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The ability to reliably predict the amount and type of salts within a wet masonry is one of the most important and challenging subjects in the field of non-destructive combat of salt attack and preserving buildings and monuments of historical or archaeological value. To investigate the potential value of complex resistivity (CR) measurements for the early detection of salt and moisture related stone altering, a controlled salt type and concentration experiment series has been performed and a new procedure of an image based effective impedance modelling developed. Complex resistivity magnitude and phase measurements in the frequency range of 1 mHz to 100 Hz were acquired on a wide variety of wholly and partially brine saturated building stone samples. Deteriorating agents NaCl, Na2SO4, CaCl2 and MgSO4 were used. Since water and salt are not measured directly, the method is incapable of deducing possible building damages lacking a priori information. In the case of saturated materials, and provided thorough calibration data are available, a reliable estimate of salt concentration is possible from the measured resistivity magnitude. Additional indication on the dominant cation in the solution can be obtained from the measured resistivity phase, which is significantly higher the lower its valency. Furthermore, the measurements reported in this study give an important guide to the limitations of CR in obtaining pore surface area and pore throat estimates. For wet porous materials, in which polarization occurs due to complex surface conduction, the dominant pore throat and amount of specific surface affect its polarizability. Sandstones, sand-limestones and aerated concretes are more qualified observation objects (pore throats between 20 and 100 μm), whereas for bricks (pore sizes often < 5 μm) the method seems far less favorable. For those materials, which exhibit a Cole-Cole (C-C) type of relaxation, the phase peak is observed to decrease significantly with pore throat size and to occur at higher frequencies. The predicted power-law correlation between the C-C relaxation time and characteristic length scale (pore throat size for consolidated materials) is supported by the presented data. The experimental salinity study reveals how responsive polarization (in terms of imaginary conductivity) is to changing the ionic concentration or composition of the pore fluid. The properties of the electrical double layer and particularly its chemical composition are most likely the crucial controlling factors. The imaginary conductivity is observed to increase for most materials up to fluid salinities of about 1 S/m - a fact, that may be attributed to a mechanism of ion saturation within the electrical double layer; further ion supply seems to counteract this leading to ion-ion interactions, which decrease ionic mobility. CR measurements on partially saturated samples demonstrate the method’s sensitivity to water content. For most materials the imaginary conductivity component decreased significantly faster than the real component. Independent of the pore fluid and even though its salinity naturally increased during the evaporative drying procedure, the normalized saturation exponent of the quadrature component was about twice as high as the real one especially for clay-rich sandstones. The results revealed diverse behavior such as decreases and increases in relaxation time with saturation. In some cases a suppression of a distinctive relaxation curve at low saturations was observed. The results indicate, that contrary to conclusions from recent related studies, the correlation between a C-C relaxation time and hydraulic properties may be limited. In order to infer information on the charge distributions within the EDL, zeta-potentials and surface charge densities were obtained from electroacoustic measurements on particle suspension containing the same amounts and types of salt like used in the brine saturation CR study. The results add weight to the assumption that there is some universal positive relationship between zeta-potential and imaginary conductivity. A notable dependence of imaginary conductivity on diffuse layer surface charge was only observed in case of one sandstone (Cottaer), this being the material with the most abundant clay content. An image based effective impedance modelling approach revealed the fact that, even though it is not able to factor scale effects in, it is helpful to study general microstructural implications on CR responses. It was observed, that an increasing salt concentration (that creates a shrinking electrical double layer) reduces the peak phase and moves it towards higher frequency. The same effect would have an increasing fluid conductivity for a otherwise fixed microstructure. For some combinations of material and salt, however, in the experimental work the peak phase was observed to shift towards lower frequency: a phenomenon that could not be explained with the modelling. Therefore, it is assumed that chemical properties, like ion mobilities or other surface chemistry properties (ionexchange processes) must be regarded to conclusively explain surface conductivity mechanisms. Other experimental observations like the alteration of CR spectra at desaturation could likewise be modelled. If these models truly mimic the effective electrical properties, the results give new implications on the effective medium behavior. Concluding, the author values the complex resistivity method as a possible effective non-destructive testing (NDT) tool for a wide range of building stones. Depending on pore size and saturation important additional information can be obtained. In all cases, a priori information and calibration data are essential, that is, CR should not be treated as a stand-alone method. Further measurements are needed to develop a more complete model of the electrical double layer and its alteration with changing salinity and ion types.
