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This presentation discusses the potentials of probabilistic methods in offshore foundation installation, from the perspective of probabilistic ground models and data-driven site characterization. We discuss about methodologies for utilizing site-specific geotechnical (CPT) and geological data, aiming to construct an integrated ground model that can predict stratigraphic profiles and useful for geotechnical design parameters at any location within a 3D domain. The predicted parameters and stratigraphy are then used to predict the probability of potential pile tip damage, upon collision with a boulder.
The aim of the study is to infer the soil stratification from the provided CPT and borehole data. We infer the soil type at any location within the domain of interest from the SBT index Ic (Robertson, 2009). This index can be directly related to the CPT data through an empirical correlation model. In addition, the soil classes contained in the borehole logs can be expressed as bounds on Ic. A log-transformation was applied to Ic, Y = ln(Ic), and Y was modelled by a 3D Random Field, with a fully Bayesian hierarchical Gaussian Process model to explicitly capture uncertainties.
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
Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM) approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a General reference model is obtained from data in the reference state at several known reference temperatures.
Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space Matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
Subspace-based damage detection handling temperature effects and uncertainty in the reference
(2019)
Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM)approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a general reference model is obtained from data in the reference state at several known reference temperatures. Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
Fault detection for linear parameter varying systems under changes in the process noise covariance
(2020)
Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only Systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models { each estimated from data measured in a reference state { are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then con icts May arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.
For the generation of renewable energy offshore wind farms play an important role. The majority of these wind generators are connected to steel foundation structures. Steady increasing power output of these wind turbines leads to new challenges as well for engineers of the related support structures. Caused by the high-cyclic loading of these structures by wind and waves fatigue plays a very important role. Besides the consideration of fatigue within the design process it is additionally an important topic and challenge to monitor the existing steel structures relating to potential fatigue cracks occurring during their lifetime. This plays a role for a fundamental understanding of mechanisms as investigated in testing but also for inspection in real structures.
Since the structures of the offshore wind generators are very large and in addition partially under water effective and reliable methods for fatigue crack detection are required. This contribution will present results of recent investigations on different crack detection methods applied on high-cycle fatigue tests on small welded steel samples as well as on welded steel components. The comparison of these measurements will show what are the advantages and disadvantages of the different methods and which method is potentially more suitable for the application on real offshore wind structures. It is outlined where challenges for detection methods exist.
Furthermore, in this context the resulting challenges for the execution of material testing especially caused by the increasing dimensions of wind energy converters will by exemplarily presented.
At present, to produce renewable energy offshore wind farms play an important role. The available space combined with the more valuable wind conditions make offshore locations very attractive for wind powered energy production. In Europe a significant number of offshore wind farms already exist, especially in the North and Baltic Sea. In future this trend will continue, and further offshore wind farms will be built. The majority of offshore wind turbines are mounted on steel foundation structures. Due to the high-cyclic loading by wind and waves fatigue stress plays a substantial role regarding structural safety.
Besides the consideration of fatigue within the design process, to monitor existing steel structures for potential fatigue cracks during their life time is a major topic and a challenge.
For the structures of the offshore wind turbines are large and partially under water effective reliable methods for the detection of fatigue cracks are required.
This contribution presents investigations on different crack detection methods applied at high-cycle fatigue tests on small-scale welded steel samples as well as on large-scale welded steel components. The tests were conducted at the BAM laboratories. For crack detection mainly three different methods were used and compared. The first method regards to the measurement of strain by conventionally strain gauges. Secondly, the crack luminescence was used as a new and effective optical method for surface monitoring. And finally, crack detection by pressure differentials of the inner and outer section of tubular steel elements was investigated. A comparison study will emphasize the advantages and disadvantages of the different methods and show which of the described methods is potentially more suitable for an application on real offshore wind structures.
Fatigue in Concrete
(2019)
The current knowledge about fatigue behavior of concrete is still incomplete. This concerns especially the progress of fatigue which precedes the fatigue failure. An overview on the fatigue behaviour in concrete is given. Therefore, the process of fatigue itself under cyclic compressive loading was investigated in a systematic and comprehensive way. The aim of this investigation was to obtain a deeper insight and to provide a better understanding of the damage process occurring within the material during fatigue loading.
