7.2 Ingenieurbau
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- 7.2 Ingenieurbau (277) (entfernen)
Brücken müssen laufend überwacht werden, damit die Unsicherheiten hinsichtlich ihres Zustands, ihrer Beanspruchung und ihrer Leistungsfähigkeit verringert werden können. Diese Aufgabe soll künftig mit digitalen Methoden erleichtert werden. Im folgenden Beitrag werden deshalb die digitale Bauwerksmodellierung und die Entscheidungsfindung beleuchtet. Dazu wird gezeigt, wie Zustandsdiagnosen und -prognosen digital ermöglicht werden und wie durch diagnostische und prognostische Modelle eine wissenschaftliche Basis für risikobasierte Entscheidungen über Erhaltungsmaßnahmen und für den Übergang vom reaktiven zum vorausschauenden Brückenmanagement gebildet werden kann. Dabei wird klar: Jede Brücken-Überwachung bedarf einer Gesamtmethodik, ihre wichtigsten Elemente sind: Datenerfassung, Datenmanagement, Datenanalyse, Bauwerksmodellierung, Bauwerksbewertung und die letztendlichen Entscheidungen über notwendige Erhaltungsmaßnahmen.
The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
Inspection and maintenance contribute significantly to the lifetime cost of bridges. There is significant potential in using information obtained through structural health monitoring to update predictive models of the condition and performance of such structures, and thus ena-ble an improved decision-making regarding inspection and maintenance activities. Within the AISTEC project funded by the German Federal Ministry of Education and Research, we develop vibration-based structural health monitoring systems aimed at continuously provid-ing information on the structural condition of bridges. Environmental variations such as changing ambient temperatures can significantly influence the dynamic characteristics of bridges and thus mask the effect of structural changes and damages. It remains a challenge to account for such influences in structural health monitoring. To study the effect of ambient temperatures on the dynamic characteristics of beam structures, we monitor the vibration response of a reinforced concrete beam in the uncracked and cracked state at varying tem-peratures in a climate chamber. We postulate a set of competing parameterized probabilistic structural models, which explicitly account for the effect of varying ambient temperatures on the mechanical properties of the system. We then combine the information provided by the structural models with the information contained in the recorded vibration data to learn the parameters of the temperature-dependent structural models and infer the plausible state of the beam using Bayesian system identification and model class selection.
Inspection and maintenance contribute significantly to the lifetime cost of bridges. There is significant potential in using information obtained through structural health monitoring to update predictive models of the condition and performance of such structures, and thus ena-ble an improved decision-making regarding inspection and maintenance activities. Within the AISTEC project funded by the German Federal Ministry of Education and Research, we develop vibration-based structural health monitoring systems aimed at continuously provid-ing information on the structural condition of bridges. Environmental variations such as changing ambient temperatures can significantly influence the dynamic characteristics of bridges and thus mask the effect of structural changes and damages. It remains a challenge to account for such influences in structural health monitoring. To study the effect of ambient temperatures on the dynamic characteristics of beam structures, we monitor the vibration response of a reinforced concrete beam in the uncracked and cracked state at varying tem-peratures in a climate chamber. We postulate a set of competing parameterized probabilistic structural models, which explicitly account for the effect of varying ambient temperatures on the mechanical properties of the system. We then combine the information provided by the structural models with the information contained in the recorded vibration data to learn the parameters of the temperature-dependent structural models and infer the plausible state of the beam using Bayesian system identification and model class selection.
This contribution presents experimental methods to detect track damage. At BAM (Federal Institute of Material Research and Testing), a measuring car with a measuring system of 72 channels, geophones, mountings, cables, harmonic and impulsive exciters is used for dynamic measurements of the track, the soil and buildings. An instrumented hammer allows force measurements and to evaluate transfer functions of the track, and the soil. Wave measurements are used to identify the soil characteristics. Train passages are measured at the track and for the train induced ground vibrations. In addition to these in situ options, tests of tracks or track elements can be performed in a large laboratory.
There is a strong need for cost-effective mitigation measures for
turnouts. SBB has initiated a series of examinations using different methodologies to gain a deeper understanding of the excitation mechanisms at low frequencies, in addition to that obtained in the RIVAS project. To date it is not yet clear what constitutes a complete measurement data set that would enable understanding most of the vibration excitation mechanisms in turnouts. Increasing vibration at turnouts in comparison to normal track is observed for all measured frequencies.
