• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.428-433
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• 2007

This paper describes the new eigenvalue algorithm exploiting the Implicit Restarted Arnoldi Method (IRAM) and its application to power systems. IRAM is a technique for combining the implicitly shifted mechanism with a k-step Arnoldi factorization to obtain a truncated form of the implicitly shifted QR iteration. The numerical difficulties and storage problems normally associated with the Arnoldi process are avoided. Two power systems, one of which has 36 state variables and the other 150 state variables, have been tested using the ARPACK program, which uses IRAM, and the eigenvalue results are compared with the results obtained from the conventional QR method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.3 s.246
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• pp.310-317
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• 2006

Currently most practical vibration and structural problems in automotive suspensions require the use of the finite element method to obtain their structural responses. When the finite element model has a very large number of degrees of freedom the harmonic and dynamic analyses are computationally too expensive to repeat within a feasible design process time. To alleviate the computational difficulty, this paper presents a moment-matching based model order reduction (MOR) which reduces the number of degrees of freedom of the original finite element model and speeds up the necessary simulations with the reduced-size models. The moment-matching model reduction via the Arnoldi process is performed directly to ANSYS finite element models by software mor4ansys. Among automotive suspension components, a knuckle is taken as an example to demonstrate the advantages of this approach for vibration simulation. The frequency and transient dynamic responses by the MOR are compared with those by the mode superposition method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.121-122
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• 2006

In the case of mechanical control systems, it is highly useful to be able to provide a compact model of the mechanical system to control engineers using the smallest number of variables, while still providing an accurate model. The reduced mechanical model can then be inserted into the complete mechanical control system models and used for system-level dynamic simulation. In this paper, a moment-matching based model order reduction (MOR) which reduces the number of degrees of freedom of an original finite element model via the Arnoldi process is considered to study the dynamic responses of a HDD actuator and suspension system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.5
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• pp.541-549
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• 2007

In the case of control for mechanical systems, it is highly useful to be able to provide a compact model of the mechanical system to control engineers using the smallest number of state variables, while still providing an accurate model. The reduced mechanical model can then be inserted into the complete system models and used for extended system-level dynamic simulation. In this paper, moment-matching based model order reductions (MOR) using Krylov subspaces, which reduce the number of degrees of freedom of an original finite element model via the Arnoldi process, are presented to study the eigenvalue and frequency response problems of a HDD actuator and suspension system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1222-1230
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• 1999

This paper presents the framework for analysis of small-signal stability. In this framework the equilibrium points of system DAE model are traced using continuation method and instability points are determined on the solution path. Especially Implicit shift QR-modified Arnoldi method is utilized to calculated the rightmost eigenvalues. Small-signal stability is becoming one of the major factors that affect the ATC in the environment of deregulation. Stability limited ATC is easily evaluated in this stability analysis process.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1211-1222
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• 2011

It is necessary to use prestressed modal analysis to calculate the modal frequencies and mode shapes of a prestressed structure such as a spinning blade, a preloaded structure, or a thermally deformed pipe, because the prestress effect sometimes causes significant changes in the frequencies and mode shapes. When the finite element model under consideration has a very large number of degrees of freedom, repeated prestressed modal analyses for investigating the prestress effects might become too computationally expensive to finish within a reasonable design-process time. To alleviate these computational difficulties, a Krylov subspace-based model order reduction, which reduces the number of degrees of freedom of the original finite element model and speeds up the necessary prestressed modal analysis with the reduced order models (ROMs), is presented. The numerical process for the moment-matching model reduction is performed directly on the full order models (FOMs) (modeled in ANSYS) by the Arnoldi process. To demonstrate the advantages of this approach for performing prestressed modal analysis, the prestressed wheel and the compressor impeller under their high-speed rotation are considered as examples.