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Die Oberflächentexturierung der Betonfahrbahndecken mittels Grinding- und Grooving steht seit einigen Jahren im Mittelpunkt der Forschung und Entwicklung des Betonstraßenbaus in Deutschland. In den vergangenen Jahren wurden die vorteilhaften Oberflächenperformances derartiger Texturen wie z.B. Griffigkeit, Ebenheit, Lärmminderung in zahlreichen Forschungsprojekten umfassend untersucht und daraus die Technologie „Texturgrinding“ entwickelt.
Im Kontext des gegenwärtig verfolgten ganzheitlichen performanceorientierten Ansatzes liegt der Fokus nun verstärkt auf der Analyse und Charakterisierung der Oberflächentopografie von Grinding- bzw. Groovingtexturen. Insbesondere gilt ein Hauptaugenmerk hierbei der zeitlichen Entwicklung der Oberflächentexturen in Abhängigkeit von äußeren Einwirkungen durch Klima und Verkehr.
Dieser Beitrag zeigt, dass durch den Einsatz eines auf Streifenlichtprojektion basierenden Messsystems, eine hochaufgelöste dreidimensionale Erfassung der Oberflächentopografie verschiedenartiger Grinding- und Groovingtexturen möglich ist. Darauf aufbauend wurden messtechnische Voraussetzungen zur Gewährleistung reproduzierbarer Messungen geschaffen, die eine Dokumentation der zeitlichen Texturveränderungen infolge klimatischer Beanspruchung ermöglichen. Anschließend wurden Auswerteroutinen zur quantitativen und statistischen Charakterisierung der Oberflächentextur entwickelt und angewandt, um exemplarisch die Veränderungen der Oberflächentopografie infolge klimatischer Beanspruchung quantitativ abzubilden.
An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design.
This paper reports on an international ‘round-robin’ exercise conducted in 2022 aiming to take stock of the computational shell buckling expertise around the world which attracted 29 submissions. Participants were asked to perform analyses of increasing complexity on a standardised benchmark of an 8-MW multi-strake steel wind turbine support tower segment, from a linear elastic stress analysis to a linear bifurcation analysis to a geometrically and materially nonlinear buckling analysis with imperfections. The results are a showcase of the significant shell buckling expertise now available in both industry and academia.
This paper is the first of a pair. The second paper presents a detailed reference solution to the benchmark, including an illustration of the Eurocode-compliant calibration of two important imperfection forms.
A systematic approach was used to investigate the weathering-induced degradation of a common water–based intumescent coating. In this study, the coatings are intended for humid indoor applications on steel substrates. The coating contains ammonium polyphosphate, pentaerythritol, melamine, and polyvinyl acetate. By replacing each ingredient with a less water-soluble substance, the most vulnerable substances, polyvinyl acetate and pentaerythritol, were identified. Furthermore, the weathering resistance of the system was improved by exchanging the ingredients. The coatings were stressed by artificial weathering tests and evaluated by fire tests. Thermogravimetry and Fourier-transform infrared spectroscopy were used to study the thermal decomposition. This study lays the foundation for the development of a new generation of water-based intumescent coatings.
A key limitation of the most constitutive models that reproduce a Degradation of quasi-brittle materials is that they generally do not address issues related to fatigue. One reason is the huge computational costs to resolve each load cycle on the structural level. The goal of this paper is the development of a temporal Integration scheme, which significantly increases the computational efficiency of the finite element method in comparison to conventional temporal integrations.
The essential constituent of the fatigue model is an implicit gradient-enhanced formulation of the damage rate. The evolution of the field variables is computed as amultiscale Fourier series in time.On a microchronological scale attributed to single cycles, the initial boundary value problem is approximated by linear BVPs with respect to the Fourier coefficients. Using the adaptive cycle jump concept, the obtained damage rates are transferred to a coarsermacrochronological scale associated with the duration of material deterioration. The performance of the developedmethod is hence improved due to an efficient numerical treatment of the microchronological problem in combination with the cycle jump technique on the macrochronological scale. Validation examples demonstrate the convergence of the obtained solutions to the reference simulations while significantly reducing the computational costs.
This work presents machine learning-inspired data fusion approaches to improve the non-destructive testing of reinforced concrete. The principal effects that are used for data fusion are shown theoretically. Their effectiveness is tested in case studies carried out on largescale concrete specimens with built-in chloride-induced rebar corrosion. The dataset consists of half-cell potential mapping, Wenner resistivity, microwave moisture and ground penetrating radar measurements. Data fusion is based on the logistic Regression algorithm.
It learns an optimal linear decision boundary from multivariate labeled training data, to separate intact and defect areas. The training data are generated in an experiment that simulates the entire life cycle of chloride-exposed concrete building parts. The unique possibility to monitor the deterioration, and targeted corrosion initiation, allows data labeling.
The results exhibit an improved sensitivity of the data fusion with logistic regression compared to the best individual method half-cell potential.
Additive manufacturing of alkali-activated materials currently attracts a lot of attention, because of the possibility to produce customized high-performance elements for a range of applications, potentially being more resource-efficient than conventionally produced parts. Here, we describe a new additive manufacturing process for alkali-activated materials that is based on selective laser-heating of lithium aluminate/microsilica slurries. The new process-material combination allows to manufacture elements with complex geometries at high building rates and high accuracy. The process is versatile and transferrable to structures of sizes differing by orders of magnitude. The mechanical strength of the obtained materials was in the range of values reported for conventional metakaolin-based geopolymers, and superior to what has been hitherto reported for alkali-activated materials produced by additive manufacturing. This mechanical performance was obtained despite the fact that the degree of reaction of the lithium aluminate and the microsilica was low, suggesting that significant reactions took place only at the surface of the microsilica particles.
