scholarly journals Model Order Reduction via a Balanced Truncation-Interpolation Approach for Gas Networks

2016 ◽  
Author(s):  
Yi Ming Lu
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
Computational Effort ◽  
Balanced Truncation ◽  
Model Order ◽  
Gas Networks ◽  
Optimization And Control ◽  
Interpolation Strategy ◽  
Matrix Interpolation ◽  
And Control

Simulation of large instationary gas networks governed by temperature-(T-)parametric nonlinear PDAEs is computationally expensive and extremely time-demanding. To reduce the computational effort and enable optimization and control, we present a parametric surrogate modeling technique composed of linearization, model order reduction (MOR) via balanced truncation (BT) and matrix interpolation strategy based on the energy modal assurance tracking (EMAT-MIS).

scholarly journals A Black-Box method for parametric model order reduction based on matrix interpolation with application to simulation and control

2016 ◽  
Vol 64 (9) ◽  
Author(s):  
Matthias Geuß
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
Black Box ◽  
Design Parameters ◽  
Dimensional Parameter ◽  
Model Order ◽  
Parametric Model Order Reduction ◽  
Box Method ◽  
Matrix Interpolation ◽  
And Control

AbstractThis thesis deals with model order reduction of parameter-dependent systems based on interpolation of locally reduced system matrices. A Black-Box method is proposed that automatically determines the optimal design parameters and delivers a reduced system with desired accuracy. In addition, the method is extended to stability preservation and interpolation for high-dimensional parameter spaces.

scholarly journals Model order reduction of linear peridynamic systems using static condensation

2020 ◽  
pp. 108128652093704
Author(s):  
Yakubu Kasimu Galadima ◽  
Erkan Oterkus ◽  
Selda Oterkus
Keyword(s):  
Model Order Reduction ◽  
Computational Models ◽  
Order Reduction ◽  
Nonlocal Theory ◽  
Computational Effort ◽  
Finite Element Models ◽  
Reduction Algorithm ◽  
Discontinuous System ◽  
Model Order ◽  
Static Condensation

Static condensation is widely used as a model order reduction technique to reduce the computational effort and complexity of classical continuum-based computational models, such as finite-element models. Peridynamic theory is a nonlocal theory developed primarily to overcome the shortcoming of classical continuum-based models in handling discontinuous system responses. In this study, a model order reduction algorithm is developed based on the static condensation technique to reduce the order of peridynamic models. Numerical examples are considered to demonstrate the robustness of the proposed reduction algorithm in reproducing the static and dynamic response and the eigenresponse of the full peridynamic models.

Model order reduction techniques applied to magnetodynamic T-Ω-formulation

2020 ◽  
Vol 39 (5) ◽  
pp. 1057-1069
Author(s):  
Fabian Müller ◽  
Lucas Crampen ◽  
Thomas Henneron ◽  
Stephane Clénet ◽  
Kay Hameyer
Keyword(s):  
Eddy Current ◽  
Model Order Reduction ◽  
Scalar Potential ◽  
Order Reduction ◽  
Computational Effort ◽  
Transient Field ◽  
Model Order ◽  
Field Problem ◽  
Content Type ◽  
Reduction Techniques

Purpose The purpose of this paper is to use different model order reduction techniques to cope with the computational effort of solving large systems of equations. By appropriate decomposition of the electromagnetic field problem, the number of degrees of freedom (DOF) can be efficiently reduced. In this contribution, the Proper Generalized Decomposition (PGD) and the Proper Orthogonal Decomposition (POD) are used in the frame of the T-Ω-formulation, and the feasibility is elaborated. Design/methodology/approach The POD and the PGD are two methods to reduce the model order. Particularly in the context of eddy current problems, conventional time-stepping algorithms can lead to many numerical simulations of the studied problem. To simulate the transient field, the T-Ω-formulation is used which couples the magnetic scalar potential and the electric vector potential. In this paper, both methods are studied on an academic example of an induction furnace in terms of accuracy and computational effort. Findings Using the proposed reduction techniques significantly reduces the DOF and subsequently the computational effort. Further, the feasibility of the combination of both methods with the T-Ω-formulation is given, and a fundamental step toward fast simulation of eddy current problems is shown. Originality/value In this paper, the PGD is combined for the first time with the T-Ω-formulation. The application of the PGD and POD and the following comparison illustrate the great potential of these techniques in combination with the T-Ω-formulation in context of eddy current problems.

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