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Lifetime aspects including fatigue failure of concrete structures were traditionally only of minor importance. Because of the growing interest in maxing out the capacities of concrete, its fatigue failure under compression has become an issue. A variety of interacting phenomena such as e.g. loss of prestress, degradation due to chemical reactions or creep and shrinkage influence the fatigue resistance. Failure due to cyclic loads is generally not instantaneous, but characterized by a steady damage accumulation. Therefore, a reliable numerical model to predict the performance of concrete over its lifetime is required, which accurately captures order effects and full three-dimensional stress states.
Many constitutive models for concrete are currently available, which are applicable for specific loading regimes, different time scales and different resolution scales.
However, a key limitation of those models is that they generally do not address issues related to fatigue on a structural level. Very few models can be found in the literature that reproduce deterioration of concrete under repeated loading-unloading cycles. This is due to the computational effort necessary to explicitly resolve every cycle which exceeds the currently available computational resources. The limitation can only be overcome by the application of multiscale methods in time.
The objective of the paper is the development of numerical methods for the simulation of concrete under fatigue loading using temporal multiscale methods.
First, a continuum damage model for concrete is developed with a focus on fatigue under compressive stresses. This includes the possibility to model stress redistributions and capture size effects. In contrast to cycle based approaches, where damage is accumulated based on the number of full stress cycles, a strain based approach is developed that can capture cyclic degradation under variable loading cycles including different amplitudes and loading frequencies. The model is designed to represent failure under static loading as a particular case of fatigue failure after a single loading cycle. As a consequence, most of the material parameters can be deduced from static tests. Only a limit set of additional constitutive parameters is required to accurately describe the evolution under fatigue loading. Another advantage of the proposed model is the possibility to directly incorporate other multi-physics effects such as creep and shrinkage or thermal loading on the constitutive level.
Second, a multiscale approach in time is presented to enable structural computations of fatigue failure with a reduced computational effort. The damage rate within the short time scale corresponding to a single cycle is computed based on a Fourier based approach. This evolution equation is then solved on the long time scale using different implicit and explicit time integration schemes. Their performance and some limitations for specific loading regimes is discussed.
Finally, the developed methods will be validated and compared to experimental data.
Half-cell potential mapping (HP) is the most popular nondestructive test (NDT)-method for the localization of corrosion damage in concrete. It is generally recognized, that HP is prone to the environmental factors that arise from salt induced deterioration, such as varying moisture and chloride gradients. Additional NDT-methods are capable to determine distinctive areas, but cannot yet be used to estimate more accurate testing results. We introduce a supervised machine learning (SML) based approach for data fusion to make use of the additional sensor information. SML are methods that explore relations between different (sensor) data from predefined data labels. We use a simple linear classifier named logistic regression to distinguish defect and intact areas. The test performance improves drastically compared to the best single method, HP. In order to generate representative, labeled data we conducted a comprehensive experiment that simulates the deterioration-cycle of a chloride-exposed building part in the lab. Our data set consist of 18 measurement campaigns, each containing HP-, ground-penetrating-radar-, microwave-moisture-, and Wenner-resistivity-data. We detail the challenges that arise with a data driven approach in NDT and how we addressed them.
The propagation of ultrasonic waves in concrete is affected by its micro- and macro-structure, geometry and properties as well as external influences as stress, temperature or moisture. In addition, age and degradation have a strong influence. Therefore, Ultrasound has been used to monitor concrete samples and structures since decades. However, early applications using conventional techniques as time-of flight or changes in amplitudes have been limited to detect changes in a late stage close to serviceability or ultimate load states.
Around 2000, several new, more sensitive techniques adopted from geophysics or other field of material sciences have been introduced to research in ultrasonic monitoring of concrete. The most discussed methodologies are coda wave interferometry, a technique which allows to detect very subtle changes from repeated ultrasonic measurements. Nonlinear acoustic techniques help to identify e. g. cracks even in an inhomogeneous background. Both techniques can be combined.
This paper reviews methods and results achieved so far on the laboratory scale and with full scale models the directions for future research and application is given as well.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
Acoustic emission and ultrasonic monitoring of a prestressed concrete bridge in its final years
(2021)
Many European bridges built in the 1950s, 60s and 70s must be re-placed in the next decade due to structural deficiencies, insufficient load capacity or other issues. However, the existing bridges must be used for another couple of years even if flaws and damages already have been detected.
In Germany, several prestressed concrete bridges have been instrumented with acoustic emission detection systems to detect wire breaks and to provide early warning signs before failure. To evaluate and interpret the consequences of wire breaks additional instrumentation and accompanying measures as finite element modeling are required.
