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In spite of the extensive research in dynamic soil-structure interaction (SSI), there still exist miscon-ceptions concerning the role of SSI in the seismic performance of structures, especially the ones founded on soft soil. This is due to the fact that current analytical SSI models that are used to evaluate the influence of soil on the overall structural behavior are approximate models and may involve creeds and practices that are not always precise. This is especially true in the codified approaches which in-clude substantial approximations to provide simple frameworks for the design. As the direct numerical analysis requires a high computational effort, performing an analysis considering SSI is computationally uneconomical for regular design applications. This paper outlines the set up some milestones for evaluating SSI models. This will be achieved by investigating the different assumptions and involved factors, as well as varying the configurations of R/C moment-resisting frame structures supported by single footings which are subject to seismic excita-tions. It is noted that the scope of this paper is to highlight, rather than fully resolve, the above subject. A rough draft of the proposed approach is presented in this paper, whereas a thorough illustration will be carried out throughout the presentation in the course of the conference.
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.
Reinforced concrete walls are commonly selected as the lateral resisting systems in seismic design of buildings. The design procedure requires reliable/robust models to predict the wall response. Many researchers, thus, have focused on using the available experimental data to be able to comment on the quality of models at hand. What is missing though is an uncertain attitude towards the experimental data since such data can be affected by different sources of uncertainty. In this paper, we introduce the database created for model quality evaluation purposes considering the uncertainties in the experimental data. This is the first step of a larger study on experience-based model quality evaluation of reinforced concrete walls. Here, we briefly present the database as well as six sample validations of the developed numerical model (the quality of which is to be assessed). The database contains the information on nearly 300 wall specimens from about 50 sources. Both the database and the numerical model, built for uncertainty/sensitivity analysis purposes, are mainly based on ten parameters. These include geometry, material, reinforcement layout and loading properties. The validation results prove that the model is able to predict the wall response satisfactorily. Consequently, the validated numerical model could be used in further quality evaluation studies.
The process of analysis and design in structural engineering requires the consideration of different partial models, for example loading, structural materials, structural elements, and analysis types. The various partial models are combined by coupling several of their components. Due to the large number of available partial models describing similar phenomena, many different model combinations are possible to simulate the same aspects of a structure. The challenging task of an engineer is to select a model combination that ensures a sufficient, reliable prognosis. In order to achieve this reliable prognosis of the overall structural behavior, a high individual quality of the partial models and an adequate coupling of the partial models is required. Several methodologies have been proposed to evaluate the quality of partial models for their intended application, but a detailed study of the coupling quality is still lacking. This paper proposes a new approach to assess the coupling quality of partial models in a quantitative manner. The approach is based on the consistency of the coupled data and applies for uni- and bidirectional coupled partial models. Furthermore, the influence of the coupling quality on the output quantities of the partial models is considered. The functionality of the algorithm and the effect of the coupling quality are demonstrated using an example of coupled partial models in structural engineering.
Methods for model quality assessment are aiming to find the most appropriate model with respect to accuracy and computational effort for a structural system under investigation. Model error estimation techniques can be applied for this purpose when kinematical models are investigated. They are counted among the class of white box models, which means that the model hierarchy and therewith the best model is known. This thesis gives an overview of discretisation error estimators. Deduced from these, methods for model error estimation are presented. Their general goal is to make a prediction of the inaccuracies that are introduced using the simpler model without knowing the solution of a more complex model. This information can be used to steer an adaptive process. Techniques for linear and non-linear problems as well as global and goal-oriented errors are introduced. The estimation of the error in local quantities is realised by solving a dual problem, which serves as a weight for the primal error. So far, such techniques have mainly been applied in
material modelling and for dimensional adaptivity. Within the scope of this thesis, available model error estimators are adapted for an application to kinematical models. Their applicability is tested regarding the question of whether a geometrical non-linear calculation is necessary or not. The analysis is limited to non-linear estimators due to the structure of the underlying differential equations. These methods often involve simplification, e.g linearisations. It is investigated to which extent such assumptions lead to meaningful results, when applied to kinematical models.
Known as a sophisticated phenomenon in civil engineering problems, soil structure interaction has been under deep investigations in the field of Geotechnics. On the other hand, advent of powerful computers has led to development of numerous numerical methods to deal with this phenomenon, resulting in a wide variety of methods trying to simulate the behavior of the soil stratum. This survey studies two common approaches to model the soil’s behavior in a system consisting of a structure with two degrees of freedom, representing a two-storey frame structure made of steel, with the column resting on a pile embedded into sand in laboratory scale. The effect of soil simulation technique on the dynamic behavior of the structure is of major interest in the study. Utilized modeling approaches are the so-called Holistic method, and substitution of soil with respective impedance functions.