The different methodologies are presented in the paper. Under-sleeper pads (USP) are a cost-effective method to reduce vibration at frequencies above 63 Hz (1/3 octave), but there is probably no improvement for frequencies below 63 Hz. A first test of new frog geometry did not show relevant improvements in Vibration emission in comparison to a reference frog geometry. Axle box acceleration measurements are an interesting method to identify defects in a turnout. A specialized measurement system of rail roughness could identify certain geometry Problem areas for some frogs. Noise increases also are observed at turnouts for frequencies ranging between 80 to 1000 Hz. The use of railway source models to calculate
contact forces for ballasted track and turnouts seems promising, in particular for understanding the influence of ground.
The identification of the dynamic behavior of structures, like bridges and towers, is relevant to address multiple issues. In many cases the dynamic parameters should be acquired only once or at a frequency that doesn’t justify the installation of distinct vibration sensors for a long-term monitoring. To identify modal frequencies of a structure, a drone based mobile sensing platform has been implemented. This sensing platform measures the relative displacement be-tween the structure and the drone, which also shows a strong dynamic behavior under wind tur-bulences. By regarding the dynamic model of the drone and additional measurements at the dis-tance sensor the absolute movement of the structure can be estimated based on the measured relative distance. This time domain data is a suitable input for various operational modal analysis algorithms. The system has been used to identify the dynamic properties of test and real structure, like a 1.5 MW wind turbine tower.
The identification of the dynamic behavior of structures, like bridges and towers, is relevant to address multiple issues. In many cases the dynamic parameters should be acquired only once or at a frequency that doesn’t justify the installation of distinct vibration sensors for a long-term monitoring. To identify modal frequencies of a structure, a drone based mobile sensing platform has been implemented. This sensing platform measures the relative displacement be-tween the structure and the drone, which also shows a strong dynamic behavior under wind tur-bulences. By regarding the dynamic model of the drone and additional measurements at the dis-tance sensor the absolute movement of the structure can be estimated based on the measured relative distance. This time domain data is a suitable input for various operational modal analysis algorithms. The system has been used to identify the dynamic properties of test and real structure, like a 1.5 MW wind turbine tower.
This article deals with two topics of vehicle-track-soil interaction, the mitigation of railway induced ground vibration by soft track elements, and the identification of track damage. Theoretical results have been achieved by a combined finite-element boundary-element method (FEBEM). The theoretical results are confronted with measurements at four sites. Improved mitigation effects have been found for soft rail pads under heavy sleepers. The insertion loss, however, can be too optimistic if a strong vehicle track resonance occurs for the un-isolated reference track. Two measurement sites show this strong vehicle-track resonance at about 80 Hz, which has been approximated by using the results of a wide parameter study including the rail pad, ballast, and soil stiffness, as well as the ballast model and the soil layering. – The detection of slab track damage is mainly based on the differences of the receptance or compliance functions. Theoretical results have been confirmed by measurements at one site where a loss of contact between track plate and base layer was visible. Measurements at a second site with a hidden damage have been compared with the theoretical results of a loose sleeper. The differences between intact (or repaired) and damaged tracks are strong enough to encourage the further development of this method for the identification of track damages.
Abstract. Three measurement campaigns of train-induced ground vibrations are evaluated for the vehicle-track-soil interaction. Ground vibrations, track vibrations and vehicle vibrations have been measured for train passages and impulse excitation and compared with theoretical results.
The soil and the track-soil system are calculated by wavenumber integrals. The influence of the vehicle is introduced by a substructure method. By comparing theory and measurement the different components of excitation force and ground vibration can be analysed, the quasi-static excitation, track-alignment errors, the out-of-roundness of wheels, the wheel and rail roughness, and moreover, scattered axle impulses and ineffective high-frequency parts of the wheelset accelerations and forces.
Three measurement campaigns of train-induced ground vibrations are evaluated for the vehicle-track-soil interaction. Ground vibrations, track vibrations and vehicle vibrations have been measured for train passages and impulse excitation and compared with theoretical results. The soil and the track-soil system are calculated by wavenumber integrals. The influence of the vehicle is introduced by a substructure method. By comparing theory and measurement the different components of excitation force and ground vibration can be analysed, the quasi-static excitation, track-alignment errors, the out-of-roundness of wheels, the wheel and rail roughness, and moreover, scattered axle impulses and ineffective high-frequency parts of the wheelset accelerations and Forces.
Three measurement campaigns of train-induced ground vibrations are evaluated for the vehicle-track-soil interaction. Ground vibrations, track vibrations and vehicle vibrations have been measured for train passages and impulse excitation and compared with theoretical results.
The soil and the track-soil system are calculated by wavenumber integrals. The influence of the vehicle is introduced by a substructure method. By comparing theory and measurement the different components of excitation force and ground vibration can be analysed, the quasi-static excitation, track-alignment errors, the out-of-roundness of wheels, the wheel and rail roughness, and moreover, scattered axle impulses and ineffective high-frequency parts of the wheelset accelerations and forces.
