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Moisture ingress is one of the major deteriorating factors for building materials. Today, the only approved way to assess such damage is the gravimetric Darr method, which is essentially destructive. Substantial progress has been made using the geophysical complex-resistivity method, which can be applied non-destructively and provides spatial information along two-dimensional sections, rather than punctual along one borehole. Considerable advantages of complex resistivity are its sensitivity to textural properties, as well as the pore-fluid chemistry of wet, porous media. In a comprehensive laboratory study, and later in field scale experiments, it could be shown that complex resistivity may even be able to distinguish between salt content and saturation degree in a single measurement. A comparison with complementary nondestructive testing techniques points to the benefit and further research to be explored in multimethodical approaches.
To date, the destructive extraction and analysis of drilling cores is the main possibility to obtain depth information about damaging water ingress in building floors. The time- and costintensive procedure constitutes an additional burden for building insurances that already list piped water damage as their largest item. With its high sensitivity for water, a ground-penetrating radar (GPR) could provide important support to approach this problem in a non-destructive way. In this research, we study the influence of moisture damage on GPR signals at different floor constructions. For this purpose, a modular specimen with interchangeable layers is developed to vary the screed and insulation material, as well as the respective layer thickness. The obtained data set is then used to investigate suitable signal features to classify three scenarios: dry, damaged insulation, and damaged screed. It was found that analyzing statistical distributions of A-scan features inside one B-scan allows for accurate classification on unknown floor constructions. Combining the features with multivariate data analysis and machine learning was the key to achieve satisfying results. The developed method provides a basis for upcoming validations on real damage cases.
Non-destructive testing methods are mostly applied and established for the detection of embedded mounting parts or structural defects in building elements. The assessment of the concrete microstructure or microstructural changes like chemical alterations or the formation of microcracks, e.g. due to material aging, freeze-thaw cycles, alkali-silica reaction and ettringite, is not in the focus of ndt research though. Concrete moisture and enhanced salt contents, which usually trigger all chemical microstructural changes, are other material properties, lacking reliable ways of measuring. But, the assessment of such material properties, on the long term also in a depth resolved manner, is definitely important, when the sustainability of our concrete infrastructure buildings shall be evaluated.
New consideration like the potential use of ndt, in particular the combination of different methods and alternate ways of data analysis are subject of research currently undertaken at BAM. These approaches involve for example working towards (i) a deeper understanding of how to measure moisture distributions reliably and follow transport phenomena, (ii) the use of stray phenomena in radar and ultrasound to locate material inhomogeneities or (iii) the application of LIBS for the delineation of diffusion and migration processes but also (iv) the use of new tools for data analysis like data fusion. First results are presented and new ideas discussed.
Measuring the moisture content of floor screeds is usually done with minor destructive testing methods like Darr drying or the Calcium Carbid (CM) method. These require small samples, deliver only punctual information and still have proven not to be very reliable. Hence, a study has been made using the standard destructive tests as well as a suite of non-destructive testing methods working out their use for moisture determination. In this study five partners from research institutes and industry worked together and intensively researched different technologies. The main focus was put on the varying sensitivity of the measuring techniques in different moisture ranges. Especially for low moisture contents ( or ‘critical’ moisture contents when the screed is dry enough to be covered with the final floor finish), several commercial devices including the most commonly used CM-method failed to determine the correct moisture content for cementitious samples. Hence the need for more accurate, if possible non-destructive methods is high, taking also into account that the chemistry (and physical properties) of screeds may vary strongly depending on their origin and purpose.
Moisture and salt loads of concrete can significantly change its microstructure and consequently lead to chemical and mechanical degradation. However, the non-destructive investigation of moisture and salt present in concrete is still difficult. In order to address and compare the sensitivity of different methods concrete samples with different pore systems realized by varying the w/z ratios have been fabricated. The focus of this study was put on the analysis of ultrasonic long and trans waves measured on the surface and in transmission mode. The results show clear dependencies of all applied methods. With the radar and microwave methods predominantly changes in the concrete moisture could be detected, whereas the different pore systems were not observed to alter the signals. In contrast for the ultrasound method also the ongoing hydration as well as the nature of the pore system strongly influenced the signals. As a consequence in a subsequent drying experiment it was also tried to delineate the effects of moisture and hydration. All specimens have been re-saturated under pressure and the drying experiment was repeated using the same multi-sensor approach.
In this ongoing research project, we study the influence of moisture damage on Ground Penetrating Radar (GPR) in different floor constructions. For this purpose, a measurement setup with interchangeable layers is developed to vary the screed material (cement or anhydrite) and insulation material (glass wool, perlite, expanded and extruded polystyrene), as well as the respective layer thickness. The evaluation of the 2 GHz common-offset radar measurements is focused on the extraction of distinctive signal features that can be used to classify the underlying case of damage without any further information about the hidden materials or layer thicknesses. In the collected dataset, we analyze the horizontal distribution of A-scan features in corresponding B-scans to detect water in the insulation layer. Furthermore, possible combinations of these features are investigated with the use of multivariate data analysis and machine learning (logistic regression) in order to evaluate the mutual dependencies. In this study, the combination of an amplitude- and frequency-based feature achieved an accuracy of 93.2 % and performed best to detect a damage in floor insulations.
The influence of moisture on the reliability of detection of larger voids in brickwork masonry was investigated using three non-destructive techniques: radar, ultrasonic and complex resistivity (CR). Radar and ultrasonic travel time tomography, as well as CR tomography, were performed over a specific cross section of a specimen containing a large void at a known position to determine the influence of different levels of moisture content in the brickwork on the wave velocities and the CR magnitude. We defined a numerical estimator to quantitatively determine the void detection efficiency from the images obtained when exposing the specimen to moisture. The results showed radar to be the most reliable technique for void detection in both dry and wet masonry, while CR performed much better in detecting larger air voids in wet masonry.