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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.
From the design experiences of arch dams in the past, it has significant practical value to carry out the shape optimization of arch dams, which can fully make use of material characteristics and reduce the cost of constructions. Suitable variables need to be chosen to formulate the objective function, e.g. to minimize the total volume of the arch dam. Additionally a series of constraints are derived and a reasonable and convenient penalty function has been formed, which can easily enforce the characteristics of constraints and optimal design. For the optimization method, a Genetic Algorithm is adopted to perform a global search. Simultaneously, ANSYS is used to do the mechanical analysis under the coupling of thermal and hydraulic loads. One of the constraints of the newly designed dam is to fulfill requirements on the structural safety. Therefore, a reliability analysis is applied to offer a good decision supporting for matters concerning predictions of both safety and service life of the arch dam. By this, the key factors which would influence the stability and safety of arch dam significantly can be acquired, and supply a good way to take preventive measures to prolong ate the service life of an arch dam and enhances the safety of structure.
The paper introduces a systematic construction management approach, supporting expansion of a specified construction process, both automatically and semi-automatically. Throughout the whole design process, many requirements must be taken into account in order to fulfil demands defined by clients. In implementing those demands into a design concept up to the execution plan, constraints such as site conditions, building code, and legal framework are to be considered. However, complete information, which is needed to make a sound decision, is not yet acquired in the early phase. Decisions are traditionally taken based on experience and assumptions. Due to a vast number of appropriate available solutions, particularly in building projects, it is necessary to make those decisions traceable. This is important in order to be able to reconstruct considerations and assumptions taken, should there be any changes in the future project’s objectives. The research will be carried out by means of building information modelling, where rules deriving from standard logics of construction management knowledge will be applied. The knowledge comprises a comprehensive interaction amongst bidding process, cost-estimation, construction site preparation as well as specific project logistics – which are usually still separately considered. By means of these rules, favourable decision taking regarding prefabrication and in-situ implementation can be justified. Modifications depending on the available information within current design stage will consistently be traceable.
In this paper experimental studies and numerical analysis carried out on reinforced concrete beam are partially reported. They aimed to apply the rigid finite element method to calculations for reinforced concrete beams using discrete crack model. Hence rotational ductility resulting from crack occurrence had to be determined. A relationship for calculating it in static equilibrium was proposed. Laboratory experiments proved that dynamic ductility is considerably smaller. Therefore scaling of the empirical parameter was carried out. Consequently a formula for its value depending on reinforcement ratio was obtained.
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.
In construction engineering, a schedule’s input data, which is usually not exactly known in the planning phase, is considered deterministic when generating the schedule. As a result, construction schedules become unreliable and deadlines are often not met. While the optimization of construction schedules with respect to costs and makespan has been a matter of research in the past decades, the optimization of the robustness of construction schedules has received little attention. In this paper, the effects of uncertainties inherent to the input data of construction schedules are discussed. Possibilities are investigated to improve the reliability of construction schedules by considering alternative processes for certain tasks and by identifying the combination of processes generating the most robust schedule with respect to the makespan of a construction project.
We investigate aspects of tram-network section reliability, which operates as a part of the model of whole city tram-network reliability. Here, one of the main points of interest is the character of the chronological development of the disturbances (namely the differences between time of departure provided in schedule and real time of departure) on subsequent sections during tram line operation. These developments were observed in comprehensive measurements done in Krakow, during one of the main transportation nodes (Rondo Mogilskie) rebuilding. All taken building activities cause big disturbances in tram lines operation with effects extended to neighboring sections. In a second part, the stochastic character of section running time will be analyzed more detailed. There will be taken into consideration sections with only one beginning stop and also with two or three beginning stops located at different streets at an intersection. Possibility of adding results from sections with two beginning stops to one set will be checked with suitable statistical tests which are used to compare the means of the two samples. Section running time may depend on the value of gap between two following trams and from the value of deviation from schedule. This dependence will be described by a multi regression formula. The main measurements were done in the city center of Krakow in two stages: before and after big changes in tramway infrastructure.
The theory of regular quaternionic functions of a reduced quaternionic variable is a 3-dimensional generalization of complex analysis. The Moisil-Theodorescu system (MTS) is a regularity condition for such functions depending on the radius vector r = ix+jy+kz seen as a reduced quaternionic variable. The analogues of the main theorems of complex analysis for the MTS in quaternion forms are established: Cauchy, Cauchy integral formula, Taylor and Laurent series, approximation theorems and Cauchy type integral properties. The analogues of positive powers (inner spherical monogenics) are investigated: the set of recurrence formulas between the inner spherical monogenics and the explicit formulas are established. Some applications of the regular function in the elasticity theory and hydrodynamics are given.
Due to increasing numbers of wind energy converters, the accurate assessment of the lifespan of their structural parts and the entire converter system is becoming more and more paramount. Lifespan-oriented design, inspections and remedial maintenance are challenging because of their complex dynamic behavior. Wind energy converters are subjected to stochastic turbulent wind loading causing corresponding stochastic structural response and vibrations associated with an extreme number of stress cycles (up to 109 according to the rotation of the blades). Currently, wind energy converters are constructed for a service life of about 20 years. However, this estimation is more or less made by rule of thumb and not backed by profound scientific analyses or accurate simulations. By contrast, modern structural health monitoring systems allow an improved identification of deteriorations and, thereupon, to drastically advance the lifespan assessment of wind energy converters. In particular, monitoring systems based on artificial intelligence techniques represent a promising approach towards cost-efficient and reliable real-time monitoring. Therefore, an innovative real-time structural health monitoring concept based on software agents is introduced in this contribution. For a short time, this concept is also turned into a real-world monitoring system developed in a DFG joint research project in the authors’ institute at the Ruhr-University Bochum. In this paper, primarily the agent-based development, implementation and application of the monitoring system is addressed, focusing on the real-time monitoring tasks in the deserved detail.
