TY - THES A1 - Fröbel, Toni T1 - Data coupled civil engineering applications: Modeling and quality assessment methods T1 - Datenkopplung für Anwendungen im Bauingenieurwesen: Methoden zur Modellierung und Qualitätsbewertung N2 - The planning process in civil engineering is highly complex and not manageable in its entirety. The state of the art decomposes complex tasks into smaller, manageable sub-tasks. Due to the close interrelatedness of the sub-tasks, it is essential to couple them. However, from a software engineering point of view, this is quite challenging to do because of the numerous incompatible software applications on the market. This study is concerned with two main objectives: The first is the generic formulation of coupling strategies in order to support engineers in the implementation and selection of adequate coupling strategies. This has been achieved by the use of a coupling pattern language combined with a four-layered, metamodel architecture, whose applicability has been performed on a real coupling scenario. The second one is the quality assessment of coupled software. This has been developed based on the evaluated schema mapping. This approach has been described using mathematical expressions derived from the set theory and graph theory by taking the various mapping patterns into account. Moreover, the coupling quality has been evaluated within the formalization process by considering the uncertainties that arise during mapping and has resulted in global quality values, which can be used by the user to assess the exchange. Finally, the applicability of the proposed approach has been shown using an engineering case study. N2 - Der Planungsprozess im Bauwesen ist hochkomplex und daher in seiner Gesamtheit nicht zu erfassen. Deshalb wird dieser in kleinere und beherrschbarere Teilaufgaben zerlegt. Auf Grund ihrer starken Wechselwirkungen ist deren Kopplung unabdingbar. Aus Sicht der Informatik wird dies jedoch durch eine große Anzahl inkompatibler Softwareanwendungen erschwert. Die Arbeit beschäftigt sich daher mit zwei wesentlichen Aufgabenfeldern im Bereich der Softwarekopplung. Als erstes werden Kopplungskonzepte unabhängig von spezifischen Hardware- oder Softwareeigenschaften beschrieben, um den Ingenieur bei der Durchführung und Auswahl von entsprechenden Kopplungsstrategien zu unterstützen. Dies wird durch eine Kopplungs-Mustersprache in Verbindung mit einer Meta-Modell-Architektur erreicht. Seine Anwendbarkeit wird an einem Kopplungsszenario gezeigt. Das zweite Aufgabenfeld beschäftigt sich mit der Qualität von gekoppelten Softwaresystemen. Eine Qualitätsbewertung erfolgt hierbei auf Basis von bewertetem Schema-Mapping. Der Ansatz ist auf Grundlage der Mengen- und Graphentheorie mathematisch beschrieben. Er berücksichtigt die gängigen Mapping-Muster und Unsicherheiten, die während des Mappingprozesses auftreten können. Der Bewertungsprozess liefert einen globalen Qualitätswert, der vom Ingenieur direkt verwendet werden kann, um den Austausch zu bewerten. Die Anwendbarkeit wird an einem Beispiel gezeigt. T3 - Schriftenreihe des DFG Graduiertenkollegs 1462 Modellqualitäten // Graduiertenkolleg Modellqualitäten - 6 KW - Data exchange, Schema mapping, Quality assessment, Uncertainty, Coupling, BIM, Design patterns, Metamodel architecture KW - Data exchange, Schema mapping, Quality assessment, Uncertainty, Coupling, BIM, Design patterns, Metamodel architecture Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20130128-18366 SN - 978-3-86068-486-3 PB - Verlag der Bauhaus-Universität Weimar 2013 CY - Weimar ER - TY - JOUR A1 - Aguinaga, José Guillermo De T1 - Error in prediction due to data type availability in a coupled hydro-mechanical model JF - Electronic Journal of Geotechnical Engineering N2 - 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. KW - Sensitivitätsanalyse KW - Damm KW - Embankment, sensitivity analysis, parameter identification, Particle Swarm Optimization KW - Fehlerabschätzung Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170413-31170 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84868020397&partnerID=40&md5=72c87bb112839303c1ef9a4afa8c6421 SP - 2459 EP - 2471 ER - TY - JOUR A1 - Motra, Hem Bahadur A1 - Hildebrand, Jörg A1 - Dimmig-Osburg, Andrea T1 - Assessment of strain measurement techniques to characterise mechanical properties of structural steel JF - Engineering Science and Technology, an International Journal N2 - Strain measurement is important in mechanical testing. A wide variety of techniques exists for measuring strain in the tensile test; namely the strain gauge, extensometer, stress and strain determined by machine crosshead motion, Geometric Moire technique, optical strain measurement techniques and others. Each technique has its own advantages and disadvantages. The purpose of this study is to quantitatively compare the strain measurement techniques. To carry out the tensile test experiments for S 235, sixty samples were cut from the web of the I-profile in longitudinal and transverse directions in four different dimensions. The geometry of samples are analysed by 3D scanner and vernier caliper. In addition, the strain values were determined by using strain gauge, extensometer and machine crosshead motion. Three techniques of strain measurement are compared in quantitative manner based on the calculation of mechanical properties (modulus of elasticity, yield strength, tensile strength, percentage elongation at maximum force) of structural steel. A statistical information was used for evaluating the results. It is seen that the extensometer and strain gauge provided reliable data, however the extensometer offers several advantages over the strain gauge and crosshead motion for testing structural steel in tension. Furthermore, estimation of measurement uncertainty is presented for the basic material parameters extracted through strain measurement. KW - Baustahl KW - Werkstoffprüfung KW - Zugversuch KW - Affecting factors; Measurement uncertainty; Materials testing; Quantitative comparison; Strain comparison; Tensile test Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170425-31540 SP - 260 EP - 269 ER - TY - CHAP A1 - Marzban, Samira A1 - Almasi, Ashkan A1 - Schwarz, Jochen T1 - REINFORCED CONCRETE STRUCTURAL WALL DATABASE DEVELOPMENT FOR MODEL VALIDATION N2 - 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. KW - Baustoff KW - RC Wall KW - reinforced concrete wall KW - Database Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20150831-24523 ER - TY - JOUR A1 - Reichert, Ina A1 - Olney, Peter A1 - Lahmer, Tom T1 - Combined approach for optimal sensor placement and experimental verification in the context of tower-like structures JF - Journal of Civil Structural Health Monitoring N2 - When it comes to monitoring of huge structures, main issues are limited time, high costs and how to deal with the big amount of data. In order to reduce and manage them, respectively, methods from the field of optimal design of experiments are useful and supportive. Having optimal experimental designs at hand before conducting any measurements is leading to a highly informative measurement concept, where the sensor positions are optimized according to minimal errors in the structures’ models. For the reduction of computational time a combined approach using Fisher Information Matrix and mean-squared error in a two-step procedure is proposed under the consideration of different error types. The error descriptions contain random/aleatoric and systematic/epistemic portions. Applying this combined approach on a finite element model using artificial acceleration time measurement data with artificially added errors leads to the optimized sensor positions. These findings are compared to results from laboratory experiments on the modeled structure, which is a tower-like structure represented by a hollow pipe as the cantilever beam. Conclusively, the combined approach is leading to a sound experimental design that leads to a good estimate of the structure’s behavior and model parameters without the need of preliminary measurements for model updating. KW - Strukturmechanik KW - Finite-Elemente-Methode KW - tower-like structures KW - experimental validation KW - mean-squared error KW - fisher-information matrix Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44701 UR - https://link.springer.com/article/10.1007/s13349-020-00448-7 VL - 2021 IS - volume 11 SP - 223 EP - 234 PB - Heidelberg CY - Springer ER -