53 research outputs found
Using parametric model order reduction for inverse analysis of large nonlinear cardiac simulations
Predictive high-fidelity finite element simulations of human cardiac mechanics commonly require a large number of structural degrees of freedom. Additionally, these models are often coupled with lumped-parameter models of hemodynamics. High computational demands, however, slow down model calibration and therefore limit the use of cardiac simulations in clinical practice. As cardiac models rely on several patient-specific parameters, just one solution corresponding to one specific parameter set does not at all meet clinical demands. Moreover, while solving the nonlinear problem, 90% of the computation time is spent solving linear systems of equations. We propose to reduce the structural dimension of a monolithically coupled structure-Windkessel system by projection onto a lower-dimensional subspace. We obtain a good approximation of the displacement field as well as of key scalar cardiac outputs even with very few reduced degrees of freedom, while achieving considerable speedups. For subspace generation, we use proper orthogonal decomposition of displacement snapshots. Following a brief comparison of subspace interpolation methods, we demonstrate how projection-based model order reduction can be easily integrated into a gradient-based optimization. We demonstrate the performance of our method in a real-world multivariate inverse analysis scenario. Using the presented projection-based model order reduction approach can significantly speed up model personalization and could be used for many-query tasks in a clinical setting
An Iterative Model Reduction Scheme for Quadratic-Bilinear Descriptor Systems with an Application to Navier-Stokes Equations
We discuss model reduction for a particular class of quadratic-bilinear (QB)
descriptor systems. The main goal of this article is to extend the recently
studied interpolation-based optimal model reduction framework for QBODEs
[Benner et al. '16] to a class of descriptor systems in an efficient and
reliable way. Recently, it has been shown in the case of linear or bilinear
systems that a direct extension of interpolation-based model reduction
techniques to descriptor systems, without any modifications, may lead to poor
reduced-order systems. Therefore, for the analysis, we aim at transforming the
considered QB descriptor system into an equivalent QBODE system by means of
projectors for which standard model reduction techniques for QBODEs can be
employed, including aforementioned interpolation scheme. Subsequently, we
discuss related computational issues, thus resulting in a modified algorithm
that allows us to construct \emph{near}--optimal reduced-order systems without
explicitly computing the projectors used in the analysis. The efficiency of the
proposed algorithm is illustrated by means of a numerical example, obtained via
semi-discretization of the Navier-Stokes equations
Een schatkamer vol oude problemen
Op 2 april werd tijdens een feestelijke bijeenkomst in museum NEMO het boek De Pythagoras Code officieel gepresenteerd. Het boek bevat een bloemlezing uit 50 jaargangen Pythagoras, met de bekende 'Denkertjes' alsmede puzzels en dionigma's. Het rakelt oude problemen op, zoals het 3n+1 vermoeden, bevat een selectie van prijsvragen en een leuk hoofdstukje 'Geschiedenis' over een aatal bekende wiskundigen. Wil Schilders doet verslag
Platform Wiskunde Nederland : plannen en terugblik
In het najaar van 2010 werd het Platform Wiskunde Nederland opgericht door het Koninklijk Wiskundig Genootschap (KWG) en de Nederlandse Vereniging vanWiskundeleraren (NVvW), ondersteund door de wiskunde-instituten van de Nederlandse universiteiten (inclusief Eurandom en het Freudenthal Instituut), de Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), het Centrum Wiskunde & Informatica (CWI), en de stichtingen Thomas Stieltjes en Compositio.
PWN is opgericht als centrale plaats binnen de Nederlandse wiskunde van waaruit alle zaken die voor de wiskunde van belang zijn op efficiënte wijze behartigd kunnen worden. In het eerste jaar is PWN als landelijke organisatie neergezet, en zijn de commissies aan de slag gegaan. Hiermee is een solide basis gelegd voor het tweede jaar. Wil Schilders, directeur van het PWN, blikt terug op het eerste jaar en licht de plannen voor de toekomst toe
Reduced order modelling of RLC-networks using an SVD-Laguerre based method
With interconnect increasingly contributing to the electrical behaviour of integrated circuits, both by higher frequencies and smaller dimensions, it becomes increasingly important to incorporate its behaviour into simulations of ICs. This can be done rather elegantly by summarizing interconnect behaviour into a compact or reduced order model which is then co-simulated with the circuit. A similar approach can be used in the case of more conventional printed circuit boards. The SVDLaguerre algorithm proposed by Knockaert and De Zutter [4] can be used for this purpose. In this paper, we describe an e#cient implementation of the algorithm for multiple inputs, and show how the mathematical reduced order models can be translated into realizable circuit elements
Krylov subspace methods in the electronic industry
Summary. Krylov subspace methods are well-known for their nice properties, but they have to be implemented with care. In this article the mathematical consequences encountered during implementation of Krylov subspace methods in an existing layout-simulator are discussed. Briefly, the representation in a circuit is visited and two methods to avoid parts of the redundancy are drawn
Error bounds for reduction of multi-port resistor networks
The interconnect layouts of chips can be modeled by large resistor networks. In order to be able to
speed up simulations of such large networks, reduction techniques are applied to reduce the size of the networks. For some class of networks, an existing reduction strategy does not provide sufficient reduction in terms of the number of resistors appearing in the final network. In this paper we propose an approach for obtaining a further reduction in the amount of resistors. The suggested approach improves sparsity of the conductance matrix by neglecting resistors which do not contribute significantly to the behavior of the circuit. Explicit error bounds, which give an opportunity to control the errors due to approximation, have been derived. Numerical examples show that the suggested approach appears promising for multi-terminal resistor networks and, in combination with the existing reduction strategy, leads to better reduction
Order reduction techniques for coupled multi-domain electromagnetic based models
This work presents a comprehensive flow able to efficiently generate reduced order models for realistic, hierarchy aware, Electromagnetic (EM) based models. Knowledge of the structure of the problem is explicitly exploited using domain partitioning and novel electromagnetic connector modeling techniques to generate a hierarchically coupled representation. This enables the efficient
use of structure preserving block model order reduction techniques to generate block-wise compressed models that satisfy overall requirements, and provide cheap evaluation and simulation accurate approximations of the complete EM behaviour
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