been made in the study of the theory and application of multi-ribbed composite slab (MRCS), the main load-bearing member of MRSS, in the multi-storied and high-rise buildings, but the study of how to optimize MRCS and harmonize the relation of its security and economy remains blank. So the dissertation has imported the economic and applied ideas into the research of this system. Taking into account the complexity of load-bearing performance of MRCS at the elastic-plastic stage, conversion method based on the orthogonal experimental design is used for optimum analysis of MRCS.results, load-oad-of MRCS. The main researbearing performance of MRCS is analyzed by ANSYS. Concrete and filled blocks are simulated by solid65 element, and kinematic hardening model and William-Warnke five-parameter failure rule are used to establish rational nonlinear FEA model. Moreover the rule of load-bearing and deformation of MRCS changed with different divided modes of frame grids is discussed.Six factors such as shear span ratio and axial compression ratio are selected. Orthogonal experimental method is adopted to design eighteen experiments of different factors'level. The rapport of shear bearing capacity and economy of MRCS is load-bearing performance at the elastic-plastic stage of each model of multi-ribbed composite slab is analyzed using APDL parametric modeling.Factors affecting degree to shear bearing capacity and cost of unit area slab are evaluated by visual and variance analysis methods. In addition, the relations between shear bearing capacity and cost of unit area slab and their each marked influencing factors are fitted.Mathematic model of optimum design of MRCS is provided, which belongs to nonlinear programming problem with constraint because most object functions and constraint conditions are nonlinear function. Then optimum design could be achieved by control function after the model is translated into linear problem using linear regression method. Thus, the conclusion can make reference to engineering application and offer a thinking fashion for structural optimum design.