Almost all building materials in civil engineering have an open porosity and interact with or are affected by the environmental conditions. Structures might suffer from effects such as moisture adsorption, carbonation, corrosion, penetration of salt ions and chemical substances, etc. In the hygroscopic range, these processes are mostly driven by diffusion. Due to the confinement of small pores ( 1 m), the Knudsen effect reduces the molecular diffusion. This reduction can become more significant in case of temporal changing pore systems because of physisorption of water vapor, carbonation, or chemisorption.
In this study, unstabilised earth blocks and earth masonry are investigated. In a first step, the pore size distribution of the blocks is measured and sorption isotherms are recorded in experiments. Besides the ordinary physisorption, the involved clay minerals undergo swelling or shrinking due to chemisorption. The following two effects must be considered: first, the reduction of the available pore space by the adsorbed water layer. For this, the Hillerborg sorption theory is used, which is a combination of the well-known Brunauer-Emmett-Teller sorption theory and the Kelvin equation. This allows the computation of adsorbed water layers even in curved pore geometries. Second, the variation of the initial pore size distribution due to chemisorption needs to be modelled. Based on these two models, the effective diffusion coefficient can be predicted. For validation, arrays of relative humidity sensors were embedded into a free-standing earth masonry wall. This monitoring was carried out over more than a year to have a broad variety of environmental conditions and was located in Berlin, Germany.
The prediction of the effective diffusion coefficient can also be transferred to other processes and allows the investigation of materials having temporarily changing pore systems. Examples are the carbonation of cementitious materials, alkali silica reaction, calcium leaching of long-lasting structures, etc. This effect becomes most prominent in the meso-pore range and might alter the effective diffusion coefficient by more than 100 %.
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.
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) 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.
Inspection and maintenance contribute significantly to the lifetime cost of bridges. There is significant potential in using information obtained through structural health monitoring to update predictive models of the condition and performance of such structures, and thus ena-ble an improved decision-making regarding inspection and maintenance activities. Within the AISTEC project funded by the German Federal Ministry of Education and Research, we develop vibration-based structural health monitoring systems aimed at continuously provid-ing information on the structural condition of bridges. Environmental variations such as changing ambient temperatures can significantly influence the dynamic characteristics of bridges and thus mask the effect of structural changes and damages. It remains a challenge to account for such influences in structural health monitoring. To study the effect of ambient temperatures on the dynamic characteristics of beam structures, we monitor the vibration response of a reinforced concrete beam in the uncracked and cracked state at varying tem-peratures in a climate chamber. We postulate a set of competing parameterized probabilistic structural models, which explicitly account for the effect of varying ambient temperatures on the mechanical properties of the system. We then combine the information provided by the structural models with the information contained in the recorded vibration data to learn the parameters of the temperature-dependent structural models and infer the plausible state of the beam using Bayesian system identification and model class selection.
Remediation of Cracks Formed in Grouted Connections of Offshore Energy Structures under Static Loads
(2018)
The future energy demand necessitates the exploration of all potential energy sources both onshore and offshore. Global trend has shifted towards offshore energy, which can be obtained from either carbon intensive or renewable options, hence requiring structures such as rigs, platforms, and monopiles. Most of these structures adopt easily installable construction techniques, where lower foundation need to be connected with the super structure by mean of grouted composite joints. Generally, these composite connections have exterior sleeve, interior pile and infill grout. Being located in remote offshore conditions, connections can experience considerable adverse loading during their lifetimes. Degradations were reported inside similar connections, which were installed in last three decades. Besides, grouting in the offshore sites may often be proven difficult, which eventually leads to reduced 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 the future. This study aims at characterizing the nature of crack generation in grouted connections and thereby identifying the potential of repair using suitable repair material. Scaled grouted joints were manufactured using a novel mold, and connections were loaded under static load to visualize the main failure pattern. The failure mechanism and loading capacity are found compatible to previous results from earlier literature. Grouted connection was then repaired using cementitious injectable grout. The effectiveness of the repair system is also discussed.