Ground Penetration Radar (GPR) as a non-destructive (NDT)-method can be applied to obtain detailed information about the inner structure and condition of bridges without damaging the structure.
In this paper the capabilities and limitations of the application of the fast inspection technique GPR will be demonstrated.
In addition to GPR investigations, geoelectrical measurements, coring and petrophysical investigations have been carried out.
The investigated railway bridge in Olesnica is a typical European masonry arch bridge (age, construction and span length).
It shows typical damage to the masonry arches such as increasing salt concentration, destruction, material losses and longitudinal cracks.
Radar measurements were carried out with two main objectives: (1) Identification of basic geometric dimensions of the bridge and identification of construction details; (2) Evaluation of the condition of the masonry, such as mechanical damage (e.g. cracks) or variation of the moisture content.
Radar antennas of different frequencies (having different penetration depths) have been used to estimate the thickness of the walls.
Because of the high attenuation in the inner masonry structure the measurements have not produced satisfying results, but the radar measurements have been successfully applied to investigate the moisture distribution in the masonry.
These results have been verified by coring and through geoelectrical measurements.
Cracks were studied at two testing areas at one wing wall of the bridge using an automatic 2D radar scanning system.
The radar data were processed using advanced data processing tools like FT-SAFT reconstruction and data fusion.
The processing sequence allowed the creation of high-resolution depth sections (C-Scans).
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.
Building stones are porous media and they can deteriorate through moisture ingress and secondary damage such as crystallization of soluble salts. Not only is this due to the increasing number of flood events in the past years but also structural damages of houses from activity such as leakage or rising moisture (groundwater) are the main causes. The potential benefit of several nondestructive testing methods to assess water damage in building stone has been studied in a field-scale experiment. Three testing walls made of fired clay brick, sandstone, and spongilite were flooded and their drying behavior monitored using infrared thermography, complex resistivity, ground penetrating radar, and ultrasonics. The results were compared to the average moisture content determined by gravimetric weighing of the specimens. Qualitatively, the results of the different nondestructive testing methods matched well. But in terms of quantitative data, some scatter was observed and the results should be viewed with care. Collecting time-consuming calibration data would help to overcome this problem, but especially when dealing with historic building structures, this is not always possible in practice.
Because of its mobility and ability to investigate exposed surfaces, single-sided (SiS) nuclear magnetic resonance (NMR) technology enables new application fields in geosciences. To test and assess its corresponding potential, we compare longitudinal (T1) and transverse (T2) data measured by SiS NMR with those of conventional geoscientific laboratory NMR. We use reference sandstone samples covering a broad range of pore sizes. Our study demonstrates that the lower signal-to-noise ratio of SiS NMR data generally tends to slightly overestimated widths of relaxation time distributions and consequently pore size distributions. While SiS and conventional NMR produce very similar T1 relaxation data, unbiased SiS NMR results for T2 measurements can only be expected for fine material, i.e. clayey or silty sediments and soils with main relaxation times below 0.05s. This limit is given by the diffusion relaxation rate due to the gradient in the primary magnetic field associated with the SiS NMR. Above that limit, i.e. for coarse material, the relaxation data is strongly attenuated. If considering the diffusion relaxation time of 0.2 s in the numerical data inversion process, the information content >0.2s is blurred over a range larger than that of conventional NMR. However, our results show that principle range and magnitudes of the relaxation time distributions are reconstructed to some extent. Regarding these findings, SiS NMR can be helpful to solve geoscientific issues, e.g. to assess the hydro-mechanical properties of the walls of underground facilities or to provide local soil moisture data sets for calibrating indirect remote techniques on the regional scale. The greatest opportunity provided by the SiS NMR technology is the acquisition of profile relaxation data for rocks with significant bedding structures at the µm scale. With this unique feature, SiS NMR can support the understanding and modeling of hydraulic and diffusional anisotropy behavior of sedimentary rocks.
Laser Induced Breakdown Spectroscopy – A Tool for Imaging the Chemical Composition of Concrete
(2022)
One of the most common causes of damage is the ingress of harmful ions into the concrete, which can lead to deterioration processes and affect structural performance. Therefore, the increasingly aging infrastructure is regularly inspected to assess durability. Regular chemical analysis can be useful to determine the extent and evolution of ion ingress and to intervene in a timely manner. This could prove more economical than extensive repairs for major damage, particularly for critical infrastructure. In addition to already established elemental analysis techniques in civil engineering such as potentiometric titration or X-ray fluorescence analysis, laser-induced breakdown spectroscopy (LIBS) can provide further important complementary information and benefits. The possibilities of LIBS are demonstrated using the example of a drill core taken from a parking garage.
