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Paper des Monats
- ja (4)
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.
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.
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.
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.
The dynamic behaviour of slab and ballast tracks has been investigated by measurements and calculations. Hammer impacts and train passages have been analysed. Measurements have been performed by geophones (velocity transducers) which have been time-integrated to displacements. The calculations are done in frequency-wavenumber domain for multi-beam-on-continuous soil models. The characteristics of the different tracks and track elements have been established in theory and experiment. The frequency-dependent compliances (displacement transfer functions) show clear rail-on-rail-pad resonances or highly damped track-soil resonances. Compared to the rail and sleeper, the track plate has much lower amplitudes. The slab track has usually the highest rail amplitudes due to soft rail pads. The train passage yields track displacements which are a superposition of the axle loads from the two neighbouring axles of a bogie and from the two bogies of two neighbouring carriages. This global behaviour is characteristic for the track plate of the slab track whereas the rails of the slab and the ballast track behave more local with only one bogie of influence. The measurements agree very well with the theory of the continuous soil in case of the six measured slab tracks and acceptably well for the six measured ballast tracks. The measurements allow to find appropriate model parameters and to check the models, for example the Winkler model of the soil has been found less appropriate as it reacts more locally.
Design challenges for Offshore wind-farms. From foundation mechanics to wind-farm aerodynamics
(2021)
This talk provides a brief introduction on general engineering design challenges for the offshore wind energy production. Some general features of the offshore wind-energy field from a civil engineering perspective are firstly presented, followed by a brief discussion of some of the main geomechanical issues for the foundation of the offshore turbines into the seabed.
In the following part, an overview of relevant fluid-structure interactions and some options for an efficient numerical analysis are provided, where the hydromechanical Wave–Tower interaction is firstly discussed. Then, some general aspects of the windfarm aerodynamics are introduced. On the one hand, some modelling possibilities for the wake analysis of single turbines and turbine groups are discussed. And on the other hand the relevance of such analyses for a proper windfarm layout optimization is pointed out.
In particular, this talk shows that: i) The bearing capacity of turbine multi-pile foundations can degrade under cyclic loading (waves, wind, …), while for monopile foundations cyclic hydromechanical coupling effects may take place, which may lead to a foundation softening; ii) Numerical analysis of a turbine’s interaction with wind/waves is useful and affordable, while simplified models can already provide a useful insight into the windfarm aerodynamics. iii) Turbulent wake analysis is very relevant for the windfarm layout.
Many measurements of train induced ground vibrations show high amplitudes for a certain mid-frequency range. This ground vibration component cannot be well explained by dynamic loads of the train. Many characteristics indicate that the axle impulses, which are scattered by an irregular soil, are the excitation. This new understanding of railway-induced ground vibration is verified by numerical analysis. The response of the regular homogeneous and irregular inhomogeneous soils has been calculated by the finite-element method in frequency domain. A specific superposition of the impulse responses has been invented including time shift, axle sequence, track filter and hanning filter. The superposition yields the quasi-static component of the ground vibration which is restricted to very low frequencies and to the close near-field of the track. In case of an irregular soil of which the stiffness varies randomly in space, the superposition yields a mid-frequency ground vibration component from the scattering of the axle impulses. The existence and the importance of this component can thus be demonstrated by the calculations. Some rules of the influence of distance, train speed, soil stiffness, strength and width of the stiffness variation have been derived from the calculations. Many measurements show the unique explanation of the mid-frequency ground vibration component by the scattered axle impulses.
This presentation deals with the phenomenology and design of pile foundations for offshore wind turbines, and is divided into two lectures.
The first lecture presents a brief introduction to the context and peculiarities of such foundations, and then focuses on the particular case of axially loaded piles. This part is most relevant for the relatively slender piles of the multi-pile substructures (i.e. jackets and tripods). A clear distinction between physical phenomenology and practical design is drawn here.
his presentation deals with the phenomenology and design of pile foundations for offshore wind turbines, and is divided into two lectures.