At a bridge in southern Germany we have complemented such a system with active ultrasonic monitoring. Repeated ultrasonic measurements are evaluated with a very sensible algorithm called coda wave interferometry. This method, inspired by seismology, has been shown to deliver early warning signs in lab experiments. Large volumes of concrete can be monitored with a limited network of ultrasonic transducers. We will report on the installation, capabilities, and lim-itations as well as first results.
Fatigue is one of the most prevalent issues, which directly influences the service life expectancy of concrete structures. Fatigue has been investigated for years for steel structures. However, recent findings suggest that concrete structures may also be significantly subjected to the fatigue phenomena that could lead to premature failure of certainfatigue prone structural elements. To date, fatigue of reinforced concrete has been given little focus. and Kknowledge on the influence factors and durability/capacity effects on this material should be improved. Current technological means to measure fatigue in civil structures like bridges and wind turbines (both onshore and offshore) are outdated, imprecise and inappropriate.
Meanwhile, this topic has got much more attention as dynamic loading on concrete structures plays an increasing role, e.g. in bridges with increasing traffic and heavier trucks, in wind energy production due to inherent vibrations e.g. in offshore wind turbine support structures affected by wind and waves.
The European Innovative Training Networks (ITN) Marie Skłodowska-Curie Actions project INFRASTAR (Innovation and Networking for Fatigue and Reliability Analysis of Structures - Training for Assessment of Risk) provides research training for 12 PhD students. The project aims to improve knowledge for optimizing the design of new structures as well as for more realistic verification of structural safety and more accurate prediction of the remaining fatigue lifetime of existing structures.
First, the INFRASTAR research framework is detailed. Then it will be exemplified through the presentation of the major results of the four PhD students involved in the work package dealing with auscultation and monitoring. This includes the development and improvement of Fiber Optics (FO) and Coda Wave Interferometry (CWI) for crack sizing and imagery, new sensor technologies and integration, information management, monitoring strategy for fatigue damage investigation and lifetime prediction.
Recent years have seen extended use of ultrasonic techniques for concrete infrastructure assessement. They are applied for quality assurance and condition assessement at bridges, power plants, dams and other important objects. However, there are still a couple of significant limitations. They include, but are not limited to depth of penetration, imaging complex structures or early stage detections of distributed damage. The talk will give information on recent research in this area. Specifically, the application of the unique deep penetration system LAUS is shown. Ultrasonic monitoring using embedded transducers to check for subtle and sudden changes in the material is introduced as well. Comments on initiatives for validation, standardization and certification will be given.
A significant number of German concrete motorway pavements have shown damage only a few years after construction. The alkali-silica-reaction (ASR) is often one of the reasons for this damage. German guidelines and regulations focus on the optimisation of the concrete composition to avoid damage due to ASR. Moreover, diverse research projects have dealt with the development and optimisation of ASR performance test methods with and without external alkali supply.
However, the influence of other parameters on the occurrence and intensity of a damaging ASR had not yet been taken into account. Such parameters include, e.g., insufficient curing and the modifications of concrete’s porosity due to the use of slip form pavers. Likewise, the increased traffic loading had not yet been considered. The Federal Institute for Materials Research and Testing (BAM) assesses these parameters and processes in a number of projects. These projects aim primarily to increase the durability of the concrete pavements, in particular by improving preventive measures that may be taken before or after the construction of concrete pavements. This paper gives a short overview of BAM’s projects concerning ASR in concrete pavements. Furthermore, results regarding the influence of the cyclic traffic loading on ASR are presented.
Ultrasound echo is a widely used NDT technique for determining the internal geometry of structures. Reverse-time migration (RTM) has been recently introduced to NDT applications, as an imaging method for ultrasound data, to overcome some of the limitations (e.g. imaging steeply dipping reflector) experienced by the Synthetic Aperture Focusing Technique (SAFT), the most commonly used imaging algorithm for these measurements.
The standard implementation of RTM also experiences some drawbacks caused by its imaging condition, which is based on the zero-lag of the cross-correlation between source and receiver wavefields and generates high-amplitude low-frequency artifacts. Three alternative imaging conditions, developed for seismic data applications, were tested for their ability to provide better images than the standard cross-correlation: illumination compensation, deconvolution and wavefield decomposition. A polyamide specimen was chosen for the simulation of a synthetic experiment and for real data acquisition. The migrations of both synthetic and real data were performed with the software Madagascar. The illumination imaging condition was able to reduce the low-frequency noise and had a good performance in terms of computing time. The deconvolution improved the resolution in the synthetic tests, but did not showed such benefit for the real experiments. Finally, as for the wavefield decomposition, although it presented some advantages in terms of attenuating the low-frequency noise and some unwanted reflections, it was not able to image the internal structure of the polyamide as well as the cross-correlation did. Suggestions on how to improve the cost-effectiveness of the implementation of the deconvolution and wavefield decomposition were presented, as well as possible investigations that could be carried out in the future, in order to obtain better results with those two imaging conditions.