Building information modeling offers a huge potential for increasing the productivity and quality of construction planning processes. Despite its promising concept, this approach has not found widespread use. One of the reasons is the insufficient coupling of the structural models with the general building model. Instead, structural engineers usually set up a structural model that is independent from the building model and consists of mechanical models of reduced dimension. An automatic model generation, which would be valuable in case of model revisions is therefore not possible. This can be overcome by a volumetric formulation of the problem. A recent approach employed the p-version of the finite element method to this problem. This method, in conjunction with a volumetric formulation is suited to simulate the structural behaviour of both „thick“ solid bodies and thin-walled structures. However, there remains a notable discretization error in the numerical models. This paper therefore proposes a new approach for overcoming this situation. It sugggests the combination of the Isogeometric analysis together with the volumetric models in order to integrate the structural design into the digital, building model-centered planning process and reduce the discretization error. The concept of the isogeometric analysis consists, roughly, in the application of NURBS functions to represent the geometry and the shape functions of the elements. These functions possess some beneficial properties regarding numerical simulation. Their use, however, leads to some intricacies related to the setup of the stiffness matrix. This paper describes some of these properties.
The application of partly decoupled approach by means of continuum mechanics facilitates the calculation of structural responses due to welding. The numerical results demonstrate the ability of a qualitative prediction of welded connections. As it is intended to integrate the local effects of a joint in structural analysis of steel constructions, it is necessary to meet higher approaches towards quality. The wide array of material parameters are presented, which are affecting the thermal, metallurgical and mechanical behavior, and which have to be identified. For that purpose further investigations are necessary to analyze the sensitivity of the models towards different material properties. The experimental determination of every material parameter is not possible due to the extraordinary laborious efforts needed. Besides that, experimentally identified parameters can be applied only for the tested steel quality for measured temperature-time regimes. For that reason alternative approaches for identification of material parameters, such as optimization strategies, have to be applied. After a definition of material parameters a quantitative prediction of welded connections will also be possible. Numerical results show the effect of phase transformation, activated by welding process, on residual stress state. As these phenomena occur in local areas in the range of crystal and grain sizes, the description of microscopic phenomena and their propagation on a macroscopic level due to approaches of homogenization might be expedient. Nevertheless, one should bear in mind, the increasing number of material parameters as well as the complexity of their experimental determination. Thus the microscopic approach should always be investigated under the scope of ability and efficiency of a required prediction. Under certain circumstances a step backwards, adopting a phenomenological approach, also can be beneficial.
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.
The evident advances of the computational power of the digital computers enable the modeling of the total system of structures. Such modeling demands compatible representations of the couplings of different structural subsystems. Therefore, models of dynamic interaction between the vehicle and the bridge and models of a bridge bearing, a coupling element between the bridge's superstructure and substructure, are of interest and discussed within this paper. The vehicle-bridge interaction may be described as a function connecting two sets of behavior. In this case, the coupling is embodied by mutual parameters that affect both systems, such as the frequency content of the bridge and the vehicle. Whereas the bridge bearings are elements used specifically to couple, in such elements the deformation and the transferred loads are used in characterizing the coupling The nature of these couplings and their influence on the bridge response is different. However, the need to assess the amount of dynamic response transferred by or within these couplings is a common argument.
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.
Long-span cable supported bridges are prone to aerodynamic instabilities caused by wind and this phenomenon is usually a major design criterion. If the wind speed exceeds the critical flutter speed of the bridge, this constitutes an Ultimate Limit State. The prediction of the flutter boundary therefore requires accurate and robust models. This paper aims at studying various combinations of models to predict the flutter phenomenon.
Since flutter is a coupling of aerodynamic forcing with a structural dynamics problem, different types and classes of models can be combined to study the interaction. Here, both numerical approaches and analytical models are utilised and coupled in different ways to assess the prediction quality of the hybrid model. Models for aerodynamic forces employed are the analytical Theodorsen expressions for the motion-enduced aerodynamic forces of a flat plate and Scanlan derivatives as a Meta model. Further, Computational Fluid Dynamics (CFD) simulations using the Vortex Particle Method (VPM) were used to cover numerical models.