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.
Quality is one of the most important properties of a product. Providing the optimal quality can reduce costs for rework, scrap, recall or even legal actions while satisfying customers demand for reliability. The aim is to achieve ``built-in'' quality within product development process (PDP). The common approach therefore is the robust design optimization (RDO). It uses stochastic values as constraint and/or objective to obtain a robust and reliable optimal design. In classical approaches the effort required for stochastic analysis multiplies with the complexity of the optimization algorithm. The suggested approach shows that it is possible to reduce this effort enormously by using previously obtained data. Therefore the support point set of an underlying metamodel is filled iteratively during ongoing optimization in regions of interest if this is necessary. In a simple example, it will be shown that this is possible without significant loss of accuracy.
Over the last decade, the technology of constructing buildings has been dramatically developed especially with the huge growth of CAD tools that help in modeling buildings, bridges, roads and other construction objects. Often quality control and size accuracy in the factory or on construction site are based on manual measurements of discrete points. These measured points of the realized object or a part of it will be compared with the points of the corresponding CAD model to see whether and where the construction element fits into the respective CAD model. This process is very complicated and difficult even when using modern measuring technology. This is due to the complicated shape of the components, the large amount of manually detected measured data and the high cost of manual processing of measured values. However, by using a modern 3D scanner one gets information of the whole constructed object and one can make a complete comparison against the CAD model. It gives an idea about quality of objects on the whole. In this paper, we present a case study of controlling the quality of measurement during the constructing phase of a steel bridge by using 3D point cloud technology. Preliminary results show that an early detection of mismatching between real element and CAD model could save a lot of time, efforts and obviously expenses.
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.
One of the most promising and recent advances in computer-based planning is the transition from classical geometric modeling to building information modeling (BIM). Building information models support the representation, storage, and exchange of various information relevant to construction planning. This information can be used for describing, e.g., geometric/physical properties or costs of a building, for creating construction schedules, or for representing other characteristics of construction projects. Based on this information, plans and specifications as well as reports and presentations of a planned building can be created automatically. A fundamental principle of BIM is object parameterization, which allows specifying geometrical, numerical, algebraic and associative dependencies between objects contained in a building information model. In this paper, existing challenges of parametric modeling using the Industry Foundation Classes (IFC) as a federated model for integrated planning are shown, and open research questions are discussed.
PARAMETER IDENTIFICATION OF MESOSCALE MODELS FROM MACROSCOPIC TESTS USING BAYESIAN NEURAL NETWORKS
(2010)
In this paper, a parameter identification procedure using Bayesian neural networks is proposed. Based on a training set of numerical simulations, where the material parameters are simulated in a predefined range using Latin Hypercube sampling, a Bayesian neural network, which has been extended to describe the noise of multiple outputs using a full covariance matrix, is trained to approximate the inverse relation from the experiment (displacements, forces etc.) to the material parameters. The method offers not only the possibility to determine the parameters itself, but also the accuracy of the estimate and the correlation between these parameters. As a result, a set of experiments can be designed to calibrate a numerical model.
This study contributes to the identification of coupled THM constitutive model parameters via back analysis against information-rich experiments. A sampling based back analysis approach is proposed comprising both the model parameter identification and the assessment of the reliability of identified model parameters. The results obtained in the context of buffer elements indicate that sensitive parameter estimates generally obey the normal distribution. According to the sensitivity of the parameters and the probability distribution of the samples we can provide confidence intervals for the estimated parameters and thus allow a qualitative estimation on the identified parameters which are in future work used as inputs for prognosis computations of buffer elements. These elements play e.g. an important role in the design of nuclear waste repositories.
It is well known that complex quaternion analysis plays an important role in the study of higher order boundary value problems of mathematical physics. Following the ideas given for real quaternion analysis, the paper deals with certain orthogonal decompositions of the complex quaternion Hilbert space into its subspaces of null solutions of Dirac type operator with an arbitrary complex potential. We then apply them to consider related boundary value problems, and to prove the existence and uniqueness as well as the explicit representation formulae of the underlying solutions.
Steel structural design is an integral part of the building construction process. So far, various methods of design have been applied in practice to satisfy the design requirements. This paper attempts to acquire the Differential Evolution Algorithms in automatization of specific synthesis and rationalization of design process. The capacity of the Differential Evolution Algorithms to deal with continuous and/or discrete optimization of steel structures is also demonstrated. The goal of this study is to propose an optimal design of steel frame structures using built-up I-sections and/or a combination of standard hot-rolled profiles. All optimized steel frame structures in this paper generated optimization solutions better than the original solution designed by the manufacturer. Taking the criteria regarding the quality and efficiency of the practical design into consideration, the produced optimal design with the Differential Evolution Algorithms can completely replace conventional design because of its excellent performance.
The sizing of simple resonators like guitar strings or laser mirrors is directly connected to the wavelength and represents no complex optimisation problem. This is not the case with liquid-filled acoustic resonators of non-trivial geometries, where several masses and stiffnesses of the structure and the fluid have to fit together. This creates a scenario of many competing and interacting resonances varying in relative strength and frequency when design parameters change. Hence, the resonator design involves a parameter-tuning problem with many local optima. As its solution evolutionary algorithms (EA) coupled to a forced-harmonic FE simulation are presented. A new hybrid EA is proposed and compared to two state-of-theart EAs based on selected test problems. The motivating background is the search for better resonators suitable for sonofusion experiments where extreme states of matter are sought in collapsing cavitation bubbles.