7.2 Ingenieurbau
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- elastische Gebäudelagerungen (1)
- fachwerkartige Stahltragwerken (1)
- layered soil (1)
- risk, reliability, inspection planning, offshore wind turbines (1)
- structural health monitoring (1)
- structural integrity management (1)
- support structures (1)
- temperature (1)
- zerstreute Achslastimpulse (1)
- Übertragungsmatrizen (1)
- Überwachung (1)
Organisationseinheit der BAM
- 7.2 Ingenieurbau (334) (entfernen)
Paper des Monats
- ja (5)
Zur Erschütterungsausbreitung an oberirdischen Bahnlinien gibt es gute Übereinstimmungen zwischen Messungen und der Theorie geschichteter Böden. Bei der Interpretation der Ergebnisse spielt die Rayleigh-Welle eine große Rolle. Je nach Frequenz und Wellenlänge hat die Rayleigh-Welle eine bestimmte Eindringtiefe und erreicht damit mehr oder weniger steife Bodenschichten. Damit bekommt man eine frequenzabhängige Bodensteifigkeit für die Erschütterungsprognose. Für die Wellenausbreitung in der Tiefe statt an der Bodenoberfläche müssen eigene Gesetzmäßigkeiten gefunden werden. Es werden die Punktlastlösungen im Frequenz-Wellenzahlbereich und durch Integration über die Wellenzahlen berechnet. Man erhält die Wellenfelder, die Terzspektren für verschiedene Entfernungen und Frequenzen. Es wird die Tiefenlage und das Bodenmodell (homogen, geschichtet und kontinuierlich zunehmende Steifigkeit) variiert. Die Rayleigh-Welle verliert ihre Bedeutung und stattdessen kann die Vollraumlösung zur Interpretation und Prognose verwendet werden. Es werden die Halbraumlösung mit und ohne Rayleigh-Welle und die Vollraumlösung in der Tiefe diskutiert und verglichen. Neben der Wellenausbreitung (der Transmission) werden auch Effekte der Erschütterungsanregung (der Emission) und der Übertragung in Gebäude (der Immission) mit Hilfe der Finite-Element-Randelement-Methode berechnet. Die Verteilung der dynamischen Achslast durch die Tunnelsohle ergibt eine Minderung gegenüber der Punktlastanregung. Bei der Immission hat man keine Freifeldanregung wie an der Bodenoberfläche. Man muss entweder neben der Wellenamplitude (Verschiebung oder Schwinggeschwindigkeit) in der Tiefe auch die Spannung der ankommenden Welle berücksichtigen, oder man muss die Freifeldamplituden nach Bodenaushub berechnen. Die Rechenergebnisse deuten darauf hin, dass man als Freifeldanregung die zweifache Vollraumlösung ansetzen kann.
Die Bemessung von tragendem Lehmmauerwerk erfolgt in Deutschland auf Basis der Lehmbau Regeln. Das dort verankerte Nachweisverfahren beruht auf einem globalen Sicherheitskonzept, welches aus zuverlässigkeitstheoretischer Sicht nicht mehr dem Stand der Technik entspricht. Auf Grund dessen wird das Bemessungskonzept für Lehmmauerwerk vom Deutschen Institut für Bautechnik (DIBt) voraussichtlich 2023 außer Kraft gesetzt. Ein statischer Nachweis von tragenden Lehmbauten wäre in Deutschland dann ausschließlich mit einer Zustimmung im Einzelfall (ZiE) oder vorhabenbezogener Bauartgenehmigung (vBg) möglich. Beides ist mit erheblichem Mehraufwand und höheren Kosten verbunden, was für den Lehmmauerwerksbau einen entscheidenden Nachteil im Vergleich zum konventionellen Mauerwerksbau darstellt. Um eine unkomplizierte Praxisanwendung von Lehmmauerwerk zu ermöglichen, werden innerhalb eines Forschungsvorhabens, welches von der Bundesanstalt für Materialforschung und -prüfung (BAM), dem Institut für Massivbau der Technischen Universität Darmstadt sowie dem Ingenieurbüro ZRS durchgeführt wird, auf Basis der Produktnormen für Lehmsteine und Lehmmauermörtel Grundlagen für ein aktualisiertes Bemessungskonzept entwickelt. Im Rahmen des Projekts wird ebenfalls untersucht, inwiefern die Bemessungsregeln nach den vereinfachten Berechnungsmethoden für unbewehrtes Mauerwerk gemäß DIN EN 1996-3 / NA auf den Lehmmauerwerksbau übertragbar sind. Falls eine Anwendung des normativen Nachweisverfahrens bei Lehmmauerwerk möglich ist, wäre zukünftig eine Aufnahme von Lehmsteinen und Lehmmauermörtel in den nationalen Anhang des Eurocode 6 denkbar, was eine bedeutsame Erweiterung des Anwendungsbereichs von Lehmmauerwerk zur Folge hätte.
