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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.
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.
Die Grundidee einer Schwingungsminderung ist es eine tiefe Eigenfrequenz der Struktur zu erreichen, so dass höhere Frequenzen abgemindert werden. Das gilt für die Minderung an der Quelle, zum Beispiel einem Eisenbahngleis, und für die Minderung am Empfänger, dem Gebäude. Die Eigenfrequenz ermittelt man aus dem Verhältnis der Auflagersteifigkeit und der Masse. Wie ist die Masse bei einem Gebäude zu wählen? Und wie ist die Untergrundsteifigkeit zu berücksichtigen? Als Referenzsituation ohne Minderungsmaßnahme? Der Beitrag bringt Rechenergebnisse zu abgefederten Gebäuden mit einfachen und komplexen (FE-) Modellen, Mess- und Rechenergebnisse zur Schwingungsübertragung von unabgefederten Gebäuden. Es wird der Einfluss der Abstimmfrequenz, der Bodensteifigkeit und der „starren“ Gebäudemasse untersucht. Die komplexen Gebäudemodelle erlauben, neben der Berechnung einer elastischen Gebäudelagerung, auch die Variation von Gebäudeparametern zur Reduktion der Deckenschwingungen. Den Ergebnissen bei der Erschütterungs-übertragung in Gebäude werden zwei ähnliche Beispiele zur elastischen Maschinenlagerung und zur elastischen Gleislagerung gegenübergestellt.
This paper scopes the specialties of a hazard identification study for large and extra-large unmanned undersea vehicles (UUVs). A generic node/function structure is derived from different large and extra-large UUV designs, partially own vehicle designs from research projects, and partially from commercial vehicles. For each node, a short overview of its components and the proper function or operations is defined. A set of guide words is used to prompt a hazard discussion for each node, which identifies unwanted functions, resulting in potential hazards and unmitigated consequences. Related to the SafeMASS-Report from DNV, this work concentrates on selected topics of the bridge-related function on voyage, control & monitoring, and abnormal situations. For unmanned vehicles without any person on board, these three topics become more important for underwater vehicles with very limited connectivity or temporary disruptions of communication whereby an operator in a remote-control center could only be provided with rough vehicle or mission states. Therefore, vehicle control, whether in hard- or software, must handle most tasks belonging to the considered functions automatically or autonomously. Hence, the most appropriate reactions of the system to unwanted system
behavior must be implemented. This HAZID study could, on the one hand, be used as background for such an implementation, and on the other hand, it is used to verify the implemented actions on the risks and hazards.
In the last three decades, the vibrations of many floors and bridges have been measured. The contribution shows some evaluation methods, experimental results and some modelling and theoretical results. Simple evaluation methods have been developed for single and coupled floors. Two coupled beams have been measured in good agreement with the theory. A more complex coupling model has been found for a large wooden floor in a castle consisting of six floor bays which correlates well with the measurements. Damaged and intact poles have been tested by their natural frequencies and damping values, and a fair correlation between the degree of damage and the shift of the frequency. Road bridges have been analysed in detail and some examples are presented. Railway bridges and trains are studied for resonant excitation. The risk of resonance can be estimated in frequency domain by using axle-sequence spectra of the train and the natural frequencies of the bridge. A measurement example shows the amplification, but even stronger the cancellation of the subsequent axle responses. Several high-speed trains and freight trains have been analysed for their potential resonance amplification.
The authors are currently investigating the possibility to apply compaction grouting for offshore pile foundations (Jacket piles as well as monopiles) as a possible retrofitting technique for an optimised foundation concept. In this research project, we are developing a design approach aiming to predict the ideal amount and properties of a grout for a specific soil situation and desired improvement of pile bearing capacity after Installation and during service time. Both numerical and experimental tests have been carried out to investigate the injection process during which a highly viscous grout is injected into the soil under high pressure to displace and compact the surrounding soil without fracturing it. The implicit Material Point Method (MPM) based on a mixed formulation is the numerical technique chosen to deal with the expected large deformations and the arbitrary shape of the developing grout bulb. The usage of MPM prevents both the need of remeshing and the numerical instability induced by extensive mesh distortion. For validation with experimental results, we have constructed a testing chamber with one transparent sidewall. This chamber enables us to observe the injection process directly at the transparent vertical window and to measure the in-plane soil displacements and strains by means of the Digital Image Correlation (DIC) technique.
The results already reveal the interrelation of soil and grout properties for a successful usage of this common ground improvement technique.
Environmental based perturbations influence significantly the ability to identify structural dam-age in Structural Health Monitoring. Strategies are needed to classify such effects and consider them appropri-ately in SHM. It has to be considered if seasonal effects just mask the structural response or if temperature itself correlates to a weakening of the structure. 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 considering environmental as well as damage-based changes of stiffness values. With the background of increasing affordability of sensing and computing technology, effort should be made to increase sensitivity, reliability and robustness of proce-dures, separating environmental from damage caused changes in SHM measures. The contribution describes an attempt to evaluate both general strategies, their advantages and drawbacks. In addition, two vibration moni-toring procedures are introduced, allowing for temperature-based perturbations of the monitoring data.
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 conflicts 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.
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 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 advantages of the data-driven residual are demonstrated in a numerical study, and the importance of including the covariance of the reference null space estimate is shown, which increases the detection Performance.