Superplasticizer and shrinkage reducing admixture dosages for microfine cement in grout systems
(2018)
Grouts have numerous applications including crack repair as maintenance in construction industries. Microfine cements are intensively used for high strength mortar and grout products. They are ideal for injection grouting in structural repair. Such grouts should have suitable rheological properties to be injectable, especially those used in repair and rehabilitation. The use of superplasticizers (SP) in these products is thus becoming increasingly crucial to achieve favorable workability and viscosity properties. A difficulty in such grouts is the plastic shrinkage due to finer particles used. It is thus necessary to determine optimum SP and shrinkage reducing admixture (SRA) dosages for a microfine cement based grout. In this study, a saturation dosage was decided from two Polycarboxylate ether (PCE) based SPs in relation to neat cement using slump flow and rheological parameters. A range of grout mixtures was formulated containing micro silica (MS) and fly ash (FA), and tested for suitable rheological and mechanical parameters. Based on the results, a grout mixture with MS and FA was selected to determine optimum SRA content. According to the results, a SP dosage of 3% by weight of neat cement is sufficient to achieve saturation. The grout material including MS and FA can produce comparable properties to neat cement grout. MS is found to improve compressive strength within the range considered, whereas a higher FA content provides favourable rheological properties. Finally, a SRA dosage of 4%, which could reduce the shrinkage by about 43% after 28d days, is determined for the grout system.
Grouting is a universal repair and strengthening technique, which is constantly used for structural remediation of concrete components, trenches, mine subsidence, dam joints, restoration of masonry structures, and geological stabilizations. Having an extremely small particle size of only few microns, ultrafine cements are ideal for grouting applications due to their superior permeability and compressive strength properties of the hardened cement paste compared to that of the less-expensive, but coarser ordinary Portland cements. Supplementary cementitious materials (SCMs) are often used to replace ultrafine cement in order to modify certain properties and to reduce costs. The aim of this experimental study is to investigate the effect of three supplementary materials: microsilica (MS), fly ash (FA), and metakaolin (MK) on the workability, and mechanical properties of an ultrafine cement based grout with a constant water-binder ratio and constant superplasticizer content. Maximum percentages of replacement with ultrafine cement were 6% by volume of cement for MS and 16% for FA, and MK. In general, results suggest that the workability is improved by addition of FA, whereas is reduced, when modified with MS and MK. The compressive strength of grout after cement replacement remains comparable to that of pure cement grout. However, there is a tendency of the MS to positively affect the compressive strength opposite to FA, whereas flexural strength is positively affected by FA. Based on the results, it is evident that grouts with Hägerman cone flow more than 500 mm and compressive strength of more than 90 MPa after 28 days can be produced.
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.
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.
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.
Owners or operators of offshore wind farms perform inspections to collect information on the condition of the wind turbine support structures and perform repairs if required. These activities are costly and should be optimized. Risk-based methods can be applied to identify inspection and repair strategies that ensure an optimal balance between the expected total service life cost of inspection and repair, and the achieved risk reduction. Such an optimization requires explicit modeling of repairs. In this paper, the impact of different repair models on the results of a risk-based optimization of inspection and repair strategies is quantified in a numerical example considering a jacket-type steel frame subject to high-cycle fatigue. The example showed that, in this specific application, there is no need for detailed modeling of the behavior of repaired welded connections.
Identifying optimal inspection and repair strategies for offshore jacket structures is a challenging task. We pre-sent an approach, which is based on recent developments in the field of risk-based operation and maintenance planning at the structural system level. The approach utilizes heuristics to define inspection and repair strate-gies at the system level and to reduce the search space of possible strategies. For each defined strategy, the expected service life cost of inspection, repair and failure is evaluated based on simulated inspection and re-pair histories. Subset simulation is applied to compute the conditional repair and failure probabilities required for this analysis. It also forms the basis for simulating inspection and repair histories. The strategy that mini-mizes the expected service life cost is the optimal one in the set of pre-selected strategies. The underlying condition and performance model accounts for the stochastic dependence among the deterioration states of the different structural elements and the structural redundancy. The approach is demonstrated in a case study considering a jacket-type frame. In this study, we essentially vary the inspection interval, the minimum num-ber of inspected components and the target reliability, and identify the combination that minimizes the ex-pected total service life cost.