Integration of fiber reinforcement in high-performance cementitious materials has become widely applied in many fields of construction. One of the most investigated advantages of steel Fiber reinforced concrete (SFRC) is the deceleration of crack growth and hence its improved sustainability.
Additional benefits are associated with its structural properties, as fibers can significantly increase the ductility and the tensile strength of concrete. In some applications it is even possible to entirely replace the conventional reinforcement, leading to significant logistical and environmental benefits.
Fiber reinforcement can, however, have critical disadvantages and even hinder the Performance of concrete, since it can induce an anisotropic material behavior of the mixture if the fibers are not appropriately oriented. For a safe use of SFRC in the future, reliable non-destructive testing (NDT) methods need to be identified to assess the fibers’ orientation in hardened concrete. In this study,
ultrasonic material testing, electrical impedance testing, and X-ray computed tomography have been investigated for this purpose using specially produced samples with biased or random Fiber orientations. We demonstrate the capabilities of each of these NDT techniques for fiber orientation measurements and draw conclusions based on these results about the most promising areas for future research and development.
An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering
(2021)
Although measurement data from the civil engineering sector are an important basis for scientific analyses in the field of non-destructive testing (NDT), there is still no uniform representation of these data. An analysis of data sets across different test objects or test types is therefore associated with a high manual effort. Ontologies and the semantic web are technologies already used in numerous intelligent systems such as material cyberinfrastructures or research databases. This contribution demonstrates the application of these technologies to the case of the 1H nuclear magnetic resonance relaxometry, which is commonly used to characterize water content and porosity distri-bution in solids. The methodology implemented for this purpose was developed specifically to be applied to materials science (MS) tests. The aim of this paper is to analyze such a methodology from the perspective of data interoperability using ontologies. Three benefits are expected from this ap-proach to the study of the implementation of interoperability in the NDT domain: First, expanding knowledge of how the intrinsic characteristics of the NDT domain determine the application of semantic technologies. Second, to determine which aspects of such an implementation can be improved and in what ways. Finally, the baselines of future research in the field of data integration for NDT are drawn.
The development of prevention methods and the detection of moisture related damages in buildings and transport infrastructure at an early stage are current issues in the field of non-destructive testing in civil engineering.
Especially the subject of partial saturation requires further research since it is more likely to occur than full saturation of the material. In fact, partial saturation in porous media is even more complicated because both fully and partly saturated pores (i.e. pores in which the surfaces are covered with thin water layers) are present.
As the non-destructive method nuclear magnetic resonance (NMR) enables the measurement and quantification of relative low moisture contents, it is suitable for the investigation of partly saturated porous building materials. Nevertheless, the differentiation between partly and fully saturated pores is still a challenge. Therefore, in this study, we investigate two sandstones types (Bozanov and Schönbrunner sandstone) at various defined saturation states by using NMR. Furthermore, we measure the relative humidities within the samples and compute the water layer thicknesses (WLT) along the pore walls of all pore sizes to calculate the corresponding degree of pore saturation. To finally assign the NMR signals to pore sizes and to differentiate between partly and fully saturated pores, the water content distribution obtained from the WLT calculation is used for calibration of the relaxation-time distribution. In this extended abstract, selected results only for Schönbrunner sandstone are presented.
Alkali-activated binders (AAB) can provide a clean alternative to conventional cement in terms of CO2 emissions. However, as yet there are no sufficiently accurate material models to effectively predict the AAB properties, thus making optimal mix design highly costly and reducing the attractiveness of such binders. This work adopts sequential learning (SL) in high-dimensional material spaces (consisting of composition and processing data) to find AABs that exhibit desired properties. The SL approach combines machine learning models and feedback from real experiments. For this purpose, 131 data points were collected from different publications. The data sources are described in detail, and the differences between the binders are discussed. The sought-after target property is the compressive strength of the binders after 28 days. The success is benchmarked in terms of the number of experiments required to find materials with the desired strength. The influence of some constraints was systematically analyzed, e.g., the possibility to parallelize the experiments, the influence of the chosen algorithm and the size of the training data set. The results show the advantage of SL, i.e., the amount of data required can potentially be reduced by at least one order of magnitude compared to traditional machine learning models, while at the same time exploiting highly complex information. This brings applications in laboratory practice within reach.
