Searched for: subject%3A%22subspace%255C+methods%22
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Sereeter, B. (author)
During the normal operation, control and planning of the power system, grid operators employ numerous tools including the Power Flow (PF) and the Optimal Power Flow (OPF) computations to keep the balance in the power system. The solution of the PF computation is used to assess whether the power system can function properly for the given...
doctoral thesis 2020
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Nord, Torodd Skjerve (author), Petersen, Oyvind (author), Hendrikse, H. (author)
Identifying the modal parameters of structures located in ice-infested waters may be challenging due to the interaction between the ice and structure. In this study, both simulated data from a state-of-the-art ice–structure interaction model and measured data of ice–structure interaction were both used in conjunction with a covariance-driven...
journal article 2019
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Sereeter, B. (author), van Westering, W.H.P. (author), Vuik, Cornelis (author), Witteveen, C. (author)
In this paper, we propose a fast linear power flow method using a constant impedance load model to simulate both the entire Low Voltage (LV) and Medium Voltage (MV) networks in a single simulation. Accuracy and efficiency of this linear approach are validated by comparing it with the Newton power flow algorithm and a commercial network design...
journal article 2019
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Astudillo Rengifo, R.A. (author)
In several applications in science and engineering, different types of matrix problems emerge from the discretization of partial differential equations.<br/>This thesis is devoted to the development of new algorithms to solve this<br/>kind of problems. In particular, when the matrices involved are sparse and<br/>non-symmetric. The new algorithms...
doctoral thesis 2018
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Kerklaan, Martijn (author)
The dynamic relation between the displacement and reaction torque of the human joint is known as joint impedance. Properly quantifying joint impedance has medical potential in the diagnosis, understanding and modelling of movement disorders associated with neuromuscular conditions like cerebral palsy, stroke, dystonia and old age. The...
master thesis 2018
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Baumann, M.M. (author)
Seismic Full-Waveform Inversion is an imaging technique to better understand the earth's subsurface. Therefore, the reflection intensity of sound waves is measured in a field experiment and is matched with the results from a computer simulation in a least-squares sense. From a computational point-of-view, but also from an economic view point,...
doctoral thesis 2018
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Gunes, Bilal (author), van Wingerden, J.W. (author), Verhaegen, M.H.G. (author)
In this paper, we present a novel multiple input multiple output (MIMO) linear parameter varying (LPV) state-space refinement system identification algorithm that uses tensor networks. Its novelty mainly lies in representing the LPV sub-Markov parameters, data and state-revealing matrix condensely and in exact manner using specific tensor...
journal article 2018
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Klingspor, M. (author), Hansson, A (author), Löfberg, J. (author), Verhaegen, M.H.G. (author)
Input selection is an important and oftentimes difficult challenge in system identification. In order to achieve less complex models, irrelevant inputs should be methodically and correctly discarded before or under the estimation process. In this paper we introduce a novel method of input selection that is carried out as a natural extension in a...
conference paper 2017
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Gunes, Bilal (author), van Wingerden, J.W. (author), Verhaegen, M.H.G. (author)
The major bottleneck in state-of-the-art Linear Parameter Varying (LPV) subspace methods is the curse-of-dimensionality during the first regression step. In this paper, the origin of the curse-of-dimensionality is pinpointed and subsequently a novel method is proposed which does not suffer from this bottleneck. The problem is related to the...
journal article 2017
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Astudillo Rengifo, R.A. (author), van Gijzen, M.B. (author)
This paper discusses the solution of large-scale linear matrix equations using the Induced Dimension reduction method (IDR(s)). IDR(s) was originally presented to solve system of linear equations, and is based on the IDR(s) theorem. We generalize the IDR(s) theorem to solve linear problems in any finite-dimensional space. This generalization...
journal article 2016
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Astudillo, R. (author), Van Gijzen, M.B. (author)
This paper discusses the solution of large-scale linear matrix equations using the Induced Dimension reduction method (IDR(s)). IDR(s) was originally presented to solve system of linear equations, and is based on the IDR(s) theorem. We generalize the IDR(s) theorem to solve linear problems in any finite-dimensional space. This generalization...
report 2015
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Torres Tapia, P.I. (author)
In this thesis, three novel state-space identification algorithms for linear interconnected systems are proposed. The computational complexity and the topology reconstruction of the interconnected system are addressed. Possible applications of this theory can be found in Biology, Economics, Transportation, Electrical and Mechanical Engineering....
doctoral thesis 2014
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He, X. (author), Neytcheva, M. (author), Vuik, C. (author)
This paper deals with fast and reliable numerical solution methods for the incompressible non-Newtonian Navier-Stokes equations. To handle the nonlinearity of the governing equations, the Picard and Newton methods are used to linearize these coupled partial differential equations. For space discretization we use the finite element method and...
report 2013
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Diao, H. (author)
This thesis attempts to explain the convergence behaviour of solving Helmholtz problem by investigating its spectral properties. Fourier analysis is employ to solve the eigenvalues of the matrices that are involved in the iterative methods. The numerical experiment is conducted to verify the conclusions by Fourier analysis and also to reveal...
master thesis 2012
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Sonneveld, P. (author)
An explanation is given of the convergence behavior of IDR(s) methods. The convergence mechanism of these algorithms has two components. The first consists of damping properties of certain factors in the residual polynomials, which becomes less important for large values of s. The second component depends on the behavior of Lanczos polynomials...
journal article 2012
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Van de Sande, G.E.M. (author)
master thesis 2012
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Van Gijzen, M.B. (author), Sleijpen, G.L.G. (author), Zemke, J.P. (author)
We give two important generalizations of the Induced Dimension Reduction (IDR) approach for the solution of linear systems. We derive a flexible and a multi-shift Quasi-Minimal Residual IDR (QMRIDR) variant. Numerical examples are presented to show the effectiveness of these new IDR variants compared to existing ones and to other Krylov subspace...
report 2011
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Sleijpen, G.L.G. (author), Van Gijzen, M.B. (author)
IDR(s) [P. Sonneveld and M. B. van Gijzen, SIAM J. Sci. Comput., 31 (2008), pp. 1035–1062] and BiCGstab(?) [G. L. G. Sleijpen and D. R. Fokkema, Electron. Trans. Numer. Anal., 1 (1993), pp. 11–32] are two of the most efficient short-recurrence iterative methods for solving large nonsymmetric linear systems of equations. Which of the two is best...
journal article 2010
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Van Gijzen, M.B. (author), Sonneveld, P. (author)
The IDR(s) method that is proposed in [18] is a very efficient limited memory method for solving large nonsymmetric systems of linear equations. IDR(s) is based on the induced dimension reduction theorem, that provides a way to construct subsequent residuals that lie in a sequence of shrinking subspaces. The IDR(s) algorithm that is given in [18...
report 2010
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Van Gijzen, M.B. (author), Collignon, T.P. (author)
The IDR(s) method that is proposed in [26] is an efficient limited memory method for solving large nonsymmetric systems of linear equations. In [11] an IDR(s) variant is described that has a single synchronisation point per iteration step, which makes this variant well-suited for parallel and grid computing. In this paper, we combine this IDR(s)...
report 2010
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