×

A highly efficient method for structural model reduction. (English) Zbl 07769217

Summary: Model reduction is a commonly used method for quickly computing the lower-order eigenvalues and eigenvectors of a structure. This article proposed a direct model reduction method without any iterations. Compared with the existing methods, the proposed technique has two main advantages. The first one is that the explicit expression of the transformation matrix can be directly obtained using a recurrence formula. The second one is that the calculation efficiency of the proposed method is very high because there is no need for iterative calculation. Three types of structure are used as examples to verify the proposed method. It is found that the lower-frequency eigenpairs calculated by the reduced model are very close to the exact ones obtained by the full model. Moreover, the calculation time of the proposed method is much less than that of the existing methods. It has been shown that the proposed method is reliable and effective.
{© 2022 John Wiley & Sons Ltd.}

MSC:

74S05 Finite element methods applied to problems in solid mechanics
74H15 Numerical approximation of solutions of dynamical problems in solid mechanics
74K10 Rods (beams, columns, shafts, arches, rings, etc.)
74K99 Thin bodies, structures
Full Text: DOI

References:

[1] PangJ, DukkipatiR, PattenWN, ShengG. Comparative analysis of model‐reductions methods. Int J Heavy Veh Syst. 2003;10(3):224‐253.
[2] KoutsovasilisP, BeitelschmidtM. Comparison of model reduction techniques for large mechanical systems. Multibody Syst Dyn. 2008;20(2):111‐128. · Zbl 1332.70024
[3] FlodénO, PerssonK, SandbergG. Reduction methods for the dynamic analysis of substructure models of lightweight building structures. Comput Struct. 2014;138:49‐61.
[4] YinT, LamHF, ChowHM, ZhuHP. Dynamic reduction‐based structural damage detection of transmission tower utilizing ambient vibration data. Eng Struct. 2009;31(9):2009‐2019.
[5] ChenHP. Mode shape expansion using perturbed force approach. J Sound Vib. 2010;329(8):1177‐1190.
[6] HosseinzadehAZ, BagheriA, AmiriGG, et al. A flexibility‐based method via the iterated improved reduction system and the cuckoo optimization algorithm for damage quantification with limited sensors. Smart Mater Struct. 2014;23(4):045019.
[7] YinT, JiangQH, YuenKV. Vibration‐based damage detection for structural connections using incomplete modal data by Bayesian approach and model reduction technique. Eng Struct. 2017;132:260‐277.
[8] GuyanRJ. Reduction of stiffness and mass matrices. AIAA J. 1965;3(2):380.
[9] IronsB. Structural eigenvalue problems‐elimination of unwanted variables. AIAA J. 1965;3(5):961‐962.
[10] O’CallahanJ. A procedure for an improved reduced system (IRS) model. Proceedings of 7th International Modal Analysis Conference, Las Vegas; 1989:17‐21.
[11] FriswellMI, GarveySD, PennyJET. Model reduction using dynamic and iterated IRS techniques. J Sound Vib. 1995;186(2):311‐323. · Zbl 1049.74725
[12] FriswellMI, GarveySD, PennyJET. The convergence of the iterated IRS method. J Sound Vib. 1998;211(1):123‐132. · Zbl 1235.74279
[13] QuZQ, FuZF. An iterative method for dynamic condensation of structural matrices. Mech Syst Signal Process. 2000;14(4):667‐678.
[14] QuZQ, SelvamRP, JungY. Model condensation for non‐classically damped systems‐part II: iterative schemes for dynamic condensation. Mech Syst Signal Process. 2003;17(5):1017‐1032.
[15] SastryCVS, MahapatraDR, GopalakrishnanS, et al. An iterative system equivalent reduction expansion process for extraction of high frequency response from reduced order finite element model. Comput Methods Appl Mech Eng. 2003;192(15):1821‐1840. · Zbl 1140.74455
[16] LinR, XiaY. A new eigensolution of structures via dynamic condensation. J Sound Vib. 2003;266(1):93‐106.
[17] XiaY, LinR. Improvement on the iterated IRS method for structural eigensolutions. J Sound Vib. 2004;270(4):713‐727.
[18] ChoiD, KimH, ChoM. Iterative method for dynamic condensation combined with substructuring scheme. J Sound Vib. 2008;317(1):199‐218.
[19] YangQW. Model reduction by Neumann series expansion. App Math Model. 2009;33(12):4431‐4434. · Zbl 1173.74015
[20] KoutsovasilisP, BeitelschmidtM. Model order reduction of finite element models: improved component mode synthesis. Math Comput Model Dyn Syst. 2010;16(1):57‐73. · Zbl 1298.34053
[21] KimJG, LeePS. An accurate error estimator for Guyan reduction. Comput Methods Appl Mech Eng. 2014;278:1‐19. · Zbl 1423.74897
[22] KimJG, ParkYJ, LeeGH, KimDN. A general model reduction with primal assembly in structural dynamics. Comput Methods Appl Mech Eng. 2017;324:1‐28. · Zbl 1439.74435
[23] NaetsF, De GregoriisD, DesmetW. Multi‐expansion modal reduction: a pragmatic semi‐a priori model order reduction approach for nonlinear structural dynamics. Int J Numer Methods Eng. 2019;118(13):765‐782. · Zbl 07865197
[24] MahdiabadiMK, BartlA, XuD, et al. An augmented free‐interface‐based modal substructuring for nonlinear structural dynamics including interface reduction. J Sound Vib. 2019;462:114915.
[25] SinhaK, SinghNK, AbdallaMM, deBreukerR, AlijaniF. A momentum subspace method for the model‐order reduction in nonlinear structural dynamics: theory and experiments. Int J Nonlinear Mech. 2020;119:103314.
[26] AllenMS, RixenD, van derSeijsM, TisoP, AbrahamssonT, MayesRL. Model reduction concepts and substructuring approaches for nonlinear systems. Substructuring in Engineering Dynamics. Springer; 2020:233‐267.
[27] HenshellRD, OngJH. Automatic masters for eigenvalue economization. Earthq Eng Struct Dyn. 1975;3:375‐383.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.