This paper aimed to perform an exploratory literature review, focusing on the aspects of hydration and rheological properties of cementitious composites with açaí fibers. The use of natural fibers as a reinforcement in cementitious matrices has been widely studied, and açaí fiber is a promising option due to its unique characteristics. However, there is still a lack of knowledge regarding the correlation between fiber parameters and the technological properties of composites, which limits the development of new applications, such as 3D printing. The review provided an overview of the main characteristics of açaí fibers and the parameters for their application in cementitious matrices. Alkali treatment with 5% NaOH solution for 1 h shows increased mechanical and physical properties in açaí fibers. Despite the potential advantages of these composites, they pose challenges due to the different fiber surface treatment and interfacial transitions and the processing conditions of the fibers. Although small addition of açaí fibers slightly decreases the cement hydration process, keeping the cross-compatibility index high (>95). To overcome these challenges, it is necessary to evaluate the rheological behavior of cementitious materials with açaí fibers, which has not been reported in the literature. By doing so, it will be possible to optimize the processing conditions and develop new applications, such as additive manufacturing, which has never been explored with açaí fibers.
Today, short- and long-term structural health monitoring (SHM) of bridge infrastructures and their safe, reliable and cost-effective maintenance has received considerable attention. From a surveying or civil engineer’s point of view, vibration-based SHM can be conducted by inspecting the changes in the global dynamic behaviour of a structure, such as natural frequencies (i. e. eigenfrequencies), mode shapes (i. e. eigenforms) and modal damping, which are known as modal parameters. This research work aims to propose a robust and automatic vibration analysis procedure that is so-called robust time domain modal parameter identification (RT-MPI) technique. It is novel in the sense of automatic and reliable identification of initial eigenfrequencies even closely spaced ones as well as robustly and accurately estimating the modal parameters of a bridge structure using low numbers of cost-effective micro-electro-mechanical systems (MEMS) accelerometers. To estimate amplitude, frequency, phase shift and damping ratio coefficients, an observation model consisting of: (1) a damped harmonic oscillation model, (2) an autoregressive model of coloured measurement noise and (3) a stochastic model in the form of the heavy-tailed family of scaled t-distributions is employed and jointly adjusted by means of a generalised expectation maximisation algorithm. Multiple MEMS as part of a geo-sensor network were mounted at different positions of a bridge structure which is precalculated by means of a finite element model (FEM) analysis. At the end, the estimated eigenfrequencies and eigenforms are compared and validated by the estimated parameters obtained from acceleration measurements of high-end accelerometers of type PCB ICP quartz, velocity measurements from a geophone and the FEM analysis. Additionally, the estimated eigenfrequencies and modal damping are compared with a well-known covariance driven stochastic subspace identification approach, which reveals the superiority of our proposed approach. We performed an experiment in two case studies with simulated data and real applications of a footbridge structure and a synthetic bridge. The results show that MEMS accelerometers are suitable for detecting all occurring eigenfrequencies depending on a sampling frequency specified. Moreover, the vibration analysis procedure demonstrates that amplitudes can be estimated in submillimetre range accuracy, frequencies with an accuracy better than 0.1 Hz and damping ratio coefficients with an accuracy better than 0.1 and 0.2 % for modal and system damping, respectively.
Alkali-activated fly ashes have been proposed for various applications where resistance against high temperatures is required, yet several details regarding the response of these materials to heat-exposure need to be clarified. In the present study, heat-induced cracking in fly ash-based alkali-activated pastes and lightweight mortars was analyzed by in-situ acoustic emission (AE) detection during complete heating-cooling cycles (up to ∼1100 °C), augmented by thermogravimetry and ex-situ SEM and XRD analyses. The applicability of the lightweight mortars as passive fire protection coatings was assessed by recording temperature-time curves of mortar-coated steel plates. Cracking during heating was limited and associated exclusively with the dehydration of the materials in the temperature range ∼90–360 °C. However, samples heated to temperatures above ∼600 °C exhibited intense cracking on cooling. This was attributed to differential deformations caused by local sintering and partial melting at the glass transition temperature, and subsequent quenching on cooling.
Additively manufactured test specimens made of polyamide 12 (PA 12) by Laser Sintering as well as of acrylonitrile butadiene styrene (ABS) by Fused Layer Modelling, were characterised with active thermography directly after manufacturing and after artificial weathering. For this, two different excitation methods (flash and pulse heating) were used and compared, regarding their suitability for the detection of constructed and imprinted defects inside the test specimens. To increase the quality of the thermograms, data processing methods like thermal signal reconstruction (TSR) and Fourier Transformation after TSR were applied. To further investigate the long-term stability of the additively manufactured test specimens towards environmental stress, like UV radiation, heat, humidity, water contact and frost with active thermography, an artificial weathering test over 2000 hours (~3 months) was applied to the specimens. The monitoring of the changes in the optical properties of the weathered plastics was supplemented by spectral reflectance and UV/VIS spectroscopy.