Tensor based nonlinear model order reduction
Web1 Jul 2015 · Unlike existing nonlinear model order reduction methods, in TNMOR high-order nonlinearities are captured using tensors, followed by decomposition and reduction to a compact tensor-based reduced ... Webperformance for two speci c parameter-dependent non-linear dynamical systems. Key words. Model order reduction, parametric dynamical systems, low-rank tensor approximations, proper orthogonal decomposition, discrete empirical interpolation method 1. Introduction. Numerical solution of parametric dynamical systems is a common prob-
Tensor based nonlinear model order reduction
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WebNonlinear model order reduction has always been a challenging but important task in various science and engineering fields. In this paper, a novel symmetric tensor-based order-reduction method (STORM) is presented for simulating large-scale nonlinear systems. The multidimensional data structure of symmetric tensors, as the higher order generalization …
Web1 Jan 2010 · Nonlinear balanced truncation is a model order reduction technique that reduces the dimension of nonlinear systems in a manner that accounts for either open- or closed-loop observability and ... WebIn sheet metal forming, the material is usually subjected to a complex nonlinear loading process, and the anisotropic hardening behavior of the material must be considered in order to accurately predict the deformation of the sheet. In recent years, the homogeneous anisotropic hardening (HAH) model has been applied in the simulation of sheet metal …
Web14 Apr 2024 · The structure of this paper is as follows: First, the concept of AM with specific focus on FDM technique is briefly presented. In Sect. 2, the experimental procedure is explained with PLA specimens for obtaining the stress-strain curves and the derivation of a hyperelastic model.Then in Sect. 4, we present the experimental results in terms of … Web1 Jul 2015 · In this paper, we utilize tensors (namely, a higher order generalization of matrices) to develop a tensor-based nonlinear model order reduction algorithm we named …
WebModel order reduction of nonlinear circuits (especially highly nonlinear circuits) has always been a theoretically and numerically challenging task. In this paper, we utilize tensors (namely, a higher order generalization of matrices) to develop a tensor-based nonlinear model order reduction algorithm we named TNMOR for the efficient simulation of …
Web1 Sep 2016 · Model order reduction is another approach which seeks to replace a large system by a system of substantially lower order. The reduced model or system can keep … megabus perth to edinburgh routeWeb6 Apr 2024 · In this paper, we propose a general framework for projection-based model order reduction assisted by deep neural networks. The proposed methodology, called ROM-net, consists in using deep learning techniques to adapt the reduced-order model to a stochastic input tensor whose nonparametrized variabilities strongly influence the … megabus perth to invernessWeb6 Mar 2015 · Model order reduction of nonlinear circuits (especially highly nonlinear circuits) has always been a theoretically and numerically challenging task. In this pap … megabus perth to liverpoolWeb8 Jan 2024 · We first introduce some definitions and results on tensor extended from matrix theory. Then we show how the general nonlinear system can be converted into the low rank form we treated in this research. We put the model order reduction of it in two frameworks, that is, polynomial framework and moment‐matching framework. megabus perth to edinburgh airportWeb1 Sep 2016 · Model order reduction is another approach which seeks to replace a large system by a system of substantially lower order. The reduced model or system can keep … names of play schoolsWeb10 Aug 2024 · This study investigates two model-order reduction (MOR) methods for the quadratic-bilinear (QB) systems which are equivalently transformed from the non-linear … megabus peterboroughWeb1 Sep 2016 · Model order reduction is another approach which seeks to replace a large system by a system of substantially lower order. The reduced model or system can keep some main properties of the original one. This approach is also widely used in many fields such as fluid systems and chemical reaction systems. megabus philadelphia stations