The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
Current standards like ISO 14837-32:2015 and DIN EN 1998-1/NA:2021 as well as prEN 1997-2:2022 allow for using correlations between the results of in-situ soil penetration tests and shear wave velocity (or shear modulus) to determine soil properties to be used in dynamic analyses. While the ISO and prEN standards even provide some recommendations on specific correlations to be used, the DIN standard does not. Due to the statistical nature of such correlations their general applicability has to be verified. We collected data sets from test sites from Germany as well as New Zealand at which cone penetration tests (CPT) as well as seismic site investigation methods were conducted. These sites comprise sandy soils as well as clayey soils, mixed soils as well as glacial soils. We compare the results of several correlations between CPT results and shear wave velocity. The accuracy of such correlations is assessed with respect to the accuracy of seismic in-situ tests. It turns out that for clean sands such correlations between CPT and Vs have a similar order of variability as seismic in-situ tests conducted at the same site. The higher the fines portion of the soil, the higher the variability of the statistical correlations, and consequently the less the general applicability. For glacial soils and other special soil types usage of statistical correlations to determine dynamic soil properties is not recommended.
Nowadays geotechnical engineering firms have powerful software tools to extent their consulting business also into dynamic soil-structure interaction, which before has been restricted to a rather small community of specialized experts in this field, and they certainly do. This is particularly true with respect to non-seismic sources, that is all kinds of human induced vibrations. Hence, there is a demand from clients as well as from contractors to have guidance on the requirements as well as the limits of numerical modelling of soil-structure interaction. From the literature as well as from relevant standards, recommendations for the numerical modelling of soil-structure interaction problems involving seismic actions are well known, e. g. ASCE/SEI 4-16. There are, however, some particularities when dealing with human-induced vibrations, which are absent in seismic analyses. For human-induced excitations very little specific guidance has been published in the past. A machine foundation on a homogeneous half space excited by harmonic loads with excitation frequency between 4 Hz and 64 Hz has been analysed by means of several commercially available software packages. Parametric studies have been performed to verify if recommendations for seismic soil-structure analyses are valid for non-seismic analyses as well. This paper provides details on the benchmark example and the most important conclusions from the undertaken parametric studies.
This article presents a solid cohesion model for the simulation of bonded granular assemblies in the frame of 3D discrete element approaches (DEM). A simple viscoplastic cohesion model for 2D geometries is extended to 3D conditions, while its yield criterion is generalized as a hyper-surface in the space of bond solicitations to include torsional moments. The model is then calibrated using experimental results of uniaxial traction at both the microscopic and macroscopic scales with an artificial granular cohesive soil. The paper finally presents some simulated results on the macromechanical sample traction application and briefly discusses the model's current limitations and promising prospects for subsequent works.
Measured train passages and hammer impacts in combination with track-soil calculation have been successfully used for the detection of damaged slab tracks. This approach is now extended to intact slab and ballast tracks. The vibrations of many tracks have been measured at several levels from rail, sleeper, track plate, base plate, base layer to the subsoil by velocity or acceleration sensors. The time histories have to be integrated once or twice to get the displacements. The displacement signals include an arbitrary time-dependent shift which must be eliminated or respected in the interpretation. On the other hand, the calculation of slab and ballast tracks have been done in frequency-wavenumber domain. The displacements along the track and the frequency-dependent compliance transfer functions can be calculated. The latter can be compared with the results of the hammer impacts on the track. The deformation of the track can be transformed to time histories for a whole train and compared to the measured train passages. Many slab (and ballast) tracks have been measured at different sites. The displacements of the tracks are presented, and the following parameters have been analysed in the measurement results: slab track vs. ballast track, different types of slab tracks, damaged slab tracks, different trains, switches at different measuring points, an elastic layer, the mortar layer, different soils at different places. The soil should have the dominant influence on the track-plate displacements. Slab and ballast track yield also big differences in maximum displacement and width of deformation. Some of the preceding aspects will be analysed in comparison of measurement and theory.
