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We present recent developments of adaptive wavelet solvers for elliptic eigenvalue problems. We describe the underlying abstract iteration scheme of the preconditioned perturbed iteration. We apply the iteration to a simple model problem in order to identify the main ideas which a numerical realization of the abstract scheme is based upon. This indicates how these concepts carry over to wavelet discretizations. Finally we present numerical results for the Poisson eigenvalue problem on an L-shaped domain.
Major problems of applying selective sensitivity to system identification are requirement of precise knowledge about the system parameters and realization of the required system of forces. This work presents a procedure which is able to deriving selectively sensitive excitation by iterative experiments. The first step is to determine the selectively sensitive displacement and selectively sensitive force patterns. These values are obtained by introducing the prior information of system parameters into an optimization which minimizes the sensitivities of the structure response with respect to the unselected parameters while keeping the sensitivities with respect to the selected parameters as a constant. In a second step the force pattern is used to derive dynamic loads on the tested structure and measurements are carried out. An automatic control ensures the required excitation forces. In a third step, measured outputs are employed to update the prior information. The strategy is to minimize the difference between a predicted displacement response, formulated as function of the unknown parameters and the measured displacements, and the selectively sensitive displacement calculated in the first step. With the updated values of the parameters a re-analysis of selective sensitivity is performed and the experiment is repeated until the displacement response of the model and the actual structure are conformed. As an illustration a simply supported beam made of steel, vibrated by harmonic excitation is investigated, thereby demonstrating that the adaptive excitation can be obtained efficiently.
In engineering science the modeling and numerical analysis of complex systems and relations plays an important role. In order to realize such an investigation, for example a stochastic analysis, in a reasonable computational time, approximation procedure have been developed. A very famous approach is the response surface method, where the relation between input and output quantities is represented for example by global polynomials or local interpolation schemes as Moving Least Squares (MLS). In recent years artificial neural networks (ANN) have been applied as well for such purposes. Recently an adaptive response surface approach for reliability analyses was proposed, which is very efficient concerning the number of expensive limit state function evaluations. Due to the applied simplex interpolation the procedure is limited to small dimensions. In this paper this approach is extended for larger dimensions using combined ANN and MLS response surfaces for evaluating the adaptation criterion with only one set of joined limit state points. As adaptation criterion a combination by using the maximum difference in the conditional probabilities of failure and the maximum difference in the approximated radii is applied. Compared to response surfaces on directional samples or to plain directional sampling the failure probability can be estimated with a much smaller number of limit state points.
In this paper an adaptive heterogeneous multiscale model, which couples two substructures with different length scales into one numerical model is introduced for the simulation of damage in concrete. In the presented approach the initiation, propagation and coalescence of microcracks is simulated using a mesoscale model, which explicitly represents the heterogeneous material structure of concrete. The mesoscale model is restricted to the damaged parts of the structure, whereas the undamaged regions are simulated on the macroscale. As a result an adaptive enlargement of the mesoscale model during the simulation is necessary. In the first part of the paper the generation of the heterogeneous mesoscopic structure of concrete, the finite element discretization of the mesoscale model, the applied isotropic damage model and the cohesive zone model are briefly introduced. Furthermore the mesoscale simulation of a uniaxial tension test of a concrete prism is presented and own obtained numerical results are compared to experimental results. The second part is focused on the adaptive heterogeneous multiscale approach. Indicators for the model adaptation and for the coupling between the different numerical models will be introduced. The transfer from the macroscale to the mesoscale and the adaptive enlargement of the mesoscale substructure will be presented in detail. A nonlinear simulation of a realistic structure using an adaptive heterogeneous multiscale model is presented at the end of the paper to show the applicability of the proposed approach to large-scale structures.
For the dynamic behavior of lightweight structures like thin shells and membranes exposed to fluid flow the interaction between the two fields is often essential. Computational fluid-structure interaction provides a tool to predict this interaction and complement or eventually replace expensive experiments. Partitioned analyses techniques enjoy great popularity for the numerical simulation of these interactions. This is due to their computational superiority over simultaneous, i.e. fully coupled monolithic approaches, as they allow the independent use of suitable discretization methods and modular analysis software. We use, for the fluid, GLS stabilized finite elements on a moving domain based on the incompressible instationary Navier-Stokes equations, where the formulation guarantees geometric conservation on the deforming domain. The structure is discretized by nonlinear, three-dimensional shell elements.
Commonly used sequential staggered coupling schemes may exhibit instabilities due to the so-called artificial added mass effect. As best remedy to this problem subiterations should be invoked to guarantee kinematic and dynamic continuity across the fluid-structure interface. Since iterative coupling algorithms are computationally very costly, their convergence rate is very decisive for their usability. To ensure and accelerate the convergence of this iteration the updates of the interface position are relaxed. The time dependent, 'optimal' relaxation parameter is determined automatically without any user-input via exploiting a gradient method or applying an Aitken iteration scheme.
We present an algebraically extended 2D image representation in this paper. In order to obtain more degrees of freedom, a 2D image is embedded into a certain geometric algebra. Combining methods of differential geometry, tensor algebra, monogenic signal and quadrature filter, the novel 2D image representation can be derived as the monogenic extension of a curvature tensor. The 2D spherical harmonics are employed as basis functions to construct the algebraically extended 2D image representation. From this representation, the monogenic signal and the monogenic curvature signal for modeling intrinsically one and two dimensional (i1D/i2D) structures are obtained as special cases. Local features of amplitude, phase and orientation can be extracted at the same time in this unique framework. Compared with the related work, our approach has the advantage of simultaneous estimation of local phase and orientation. The main contribution is the rotationally invariant phase estimation, which enables phase-based processing in many computer vision tasks.
