Clustered rocket parameter updatingby hybrid global optimization algorithms
Authors: Shkapov P.M., Sulimov A.V., Sulimov V.D.
Published in issue: #9(105)/2020
DOI: 10.18698/2308-6033-2020-9-2012
Category: Mechanics | Chapter: Dynamics, Strength of Machines, Instruments, and Equipment
Direct simulation of complex systems does not provide the necessary quality of the required analytical models. The paper considers the inverse problems of the change of the clustered rocket finite element model according to the modal data obtained during the measurements. In general, criterial functions are assumed to be multidimensional, continuous, multiextremal, and not everywhere differentiable. We implemented an approach using new hybrid global nondifferentiable optimization algorithms. The proposed hybrid algorithms combine the efficient stochastic QRM-PCA algorithm, which scans the space of numbers, and deterministic local search methods. Using a hybrid algorithm, we carried out a model change of the stiffness characteristics of communication nodes between the central unit and accelerators. The study gives numerical solutions of the inverse problems of the change of the clustered rocket finite element model.
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