Explosion-induced ground vibrations have been measured at several places. Results about the wave propagation are shown in this contribution. The particle velocities of the soil have been measured at up to 1000 m distance from the explosion and are presented as time records (seismograms) and one-third octave band spectra (transfer functions). The results are compared with the results of hammer impacts. The seismograms clearly show different wave types, compressional waves of the air, the water and the soil, and the Rayleigh wave. The hammer impacts yield good results up to 100 m and incorporate higher frequencies at about 50 Hz, whereas the explosion results in a ground vibration with frequencies around 10 Hz and a longer range of influence. Explosion and hammer excitations are evaluated for the wave velocities of the soil by using the wavenumber and the spatial auto-correlation method. The attenuation of the ground vibration amplitudes A with distance r can well be presented by a power law A ~ r -q. This type of amplitude-distance law and the corresponding power q > 1 are substantiated in the contribution. The influence of the charge weight W is evaluated as an additional power law A ~ W -p for each measuring site. The power is found quite similarly around q 0.6 as all sites have a medium soft soil such as sand and clay. The obtained amplitude-charge-distance law can be used to predict the explosion-induced ground and building vibrations at other sites.
As many wind turbines approach the end of their design lifetime, from a technical point of view, comprehensive fatigue analysis of all critical parts is necessary to decide what comes after – continued operation, repowering, or decommissioning. Typically, it is a two-stage evaluation process consisting of a physical inspection of the structure and an analytical part to compare the design and actually experienced loading conditions. Structural health monitoring helps to reduce the uncertainties in the estimations by providing insight into deviations between the designed and the built structure. Furthermore, it allows the evaluation of the consumed fatigue lifetime by analyzing the strain measurements that mirror the actual structural response to experienced environmental and operational conditions. However, the measurement values are limited to a sparse number of instrumented spots on the structure, and further extrapolation to the non-instrumented (critical) sections is required to perform a complete fatigue assessment. One known approach is the external force reconstruction, which has only scarcely been considered for application in offshore wind turbines. In order to extend the previously developed thrust force reconstruction framework, this work discusses the possibilities and challenges of wind and wave loading reconstruction in offshore wind turbine support structures.
Reinforced concrete (RC) is used as structural material in most diverse civil engineering applications. For the variability of its physical properties it is still an engineering challenge to meet all necessary requirements for the prediction of dynamic effects under impact loading. In this paper, investigations are shown within the scope of quantifying and evaluating the damage caused by an impact. The experimental investigations are performed in the field of low- and medium-velocity impact. The chosen flat nose shape results in small penetrations on the top side and scabbing on the bottom side. The plate is scanned with an adapted planar tomographic examination after the impact, and the damage is analysed, afterwards. Cracks and spalling are made visible with a reconstruction. The numerical model validated on the tomographic results justifies the application for further predictions of the damage description.
Prediction of dynamic effects of reinforced concrete structures under impact loading is a technical challenge. This is a consequence of the great variability of the physical properties resulting from the wide adaptability of reinforced concrete and a consequence of the wide range of impact loading. Experiments and numerical investigations are normally used on a small scale to address the problem. In this paper, impact tests on reinforced conrete plates with the lateral dimensions of 1.5 m x 1.5 m and a thickness of 30 cm are presented. In bending reinforcement, besides the velocity two properties are varied, the diameter and the spatial distribution of the rebars. Experiments are performed at the Otto-Mohr-Laboratory of the Institute of Concrete Structures of the Technische Universit¨at Dresden. Due to the accelerated fall of the impactor the velocity ranges between 20 and 70 m/s. In addition to the measured quantities such as bearing forces, accelerations are also measured at 4 different positions on and under the plate, as well as the deflection at several positions. The measured data are used for the analysis of the damage form and the numerical examinations with the program Ansys Autodyn and the material model after Drucker-Prager. Numerical investigations support the tests, with detailed analysis of individual effects. These numerical computations and the planar tomographic investigations were carried out at BAM in Berlin. With the help of planar tomographic evaluation, the damaged structure is made visible and compared with the numerical results. Influences of the bending reinforcement are explained on the basis of damage evaluation in the local area and on selected measured values. In addition to the test evaluation, the tomographic and numerical methods are presented.
Due to the many possible applications, the uncomplicated production and the high application range, reinforced concrete is a widely used building material. This large range of physical material properties still poses an engineering challenge in determining all necessary requirements for predicting dynamic effects under impact load.
