Last modified: 2017-06-30
Abstract
In the actual structure, rational optimization of truss structure section size, can make each bar bear maximum load and play a role. By this way, we can not only make the truss material give full play to its own performance, but also reduce weight of truss, and cost savings. At present, there are two methods for section size optimization: Mechanical criterion method and mathematical programming method. This paper combines the two methods and analyze a truss-braced structure. In this paper, the truss node displacement is used as the constraint condition. It takes the cross section area of the bar in the truss as the independent variable and takes the steel weight of the truss as objective function. It uses constrained variation principle and force method equation to create a hybrid numerical method. Through concrete examples, the results of this algorithm are compared with the simulation results, and the reliability and correctness of truss section size optimization are verified. In the theoretical calculation stage, this paper simplifies the truss structure to the structure with three degree indeterminacy. Considering the actual condition and establishing the force method equation, it get the target node deflection function connected with cross-sectional area of the truss. The correction function of amount of steel connected with cross-sectional area of the truss regards the deflection of the node in the structure as an additional condition which is less than 1/60 of the total height of the structure. In the simulation stage, based on the evolutionary optimization method, this paper gets the section size of structure under the minimum quality on the premise of meet the requirements of the target node deflection.This paper is based on the numerical method combined with the simulation and get the best cross-sectional area of the truss in order to get the optimization of the size not only meeting the requirement of strength, but also making full use of the performance of the material.