SVD-based improvements for component mode synthesis in elastic multibody systems

Holzwarth, Philip; Eberhard, Peter

doi:10.1016/j.euromechsol.2014.08.009

Cited by 36 publications

(16 citation statements)

References 17 publications

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“…The dynamic model of FMS is nonlinear differential equations. In order to improve computing efficiency, the MOR method is used to reduce geometric nonlinearities of FMS, such as component mode synthesis and modern reduction schemes based on balanced truncation [14]. The common idea of the methods is to use orthogonal projection into a subspace of discretized ansatz functions [14].…”

Section: Nonlinear Model Order Reductionmentioning

confidence: 99%

A stochastic surrogate model for time-variant reliability analysis of flexible multibody system

Kan¹,

Zhang²,

Wang³

2017

Vib. proced.

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Abstract. The dynamic model of the flexible multibody systems (FMS) is usually the differential equations with time-variant, high nonlinear and strong coupling characteristics. The traditional reliability models are inefficient to solve these problems. And the reliability model is poor in accuracy and computational efficiency. Based on this point, a new stochastic surrogate model for time-variant reliability analysis of FMS is proposed. Combined model order reduction with generalized polynomial chaos, the stochastic surrogate model is established and the statistical characteristics of system responses are obtained. The calculation method of kinematic time-variant reliability is given. Finally, the effectiveness of the method is verified by a rotating flexible beam. The results show that this method has high computational accuracy compared with Monte Carlo method.

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Section: Nonlinear Model Order Reductionmentioning

confidence: 99%

A stochastic surrogate model for time-variant reliability analysis of flexible multibody system

Kan¹,

Zhang²,

Wang³

2017

Vib. proced.

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“…The system consists of the brake disc (green), two brake pads (red, blue) and the caliper (olive), modeled as finite-element structures and reduced using modal reduction. The generation of the elastic bodies is performed with the EMBS-specific preprocessor MatMorembs [9], where more advanced methods are available in addition to modal reduction [10,11].…”

Section: Example Of a Self-excited Disc Brakementioning

confidence: 99%

Influence of Uncertainties on the Stability of a Self-Excited Elastic Multibody System

Iroz¹,

Hanss²,

Eberhard³

2015

Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECO

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Abstract. In this paper, uncertainty analyses based on fuzzy arithmetic are performed and illustrated for a disc brake affected by friction-induced vibrations and modeled as an elastic multibody system. By the use of fuzzy-valued model parameters, the nominal results of conventional, crisp-valued models are extended to the inclusion of uncertainties, and valuable conclusions on the overall effect as well as on the individual influence of uncertain parameters on the output of the model can be drawn. For the definition, the simulation and the evaluation of the fuzzy-parameterized model, the software package FAMOUS is used and coupled to the multibody simulation program Neweul-M 2 .

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“…The usage of a moment-matching based model order reduction method has been shown in [14]. A possible combination of a CMS and a moment-matching based method has also been presented in [15].…”

Section: Introductionmentioning

confidence: 99%

“…Similar to the solution of the generalized eigenvalue problem within the BKS solver, a sparse system of linear equations with the indefinite coefficient matrix A has to be solved at each frequency point f i and optionally multiple times if higher-order derivatives are desired. With the calculated projection matrix V the equation of motion of the reduced elastic body can be described byMq +Kq =Bu (15) with the reduced mass matrixM = V MV , the reduced stiffness matrixK = V KV as well as the reduced input matrixB = V B. These reduced systems are then included into the multibody formulation.…”

Section: Introductionmentioning

confidence: 99%

Model Order Reduction of Large-Scale Finite Element Systems in an MPI Parallelized Environment for Usage in Multibody Simulation

Volzer

Eberhard

2016

Archive of Mechanical Engineering

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The use of elastic bodies within a multibody simulation became more and more important within the last years. To include the elastic bodies, described as a finite element model in multibody simulations, the dimension of the system of ordinary differential equations must be reduced by projection. For this purpose, in this work, the modal reduction method, a component mode synthesis based method and a momentmatching method are used. Due to the always increasing size of the non-reduced systems, the calculation of the projection matrix leads to a large demand of computational resources and cannot be done on usual serial computers with available memory. In this paper, the model reduction software Morembs++ is presented using a parallelization concept based on the message passing interface to satisfy the need of memory and reduce the runtime of the model reduction process. Additionally, the behaviour of the Block-Krylov-Schur eigensolver, implemented in the Anasazi package of the Trilinos project, is analysed with regard to the choice of the size of the Krylov base, the blocksize and the number of blocks. Besides, an iterative solver is considered within the CMS-based method.

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SVD-based improvements for component mode synthesis in elastic multibody systems

Cited by 36 publications

References 17 publications

A stochastic surrogate model for time-variant reliability analysis of flexible multibody system

A stochastic surrogate model for time-variant reliability analysis of flexible multibody system

Influence of Uncertainties on the Stability of a Self-Excited Elastic Multibody System

Model Order Reduction of Large-Scale Finite Element Systems in an MPI Parallelized Environment for Usage in Multibody Simulation

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