The structural representations were dimensionally reduced to two degree of freedom section models calibrated from global models as well as a fully three-dimensional Finite Element (FE) model. A two degree of freedom system was analysed analytically as well as numerically.
Generally, all models were able to predict the flutter phenomenon and relatively close agreement was found for the particular bridge. In conclusion, the model choice for a given practical analysis scenario will be discussed in the context of the analysis findings.
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.
Nonlinear analyses are characterised by approximations of the fundamental equations in different quality. Starting with a general description of nonlinear finite element formulation the fundamental equations are derived for plane truss elements. Special emphasis is placed on the determination of internal and external system energy as well as influence of different quality approaches for the displacement-strain relationship on solution quality. To simplify the solution procedure the nonlinear function describing the kinematics is expanded into a Taylor series and truncated after the n-th series term. The different kinematics influence speed of convergence as well as exactness of solution. On a simple truss structure this influence is shown. To assess the quality of different formulations concerning the nonlinear kinematic equation three approaches are discussed. First the overall internal and external energy is compared for different kinematical models. In a second step the energy content related to single terms describing displacement-strain relationship is investigated and used for quality control following two different paths. Based on single ε-terms an adaptive scheme is used to change the kinematical model depending on increasing nonlinearity of the structure. The solution quality has turned out satisfactory compared to the exact result. More detailed investigations are necessary to find criteria for the threshold values for the iterative process as well as for decision on number and step size of incremental load steps.
The present research analyses the error on prediction obtained under different data availability scenarios to determine which measurements contribute to an improvement of model prognosis and which not. A fully coupled 2D hydromechanical 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 ranked by scaled sensitivities, Particle Swarm Optimization is applied to determine the optimal parameter values and model validation is performed to determine the magnitude of error forecast. We compare the predictions of the optimized models with results from a forward run of the reference model to obtain actual prediction errors.
The analyses presented here were performed to 31 data sets of 100 observations of varying data types. Calibrating with multiple information types instead of only one sort, brings better calibration results and improvement in model prognosis. However, when using several types of information the number of observations have to be increased to be able to cover a representative part of the model domain; otherwise a compromise between data availability and domain
coverage prove best. Which type of information for calibration contributes to the best prognoses, could not be determined in advance. For the error in model prognosis does not depends on the error in calibration, but on the parameter error, which unfortunately can not be determined in reality since we do not know its real value. Excellent calibration fits with parameters’ values near the limits of reasonable physical values, provided the highest prognosis errors. While models which included excess pore pressure values for calibration provided the best prognosis, independent of the calibration fit.
Polymer-modified cement concrete (PCC) is a heterogeneous building material with a hierarchically organized microstructure. Therefore, continuum micromechanics-based multiscale models represent a promising method to estimate the mechanical properties. By means of a bottom-up approach, homogenized properties at the macroscopic scale are derived considering microstructural characteristics. The extension of existing multiscale models for the application to PCC is the main objective of this work. For that, cross-scale experimental studies are required. Both macroscopic and microscopic mechanical tests are performed to characterize the elastic and viscoelastic properties of different PCC. The comparison between experiment and model prediction illustrates the success of the modeling approach.
By the use of numerical methods and the rapid development of computer technology in the recent years, a large variety, complexity, refinement and capability of partial models have been achieved. This can be noticed in the evaluation of the reliability of structures, e.g. the increased use of spatial structural systems. For the different fields of civil engineering, well developed partial models already exist. Because these partial models are most often used separately, the general view is not entirely illustrated. Until now, there has been no common methodology for evaluating the efficiency of models; the trust in the prediction of a special engineering model has generally relied on the engineer’s experience. In this paper the basics of evaluation of simple models and coupled partial models of frame structures will be discussed using sustainable numerical methods. Furthermore, quality classes (levels) of design tasks will be defined based on their practical relevance. In addition, analysis methods will be systemized. After analysis of different published assessment methods, it may be noted, that the Efficiency Indicator Method (EWM) is most suitable for the observed evaluation problem. Therefore, the EWM was modified to the Model Efficiency Analysis (MEA) for the purpose of a holistic evaluation. The criteria are characterized by two groups, benefit and expenditure, and it is possible by calculating the quotient (benefit/expenditure) to make a statement about the efficiency of the observed models. Presently, the expenditure value is not a subject of investigation, and so the model efficiency is calculated only by the benefit value. This paper also contains the associated criteria catalog, different normalization methods, as well as weighting possibilities.
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.
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.
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.