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Nuclear magnetic resonance (NMR) with focus on 1H protons is increasingly applied for non-destructive testing applications. Besides mobile NMR, laboratory devices such as the NMR core-analyzing tomograph are used. As their magnetic field is more homogeneous, they enable measurements with higher signal-to-noise ratios (SNR), but with limited sample sizes. The tomograph presented here (8.9 MHz) was constructed for a maximum sample diameter of 70 mm and length of up to 1 m. The resolution, the echo time (min. 50 µs), the SNR and the measurement type can be adjusted by means of exchangable coils. The tomograph enables measurements along the complete sensitive length, slice-selective and even 2- or 3-dimensional measurements. A movable sample lifting system thereby allows a precise positioning of the sample.
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.
In Germany there is an existing built infrastructure worth about 50 trillion Euros. The expected lifetimes of individual structures are up to 100 years. Considerable costs (annually about 35 billion Euros, the trend continues upwards) are involved in order to maintain and rehabilitate both residential as well as transportation infrastructure buildings. Most damages we observe on our built infrastructure are moisture-induced processes. Consequently reliable moisture measurement tools a highly needed for meaningful building diagnosis investigations. The optimal moisture measuring technique would be non-destructive, fast, repeatable, reliable, independent of steel in the vicinity, the surface condition or possible salt loads of the material under test. Since this is unfortunately not the case for any non-destructive method, it is often very difficult to decide for users which method to use for the particular testing problem. The only standardized methods in Germany are the “direct” and destructive Darr- and the CM tests. Although they can be highly accurate (when handled with care during the sampling), they deliver only punctual information and cannot be used for monitoring. The other, non-destructive methods are based on the change in humidity-dependent physical material properties. The underlying physics, their particular advantages and disadvantages are discussed in this paper.
Moisture measurement methods
(2016)
Moisture can cause imperfect sealings, faulty roof constructions, cracks and other kind of damages. For measuring the moisture in construction materials like concrete and screed, there are destructive(direct) and non-destructive(indirect) methods, that can be used. This presentation gives an overview and a comparison of these methods.
Measuring the moisture state of screeds is critical for floorers in order to prevent structural damages of bottom coverings. Typically destructive tests are carried out on small samples delivering only punctual information. We tested several non-destructive testing methods in terms of sensitivity in the critical low moisture range and observed substantially different drying behavior for the two tested cement based and calcium-sulphate based screed samples. Our findings are supported by moisture gradient measurements using the nuclear magnetic resonance technique.
A large amount of data and information is collected in the field of non-destructive testing (NDT) in civil engineering. The weakly structured data are usually evaluated with regard to specific testing tasks (e.g. geometry determination, damage localization, quality assurance). While the data offers great economic potential, i.e. to support construction planning, monitoring and maintenance processes, the evaluation is manual and case-by-case and therefore too inefficient for broader applications. We present recent visions and approaches how these large amounts of data need to be handled in the future and how we aim to make the acquired knowledge accessible to our stakeholders. Building on initiatives in materials research, we stress the importance of further research in the field of semantic data integration particularly motivate why an ontology is needed for the area of NDT in civil engineering.
Integration of fibre reinforcement in high-performance cementitious materials has become widely applied in many fields of construction. One of the most investigated advantages of steel fibre reinforced concrete (FRC) is the deceleration of crack growth and hence it’s improved sustainability due to e.g. decrease of permeability of concrete by aggressive substances. Additional benefits are associated with the structural properties of FRC, where fibres can significantly increase the ductility and the tensile strength of concrete. In some applications, such as tunnel linings or industrial slabs, it is even possible to entirely replace the conventional reinforcement, leading to significant logistical and environmental benefits. Fibre reinforcement can, however, have critical disadvantages and even hinder the performance of concrete, since it can induce an anisotropic material behaviour of the mixture if the fibres are not appropriately oriented. For a safe use of FRC in the future, reliable non-destructive methods need to be identified to assess the fibres’ orientation in hardened concrete. In this study, ultrasonic material testing, electrical impedance testing, and X-ray computer tomography have been investigated for this purpose using specially produced samples with biased or random fibre orientations. This paper demonstrates the capabilities of each of these NDT techniques for fibre orientation measurements and draws conclusions based on these results about the most promising areas for future research and development using these techniques.
In this paper, we demonstrate the value of 1H NMR
relaxometry for studying the hydration of clinker-reduced, more
climate-friendly cementitious binders. The results were obtained
on typical CEM I cements and samples containing two different
reactive agricultural ashes as well as non-reactive biochars as
supplementary cementitious materials. The findings prove that
time-resolved NMR measurements provide valuable additional
information when combined with classical heat flow calorimetry.