Many aspects of impact have already been examined and some correlations have been studied intensively. Examples are the work of Lastunen and Booker, who studied the influence of projectile properties on the impact form. Li has also investigated the local effects of an impact. The field of detailed damage analysis has not been in focus so far.
This presentation shows some studies in medium-velocity impact with the focus on post-impact damage evaluation. The impactor is modified so that the test plates show low penetration on the top and scabbing on the bottom. With the unique tomography lab test stand at BAM the plate is scanned after the impact and the damage is analyzed. Cracks and scabbing are made visible with a reconstruction. The comparison of simulation and tomography allows to create prognosis models for damage characterization.
The local asymptotic approach is promising for vibration-based fault diagnosis when associated to a subspace-based residual function and efficient hypothesis testing tools. It has the ability of detecting small changes in some chosen system parameters. In the residual function, the left null space of the observability matrix associated to a reference model is confronted to the Hankel matrix of output covariances estimated from test data. When this left null space is not perfectly known from a model, it should be replaced by an estimate from data to avoid model errors in the residual computation. In this paper, the asymptotic distribution of the resulting data-driven residual is analyzed and its covariance is estimated, which includes also the covariance related to the reference null space estimate. The importance of including the covariance of the reference null space estimate is shown in a numerical study.
The shaft bearing capacity often plays a dominant role for the overall structural behaviour of axially loaded piles in offshore deep foundations. Under cyclic loading, a narrow zone of soil at the pile-soil interface is subject to cyclic shearing solicitations. Thereby, the soil may densify and lead to a decrease of confining stress around the pile due to microphenomena such as particle crushing, migration and rearrangement. This reduction of radial stress has a direct impact on the shaft capacity, potentially leading in extreme cases to pile failure. An adequate interface model is needed in order to model this behaviour numerically. Different authors have proposed models that take typical Interface phenomena in account such as densification, grain breakage, normal pressure effect and roughness. However, as the models become more complex, a great number of material parameters need to be defined and calibrated. This paper proposes the adoption and transformation of an existing soil bulk model (Pastor- Zienkiewicz) into an interface model. To calibrate the new interface model, the results of an experimental campaign with the ring shear device under cyclic loading conditions are here presented. The constitutive model shows a good capability to reproduce typical features of sand behaviour such as cyclic compaction and dilatancy, which in saturated partially-drained conditions may lead to liquefaction and cyclic mobility phenomena.
The structural performance of many geotechnical systems (e.g. axially-loaded pile foundations), depends on the shearing resistance at the soil interface, which may govern the load bearing capacity of the foundation. Experimental investigations have shown that this interaction is mainly localised within a narrow shear band next to the structure. Under cyclic loading, a contraction of the soil at the interface may arise (net volume loss), possibly leading to a stress relaxation and thus to a reduction of the load bearing capacity (the so-called friction fatigue). Based on the constitutive similarities between soil continua and interfaces, we propose here the adaption of a Generalized Plasticity model for sandy soils for the numerical analysis of interface problems. In this contribution, the results of an experimental campaign for the parameter calibration of the constitutive model are presented. The tests have been conducted with a ring shear device involving different normal stresses, roughness of the steel plates as well as cyclic loading. The new modelling approach shows promising results and has the additional practical advantage that the interface zone and the soil continuum can both be described with the same constitutive model in general boundary value problems.
The response of many geotechnical systems, whose structural behavior depends on shearing effect, is closely related to soil structure interaction phenomenon. Experimentally it is found that the localisation of these effect happens at a narrow soil layer next to the structure. Numerically, this behavior can be modelled through interface elements and adequate constitutive models. In this work, a constitutive model in the framework of Generalized Plasticity for sandy soils has been chosen to be adapted for the interface zone.
From the direct shear experiments a sandy soil at loose and dense states under different normal pressures is considered. The adapted constitutive model is able to reproduce contraction and dilatation of the soil according to its relative density and it shows a good agreement with the experimental data.
