Simulation Of Earthquake Ground Motions Compatible With Multi-damping-ratio-spectra Based On Genetic Algorithms

Artificial ground motions, for their optional and statistic properties, are regarded as an important form of input for structural time history analysis in contrast to the actual records. Present simulation methods which are mostly derived from spectra-compatible technique do well suit for single-damping-ratio-spectra simulation, but the simulation precision is not satisfactory when the spectrum isn't the object spectrum. In fact, there should be different design spectra corresponding with the structures of different damping-ratios, the new Code for Seismic Design for Buildings (GB50011-2001) has provided corresponding spectra for structures with different damping-ratios. Obviously, the artificial ground motions used for structural time history analysis should well coincide with multi-damping-ratio-spectra.Based on the comparison of the conventional algorithms for multi-objective optimization and genetic algorithms, a method for the simulation of multi-damping-ratio-spectra is proposed in the thesis which combines the multi-objective optimization algorithms and genetic algorithms. The program corresponding to the method is also developed and the method is proved to be feasible and convenient by an example at the end of the thesis.The main conclusions drawn from the research of the thesis are as follows.â‘  The method proposed in this thesis do well in solving the problems of multi-damping-ratio-spectra simulation.â‘¡ It is convenient to obtain the Pareto optimal solution set of the multi-object question by using implicit parallel genetic algorithms and the method can meet the practical needs for simulating ground motions coinciding with multi-damping-ratio-spectra in seismic design.â‘¢ The crossing rate and variance rate are important parameters of genetic algorithms which affect the rate of convergence, the adapting rate of cross and variation in this paper can auto-adapt and according to stand or fall of current sample, it assures the sample approach to the Pareto optimal solution set in fast convergent speed.At the end of this paper, the disadvantages of present study and the recommendations for future research are set forth.