Probability-based Intelligent Optimum Design Of Structural Systems

Probability-based intelligent optimum design of structural systems is a new subject in recent tens years. It considers structures as a whole, and studies the randomness of the structures in the future. It is more rational than the traditional way. Introducing some intelligent methods into the area of probabilistic optimum design is one of focuses of this field.First of all, the thesis introduces the progress of probability-based intelligent optimum design of structural systems and its analysis methods. Then it narrates the essential theory of the methods for reliability analysis of structural systems concisely and the methods in this thesis. The thesis, in the probability analysis and computation, considers the failure history of space frames and trusses, adopts the bound criterion and algorithms on the base of system's critical strength, and introduces the soft self-adaptation control bound into the identification of dominant failure modes; at the same time, with the incremental load method and differential equalized recursive method, computes the limit-state function of failure mode and probability index precisely under no leaking the dominant failure modes. Programs are developed which are adaptable to the automatic reliability analysis of structural system. The thesis gives some calculating examples. It also studies some problems of reliability theory and algorithms, and presents some conclusions. It is tested that the method is effective.Because of the complexity of question and the limitation of traditional methods, computational intelligence is developed. Genetic algorithm (GA) is popularly used to settle the optimum problem. So the important work of the thesis is to develop a program for Probability-based intelligent optimum design of structural systems based on GA. Firstly, the thesis introduces the fundamental theory of GA and probabilistic optimum design, designs an advanced GA methods. Then programs a program to deal with the optimization, including continuous variables and disperse variables, introduces the function, structural and flow chart of the program, and gives some calculating examples and results' analysis. Through the analysis and contrast on the examples, it proves that the methods of reliability computation, the improving of GA and program are reliable and efficient. It is a suitable new way to deal withprobabilistic analysis and optimum design of structural systems.Finally, probability-based intelligent optimum design of structural systems is summarized and expected, and next work is presented.