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Für geometrisch imperfekte Strukturen wird die Versagenswahrscheinlichkeit bezüglich Stabilitätskriterien bestimmt. Eine probabilistische Beschreibung der geometrischen Imperfektionen erfolgt mit skalaren ortsdiskretisierten Zufallsfeldern. Die Stabilitätsberechnungen werden mit der Finite Elemente Methode durchgeführt. Ausgangspunkt der Berechnung ist eine systematische Formulierung probabilistisch gewichteter Imperfektionsformen durch eine Eigenwertzerlegung der Kovarianzmatrix. Wenn mit einer strukturmechanisch orientierten Sensitivitätsanalyse ein Unterraum zur näherungsweisen Beschreibung des probabilistischen Strukturverhaltens gefunden wird, kann die Versagenswahrscheinlichkeit numerisch sehr effizient durch ein Interaktionsmodell bestimmt werden. Es zeigte sich, daß dies genau dann möglich ist, wenn die Beulform merklich im Imperfektionsfeld enthalten ist. Die Imperfektionsform am Bemessungspunkt entspricht dann, unabhängig vom Lastniveau, gerade der Beulform. Wenn die Beulform im Imperfektionsfeld einen untergeordneten Beitrag liefert, erscheint eine Reduktion des stochastischen Problems auf wenige Zufallsvariablen dagegen nicht möglich.
In this contribution the software design and implementation of an analysis server for the computation of failure probabilities in structural engineering is presented. The structures considered are described in terms of an equivalent Finite Element model, the stochastic properties, like e.g. the scatter of the material behavior or the incoming load, are represented using suitable random variables. Within the software framework, a Client-Server-Architecture has been implemented, employing the middleware CORBA for the communication between the distributed modules. The analysis server offers the possibility to compute failure probabilities for stochastically defined structures. Therefore, several different approximation (FORM, SORM) and simulation methods (Monte Carlo Simulation and Importance Sampling) have been implemented. This paper closes in showing several examples computed on the analysis server.
The complex failure process of concrete structures can not be described in detail by standard engineering design formulas. The numerical analysis of crack development in concrete is essential for several problems. In the last decades a large number of research groups have dealt with this topic and several models and algorithms were developed. However, most of these methods show some difficulties and are limited to special cases. The goal of this study was to develop an automatic algorithm for the efficient simulation of multiple cracking in plain and reinforced concrete structures of medium size. For this purpose meshless methods were used to describe the growth of crack surfaces. Two meshless interpolation schemes were improved for a simple application. The cracking process of concrete has been modeled using a stable criterion for crack growth in combination with an improved cohesive crack model which can represent the failure process under combined crack opening and crack sliding very well. This crack growth algorithm was extended in order to represent the fluctuations of the concrete properties by enlarging the single-parameter random field concept for multiple correlated material parameters.
We present an extended finite element formulation for dynamic fracture of piezo-electric materials. The method is developed in the context of linear elastic fracture mechanics. It is applied to mode I and mixed mode-fracture for quasi-steady cracks. An implicit time integration scheme is exploited. The results are compared to results obtained with the boundary element method and show excellent agreement.
Realistic uncertainty description incorporating aleatoric and epistemic uncertainties can be described within the framework of polymorphic uncertainty, which is computationally demanding. Utilizing a domain decomposition approach for random field based uncertainty models the proposed level-based sampling method can reduce these computational costs significantly and shows good agreement with a standard sampling technique. While 2-level configurations tend to get unstable with decreasing sampling density 3-level setups show encouraging results for the investigated reliability analysis of a structural unit square.