7.2 Ingenieurbau
Filtern
Erscheinungsjahr
- 2022 (52) (entfernen)
Dokumenttyp
- Vortrag (27)
- Beitrag zu einem Tagungsband (14)
- Zeitschriftenartikel (11)
Schlagworte
- Ground vibration (7)
- Structural Health Monitoring (7)
- Gründungsstrukturen (4)
- Structural health monitoring (4)
- Belastungsversuch (3)
- Building vibration (3)
- Großer Fallturm Horstwalde (3)
- Leichtbau (3)
- Modalanalyse (3)
- Offshore Windenergieanlagen (3)
- Offshore wind energy (3)
- Schwingungsdynamik (3)
- Artificial intelligence (2)
- Automatisierte schweißtechnische Fertigung (2)
- Bayesian System Identification (2)
- Brücke (2)
- Compressive strength (2)
- Digitalisierung (2)
- Earth block masonry (2)
- Elastische Elemente (2)
- Erschütterungen (2)
- Evaluation (2)
- Faseroptik (2)
- Finite Elemente Simulation (2)
- Irregularities (2)
- Layered soil (2)
- Measurement (2)
- Moisture content (2)
- Monitoring (2)
- Offshore Wind Energy (2)
- Optimal Sensor Placement (2)
- Radar (2)
- Railways (2)
- Research data management (2)
- Strukturmonitoring (2)
- Tomographic damage evaluation (2)
- Value of Information (2)
- Vehicle-track interaction (2)
- Vibration (2)
- Wellenausbreitung in der Tiefe (2)
- Acoustic emission (1)
- Ambient excitation (1)
- Asymptotic local approach (1)
- Attenuation (1)
- Automatisierte Fertigung (1)
- Automatisierte schweißtechniche Fertigung (1)
- Axle loads (1)
- Axle pulses (1)
- Bahngleis (1)
- Bauwerksdiagnostik (1)
- Bauwerksmonitoring (1)
- Bauwerksüberwachung (1)
- Belastungsfahrt (1)
- Belastungstest (1)
- Bionik (1)
- Bodenschlitz (1)
- Brücken (1)
- Buckling (1)
- Building information modelling (1)
- Combined finite-element boundary-element method (1)
- Compression tests (1)
- Concrete (1)
- Continuously inhomogeneous geological media (1)
- Coupler systems (1)
- Damage detection (1)
- Damage evolution (1)
- Datenmanagement (1)
- Dynamic axle loads (1)
- Dynamische Bodensteifigkeit (1)
- Einflusslinien (1)
- Einfügungsdämmung (1)
- Entscheidungsfindung (1)
- Ermüdungsprüfung (1)
- Erschütterungen im Fernfeld (1)
- Erschütterungsminderung (1)
- Fatigue (1)
- Filter effects (1)
- Finite element method (1)
- Finite elements (1)
- Foundation reliability analysis (1)
- Foundations (1)
- GNSS (1)
- Gebäudelagerung (1)
- Geometric vehicle and track irregularities (1)
- Global ambient vibrations (1)
- Hammer impact (1)
- High-speed (1)
- Impact (1)
- Impact damage of reinforced concrete (1)
- Impact damage on reinforced concrete (1)
- Impedanzmethode (1)
- Kraft auf den Boden (1)
- LBM-DEM (1)
- Leichtbauprinzipien (1)
- Load tests (1)
- Load-bearing behaviour (1)
- Maschinenbetrieb (1)
- Micromechanical simulation (1)
- Minderungsmaßnahmen (1)
- Modal analysis (1)
- Model update (1)
- Modell-Update (1)
- Modellierung (1)
- Modes (1)
- Modes and waves (1)
- Monopile installation risks (1)
- Monopiles (1)
- Multi-beam track model (1)
- Nachgiebigkeiten (1)
- Nelson’s method (1)
- Numerical damage simulation (1)
- Numerical simulation of impact damage (1)
- Offshore (1)
- Offshore Windenergie (1)
- Offshore geotechnics (1)
- Perfectly Matched Layer (PML) (1)
- Pfahlnachgiebigkeiten (1)
- Pile retrofit system (1)
- Prediction (1)
- Probabilistic modelling (1)
- Probability of detection (1)
- Propagation from a tunnel (1)
- Rail roughness (1)
- Railway trafiic (1)
- Random dynamics and vibrations (1)
- Randomly heterogeneous soil (1)
- Reinforcement (1)
- Relative humidity (1)
- Risslumineszenz (1)
- Rissprozes (1)
- Rissprozess (1)
- Scattering (1)
- Schadensüberwachung (1)
- Schienenfahrweg (1)
- Schienenfahrwege (1)
- Schwingungsmonitoring (1)
- Sensitivity vectors (1)
- Simple and fast prediction (1)
- Simple prediction (1)
- Soil-building interaction (1)
- Soil-wall-floor model (1)
- Sorption isotherm (1)
- Spatially varying ground conditions (1)
- Static axle loads (1)
- Statistical tests (1)
- Stiffness variation (1)
- Stress stiffening (1)
- Stress-strain relation (1)
- Structural integrity maintenance (1)
- Structural system identification (1)
- Support structures (1)
- Surface line (1)
- Systemidentifikation (1)
- Track damage quantification (1)
- Track filtering (1)
- Train passage (1)
- Train-induced ground vibration (1)
- Tunnel (1)
- Tunnel line (1)
- Tunnel-pile transfer (1)
- UAS (1)
- Ultrasonic testing (1)
- Unbounded domain (1)
- Uncertainty quantification (1)