Three measurement campaigns of train-induced ground vibrations are evaluated for the vehicle-track-soil interaction. Ground vibrations, track vibrations and vehicle vibrations have been measured for train passages and impulse excitation and compared with theoretical results. The soil and the track-soil system are calculated by wavenumber integrals. The influence of the vehicle is introduced by a substructure method. By comparing theory and measurement the different components of excitation force and ground vibration can be analysed, the quasi-static excitation, track-alignment errors, the out-of-roundness of wheels, the wheel and rail roughness, and moreover, scattered axle impulses and ineffective high-frequency parts of the wheelset accelerations and forces.
Ground vibrations near railway lines are generated by the forces that are acting between wheel and rail. It seems to be a straight forward assumption that the vehicle dynamics are important for the level and the frequencies of the excitation forces. Different vehicle dynamics phenomena are analysed for their role in the excitation of ground vibrations: rigid body modes of the bogies, elastic (bending) modes of the car body, and elastic modes of the wheelset. The theoretical analyses use rigid body models, simplified elastic models, and detailed elastic models. Some of these problems are vehicle–track interaction problems where 3D finite‑element boundary‑element models have been used for the track and soil. It is shown that the rigid or flexible vehicle modes are well in the frequency range of ground vibrations (4 to 100 Hz). They have an influence on the excitation force but the additional forces are rather small and can be neglected in ground vibration prediction. The theoretical results are checked by experimental results of a simultaneous measurement of vehicle,
track, and ground vibrations.
Use of DEM-LBM modeling to prove the relevance of free jet model for soil erosion by impinging jet
(2018)
The aim of this study is to provide a micromechanical insight into the mechanisms taking place during the erosion of a cohesive granular material driven by a fluid flow, the objectives are summarized as follows:
Perform numerical erosion tests.
Parallelization of the code (Gpu).
Extensive parametric analysis => rely micro parameters (eg. Cohesion) to macro parameters (eg. Soil erodibility, mechanical strengths).
Kontinuierliche Sensorbasierte Bauwerksmessungen leisten einen wichtigen Beitrag zur Sicherheit von Verkehrsbauwerken. Hierzu werden im Vorhaben AISTEC Referenzbauwerke und Referenzverfahren untersucht mit Schwerpunkt auf den Einfluss klimatischer Bedingungen. Der Vortrag stellt den aktuellen Projektstand des FB 7.2 vor.
Unterraumbasierte Detektion von Strukturschäden an Jacket-Gründungen von Offshore-Windenergieanlagen
(2018)
Die vorliegende Arbeit beschreibt die Adaption eines globalen, schwingungsbasierten Verfahrens zur frühzeitigen Erkennung von Strukturschäden an Gründungsstrukturen offshore installierter Windenergieanlagen (OWEA). Damit soll es, Betreibern von Offshore-Windparks ermöglicht werden, im Rahmen periodisch durchgeführter messtechnischer Überwachungsmaßnahmen mit einem gegenüber wiederkehrender Inspektionen wesentlich geringen Aufwand auftretende Schäden an der Struktur zuverlässig zu delektieren.
Das untersuchte und implementierte Verfahren basiert auf der Methode der stochastischen unterraumbasierten Schadensdetektion. Dabei erfolgt eine statistische Analyse des wiederkehrend messtechnisch aufgenommenen dynamischen Antwortverhaltens des mechanischen Systems. Mittels statistischem Test werden signifikante Änderungen in dessen Eigenstruktur und damit Schäden delektiert.
Im Rahmen der vorliegenden Arbeit wurden umfangreiche experimentelle als auch numerische Untersuchungen zur Sensitivität und Robustheit des beschriebenen Schadensindikators durchgeführt. Dazu sind zunächst an einem Labormodell mittels künstlich und reversibel eingebrachter Schäden grundlegende Analysen zu den Einflüssen signal- und verfahrensinhärenter Kenngrößen durchgeführt worden. Auf der Basis dieser Ergebnisse wurde im Anschluss mittels numerischer Analysen das Antwortverhalten von OWEA simuliert und der entwickelte Algorithmus zur Schadensdetektion an den so realisierten Datensätzen angewendet.
Anhand der Ergebnisse der Arbeit wird aufgezeigt, dass, vorausgesetzt die Windenergieanlage befindet sich in Parkposition, eine Detektion von schon geringen Schäden an Gründungs-strukturen mit dem beschriebenen Verfahren, auch unter Einsatz weniger Messaufnehmer, zuverlässig möglich ist.