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Different types of data provide different type of information. The present research analyzes the error on prediction obtained under different data type availability for calibration. The contribution of different measurement types to model calibration and prognosis are evaluated. A coupled 2D hydro-mechanical model of a water retaining dam is taken as an example. Here, the mean effective stress in the porous skeleton is reduced due to an increase in pore water pressure under drawdown conditions. Relevant model parameters are identified by scaled sensitivities. Then, Particle Swarm Optimization is applied to determine the optimal parameter values and finally, the error in prognosis is determined. We compare the predictions of the optimized models with results from a forward run of the reference model to obtain the actual prediction errors. The analyses presented here were performed calibrating the hydro-mechanical model to 31 data sets of 100 observations of varying data types. The prognosis results improve when using diversified information for calibration. However, when using several types of information, the number of observations has to be increased to be able to cover a representative part of the model domain. For an analysis with constant number of observations, a compromise between data type availability and domain coverage proves to be the best solution. Which type of calibration information contributes to the best prognoses could not be determined in advance. The error in model prognosis does not depend on the error in calibration, but on the parameter error, which unfortunately cannot be determined in inverse problems since we do not know its real value. The best prognoses were obtained independent of calibration fit. However, excellent calibration fits led to an increase in prognosis error variation. In the case of excellent fits; parameters' values came near the limits of reasonable physical values more often. To improve the prognoses reliability, the expected value of the parameters should be considered as prior information on the optimization algorithm.

The analysis of the response of complex structural systems requires the description of the material constitutive relations by means of an appropriate material model. The level of abstraction of such model may strongly affect the quality of the prognosis of the whole structure. In context to this fact, it is necessary to describe the material in a convenient sense as exact but as simple as possible. All material phenomena of crystalline materials e.g. steel, affecting the behavior of the structure, rely on physical effects which are interacting over spatial scales from subatomic to macroscopic range. Nevertheless, if the material is microscopically heterogenic, it might be appropriate to use phenomenological models for the purpose of civil engineering. Although constantly applied, these models are insufficient for steel materials with microscopic characteristics such as texture, typically occurring in hot rolled steel members or heat affected zones of welded joints. Hence, texture is manifested in crystalline materials as a regular crystallographic structure and crystallite orientation, influencing macroscopic material properties. The analysis of structural response of material with texture (e.g. rolled steel or heat affected zone of a welded joint) obliges the extension of the phenomenological material description of macroscopic scale by means of microscopic information. This paper introduces an enrichment approach for material models based on a hierarchical multiscale methodology. This has been done by describing the grain texture on a mesoscopic scale and coupling it with macroscopic constitutive relations by means of homogenization. Due to a variety of available homogenization methods, the question of an assessment of coupling quality arises. The applicability of the method and the effect of the coupling method on the reliability of the response are presented on an example.

The aim of this study is to show an application of model robustness measures for soilstructure interaction (henceforth written as SSI) models. Model robustness defines a measure for the ability of a model to provide useful model answers for input parameters which typically have a wide range in geotechnical engineering. The calculation of SSI is a major problem in geotechnical engineering. Several different models exist for the estimation of SSI. These can be separated into analytical, semi-analytical and numerical methods. This paper focuses on the numerical models of SSI specific macro-element type models and more advanced finite element method models using contact description as continuum or interface elements. A brief description of the models used is given in the paper. Following this description, the applied SSI problem is introduced. The observed event is a static loaded shallow foundation with an inclined load. The different partial models to consider the SSI effects are assessed using different robustness measures during numerical application. The paper shows the investigation of the capability to use these measures for the assessment of the model quality of SSI partial models. A variance based robustness and a mathematical robustness approaches are applied. These different robustness measures are used in a framework which allows also the investigation of computational time consuming models. Finally the result shows that the concept of using robustness approaches combined with other model–quality indicators (e.g. model sensitivity or model reliability) can lead to unique model–quality assessment for SSI models.

The topic of structural robustness is covered extensively in current literature in structural engineering. A few evaluation methods already exist. Since these methods are based on different evaluation approaches, the comparison is difficult. But all the approaches have one in common, they need a structural model which represents the structure to be evaluated. As the structural model is the basis of the robustness evaluation, there is the question if the quality of the chosen structural model is influencing the estimation of the structural robustness index. This paper shows what robustness in structural engineering means and gives an overview of existing assessment methods. One is the reliability based robustness index, which uses the reliability indices of a intact and a damaged structure. The second one is the risk based robustness index, which estimates the structural robustness by the usage of direct and indirect risk. The paper describes how these approaches for the evaluation of structural robustness works and which parameters will be used. Since both approaches needs a structural model for the estimation of the structural behavior and the probability of failure, it is necessary to think about the quality of the chosen structural model. Nevertheless, the chosen model has to represent the structure, the input factors and reflect the damages which occur. On the example of two different model qualities, it will be shown, that the model choice is really influencing the quality of the robustness index.

A numerical analysis of the mode of deformation of the main load-bearing components of a typical frame sloping shaft headgear was performed. The analysis was done by a design model consisting of plane and solid finite elements, which were modeled in the program «LIRA». Due to the numerical results, the regularities of local stress distribution under a guide pulley bearing were revealed and parameters of a plane stress under both emergency and normal working loads were determined. In the numerical simulation, the guidelines to improve the construction of the joints of guide pulleys resting on sub-pulley frame-type structures were established. Overall, the results obtained are the basis for improving the engineering procedures of designing steel structures of shaft sloping headgear.