- Varying soil stiffness (1)
- Varying stiffness (1)
- Varying track stiffness (1)
- Vibration measurement (1)
- Waves (1)
- Wheelset (1)
- Windenergieanlagen (1)
- Windenergy (1)
- building information modelling (1)
- layered soil (1)
- structural health monitoring (1)
- structural integrity management (1)
- support structures (1)
- Überwachung (1)
Organisationseinheit der BAM
- 7 Bauwerkssicherheit (52)
- 7.2 Ingenieurbau (52)
- 8 Zerstörungsfreie Prüfung (4)
- 9 Komponentensicherheit (4)
- 9.3 Schweißtechnische Fertigungsverfahren (4)
- 3 Gefahrgutumschließungen; Energiespeicher (3)
- 3.3 Sicherheit von Transportbehältern (3)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (2)
- 8.5 Röntgenbildgebung (2)
- 8.6 Faseroptische Sensorik (2)
Paper des Monats
- ja (1)
Eingeladener Vortrag
- nein (27)
Aim of this study is to provide information about moisture dependent material behaviour of unstabilised loadbearing earth blocks and mortars. Compressive strength and Young’s modulus were investigated after conditioning in varying relative humidity reaching from 40 % up to 95 %. The material composition and physical properties were investigated to understand the influence of relative humidity onto the mechanical properties. A normalisation of strength and stiffness by the values obtained at 23 ◦C and 50 % relative humidity reveals a linear dependence of compressive strength and Young’s modulus that is regardless of the material composition.
Thus, it is possible to describe the influence of relative humidity onto the load-bearing behaviour of unstabilised earth masonry materials in a generally valid formulation.
block and mortar types is analysed with particular regard to the influence of varying relative humidity. The uniaxial compressive strength and deformation characteristics of unstabilised earth blocks and mortars as well as of unstabilised earth block masonry are studied in detail and compared to conventional masonry to evaluate whether the structural design can be made accordingly. An increase of 30 % points in relative humidity leads to a reduction of the masonry´s compressive strength between 33 % and 35 % whereas the Young´s modulus is reduced by 24–29 %. However, the ratio between the Young´s modulus and the characteristic compressive strength of earth block masonry ranges between E33/fk = 283–583 but is largely independent of the relative humidity. The results show that the mechanical properties of the investigated unstabilised earth block masonry are sufficient for load-bearing structures, yielding a masonry compressive strength between 2.3 MPa and 3.7 MPa throughout the range of moisture contents
investigated. In general, the design concept of conventional masonry can be adapted for unstabilised earth masonry provided that the rather low Young´s modulus as well as the moisture dependence of both, compressive strength and Young´s modulus, are sufficiently taken into
account.
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.
The fatigue process of concrete under compressive cyclic loading is still not completely explored. The corresponding damage processes within the material structure are especially not entirely investigated. The application of acoustic measurement methods enables a better insight into the processes of the fatigue in concrete. Normal strength concrete was investigated under compressive cyclic loading with regard to the fatigue process by using acoustic methods in combination with other nondestructive measurement methods. Acoustic emission and ultrasonic signal measurements were applied together with measurements of strains, elastic modulus, and static strength. It was possible to determine the anisotropic character of the fatigue damage caused by uniaxial loading based on the ultrasonic measurements. Furthermore, it was observed that the fatigue damage seems to consist not exclusively of load parallel oriented crack structures. Rather, crack structures perpendicular to the load as well as local compacting are likely components of the fatigue damage. Additionally, the ultrasonic velocity appears to be a good indicator for fatigue damage beside the elastic modulus. It can be concluded that acoustic methods allow an observation of the fatigue process in concrete and a better understanding, especially in combination with further measurement methods.