Diverse wissenschaftliche Untersuchungen konnten zeigen, dass bemessungsrelevante Festigkeits- und Verformungseigenschaften von Lehmmauerwerksbaustoffen stark von der vorherrschenden Materialfeuchte abhängen, welche im hygroskopischen Wassergehaltsbereich im Wesentlichen von der relativen Luftfeuchte (RLF) bestimmt wird. Auch die Zwischenergebnisse des laufenden Forschungsvorhabens zur Entwicklung eines Bemessungskonzepts für Lehmmauerwerk ergaben eine deutlich erkennbare Abhängigkeit zwischen der Materialfeuchte und den relevanten Festigkeits- und Verformungseigenschaften. Eine detaillierte Kenntnis des feuchteabhängigen Materialverhaltens von Lehmsteinen, -mörtel und -mauerwerk ist zwingend erforderlich, um ein konsistentes und zuverlässiges Bemessungskonzept für Lehmmauerwerk zu entwickeln. Im Rahmen des laufenden Forschungsprojektes werden deshalb umfangreiche Versuche zum Drucktragverhalten von Lehmsteinen und -mörtel sowie Lehmmauerwerk nach Konditionierung bei unterschiedlichen RLF durchgeführt und analysiert. Weiterhin werden auf Basis der experimentellen Ergebnisse numerische Modelle kalibriert, welche die detaillierte Analyse der Biegedrucktragfähigkeit von Lehmmauerwerk ermöglichen.
In diesem Beitrag werden zunächst die bisherigen Zwischenergebnisse bezüglich der experimentell ermittelten feuchteabhängigen Materialkennwerte von Lehmsteinen, -mörtel und -mauerwerk dargelegt. Darauf aufbauend werden numerische Untersuchungen zur Bestimmung der Systemtragfähigkeit von Lehmmauerwerk unter Feuchteeinflusses durchgeführt und erläutert.
Measurements at the foundation, the surrounding soil and nearby buildings have been done during several drop tests of different containers on different foundations. The first measurements have been done on a big foundation where it should be guaranteed that the foundation is rigid and the container is tested properly. It was controlled that the foundation does not absorb more than 2 percent of the energy of the container. Most of the drop energy is lost in shock absorbers. Later on, a smaller drop test facility has been built on the ground but inside an existing building. It had to be controlled by prediction and measurements that the drop test will not damage the building. Tests from different heights on soft, medium, and stiff targets have been done to find out rules which allow to identify acceptable and unacceptable drop tests. Later on, the biggest drop test facility has been built for masses up to 200 t. It was necessary for the design of the foundation to estimate the forces which occur during the drop tests. On the other hand, the acceptable tests should be selected and controlled by measurements where the impact duration is important. Different sensors, accelerometers, accelerometers with mechanical filters, geophones (velocity transducers), strain gauges, and pressure cells have been applied for these tasks. The signals have been transformed to displacements which proved to be best suited for the interpretation of the impact mechanism. Modell calculations have been used to check and understand the dynamic measurements. The simplest law is the conservation of the momentum which is a good approximation if the impact is short. If the soil under the foundation has an influence on the deceleration of the container, the maximum foundation velocity is lower than the simple estimation. The amplitudes of the foundation could also be estimated from the ground vibrations and their amplitude-distance law.