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.
In a joint project of partners from industry and research, the automated recycling of construction and demolition waste (CDW) is investigated and tested by combing laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.). The project focuses primarily on the Berlin site to analyze the entire value chain, minimize economic/technological barriers and obstacles at the cluster level, and sustainably increase recovery and recycling rates. First measurements with LIBS and NIR spectroscopy show promising results in distinguishing various material types and indicate the potential for a successful combination. In addition, X-ray fluorescence (XRF) spectroscopy is being performed to obtain more information about the quantitative elemental composition of the different building materials. Future work will apply the developed sorting methodology in a fully automated measurement setup with CDW on a conveyor belt.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) and visual (VIS)/ near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.). Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic/technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
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.
In our current research project „Reincarnate“ we aim to anchor the idea of the circular economy in the European construction industry and significantly extend the life cycle of buildings, construction products and materials through innovative solutions. On the long term, this is an approach reduce construction waste by 80 percent and the CO2 footprint of the construction sector by 70 percent."
This project has received funding from the European Union’s Horizon Europe research and innovation programme and will take you on a tour on what are the drivers, what is the goal, who are the partners and how we want to make the world a better place!
Vorstellung der Themen der Nachwuchsgruppe "Materialcharakterisierung und -informatik für die Nachhaltigkeit im Bauwesen" von Prof. Sabine Kruschwitz (TU Berlin und BAM)
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.
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.
Permeability estimation from spectral induced
polarization (SIP) measurements is based on a
fundamental premise that the characteristic relaxation
time (t) is related to the effective hydraulic radius (reff)
controlling fluid flow. The approach requires a reliable
estimate of the diffusion coefficient of the ions in the
electrical double layer. Others have assumed a value for
the diffusion coefficient, or postulated different values for
clay versus clay-free rocks. We examine the link between
t and reff for an extensive database of sandstone samples
where mercury porosimetry data confirm that reff is
reliably determined from a modification of the Hagen-
Poiseuille equation assuming that the electrical tortuosity
is equal to the hydraulic tortuosity. Our database does not
support the existence of 1 or 2 distinct representative
diffusion coefficients but instead demonstrates strong
evidence for 6 orders of magnitude of variation in an
apparent diffusion coefficient that is well correlated with
both reff and the specific surface area per unit pore
volume (Spor). Two scenarios can explain our findings:
(1) the length-scale defined by t is not equal to reff and is
likely much longer due to the control of pore surface
roughness; (2) the range of diffusion coefficients is large
and likely determined by the relative proportions of the
different minerals (e.g. silica, clays) making up the rock.
In either case, the estimation of reff (and hence
permeability) is inherently uncertain from SIP relaxation
time.
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.
We have compared the performance of the typical Darr and CM moisture testing techniques, which are destructive with several non-destructive testing techniques on two types of floor screeds. In case of cement based screeds these destructive tests failed to deliver reliable results. Moreover, our measurements indicate significantly different drying and moisture transport behavior for the investigated cement based and calcium-sulphate based screeds. Whereas we have strong with depth decreasing moisture gradients in the CT material, we observe in the penetrated volumes of our ndt methods basically no clear moisture gradient in the CA samples. The findings with ndt methods could be supported by moisture gradient studies with nuclear magnetic resonance measurements.
Eight different screed types are tested including two different sample heights of 35 and 70 mm. The moisture of the four cement based and four sulphate based screeds are monitored during hydration and evaporation. All samples are stored in a climatic chamber at 23◦ C and 50 % relative humidity. Embedded sensors like temperature arrays, humidity sensor arrays, and multi-ring electrodes are embedded in the samples to yield a detailed moisture evolution with high depth resolution. Furthermore, nuclear magnetic resonance is used to quantify the water content at different depths. This multi-sensor approach allows a comprehensive monitoring of the moisture and its gradient in the different screed samples. This yields a deeper insight into the hydration, moisture convection, and diffusion processes.
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.
