Certificate of Registration Media number Эл #ФС77-53688 of 17 April 2013. ISSN 2308-6033. DOI 10.18698/2308-6033
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Clustered rocket parameter updatingby hybrid global optimization algorithms

Published: 11.09.2020

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.

[1] Pulecchi T., Casella F., Lovera M. Object-oriented modelling for spacecraft dynamics: Tools and applications. Simulation Modelling and Theory, 2010, vol. 18, no. 1, pp. 63‒86.
[2] Martins J.R., Lambe A.B. Multidisciplinary design optimization: A survey of architectures. AIAA Journal, 2013, vol. 51, no. 9, pp. 2049‒2075.
[3] Lee E.-T., Eun H.-C. Update of corrected stiffness and mass matrices based on measured dynamic modal data. Applied Mathematical Modelling, 2009, vol. 33, no. 5, pp. 2274‒2281.
[4] Berns V.A., Levin V.E., Krasnorutskiy D.A., Marinin D.A., Zhukov E.P., Malenkova V.V., Lakiza P.A. Kosmicheskie apparaty i tekhnologii ― Spacecrafts & Technologies, 2018, vol. 2, no. 3, pp. 125‒133.
[5] Cai J., Chen J. Iterative solutions of generalized inverse eigenvalue problem for partially bisymmetric matrices. Linear and Multilinear Algebra, 2017, vol. 65, no. 8, pp. 1643‒1654.
[6] Arora V. Comparative study of finite element method model updating methods. Journal of Vibration and Control, 2011, vol. 17, no. 13, pp. 2023‒2039.
[7] Benning M., Burger M. Modern regularization methods for inverse problems. Acta Numerica, 2018, vol. 27, pp. 1‒111.
[8] Bartilson D.T., Jang J., Smyth A.W. Finite element model updating using objective-consistent sensitivity-based parameter clustering and Bayesian regularization. Mechanical Systems and Signal Processing, 2019, vol. 114, pp. 328‒345.
[9] Alkayem N.F., Gao M., Zhang Y., Bayat M., Su Z. Structural damage detection using finite element model updating with evolutionary algorithms: a survey. Neural Computing and Applications, 2018, vol. 30, pp. 389‒411.
[10] Kolesnikov K.S. Dinamika raket [Dynamics of rockets]. 2nd ed. Moscow, Mashino-stroenie Publ., 2003, 520 p. (in Russ.).
[11] Dyachenko M.I., Pavlov A.M., Temnov A.N. Vestnik MGTU im. N.E. Baumana. Ser. Mashinostroenie ― Herald of the Bauman Moscow State Technical University. Series Mechanical Engineering, 2015, no. 5, pp. 14‒24.
[12] Tang F.T.P., Polizzi E. FEAST as a subspace iteration eigensolver accelerated by approximate spectral projection. SIAM Journal on Matrix Analysis and Applications, 2014, vol. 35, no. 2, pp. 354‒390.
[13] Bleyer I.R., Ramlau R. A double regularization approach for inverse problems with noisy data and inexact operator. Inverse Problems, 2013, vol. 29 (025004), p. 16.
[14] Floudas C.A., Gounaris C.E. A review of recent advances in global optimization. Journal of Global Optimization, 2009, vol. 45, no. 1, pp. 3‒38.
[15] Karpenko A.P. Sovremennye algoritmy poiskovoy optimizatsii. Algoritmy, vdokhnovlennye prirodoy [Modern search engine optimization algorithms. Algorithms inspired by nature]. Moscow, BMSTU Publ., 2014, 446 p.
[16] Torres R.H., da Luz E.F.P., de Campos Velho H.F. Multi-particle collision algorithm with reflected points. Proceeding Series of the Brazilian Society of Applied and Computational Mathematics, 2015, vol. 3, no. 1 (010433), 6 p.
[17] Torres R.H., de Campos Velho H.F. Rotation-based multi-particle collision algorithm with Hooke–Jeeves. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, 2017, vol. 5, no. 1 (010433), 6 p.
[18] Liu J., Zhang S., Wu C., Liang J., Wang X., Teo K.L. A hybrid approach to constrained global optimization. Applied Soft Computing, 2016, vol. 47, pp. 281‒294.
[19] Rios-Coelho A.C., Sacco W.f., Henderson N. A Metropolis algorithm combined with Hooke-Jeeves local search method applied to global optimization. Applied Mathematics and Computation, 2010, vol. 217, no. 2, pp. 843‒845.
[20] Sulimov V.D., Shkapov P.M., Sulimov A.V. Vestnik MGTU im. N.E. Baumana. Ser. Estestvennye nauki ― Herald of the Bauman Moscow State Technical University. Series Natural Sciences, 2016, no. 5 (68), pp. 46‒66.
[21] Sulimov V.D., Shkapov P.M., Sulimov A.V. Jacobi stability and updating parameters of dynamical systems using hybrid algorithms. IOP Conference Series: Materials Science and Engineering, 2018. no. 468 (012040), 11 p.