Zur Erschütterungsausbreitung an oberirdischen Bahnlinien gibt es gute Übereinstimmungen zwischen Messungen und der Theorie geschichteter Böden. Bei der Interpretation der Ergebnisse spielt die Rayleigh-Welle eine große Rolle. Je nach Frequenz und Wellenlänge hat die Rayleigh-Welle eine bestimmte Eindringtiefe und erreicht damit mehr oder weniger steife Bodenschichten. Damit bekommt man eine frequenzabhängige Bodensteifigkeit für die Erschütterungsprognose. Für die Wellenausbreitung in der Tiefe statt an der Bodenoberfläche müssen eigene Gesetzmäßigkeiten gefunden werden. Es werden die Punktlastlösungen im Frequenz-Wellenzahlbereich und durch Integration über die Wellenzahlen berechnet. Man erhält die Wellenfelder, die Terzspektren für verschiedene Entfernungen und Frequenzen. Es wird die Tiefenlage und das Bodenmodell (homogen, geschichtet und kontinuierlich zunehmende Steifigkeit) variiert. Die Rayleigh-Welle verliert ihre Bedeutung und stattdessen kann die Vollraumlösung zur Interpretation und Prognose verwendet werden. Es werden die Halbraumlösung mit und ohne Rayleigh-Welle und die Vollraumlösung in der Tiefe diskutiert und verglichen. Neben der Wellenausbreitung (der Transmission) werden auch Effekte der Erschütterungsanregung (der Emission) und der Übertragung in Gebäude (der Immission) mit Hilfe der Finite-Element-Randelement-Methode berechnet. Die Verteilung der dynamischen Achslast durch die Tunnelsohle ergibt eine Minderung gegenüber der Punktlastanregung. Bei der Immission hat man keine Freifeldanregung wie an der Bodenoberfläche. Man muss entweder neben der Wellenamplitude (Verschiebung oder Schwinggeschwindigkeit) in der Tiefe auch die Spannung der ankommenden Welle berücksichtigen, oder man muss die Freifeldamplituden nach Bodenaushub berechnen. Die Rechenergebnisse deuten darauf hin, dass man als Freifeldanregung die zweifache Vollraumlösung ansetzen kann.
Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presentedand applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably.
The statistical subspace-based damage detection technique has shown promising theoretical and practical results for vibration-based structural health monitoring. It evaluates a subspacebased residual function with efficient hypothesis testing tools, and has the ability of detecting small changes in chosen system parameters. In the residual function, a Hankel matrix of Output covariances estimated from test data is confronted to its left null space associated to a reference model. The hypothesis test takes into account the covariance of the residual for decision making. Ideally, the reference model is assumed to be perfectly known without any uncertainty, which is not a realistic assumption. In practice, the left null space is usually estimated from a reference data set to avoid model errors in the residual computation. Then, the associated uncertainties may be non-negligible, in particular when the available reference data is of limited length. In this paper, it is investigated how the statistical distribution of the residual is affected when the reference null space is estimated. The asymptotic residual distribution is derived, where its refined covariance term considers also the uncertainty related to the reference null space estimate. The associated damage detection test closes a theoretical gap for real-world applications and leads to increased robustness of the method in practice. The importance of including the estimation uncertainty of the reference null space is shown in a numerical study
and on experimental data of a progressively damaged steel frame.
Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presentedand applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably
Im AISTEC Projekt erforscht der FB 7.2 Verfahren zur Bewertung von Verkehrsbrücken auf der Gruandlage von sensorbasierten Bauwerksmessungen. In diesem Vortrag wird ein Überlick über die Forschungsarbeiten des FB 7.2 präsentiert. Des Weiteren wird ein Ausblick zur quantitativen Integration von sensorbasierten Bauwerksmessungen in die risiko-basierte prädiktive Planung von Inspektionen und Reparaturen von Ingenieurbauwerken gegeben.
