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Buildings can be divided into various types and described by a huge number of parameters. Within the life cycle of a building, especially during the design and construction phases, a lot of engineers with different points of view, proprietary applications and data formats are involved. The collaboration of all participating engineers is characterised by a high amount of communication. Due to these aspects, a homogeneous building model for all engineers is not feasible. The status quo of civil engineering is the segmentation of the complete model into partial models. Currently, the interdependencies of these partial models are not in the focus of available engineering solutions. This paper addresses the problem of coupling partial models in civil engineering. According to the state-of-the-art, applications and partial models are formulated by the object-oriented method. Although this method solves basic communication problems like subclass coupling directly it was found that many relevant coupling problems remain to be solved. Therefore, it is necessary to analyse and classify the relevant coupling types in building modelling. Coupling in computer science refers to the relationship between modules and their mutual interaction and can be divided into different coupling types. The coupling types differ on the degree by which the coupled modules rely upon each other. This is exemplified by a general reference example from civil engineering. A uniform formulation of coupling patterns is described analogously to design patterns, which are a common methodology in software engineering. Design patterns are templates for describing a general reusable solution to a commonly occurring problem. A template is independent of the programming language and the operating system. These coupling patterns are selected according to the specific problems of building modelling. A specific meta-model for coupling problems in civil engineering is introduced. In our meta-model the coupling patterns are a semantic description of a specific coupling design.
In this paper the influence of changes in the mean wind velocity, the wind profile power-law coefficient, the drag coefficient of the terrain and the structural stiffness are investigated on different complex structural models. This paper gives a short introduction to wind profile models and to the approach by Davenport A. G. to compute the structural reaction of wind induced vibrations. Firstly with help of a simple example (a skyscraper) this approach is shown. Using this simple example gives the reader the possibility to study the variance differences when changing one of the above mentioned parameters on this very easy example and see the influence of different complex structural models on the result. Furthermore an approach for estimation of the needed discretization level is given. With the help of this knowledge the structural model design methodology can be base on deeper understanding of the different behavior of the single models.
ESTIMATING UNCERTAINTIES FROM INACCURATE MEASUREMENT DATA USING MAXIMUM ENTROPY DISTRIBUTIONS
(2010)
Modern engineering design often considers uncertainties in geometrical and material parameters and in the loading conditions. Based on initial assumptions on the stochastic properties as mean values, standard deviations and the distribution functions of these uncertain parameters a probabilistic analysis is carried out. In many application fields probabilities of the exceedance of failure criteria are computed. The out-coming failure probability is strongly dependent on the initial assumptions on the random variable properties. Measurements are always more or less inaccurate data due to varying environmental conditions during the measurement procedure. Furthermore the estimation of stochastic properties from a limited number of realisation also causes uncertainties in these quantities. Thus the assumption of exactly known stochastic properties by neglecting these uncertainties may not lead to very useful probabilistic measures in a design process. In this paper we assume the stochastic properties of a random variable as uncertain quantities caused by so-called epistemic uncertainties. Instead of predefined distribution types we use the maximum entropy distribution which enables the description of a wide range of distribution functions based on the first four stochastic moments. These moments are taken again as random variables to model the epistemic scatter in the stochastic assumptions. The main point of this paper is the discussion on the estimation of these uncertain stochastic properties based on inaccurate measurements. We investigate the bootstrap algorithm for its applicability to quantify the uncertainties in the stochastic properties considering imprecise measurement data. Based on the obtained estimates we apply standard stochastic analysis on a simple example to demonstrate the difference and the necessity of the proposed approach.
There are many different approaches to simulate the mechanical behavior of RC−Frames with masonry infills. In this paper, selected modeling techniques for masonry infills and reinforced concrete frame members will be discussed − stressing the attention on the damaging effects of the individual members and the entire system under quasi−static horizontal loading. The effect of the infill walls on the surrounding frame members is studied using equivalent strut elements. The implemented model consider in−plane failure modes for the infills, such as bed joint sliding and corner crushing. These frame member models differ with respect to their stress state. Finally, examples are provided and compared with experimental data from a real size test executed on a three story RC−Frame with and without infills. The quality of the model is evaluated on the basis of load−displacement relationships as well as damage progression.
Tests on Polymer Modified Cement Concrete (PCC) have shown significant large creep deformation. The reasons for that as well as additional material phenomena are explained in the following paper. Existing creep models developed for standard concrete are studied to determine the time-dependent deformations of PCC. These models are: model B3 by Bažant and Bajewa, the models according to Model Code 90 and ACI 209 as well as model GL2000 by Gardner and Lockman. The calculated creep strains are compared to existing experimental data of PCC and the differences are pointed out. Furthermore, an optimization of the model parameters is performed to fit the models to the experimental data to achieve a better model prognosis.