An Improved Adaptive Genetic Algorithm for Optimizing Pyroshock Acceleration Synthesis

Abstract

The shock response spectrum (SRS) applied to pyroshock designs and tests for space systems does not include input acceleration time history; therefore, it cannot be used directly in structural nonlinear dynamic analysis before acceleration time history is synthesized. Existing synthesis methods typically rely on certain experimental data. In this study, a combined method for pyroshock acceleration synthesis is presented using a series of wavelets at low frequencies and damped sines at medium-high frequencies in the absence of experimental data. To improve the quality of the synthesized SRS, we develop an improved adaptive genetic algorithm (IAGA) with nonlinear adaptive adjustments of crossover and mutation probabilities. Numerical tests show that combined with the developed IAGA, the new method achieves higher accuracy and practicability in the synthesis of pyroshock acceleration compared with traditional methods. This work is expected to improve the calculation accuracy of spacecraft structure response under pyroshock loads.

Keywords

• Genetic algorithm
• optimization
• pyroshock acceleration synthesis
• shock response spectrum
• aerospace simulation