Der Vortrag stellt die Durchführung und die ersten Ergebnisse der Belastungsfahrten der BAM im Rahmen des AISTEC Projekts an der Maintalbrücke am 19.05. und 20.05.2021 vor. Es wurden Tragwerksreaktionen des Bauwerks mit dem installierten Dauermonitoringsystem und insbesondere dem Betongelenk mit zusätzlich installierter Sensorik aufgezeichnet. Für die Ermittlung der Lastposition wurden mehrere Verfahren eingesetzt und verglichen.
Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data.
Nach den bisherigen Regeln werden Bauwerksprüfungen von Brücken in starr definierten Intervallen durchgeführt. Diese starre, periodische, zustandsbasierte Instandhaltungsstrategie soll zukünftig durch eine flexible und prädiktive Instandhaltung ersetzt werden. Hierbei sollen Inspektionen und Instandhaltungsmaßnahmen unterstützt durch autonome Systeme auf der Grundlage von Monitoringdaten geplant und zusätzlich bei unvorhergesehenen Ereignissen ausgelöst werden. Im Rahmen des Verbundforschungsvorhabens AISTEC wird ein Vorgehen für Großbauwerke und kleinere Regelbauwerke zur Umsetzung eines kombinierten globalen, schwingungsbasierten und quasistatischen Monitorings entworfen. An der Maintalbrücke Gemünden – einer semiintegralen Rahmenbrücke aus Spannbeton auf der Schnellfahrstrecke Hannover–Würzburg – wurde als Demonstrator ein Dauermonitoring realisiert.
Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data.
The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability.
Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model.
The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic Engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the
probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability.
Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model.
Fatigue is one of the main deterioration processes affecting the performance of welded steel support structures of wind turbines in offshore wind farms. In this contribution, we present a probabilistic physics-based fatigue deterioration model of a wind farm that accounts for the stochastic dependence among the fatigue behavior of different hotspots at turbine and wind farm level. The dependence exists because of uncertain common influencing factors such as similar material properties, fabrication qualities and load conditions. These system effects signify that an inspection of one hotspot provides indirect information of the condition of the remaining hotspots and thus enable an optimization of the inspection effort for a wind farm.
The wind farm model consists of two levels: A turbine support structure (level 1 system model) is represented by its fatigue hotspots and their stochastic dependence. The fatigue performance of a hotspot is described by a probabilistic fracture mechanics (FM) fatigue model. The probabilistic model of the parameters of the FM fatigue model is calibrated based on design data and is thus directly linked to the design of the turbine support structures. Dependence among the fatigue performances of different hotspots in a turbine support structure is modeled by introducing correlations between the stochastic parameters of the FM fatigue models. A wind farm (level 2 system model) consists of different turbine support structures (level 1 system models). Additional correlations are introduced at wind farm level to account for the dependence among the fatigue behavior of hotspots belonging to different turbine support structures. The wind farm model enables the computation of (marginal) hotspot fatigue reliabilities, system fatigue reliabilities of individual turbine support structures and the system fatigue reliability of an entire wind farm. The probabilistic model of the parameters of the two-level system model can be consistently updated with inspection outcomes using Bayesian methods. The updated probabilistic model of the model parameters then forms the basis for updating the estimates of the fatigue reliabilities.
We implement the wind farm model in a software tool named SysPark. The tool provides the means for planning inspections at wind farm level using an adaptive reliability-based threshold approach. In this approach, the first inspection campaign is planned in the year before the fatigue failure rates of the hotspots with the lowest fatigue reliabilities exceed a threshold failure rate. Once inspection results become available, the probabilistic model of the parameters of the wind farm model is updated. If repairs are performed, the wind farm model is additionally modified to describe the behavior of the repaired hotspots. The updated and modified model then enables the planning of the next inspection campaign and so on. The software tool is demonstrated in a case study considering a generic wind farm consisting of turbines with jacket support structures.