This paper presents a methodology for uncertainty quantification in cyclic creep analysis. Several models- , namely BP model, Whaley and Neville model, modified MC90 for cyclic loading and modified Hyperbolic function for cyclic loading are used for uncertainty quantification. Three types of uncertainty are included in Uncertainty Quantification (UQ): (i) natural variability in loading and materials properties; (ii) data uncertainty due to measurement errors; and (iii) modelling uncertainty and errors during cyclic creep analysis. Due to the consideration of all type of uncertainties, a measure for the total variation of the model response is achieved. The study finds that the BP, modified Hyperbolic and modified MC90 are best performing models for cyclic creep prediction in that order. Further, global Sensitivity Analysis (SA) considering the uncorrelated and correlated parameters is used to quantify the contribution of each source of uncertainty to the overall prediction uncertainty and to identifying the important parameters. The error in determining the input quantities and model itself can produce significant changes in creep prediction values. The variability influence of input random quantities on the cyclic creep was studied by means of the stochastic uncertainty and sensitivity analysis namely the Gartner et al. method and Saltelli et al. method. All input imperfections were considered to be random quantities. The Latin Hypercube Sampling (LHS) numerical simulation method (Monte Carlo type method) was used. It has been found by the stochastic sensitivity analysis that the cyclic creep deformation variability is most sensitive to the Elastic modulus of concrete, compressive strength, mean stress, cyclic stress amplitude, number of cycle, in that order.

Civil engineers take advantage of models to design reliable structures. In order to fulfill the design goal with a certain amount of confidence, the utilized models should be able to predict the probable structural behavior under the expected loading schemes. Therefore, a major challenge is to find models which provide less uncertain and more robust responses. The problem gets even twofold when the model to be studied is a global model comprised of different interacting partial models. This study aims at model quality evaluation of global models with a focus on frame-wall systems as the case study. The paper, presents the results of the first step taken toward accomplishing this goal. To start the model quality evaluation of the global frame-wall system, the main element (i.e. the wall) was studied through nonlinear static and dynamic analysis using two different modeling approaches. The two selected models included the fiber section model and the Multiple-Vertical-Line-Element-Model (MVLEM). The influence of the wall aspect ratio (H=L) and the axial load on the response of the models was studied. The results from nonlinear static and dynamic analysis of both models are presented and compared. The models resulted in quite different responses in the range of low aspect ratio walls under large axial loads due to different contribution of the shear deformations to the top displacement. In the studied cases, the results implied that careful attention should be paid to the model quality evaluation of the wall models specifically when they are supposed to be coupled to other partial models such as a moment frame or a soil-footing substructure which their response is sensitive to shear deformations. In this case, even a high quality wall model would not result in a high quality coupled system since it fails to interact properly with the rest of the system.

This paper is focused on the first numerical tests for coupling between analytical solution and finite element method on the example of one problem of fracture mechanics. The calculations were done according to ideas proposed in [1]. The analytical solutions are constructed by using an orthogonal basis of holomorphic and anti-holomorphic functions. For coupling with finite element method the special elements are constructed by using the trigonometric interpolation theorem.

Many structures in different engineering applications suffer from cracking. In order to make reliable prognosis about the serviceability of those structures it is of utmost importance to identify cracks as precisely as possible by non-destructive testing. A novel approach (XIGA), which combines the Isogeometric Analysis (IGA) and the Extended Finite Element Method (XFEM) is used for the forward problem, namely the analysis of a cracked material, see [1]. Applying the NURBS (Non-Uniform Rational B-Spline) based approach from IGA together with the XFEM allows to describe effectively arbitrarily shaped cracks and avoids the necessity of remeshing during the crack identification problem. We want to exploit these advantages for the inverse problem of detecting existing cracks by non-destructive testing, see e.g. [2]. The quality of the reconstructed cracks however depends on two major issues, namely the quality of the measured data (measurement error) and the discretization of the crack model. The first one will be taken into account by applying regularizing methods with a posteriori stopping criteria. The second one is critical in the sense that too few degrees of freedom, i.e. the number of control points of the NURBS, do not allow for a precise description of the crack. An increased number of control points, however, increases the number of unknowns in the inverse analysis and intensifies the ill-posedness. The trade-off between accuracy and stability is aimed to be found by applying an inverse multilevel algorithm [3, 4] where the identification is started with short knot vectors which successively will be enlarged during the identification process.

THE INFLUENCE OF THE LOCAL CONCAVITY ON THE FUNCTIONING OF BEARING SHELL OF HIGH-RISE CONSTRUCTION
(2012)

Areas with various defects and damages, which reduce carrying capacity, were examined in a study of metal chimneys. In this work, the influence of the local dimples on the function of metal chimneys was considered. Modeling tasks were completed in the software packages LIRA and ANSYS. Parameters were identified, which characterize the local dimples, and a numerical study of the influence of local dimples on the stress-strain state of shells of metal chimneys was conducted. A distribution field of circular and meridional tension was analyzed in a researched area. Zones of influence of dimples on the bearing cover of metal chimneys were investigated. The bearing capacities of high-rise structures with various dimple geometries and various cover parameters were determined with respect to specified areas of the trunk. Dependent relationships are represented graphically for the decrease in bearing capacity of a cover with respect to dimples. Diameter and thickness of covers of metal chimneys were constructed according to the resulting data.