The second lecture continues with the case of laterally loaded offshore piles, which bears most relevance for the case of the monopile foundations. Here again, a clear separation between physical reality and design methods is intended.
Finally, the last part of the second lecture introduces several advanced topics which lie outside the classical design approaches, namely the hydromechanical coupling effects (i.e. the excess pore-pressure generation around the monopiles), the cyclic pile fatigue and the so-called pile setup (i.e. the time effects on the axial pile capacity). The relevance of the latter two topics is illustrated with experimental results from a field testing campaign on real large-scale piles.
This document presents the specification for the execution and evaluation of high-speed tensile tests on reinforcement bar coupler systems. This specification was developed at BAM - Bundesanstalt für Materialforschung und -prüfung (Federal Institute for Materials Research and Testing, Germany) - following test principles from related international standards.
The present document represents the latest status of the test specification. It is noted that until 2010 the test procedure was characterised on a test velocity based on L0. In an improved test conception and after intensive investigations in cooperation with industry partners, this procedure has been updated to consider instead a test velocity based on Lr, since this warrants more comparable and meaningful results.
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.
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
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.
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.
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.
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.
In this presentation, we discuss the potential of probabilistic approaches to the design and assessment of offshore foundations. The potential is demonstrated in a numerical example considering a laterally loaded monopile. As an outlook, we present a concept for managing the risk associated with installing large monopiles.
Grouted connections are intensively used in offshore rigs, platforms as well as jacket and monopile offshore wind turbine structures. Being located in remote offshore conditions, these connections can experience considerable adverse loading during their lifetimes. Degradation was reported inside similar connections, which were installed in the last three decades. Grouting in the offshore sites may often be proven difficult, which eventually leads to reduced load-bearing capacity of connections in the long run. Thus, repair and rehabilitation of such connections should be planned ahead to minimize operational delays and costs. In this study, scaled grouted connections were manufactured using a novel mould, whose integrity were monitored using digital image correlation (DIC). The connections were loaded under static load to visualize the main failure pattern using distributed fibre optic sensors and acoustic emission (AE) analysis. Grouted connections were then repaired using a cementitious injectable grout. The effectiveness of the grout injection was monitored using dye penetration technique. Finally, specimens are reloaded to identify the potential of such repair for grouted connections.
Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data.
Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load
events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data
measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to
varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load
bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the
monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To
address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems
that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data
obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods
and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital
twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam
in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass
monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian
system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data.
In this presentation, a framework for integrating vibration-based structural health monitoring data into the optimization of inspection and maintenance of deteriorating structural systems is presented. The framework is demonstrated in an illustrative example considering a steel frame subject to fatigue.
The Perfectly Matched Layer (PML) method is an efficient approach to imposing radiation conditions at the bounded region of interest in case of wave propagation in unbounded domains. This paper presents and validates 3D FE/PML numerical schemes based on two different PML formulations for homogeneous and inhomogeneous geological media exhibiting discrete or continuous inhomogeneity. In the equation of motion for the PML domain the applied stretching behavior is expressed either as complex material properties or as complex coordinates. Both PML formulations are implemented in the FEM and verified against analytical solutions. Three different types of material inhomogeneity are considered: layered half-space, continuously inhomogeneous half-space with linear velocity profile and continuously inhomogeneous half-space with nonlinear velocity profile. Sensitivity analyses are conducted, and the performance of the developed numerical schemes is investigated taking into account a broad variation of the PML parameters. Recommendations are given for the optimal values of the PML parameters for the case of homogeneous and inhomogeneous geological media.
The attenuation of wave amplitudes is ruled by the planar, cylindrical or spher-ical 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 homoge-neous 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 gen-eralised power laws and some reasons will be discussed. The theoretical filter effects can well be found in the measurements.
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.