Reinforced concrete is a widely used material for power generation structures, where load scenarios like impact loadings need to be considered. In this context mechanical splicing systems for the connection of reinforcement bars are of specific interest and impact resistance for the splicing systems has to be verified. High speed tensile tests need to be performed on splicing systems for reinforcement bars to confirm the capability of the coupler to resist impact loading. Furthermore, the ability of the reinforcement steel to dissipate energy by ductile behaviour with pronounced plastic strains should be confirmed by these tests. During the last decades comprehensive experiences were developed at BAM performing high speed tensile tests on reinforcement bars as well as on several splicing systems. For the lack of available standards defining these tests in detail an appropriate test procedure was developed and continuously optimized during this period at BAM. The test procedure is partially based on testing principles adapted from available standards. The main intention behind this test procedure is to perform high-speed tensile tests with a specific constant strain rate generated at the specimen. Furthermore, main objective was to establish a procedure to guarantee the comparability of test results for different diameter of reinforcement as well as for different types of couplers. Besides the pure execution of the high-speed tensile tests, the test specification also declares how to evaluate the measurements and the test results. Finally, some typical results will be presented in this contribution.
Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system.
Die Infrastruktursysteme der Industriestaaten erfordern heute und in Zukunft ein effizientes Management bei alternder Bausubstanz, steigenden Lasten und gleichbleibend hohem Sicherheitsniveau. Digitale Technologien bieten ein großes Potenzial zur Bewältigung der aktuellen und künftigen Herausforderungen im Infrastrukturmanagement. Im BMBF-geförderten Projekt Bewertung alternder Infrastrukturbauwerke mit digitalen Technologien (AISTEC) wird untersucht, wie unterschiedliche Technologien und deren Verknüpfung gewinnbringend eingesetzt werden können. Am Beispiel der Maintalbrücke Gemünden werden ein sensorbasiertes Bauwerksmonitoring, bildbasierte Inspektion mit durch Kameras ausgestatteten Drohnen (UAS) und die Verknüpfung digitaler Bauwerksmodelle umgesetzt. Die aufgenommenen Bilder dienen u. a. als Grundlage für spätere visuelle Anomaliedetektionen und eine 3D-Rekonstruktion, welche wiederum für die Kalibrierung und Aktualisierung digitaler Tragwerksmodelle genutzt werden. Kontinuierlich erfasste Sensordaten werden ebenfalls zur Kalibrierung und Aktualisierung der Tragwerksmodelle herangezogen. Diese Modelle werden als Grundlage für Anomaliedetektionen und perspektivisch zur Umsetzung von Konzepten der prädiktiven Instandhaltung verwendet. Belastungsfahrten und historische Daten dienen in diesem Beitrag der Validierung von kalibrierten Tragwerksmodellen.
Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data
are performed and modelled in the RDM system.
Die aktuelle Instandhaltungsstrategien von Ingenieurbauwerken arbeiten zustandsbasiert und stützen sich auf visuelle Inspektionen in kurzen, starren Intervallen. Beim Übergang zu Predicitive-Maintenance-Strategien können Sensordaten eigesetzt werden um Prognosemodelle der Bauwerke zu aktualisieren. Ein erster Schritt hierzu ist die sensorbasierte Systemidentifikation.
In this contribution, we consider two applications in which probabilistic approaches can potentially complement or enhance the design and assessment of offshore wind turbine foundations. First, we illustrate in a numerical example that probabilistic modelling can be helpful in dealing with chang-es in turbine locations during the planning phase of an offshore wind farm. In this case, spatial probabilistic modelling of the ground conditions enables (a) an inference of the soil properties at the modified turbine location from field data collected at different locations across an offshore wind farm site and (b) an optimisation of further site investigations. Second, we discuss the uncer-tainties and risks associated with the installation of large diameter monopiles in soils with hetero-geneities such as strong layers and/or embedded boulders. Subsequently, we present a concept for modelling, understanding, and managing these risks based on a probabilistic model of the subgrade conditions, monopile, and subgrade-pile-interaction.