Global energy consumption will increase in the future necessitating both fossil fuels and renewable energy choices - especially wind energy. Such high energy demand requires installation of offshore energy structures, rigs, platforms and towers, which are susceptible to adverse environmental conditions along with maintenances. Due to their large size and remote locations, cylindrical grouted joints are often adopted between substructure and foundation in these offshore platforms and wind structures such as monopiles. However, these connections are composite structures with exterior sleeve, interior pile and infill mortar. Degradation and settlements were reported inside similar connections, which were installed in last three decades. Besides, grouting in the offshore sites were proven difficult to obtain ideal load bearing capacity. In-situ loading conditions were also found to be affecting the failure mechanism inside such connections. This study aims at characterizing the nature of cracks generated in these grouted connections under both static and cyclic loading. Scaled grouted joints were manufactured using a novel reusable mold, and connections were loaded to failure to visualize the main failure patterns. An assessment between failure under these two types of load is drawn along with comparison to previously available literature.
Grouts are particularly favoured in rehabilitation of structures due to penetrability and convenience of application. Grouts for repair applications typically require high-performance properties such as rapid strength development and superior shrinkage characteristics. Sometimes industrial by-products referred as supplementary cementitious materials (SCM) are used with neat cement due to their capabilities to provide binding properties at delayed stage. Micro silica, fly ash and metakaolin are such SCMs, those can modify and improve properties of cement products. This study aims at investigating long-term mass loss and linear shrinkage along with long-term compressive and flexural strength for grouts produced from ultrafine cement and SCMs. A series of mixtures were formulated to observe the effect of SCMs on these grout properties. Properties were determined after 365 days of curing at 23 °C and 55% relative humidity. The effect of SCMs on the properties are characterised by statistical models. Response surfaces were constructed to quantify these properties in relation to SCMs replacement. The results suggested that shrinkage was reduced by metakaolin, while micro silica and fly ash had positive effects on compressive and flexural strength, respectively.
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.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
The identification of the dynamic behavior of structures, like bridges and towers, is relevant to address multiple issues. In many cases the dynamic parameters should be acquired only once or at a frequency that doesn’t justify the installation of distinct vibration sensors for a long-term monitoring. To identify modal frequencies of a structure, a drone based mobile sensing platform has been implemented. This sensing platform measures the relative displacement be-tween the structure and the drone, which also shows a strong dynamic behavior under wind tur-bulences. By regarding the dynamic model of the drone and additional measurements at the dis-tance sensor the absolute movement of the structure can be estimated based on the measured relative distance. This time domain data is a suitable input for various operational modal analysis algorithms. The system has been used to identify the dynamic properties of test and real structure, like a 1.5 MW wind turbine tower.
At the Bundesanstalt für Materialforschung und -prüfung (BAM) full scale specimens for nuclear transport and storage containers (casks) are tested for their structural integrity in a series of drop tests on the Test Site Technical Safety in Horstwalde, 50 km south of Berlin. These drop tests cause a major stress not only on the casks, but also on the steel tower structure of the test facility, itself. The load pattern makes the structure very interesting for detailed investigation. The focus of the monitoring lies on the bolted joints of the flange connections that are a typical connection for cylindrical elements if welding is technical or economical unfavorable. The definition of the monitoring takes was done by investigating the existing documents and inspection results accompanied by building an initial digital representation of the structure, consisting of two finite element (FE) models and a geometrical 3D point cloud representation. As a first step the structures behavior during static and dynamic loading was analyzed using measurement data and an updated numerical FE Model. The idea behind is to use models for a digital planning and operation/evaluation of the structural health monitoring. A static FE simulation and a dynamic FE simulation are generated, to investigate how the structure behaves under the load conditions.
The long-term preservation of our infrastructure requires not only intelligent sensor technology and highly developed monitoring procedures, but also innovative digital tools for analyzing, evaluating and utilizing the results. This includes mathematical and, in particular, probabilistic methods for damage detection and tracking as well as for calculating service life and maintenance cycles and data management. The example project Maintal Bridge Gemuenden as part of the AISTEC project shows the workflow for the implementation of structural health monitoring and experimental tests with a train of Deutsche Bahn. The influence lines, as one possible way for damage detection, were measured with a highly accurate GNSS System to locate the trains position when crossing the bridge. The results were compared to measurements from 1987 just before the bridge went in operation.