Train-induced ground vibrations are all generated by the vehicle, by static or dynamic vehicle loads. The most important and most accepted excitation are the dynamic wheel loads from the passage over track irregularities. Dynamic wheel loads will be compared from parallel axle-box and ground vibration measurements at more than seven sites. Some low-frequency excitation of ground vibrations, typically between 10 and 30 Hz, cannot be found in the axle-box measurements. Therefore, other vehicle modes, such as rigid bogie modes, flexible carriage modes, rigid and flexible wheelset modes, have been analysed for additional excitation forces. These vehicle dynamics analyses give an explanation for higher axle-box results at high frequencies, but not for the excitation of the higher low-frequency ground-vibration component. Finally, the effect of the moving static train loads will be analysed. For a regular track and soil, the moving static train loads yield the quasi-static response which exists only in the low-frequency nearfield of the track. If the support stiffness is randomly varying along the track, the pulses on the track generate an additional low-frequency component which is called the irregular pulse responses.
This component will be demonstrated by numerical analysis where all axle pulses are superposed in frequency domain.
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.
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.
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.
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.
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.
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.
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 which are generated by the acceleration of the unsprung mass (from the varying wheel displacements under the static axle load). 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.
Irregularities of the track are a main cause of train-induced ground vibration, and track maintenance is of great importance. Although geometric irregularities at the wheel-rail contact are widely used, other types of irregularities, such as stiffness irregularities, irregularities from different track positions and irregularities in the wave propagation, were analysed in the present study. The track behaviour was investigated by a multi-beam-on-soil model. This track model is coupled with a vehicle model to calculate the vehicle–track interaction. The track model was also used for the track filtering, which transfers a track support error to the equivalent rail irregularity or, conversely, the sharp axle pulse on the rail to a smoother pulse on the soil. In the case in which this filtering varies randomly along the track, the pulses of the moving static load induce a certain ground Vibration component (“the scatter of axle pulses”). This effect was calculated by the superposition of axle pulses in the frequency domain and by a stochastic simulation. Simultaneous vehicle, track and soil measurements at a certain site were used to evaluate the different excitation and ground Vibration components. The agreement between calculations and axle-box and soil measurements is good. The ground vibrations calculated from rail irregularities and corresponding dynamic loads, however, clearly underestimate the measured ground vibration amplitudes. Only the static load that is moving over a varying track support stiffness can produce the important mid-frequency ground Vibration component by the scatter of axle pulses.
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.
A prediction software has been developed by BAM. The following topics have still be solved. A realistic irregularity spectrum can be derived from axle-box measurements. It agrees wel with the spectrum used for the high-speed 2 project in the United Kingdom. In addition, the scattering of axle pulses should be included. This mid-frequency component can also be found in the HS2 procedure. Finally, the reduction in case of a tunnel line compared to a surface line should be included. Some measurement results of BAM, HS2 and other institutes show a certain mid-frequency reduction. This is due to the load distribution of the tunnel which yields softer axle pulses and the scattered axle impulses are reduced.
Structural health monitoring is a promising technology to automatically detect structural changes based on permanently installed sensors. Vibration-based methods that evaluate the global system response to ambient excitation are suited to diagnose changes in boundary conditions, i.e., changes in member prestress or imposed displacements. In this paper, these changes are evaluated based on sensitivity-based statistical tests, which are capable of detecting and localizing parametric structural changes. The main contribution is the analytical calculation of sensitivity vectors for changes in boundary conditions (i.e., changes in prestress or support conditions) based on stress stiffening, and the combination with a numerically efficient algorithm, i.e., Nelson’s method. One of the main advantages of the employed damage diagnosis algorithm is that, although it uses physical models for damage detection, it considers the uncertainty in the data-driven features, which enables a reliabilitybased approach to determine the probability of detection. Moreover, the algorithm can be trained and the probability of detecting future damages can be predicted based on data and a model from the undamaged structure,
in an unsupervised learning mode, making it particularly relevant for unique structures, where no data from the damaged state is available. For proof of concept, a numerical case study is presented. The study assesses the loss of prestress in a two-span reinforced concrete beam and showcases suitable validation approaches for the sensitivity calculation.
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.
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) 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.
The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation.
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.
The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation.
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.