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Right from the beginning of applying SHM to bridge structures it was obvious that environmental based perturbations on the measurement significantly influence the ability to identify structural damage. Strategies are needed to classify such effects and consider them appropriately in SHM. Various methods have been developed and analyzed to separate environmental based effects from damage induced changes in the measures. Generally, two main approaches have emerged from research activity in this fields: (a) statistics based tools analyzing patterns in the data or in computed parameters and (b) methods, utilizing the structural model of the bridge taking into account environmental as well as damage based changes of stiffness values.
With the back-ground of increasing affordability of sensing and computing technology, effort should be made to increase sensitivity, reliability and robustness of procedures, separating environmental from damage caused changes in SHM measures. The contribution describes both general strategies and points out their Advantages and drawbacks. As basis, a review on relevant methods was conducted. The aim of the study is to classify approaches for separating damage describing information from environmental based perturbations in dependency of the SHM objective. And such, it is intended to describe a best practice in designing concepts for Monitoring infrastructure, naturally effected by environmental influences.
This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons.
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.
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.
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.
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.
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.
Superplasticizer and Shrinkage Reducing Admixture Dosages for Microfine Cement in Grout Systems
(2019)
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.
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.
Repair is an indispensable part of the maintenance of structures over their lifetimes. Structural grouting is a widely used remediation technique for concrete components, trenches, mine subsidence, dam joints, restoration of masonry structures, and geological stabilizations. A structural grout system should be injectable in narrow spaces and hence include ingredients with finer particles. Ultrafine cements are ideal for these type of demanding grouts due to their superior properties compared to that of the less expensive, but coarser ordinary Portland cement (OPC). Supplementary cementitious materials (SCMs) are often used to replace OPC clinker based binder in order to modify certain properties and to reduce costs. The most commonly used SCMs are fly ash (FA), and ground granulated blast furnace slag (GGBS). For various special applications microsilica (MS), and metakaolin (MK) are also used. Identifying the optimum replacement contents of OPC by SCMs are a challenge during the design of such grouts. The aim of this experimental study is to investigate the effect of the selected SCMs (FA, MS and MK) on the slump flow, time of efflux, viscosity, shrinkage, and compressive and flexural strength of ultrafine cement based grouts with constant water-binder ratio and superplasticizer content. The test program was formulated using Box-Behnken design principles. Maximum percentages of replacement with ultrafine cement was 6% by volume of cement for MS and 16% for FA, and MK. The results suggest that most investigated grouts have the potential to be used for structural applications. The appropriate quadratic models are then formulated through statistical tools and presented as response surfaces. The trends indicate that fly ash improves the rheological properties, whereas microsilica and metakaolin positively affect shrinkage and mechanical properties to some extent. Based on the influence of SCMs and priorities among the properties, Decision Matrix Analysis (DMA) is carried out to select the most suitable ones among the SCMs. The analysis suggests that microsilica and fly ash are more suitable as SCMs than metakaolin without affecting the properties.
The vehicle–track interaction generates forces and consequently vibrations in the environment. The interaction has been analysed by the simultaneous measurements of vehicle, track and ground vibrations during test runs with varied train speeds. The special effects of the passage over a bridge and through a tunnel are studied and compared with the measurements on a conventional ballasted surface line. The maximum amplitudes, narrow band and one-third octave band spectra are presented for the axle-box accelerations and for the track, bridge and ground vibrations. The different frequencies and frequency bands are related to wheel out-of-roundness, track alignment errors, the sleeper passage and the wheelset–track resonance. An axle impulse component has been observed at the track, at the near-field soil and as a scattered version in the far field. Specific results can be found for the bridge track, where clearly speed-dependent bridge resonances occur due to the axle sequence of the train, and for the tunnel track where soft rail pads are responsible for a strong amplification around the wheelset–track resonance. On the other hand, the axle impulses are strongly reduced by the tunnel track, and the scattered axle impulse component is not as relevant as for the surface track. As a consequence, a strong mid-frequency amplitude reduction of the tunnel compared to the surface line has been measured for low and high train speeds by the Federal Institute of Material Research and Testing (BAM) and by other institutes.
