| Compared to traditional cast-in-place buildings,prefabricated buildings are faster and less polluted.However,as the manufacturing and transportation costs of precast components used in prefabricated buildings are higher than those of cast-in-place buildings,the promotion of prefabricated buildings is therefore hindered.This paper uses MATLAB,ETABS and an improved immune genetic algorithm to optimise the number of prefabricated elements,the location of prefabricated elements and the selection of prefabricated elements for assembled monolithic shear wall structures.The main research contents and findings of this paper are as follows:(1)Precast walls and beams are calculated as combined components according to the characteristics of precast components.The formula for calculating the stiffness-displacement stratification of a continuous structure based on the basic principle of energy conservation is improved and validated to make it more suitable for iterative calculations.On the basis of the above theory,the number of precast components is optimized for the minimum total volume using an immune genetic algorithm under integer coding,with the story drifts and the maximum number of components as constraints.(2)Based on the results of the quantity optimization,the positions of the precast components are optimized.The position optimization takes into account the position of the X-directional and Y-directional member arrangements and the seismic effects at the same time.The floor shear is calculated using the vibration decomposition reaction spectrum method under the rational lateral stiffness calculation method.The position optimization incorporates an immune genetic algorithm using positive integer coding,with the number of members,member position,torsional displacement ratio,story drifts,period ratio,stiffness to weight ratio and axial compression ratio as constraints,and the total volume of precast components is minimized as the objective function to achieve rational position optimization of precast components.(3)After the location optimization,the selection of precast components is optimized for the structure.The prices of precast components in different regions and at different times are discussed.A reasonable number of optimization iterations is discussed in the immune genetic algorithm and the most optimal result out of ten optimizations is selected as the final result.The immune genetic algorithm uses a decimal code with two valid digits to achieve precast component selection optimization with the prefabricated rate,assembly rate and national evaluation standards for assembled buildings as constraints and the minimum precast component price as the objective function.(4)While realizing the optimization of the number of precast combined components,the optimization of the location and the optimization of the selection of precast components,the relevant optimization program was written using MATLAB and the verification of the relevant examples was carried out.The calculation results show that the program in this paper has a good optimization effect on the prefabricated monolithic shear wall structure and improves the efficiency of the optimization calculation. |
