7.2 Ingenieurbau
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Die Definition und Beschreibung der Einfügedämmung im Normentwurf DIN 45673-4 ist noch nicht richtig. Es wird die Beschreibung aus DIN 45673-3 herangezogen, die für Messungen gilt. Für die drei Rechenverfahren gibt es jeweils eine passende Beschreibung. Mit diesen Vorlagen ist eine vernünftige Definition der Einfügungsdämmung zu finden. Es bedarf einer Abgrenzung gegenüber anderen (falschen) Möglichkeiten. Des Weiteren ist der Anhang 2 erweitert und der Parametersatz im Anhang 1 auf das Wesentliche reduziert worden.
This paper presents an erosion interpretation of cohesive granular materials stressed by an impinging jet based on the results of a micromechanical simulation model. The numerical techniques are briefly described, relying on a two-dimensional Lattice Boltzmann Method coupled with a Discrete Element Methods including a simple model of solid intergranular cohesion.
These are then used to perform a parametric study of a planar jet in the laminar regime impinging the surface of granular samples with different degrees of cohesive strength. The results show the pertinence of using a generalized form of the Shields criterion for the quantification of the erosion threshold, which is valid for cohesionless samples, through empirical calibration, and also for cohesive ones. Furthermore, the scouring kinetics are analysed here from the perspective of a selfsimilar expansion of the eroded crater leading to the identification of a characteristic erosion time and the quantification of the classical erosion coefficient. However, the presented results also challenge the postulate of a local erosion law including erodibility parameters as intrinsic material properties. The paper then reviews the main limitations of the simulation and current interpretation models, and discusses the potential causes for the observed discrepancies, questioning the pertinence of using time-averaged macroscopic relations to correctly describe soil erosion. The paper concludes addressing this question with a complementary study of the presented simulations re-assessed at the particle-scale. The resulting local critical shear stress of single grains reveals a very wide dispersion of the data but nevertheless appears to confirm the general macroscopic trend derived for the cohesionless samples, while the introduction of cohesion implies a significant but systematic quantitative deviation between the microscopic and macroscopic estimates. Nevertheless, the micro data still shows consistently that the critical shear stress does actually vary approximately in linear proportion of the adhesive force.
This talk provides a brief overview on some geomechanical phenomena and problematic issues in the field of offshore wind-energy geotechnics, with reference to their associated challenges for a numerical analysis/simulation. These may include large deformations, fluid coupling and grain-scale phenomena, all of which are generally difficult to be addressed with conventional FE techniques.
These challenges are illustrated here with a practical example for the retrofit of axially loaded piles using compaction grouting techniques. In this case, the mechanical effects of the retrofit may be analysed with standard FE techniques, but require the adoption of strong assumptions, while the injection process itself can only be analysed with special techniques such as the MPM.
Finally, an LBM-DEM framework for the micromechanical analysis of such problems is introduced and a practical application for the estimation of the soil resistance to driving (SRD) in layered profiles is discussed.
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 train passages over intact or damaged slab tracks on different soils have been calculated by two methods. The finite element method (FEM) uses a Winkler soil under the track model by adding a thin “soil layer”. The combined finite element boundary element method has a continuous soil model which is included by the boundary element method. The basic results are the distributions of the track (rail, track plate, and base layer) displacements along the track for a single axle laod. These solutions are superposed to a complete train load and transformed to time histories. The influence of track and soil parameters has been analysed. The main interest is the influence of the track damage. A gap between track plate and base layer of different lengths has been studied for changes in amplitudes and widths of deflection. A best fit to measured track displacements has been found so that the track damage can be identified and quantified. The FEM model with Winkler soil cannot be fitted to the amplitude and width with the same soil parameters. Therefore, the FEBEM model is preferable for these railway track problems.
The attenuation of wave amplitudes is ruled by the planar, cylindrical or spherical geometry of the wave front (the geometric or power-law attenuation) but also by the damping of the soil (an exponential attenuation). Several low- and high-frequency filter effects are derived for the layering and the damping of the soil, for the moving static and the distributed train loads and for a homogeneous or randomly heterogeneous soil. Measurements of hammer- and train-induced vibrations at five sites have been analysed for these attenuation and filter effects. The measured attenuation with distance can be discribed by generalised power laws and some reasons will be discussed. The theoretical filter effects can well be found in the measurements.
A simple and fast prediction scheme is presented for train-induced ground and building vibrations. For the emission, finite-element boundary-element or multiple-beam-on-continuous-soil models of the track have been analysed and approximated by faster track-on-Winkler-soil models. The vehicle-track interaction due to irregularities yields the excitation forces. For the transmission of waves in the soil, the wavenumber integral of the compliance of layered soils has been evaluated. The calculation time is reduced for the prediction by using the solution of a homogeneous half-space with a frequency-dependent wave velocity (the dispersion) of the soil. For the immision, many 2 and 3-dimenisonal finite-element building models have been investigated, and a good approximation has been established by a 1-dimensional soil-wall-floor model. In addition, the axle sequence of the train, the quasi-static and the “scattered” response of the soil, and the wave propagation from a tunnel to a pile foundation of a building have been included.