In case one wants to predict or design the bearing capacity of a foundation pile and there are no possibilities to perform an in-situ test, such as a Cone Penetration Test, the pile bearing capacity is in most cases estimated with analytical formulas. The most known and used method is the Meyerhof method published some decades ago. There are also other design methods such as derived from a certain failure mechanism around the pile tip, which is, in most cases, wedge failure mechanism. This failure mechanism was originally developed for a shallow (infinite) strip foundation, though. Therefore, it represents a plane failure mechanism.
Numerical simulations on loaded foundation piles performed with the Plaxis software Show however, that the failure mechanism of a foundation pile represents a far more complex threedimensional failure mechanism around the pile tip.
In addition, the existing analytical methods for foundation piles are based on the vertical stresses in the soil, as if the failure mechanism is the same as of a shallow foundation. Numerical simulations, performed in Plaxis show that, not the vertical, but the horizontal stresses, play an important role on the pile bearing capacity. Plaxis represents the stresses in the soil by using the procedure. So, different horizontal soil stresses are obtained for different values of the lateral earth pressure coefficient. The results show that the pile tip bearing capacity depends strongly on the horizontal stresses in the soil, but only for. The same results were observed by using a Material Point Method (MPM). Consequently, the analytical methods should estimate the pile bearing.
A study on building vibrations has been performed by finite element calculations. Family houses, multi-storey residential buildings, office buildings and office towers have been modelled in detail. The frequency-dependent response due to a free-field excitation has been evaluated for walls, columns and floors. The ratio of building amplitudes to free-field amplitudes starts with uB/u0 = 1 at zero frequency and is usually lower than 1 at 50 Hz, the end of the frequency range considered here. In between, amplifications occur due to several reasons. There are „soil resonances“ where the whole building is vibrating on the compliant soil, “column resonances” where the upper storeys are vibrating on the compliant columns, and the “floor resonances” where the floors are vibrating excited by their supports. Results are presented for all building types, but a special focus is set on office buildings. A parameter study shows the influence of the stiffness of the soil, the number of storeys, and the width of the building. It has been found that the “soil resonance” is strongly modified by the low-frequency floor resonances for the normal office building. The main resonance of a twenty-storey office tower is determined equally by the “soil mode” and the “column mode”. It is an important observation for these office buildings that the resonances can differ for different parts of the building such as the centre, the edge, the corner, and the core of the building. This leads to non-uniform vibration modes across the building, which look like another type of “floor resonance” and which have been observed in several real building projects. Experimental results will be shown which can confirm the calculated phenomena.
A study on building vibrations has been performed by finite element calculations. Family houses, multi-storey residential buildings, office buildings and office towers have been modelled in detail. The frequency-dependent response due to a free-field excitation has been evaluated for walls, columns and floors. The ratio of building amplitudes to free-field amplitudes starts with uB/u0 = 1 at zero frequency and is usually lower than 1 at 50 Hz, the end of the frequency range considered here. In between, amplifications occur due to several reasons. There are „soil resonances“ where the whole building is vibrating on the compliant soil, “column resonances” where the upper storeys are vibrating on the compliant columns, and the “floor resonances” where the floors are vibrating excited by their supports. Results are presented for all building types, but a special focus is set on office buildings. A parameter study shows the influence of the stiffness of the soil, the number of storeys, and the width of the building. It has been found that the “soil resonance” is strongly modified by the low-frequency floor resonances for the normal office building. The main resonance of a twenty-storey office tower is determined equally by the “soil mode” and the “column mode”. It is an important observation for these office buildings that the resonances can differ for different parts of the building such as the centre, the edge, the corner, and the core of the building. This leads to non-uniform vibration modes across the building, which look like another type of “floor resonance” and which have been observed in several real building projects. Experimental results will be shown which can confirm the calculated phenomena.
