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Analysis of the reinforced concrete chimney geometry changes and their influence on the stresses in the chimney mantle was made. All the changes were introduced to a model chimney and compared. Relations between the stresses in the mantle of the chimney and the deformations determined by the change of the chimney's vertical axis geometry were investigated. The vertical axis of chimney was described by linear function (corresponding to the real rotation of the chimney together with the foundation), and by parabolic function (corresponding to the real dislocation of the chimney under the influence of the horizontal forces - wind). The positive stress pattern in the concrete as well as the negative stress pattern in the reinforcing steel have been presented. The two cases were compared. Analysis of the stress changes in the chimney mantle depending on the modification in the thickness of the mantle (the thickness of the chimney mantle was altered in the linear or the abrupt way) was carried out. The relation between the stresses and the chimney's diameter change from the bottom to the top of the chimney was investigated. All the analyses were conducted by means of a specially developed computer program created in Mathematica environment. The program makes it also possible to control calculations and to visualize the results of the calculations at every stage of the calculation process.
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.
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.
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.
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.
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.
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.
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.
The Element-free Galerkin Method has become a very popular tool for the simulation of mechanical problems with moving boundaries. The internally applied Moving Least Squares approximation uses in general Gaussian or cubic weighting functions and has compact support. Due to the approximative character of this method the obtained shape functions do not fulfill the interpolation condition, which causes additional numerical effort for the imposition of the essential boundary conditions. The application of a singular weighting function, which leads to singular coefficient matrices at the nodes, can solve this problem, but requires a very careful placement of the integration points. Special procedures for the handling of such singular matrices were proposed in literature, which require additional numerical effort. In this paper a non-singular weighting function is presented, which leads to an exact fulfillment of the interpolation condition. This weighting function leads to regular values of the weights and the coefficient matrices in the whole interpolation domain even at the nodes. Furthermore this function gives much more stable results for varying size of the influence radius and for strongly distorted nodal arrangements than classical weighting function types. Nevertheless, for practical applications the results are similar as these obtained with the regularized weighting type presented by the authors in previous publications. Finally a new concept will be presented, which enables an efficient analysis of systems with strongly varying node density. In this concept the nodal influence domains are adapted depending on the nodal configuration by interpolating the influence radius for each direction from the distances to the natural neighbor nodes. This approach requires a Voronoi diagram of the domain, which is available in this study since Delaunay triangles are used as integration background cells. In the numerical examples it will be shown, that this method leads to a more uniform and reduced number of influencing nodes for systems with varying node density than the classical circular influence domains, which means that the small additional numerical effort for interpolating the influence radius leads to remarkable reduction of the total numerical cost in a linear analysis while obtaining similar results. For nonlinear calculations this advantage would be even more significant.