Usually, geometric irregularities are considered as the main cause of ground vibrations from trains. A varying stiffness of the track, the track support and the soil can also generate ground vibrations. The regular stiffness variation of the track on and between the sleepers results in a deterministic dynamic axle load. The random stiffness variation of the track support yields also dynamic axle loads. The dynamic axle loads are generated by the varying wheel displacements under the static axle load by the acceleration of the unsprung mass of the rail vehicle. The random stiffness variation has a second effect. The pulses from the passage of the static axle loads are superposed regularly to the quasi-static response, but also irregularly to yield a “scattered” part of the axle pulses. The same holds for a random variation of the soil stiffness. All these effects of stiffness variations have been calculated by wavenumber-domain multi-beam track models, a random finite-element soil model and the superposition of axle impulses in a stochastic simulation. The results are confronted with many measurements at different sites. It is concluded that the stiffness variation of the track and the soil generate an important ground vibration component near railway lines.
Vibration measurements have many causes and many technical and natural sources. Problems can sometimes be solved by short-term measurements, but in many cases, a long-term measurement is necessary. In long-term measurements of days, weeks, months and even years, it is easy to collect a huge quantity of raw data, but at the end, the post-processing of these data can be exhausting (for example one-year vibration data of a wind energy tower). A software has been developed which con-sists of measuring and evaluation routines where the measuring routines can operate different meas-uring systems and different measuring cards. The main advantage of this software is the fact that the interesting evaluations can be integrated in the measuring process so that the characteristics of the vibration can be extracted without storing all the raw data. Only important time segments are stored, for example train passages. The overall concept of the software and the main evaluation routines will be described in some details. Examples of our measurement experience will illustrate the capabilities of the software. 1) Surveying construction work in nearby sensitive buildings (for example an old wind tunnel), including a stable alarm system and meaningful vibration limits. 2) Prediction of train-induced vibration for a planned building to prevent annoyance and to improve the building design. 3) Modal analysis and long term measurements of several single- or multi-span, concrete or steel bridges 4) Modal and wave analysis of coupled floors in a historical building (“Neues Palais” at Potsdam). 5) Soil properties of various measurement sites (different routines to evaluate the dispersion). Moreover, from many projects, amplitudes, frequencies, and attenuation laws have been collected and analysed for the different sources such as vibratory or impact pile driving and ground compaction, demolition work with different machines, blasting in quarries and in tunnel works, bomb and mine clearing.
Automated vibration-based damage detection is of increasing interest for structural health monitoring of engineering structures. In this context, stochastic subspace-based damage detection (SSDD) compares measurements from a testing state to a data-driven reference model in a statistical framework. In this thesis theoretical developments have been proposed to improve the robustness of SSDD for realistic applications conditions. First, a statistical test has been proposed considering the statistical uncertainties about the model obtained from the reference data. This leads to a precise description of the test’s distribution properties and damage detection thresholds. Second, an approach has been developed to account for environmental effects in SSDD. Based on reference measurements at few different environmental conditions, a test is derived with respect to an adequate interpolated reference.
The proposed methods are validated in numerical simulations and applied to experimental data from the laboratory and outdoor structures.
Brücken werden durch Inspektionen und teilweise durch Monitoring überwacht, um Daten und Informationen über den Zustand und die Einwirkungen zu sammeln. Auf deren Grundlage werden Entscheidungen hinsichtlich Maßnahmen zur Gewährleistung der Sicherheit und Verfügbarkeit getroffen. In diesem Vortrag werden die Potentiale der Digitalisierung zur Unterstützung und Verbesserung der Brückenüberwachung diskutiert. Insbesondere werden die Bereiche Datenmanagement, Brückenmodellierung und Entscheidungsfindung betrachtet.
Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders.
Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders.
Die B1 Brücke am Altstädter Bahnhof in Brandenburg an der Havel wurde im Dezember 2019 aufgrund von während einer turnusmäßigen Inspektion entdeckten Rissen und Hohlstellen entlang der vorgespannten Längsträger gesperrt und im Mai 2021 abgebrochen. In der Zwischenzeit wurde die Brücke detailliert überwacht. Vor dem Abriss wurden zudem umfangreiche Untersuchungen zur Bestandsaufnahme und Schadensanalyse sowie Tests moderner Sensorik vorgenommen. Dabei konnte sowohl die richtige, zuvor nicht sicher bekannte Anzahl von Spanngliedern in den Querträgern sicher ermittelt werden als auch durch moderne Varianten der Schwingungsmessungen und der faseroptischen Sensorik zusätzliche Kenntnisse püber das Bauwerksverhalten ermittelt werden . In dem Beitrag werden die Verfahren mit ihren Möglichkeiten und Grenzen vorgestellt, die Ergebnissee an der Brücke in Brandenburg erläutert und zukünftige Einsatzmöglichkeiten diskutiert.
Die B1 Brücke am Altstädter Bahnhof in Brandenburg an der Havel wurde im Dezember 2019 aufgrund von während einer turnusmäßigen Inspektion entdeckten Rissen und Hohlstellen entlang der vorgespannten Längsträger gesperrt und im Mai 2021 abgebrochen. In der Zwischenzeit wurde die Brücke detailliert überwacht. Vor dem Abriss wurden zudem umfangreiche Untersuchungen zur Bestandsaufnahme und Schadensanalyse sowie Tests moderner Sensorik vorgenommen. Dabei konnte sowohl die richtige, zuvor nicht sicher bekannte Anzahl von Spanngliedern in den Querträgern sicher ermittelt werden als auch durch moderne Varianten der Schwingungsmessungen und der faseroptischen Sensorik zusätzliche Kenntnisse püber das Bauwerksverhalten ermittelt werden . In dem Beitrag werden die Verfahren mit ihren Möglichkeiten und Grenzen vorgestellt, die Ergebnissee an der Brücke in Brandenburg erläutert und zukünftige Einsatzmöglichkeiten diskutiert.
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.
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.
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.