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 current practice of operating and maintaining deteriorating structural systems ensures acceptable levels of structural reliability, but it is not clear how efficient it is. Changing the current prescriptive approach to a risk-based approach has great potential to enable a more efficient management of such systems. Risk-based optimization of operation and maintenance strategies identifies the strategy that optimally balances the cost for controlling deterioration in a structural system with the achieved risk reduction. Inspections and monitoring are essential parts of operation and maintenance strategies. They are typically performed to reduce the uncertainty in the structural condition and inform decisions on future operation and maintenance actions. In risk-based optimization of operation and maintenance strategies, Bayesian updating is used to include information contained in inspection and monitoring data in the prediction of the structural reliability. All computations need to be repeated many times for different potential inspection and monitoring outcomes. This motivates the development of robust and efficient approaches to this computationally challenging task.
The reliability of deteriorating structural systems is time-variant because the loads on them and their capacities change with time. In most practical applications, the reliability analysis of deteriorating structural systems can be approached by dividing their lifetime into discrete time intervals. The time-variant reliability problem can then be represented by a series of time-invariant reliability problems. Using this methodology as a starting point, this thesis proposes a novel approach to compute the time-variant reliability of deteriorating structural systems for which inspection and monitoring data are available. The problem is formulated in a nested way in which the prediction of the structural condition is separated from the computation of the structural reliability conditional on the structural condition. Information on the structural condition provided by inspections and monitoring is included in the reliability assessment through Bayesian updating of the system deterioration model employed to predict the structural condition. The updated system reliability is obtained by coupling the updated deterioration model with a probabilistic structural model utilized to calculate the failure probability conditional on the structural condition. This approach is the first main outcome of this thesis and termed nested reliability analysis (NRA) approach. It is demonstrated in two numerical examples considering inspected and monitored steel structures subject to high-cycle fatigue.
An alternative – recently developed – approach, which also follows the strategy of discretizing time, describes deteriorating structural systems with hierarchical dynamic Bayesian networks (DBN). DBN combined with approximate or exact inference algorithms also enable the computation of the time-variant reliability of deteriorating structural systems conditional on information provided by inspection and monitoring data. In this thesis – as a proof of concept – a software prototype is developed based on the DBN approach, which can be used to assess the reliability of a corroding concrete box girder for which half-cell potential measurements are available. This is the second main outcome of this thesis.
Both approaches presented in this thesis enable an integral reliability analysis of inspected and monitored structures that accounts for system effects arising from (a) the correlation among deterioration states of different structural elements, (b) the interaction between element deterioration and system failure, and (c) the indirect information gained on the condition of all unobserved structural elements from inspecting or monitoring the condition of some structural elements. Thus, both approaches enable a systemwide risk-based optimization of operation and maintenance strategies for deteriorating structural systems.
The NRA approach can be implemented relatively easily with subset simulation, which is a sequential Monte Carlo method suitable for estimating rare event probabilities. Subset simulation is robust and considerably more efficient than crude Monte Carlo simulation. It is, however, still sampling-based and its efficiency is thus a function of the number of inspection and monitoring outcomes, as well as the value of the simulated event probabilities. The current implementation of the NRA approach performs separate subset simulation runs to estimate the reliability at different points in time. The efficiency of the NRA approach with subset simulation can be significantly improved by exploiting the fact that failure events in different years are nested. The lifetime reliability of deteriorating structural systems can thus be computed in reverse chronological order in a single subset simulation run.
The implementation of the DBN approach is much more demanding than the implementation of the NRA approach but it has two main advantages. Firstly, the graphical format of the DBN facilitates the presentation of the model and the underlying assumptions to stakeholders who are not experts in reliability analysis. Secondly, it can be combined with exact inference algorithms. In this case, its efficiency neither depends on the number of inspection and monitoring outcomes, nor on the value of the event probabilities to be calculated. However, in contrast to the NRA approach with subset simulation, the DBN approach with exact inference imposes restrictions on the number of random variables and the dependence structure that can be implemented in the model.
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.