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Showing 1 to 20 of 84 for “"Model-order reduction"”.
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Model Order Reduction in Structural Mechanics
… welche in der Strukturmechanik als Modellordnungsreduktion bekannt ist. Im Mittelpunkt stehen Kopplungsprozesse von starren und elastischen Mehrkörpersystemen - sowohl in theoretischer Hinsicht als auch bezüglich der praktischen Realisation im Rahmen des Finite-Elemente-Programms …
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Model order reduction for nonlinear systems
… thesis presents some practical methods for doing model order reduction for a general type of nonlinear systems. Based on quadratic or even higher degree approximation and tensor reduction with assistance of Arnoldi type projection, we demonstrate a much better accuracy for the reduced nonlinear …
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Model Order Reduction Based on Semidefinite Programming
The main topic of this PhD thesis is complexity reduction of linear time-invariant models. The complexity in such systems is measured by the number of differential equations forming the dynamical system. This number is called the order of the system. Order reduction is typically used as a tool to …
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Model Order Reduction: Application to Electromagnetic Problems
… increase in computational resources, numerical modeling has grown expo- nentially these last two decades. From structural analysis to combustion modeling and electromagnetics, discretization methods–in particular the finite element method–have had a tremendous impact. Their main advantage …
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Model order reduction of electro-thermal MEMS
The modeling of electro-thermal processes, for example Joule heating, is becoming increasingly important in microsystems (in the following MEMS) development. In microelectronic systems, for example, high temperatures may cause the malfunction or even destruction of the device. Other devices, such …
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Model order reduction techniques for circuit simulation
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Parameterized model order reduction for nonlinear dynamical systems
… techniques for generating Parameterized Reduced Order Models (PROMs) of nonlinear dynamical systems. Such reduced order models could serve as a first step towards the automatic and accurate characterization of geometrically complex components and subcircuits, eventually enabling their synthesis …
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Model-Order Reduction Techniques for Circuits and Interconnects Simulation
… of this dissertation is to extend the use of order-reduction techniques as accurate methods for analyzing complex electronic systems. The theoretical and practical aspects of moment-matching, Krylov subspace-based methods, and rational approximations techniques are studied. The moment-matching …
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A shifting method for dynamic system Model Order Reduction
Model Order Reduction (MOR) is becoming increasingly important in computational applications. At the same time, the need for more comprehensive models of systems is generating problems with increasing numbers of outputs and inputs. Classical methods, which were developed for Single-Input …
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Type-C wind turbine model order reduction and parameter identification
… power, engineers are finding it useful to have models to investigate wind turbine performance. For different applications, an accurate modeling of aerodynamics, power electronics, electrical transients, or control systems are necessary. In other scenarios, these models may be unavailable or …
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Efficient Stochastic Collocation Based Variability Analysis Using Model-Order Reduction Techniques
… In addition, the proposed method is based on the Model Order Reduction algorithms coupled with the Numerical Inverse Laplace Transform approach.
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Efficient Projection-Based Stability Guaranteed Model Order Reduction for Active Circuits
Moments matching model reduction method is an important tool for accelerating simulation of large scale system originating in circuit area. But this kind of method cannot guarantee the stability of the reduced model in the case of active circuits. To address this problem, a novel moments matching …
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Convergence and Boundedness of Probability-One Homotopies for Model Order Reduction
The optimal model reduction problem, whether formulated in the H² or H<sup>∞</sup> norm frameworks, is an inherently nonconvex problem and thus provides a nontrivial computational challenge. This study systematically examines the requirements of probability-one homotopy methods to guarantee global …
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Incorporation of Hysteretic Effects in Model-Order Reduction Analysis of Magnetic Devices
… development and simulation of wide-bandwidth models requires detailed, physics-based simulations that utilize significant computational resources. Balancing the trade-offs between model computational overhead and accuracy can be cumbersome, especially when the nonlinear effects of saturation …
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Model order reduction in the frequency domain via spectral proper orthogonal decomposition
In this thesis, we introduce a novel model order reduction framework for harmonically and randomly forced dynamical systems. Specifically, we emphasize the usage of spectral proper orthogonal decomposition (SPOD), recently revived by Towne et. al. (2018), which results in sets of orthogonal modes, …
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Theoretical and practical aspects of linear and nonlinear model order reduction techniques
Model order reduction methods have proved to be an important technique for accelerating time-domain simulation in a variety of computer-aided design tools. In this study we present several new techniques for model reduction of the large-scale linear and nonlinear systems. First, we present a method …
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Model-order reduction techniques for the numerical solution of electromagnetic wave scattering problems
… of this work to contribute to the development of model-order reduction (MOR) techniques for the field of computational electromagnetics in relation to the electric field integral equation (EFIE) formulation. The ultimate goal is to enable a fast-sweep analysis. In a fast-sweep problem, some …
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GPU and Krylov Based Parallel Model Order Reduction Algorithms for MIMO Circuit Reductions
… manufacturing. However, working with full-scale models can lead to circuits with millions of nodes incurring prohibitively excessive computational costs. To circumvent such problems, Model Order Reduction (MOR) schemes utilizing Krylov Subspace based projections such as the Passive Reduced …
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A trajectory piecewise-linear approach to model order reduction of nonlinear dynamical systems
… which result in improved accuracy of the reduced order TPWL models, as well as discuss approaches leading to guaranteed stable and passive TPWL reduced-order models.
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