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- 2019 (5) (entfernen)
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- Englisch (5) (entfernen)
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- Building materials (1)
- Cement (1)
- Chloride (1)
- Corrosion (1)
- Electric impedance (1)
- Embedded sensors (1)
- Evaporative drying (1)
- LIBS (1)
- Machine learning (1)
- Material moisture (1)
Organisationseinheit der BAM
The moisture content of screed samples is monitored by means of embedded sensors. Relative humidity sensors and multi-ring-electrodes are used to measure the spatial moisture distribution during desorption. Based on the humidity data and the pore volume distribution, the moisture and the water layer thickness within the pore space are predicted.
Slit shape as well as cylindrical pores are evaluated. Finally, the measured real part of the electrical impedance and the calculated water layer thickness are correlated. Based on the available data, a significant trend change of the impedance is documented at a water layer thickness of approximately 3 nm. This water layer thickness corresponds to a relative humidity of 88.3%.
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.
NMR is gaining increasing interest in civil engineering applications for the use of microstructure characterization as e.g. pore size determination and monitoring of moisture transport in porous materials. In this study, the use of NMR as a tool for pore size characterization was investigated. For our study we used screed and synthetic materials at partial and full saturation. A successful determination could be achieved when having a reference or calibration method, although partly diffusion effects have been registered. Due to these diffusion effects, for the determination of pore size distributions of synthetic materials another NMR device was needed. Finally, the determination of the surface relaxivity of screed (50 μm/s) led to a higher value than first expected from literature.
The presented work discusses the accuracy of Laser Induced Breakdown Spectroscopy (LIBS) in determining the total chloride content in cement pastes. LIBS as an emission spectroscopy method is used to detect simultaneously several elements present in cement-based materials. By scanning surfaces the variability in the spatial distribution of elements can be visualised. However, for a quantification of the results, studies are necessary to characterise possible influences due to the wide variation of the chemical compositions in which cement can occur. It is shown how the calibration can be done, how the calibration samples were produced, and which statistical parameters are necessary to describe the precision of the regression. The performance of LIBS is estimated by detecting chloride in validation samples. Therefore, 55 samples and 7 ets with changing mix ompositions were produced. The presented study deals with possible influences of different mix compositions, ncluding different cations of chloride, varying w/c-ratios and the artial replacement of Portland cement with last furnace slag (50% BFS) and limestone (30% LS). Comparing the LIBS results with otentiometric titration, n accuracy of±0.05 wt%/total has been determined.
Dehydration is a common process occurring in natural environments, rocks, and building materials. Suitable methods for monitoring the changing moisture content should be identified.
We have investigated the impact of dehydration of sandstones on complex conductivity spectra. Spectral induced polarization measurements were performed on five sandstone samples during evaporative drying. The complex conductivity spectra indicate considerable changes with decreasing saturation. The relationship between conductivity and saturation can be described by a power law known as the second empirical Archie equation. Separate saturation exponents have been determined for the real and imaginary parts of conductivity. The imaginary part of conductivity indicates higher saturation exponents for the investigated sandstones compared to the real part. Obviously, the saturation exponents depend on the method used for changing water saturation. Evaporative drying, which is used in our experiments, causes an increase of pore-water salinity and results in lower saturation exponents for the real part of conductivity but higher exponents for the imaginary part in comparison with the classical imbibition/Drainage technique. We evaluate a theoretical approach that considers the influence of pore water salinity on the saturation exponents of the real and imaginary parts of conductivity. The complex conductivity spectra are processed by a Debye decomposition procedure.
The resulting integrating parameters such as direct current resistivity, total chargeability, normalized chargeability, and mean relaxation time indicate a power law dependence on saturation. Our experiments indicate that the imaginary part of conductivity and normalized chargeability have a high sensitivity related to the drying process of rocks and might be suitable indicators to Monitor the changes of moisture content in sandstones.