Mikroelektronik und Mikrosystemtechnik in Kombination mit Informations- und Kommunikations-technik erlauben es mittlerweile, Rechenleistung und Kommunikationsfähigkeit in kleinsten Formaten, mit geringsten Energien und zu günstigen Preisen nutzbringend in unser privates und berufliches Umfeld einzubringen. Beispiele sind Notebook-PC, PDA, Handy und das Navigationßystem im Auto. Aber auch eingebettete Elektronik in Komponenten, Geräten und Systemen ist nunmehr zur Selbstverständlichkeit geworden. Bekannte Beispiele aus der Haustechnik sind Mikroprozeßoren in Heizungs- und Alarmanlagen und aber auch in Komponenten wie Brand- und Bewegungsmelder. Wir nähern uns dem vor einigen Jahren noch als Vision bezeichneten Zustand der überall vorhandenen elektronischen Rechenleistung (engl. ubiquitous computing) bzw. des von Informationsverarbeitung durchdrungenen täglichen Umfelds (engl. pervasive computing). Werden die TGA-Komponenten genau wie die größeren Computerkomponenten (z.B. PCs, Server) über Datenschnittstellen zu räumlich verteilten Netzwerken verknüpft (z.B. Internet, Intranet) und mit einer systemübergreifenden und adäquaten Intelligenz (Software) programmiert, so können neuartige Funktionalitäten im jeweiligen Anwendungsumfeld (engl. ambient intelligence, kurz AmI, [1]) entstehen. Hier liegt bei Gebäuden und Räumen speziell eine große Chance, die bislang einer ganzheitlichen Systemkonzeption unter Einschluß von Architektur, Gebäudephysik, technischer Gebäudeausrüstung (TGA) und Gebäudeautomation (GA) im Wege stehende Gewerketrennung zu überwinden. Es entstehen für div. Anwendungszwecke systemisch integrierte >smart areas< (nach Prof. Becker, FH Biberach). Im vorliegenden Beitrag erläuterte Beispiele für AmI-Lösungen im Immobilienbereich sind Raumsysteme zur automatischen und sicheren Erkennung von Notfällen, z.B. in Pflegeheimen; sich automatisch an die Nutzung und den Nutzer bzgl. Klima und Beleuchtung adaptierende Raumsysteme im Büro- oder Hotelbereich und die elektronische Aßistenz des Bau- und Betriebsprozeßes von Gebäuden. Im Duisburger inHaus-Innovationszentrum für Intelligente Raum- und Gebäudesysteme der Fraunhofer-Gesellschaft wurden in den letzten Jahren erste Lösungen mit diesem neuartigen Ansatz konzipiert, entwickelt und erprobt. Der Beitrag beschreibt nach einer kurzen Skizzierung des Ambient-Intelligence-Ansatzes an Beispielen Möglichkeiten für den Transfer dieser neuen Technologie in den Raum- und Gebäudebereich. Es folgt eine abschließende Zusammenfaßung und eine Einschätzung der Zukunftspotenziale der Ambient Intelligence in Raum und Bau.
The application of a recent method using formal power series is proposed. It is based on a new representation for solutions of Sturm-Liouville equations. This method is used to calculate the transmittance and reflectance coefficients of finite inhomogeneous layers with high accuracy and efficiency. Tailoring the refraction index profile defining the inhomogeneous media it is possible to develop very important applications such as optical filters. A number of profiles were evaluated and then some of them selected in order to perform an improvement of their characteristics via the modification of their profiles.
In the context of finite element model updating using vibration test data, natural frequencies and mode shapes are used as validation criteria. Consequently, the order of natural frequencies and mode shapes is important. As only limited spatial information is available and noise is present in the measurements, the automatic selection of the most likely numerical mode shape corresponding to a measured mode shape is a difficult task. The most common criterion to indicate corresponding mode shapes is the modal assurance criterion. Unfortunately, this criterion fails in certain cases. In this paper, the pure mathematical modal assurance criterion will be enhanced by additional physical information of the numerical model in terms of modal strain energies. A numerical example and a benchmark study with real measured data are presented to show the advantages of the enhanced energy based criterion in comparison to the traditional modal assurance criterion.
The modeling of crack propagation in plain and reinforced concrete structures is still a field for many researchers. If a macroscopic description of the cohesive cracking process of concrete is applied, generally the Fictitious Crack Model is utilized, where a force transmission over micro cracks is assumed. In the most applications of this concept the cohesive model represents the relation between the normal crack opening and the normal stress, which is mostly defined as an exponential softening function, independently from the shear stresses in tangential direction. The cohesive forces are then calculated only from the normal stresses. By Carol et al. 1997 an improved model was developed using a coupled relation between the normal and shear damage based on an elasto-plastic constitutive formulation. This model is based on a hyperbolic yield surface depending on the normal and the shear stresses and on the tensile and shear strength. This model also represents the effect of shear traction induced crack opening. Due to the elasto-plastic formulation, where the inelastic crack opening is represented by plastic strains, this model is limited for applications with monotonic loading. In order to enable the application for cases with un- and reloading the existing model is extended in this study using a combined plastic-damage formulation, which enables the modeling of crack opening and crack closure. Furthermore the corresponding algorithmic implementation using a return mapping approach is presented and the model is verified by means of several numerical examples. Finally an investigation concerning the identification of the model parameters by means of neural networks is presented. In this analysis an inverse approximation of the model parameters is performed by using a given set of points of the load displacement curves as input values and the model parameters as output terms. It will be shown, that the elasto-plastic model parameters could be identified well with this approach, but require a huge number of simulations.