This paper studies the spatial and temporal spectral absorption of reflector signals of a 1.5 GHz ground penetrating radar (GPR) during a drying process of a brickwall from initial wet to later dry state. The non-stationary GPR signals were processed with short time-Fourier transform (STFT) and wavelet transform (WT) in a novel spatial-timefrequency (STF) domain. Spatial distribution of peak frequency at the direct wave (DW) across the antenna and a backwall reflection was studied to characterize the mechanism of spectral absorption of GPR wave. Results from WT were shown to be more preferred to those from STFT because the WT offers multiple resolutions to cope with both low and high frequency components in GPR wavelets but STFT does not. In addition to the traditional GPR signal interpretation in time-domain and our previous works on time–frequency domain, the analysis method operated in the STF domain provides another possibility of material characterization by GPR in large and field scale.
Many damage processes in building stones are driven by moisture ingress and subsequent decay due to solving, blistering or different types of corrosion. Hence, measuring moisture and/or any material property that is connected to the absorption/desorption behaviour of a porous medium is helpful for building engineers concemed with Conservation or restoration. Since the SEP method is sensitive to both the amount and chemistry of a pore fluid and pore space properties ist applicability and practical use as a non-destructive testing tool for moisture damages is studied at BAM.
A number of recent investigations have highlighted the potential value of using relaxation times derived from electrical spectra to infer key physical properties of permeable rocks. To date, most studies have assumed a grain size or pore throat as a measure of the length scale of the ionic diffusive process, although this has been challenged in recent experimental investigations. We compare the electrical spectra of three sandstones, adopting a new approach in which the temperature of the rock samples is perturbed and the relaxation time measured as a function of temperature. Our results suggest that, for the sandstones tested here, the effective diffusion coefficient should be considered as a function of the electrical tortuosity. These findings may help explain the apparent long relaxation times observed in low-permeability rocks in recent experimental studies. We also highlight the need to account for temperature in related studies of electrical spectra.
The results from several laboratory studies of the relationships between electrical polarization and physical properties of porous media have prompted interest in the potential use of low-frequency electrical spectra to qualitatively or quantitatively map variation in hydrogeologic properties in the field. Compiling several published and unpublished data sets, supported by new measurements, we have examined the low-frequency electrical spectra of a range of natural and artificial porous media to assess the generality of proposed relationships between electrical and physical properties. Our work confirms a significant positive correlation between the magnitude of electrical polarization (quantified as imaginary conductivity at a specific frequency) and the surface-area/pore-volume ratio Spor. Analyzing the parameters of ageneralized Cole-Cole resistivity relaxation model fitted to many electrical spectra, we observe two apparent controls on the electrical relaxation. For samples with abundant relatively large pore throats, we observe a distinct increase in the time constant of the model with modal pore-throat size, in accordance with classical electrical relaxation models. However, for media with pore structures dominated by small pore throats, the diffusion-length scales do not appear to be controlled by modal pore-throat size. We conclude that for such media, the microstructure of the network of small pores leads to some connectivity of diffusion paths; thus, these samples exhibit relatively large time constants. There is potential value in addition to limitations when using electrical spectra to estimate physical properties of porous media, and we see the need for more appropriate generalized theories of electrical polarization in hydrogeologic media.
Reinforced concrete bridge decks are exposed to several types of deterioration processes: corrosion, alkali silica reaction, carbonation, shrinkage, freeze thaw actions, and so forth. The most commonly found problem is corrosion-induced bridge deck delamination. Previous studies have shown that surveys of bridges relying on a single nondestructive evaluation (NDE) technology provide limited information about the condition of concrete bridge decks. To overcome limitations of individual technologies, a complementary approach using several NDE technologies should be used in bridge deck evaluation. The presented approach utilizes a suite of NDE technologies, namely, impact echo (IE), ultrasonic surface waves (USW), ground-penetrating radar (GPR), half-cell potential (HCP), and electrical resistivity (ER). The suite of NDE technologies was implemented in the evaluation of bridge decks on nine bridges in Iowa. The NDE was complemented by ground-truth measurements on the cores extracted from all nine bridge decks. Condition assessment with the five NDE technologies has clearly shown their advantages and limitations. For example, the GPR surveys provided assessment of concrete deterioration at relatively high speeds of data collection. In contrast, IE provided high accuracy in detection and characterization of delaminations in the deck but at a lower testing speed. HCP and ER tests provided assessment of the likelihood of corrosion, whereas the USW test provided accurate assessment of the effects of deterioration processes and defects on mechanical properties, primarily the degradation of the elastic modulus. Most important, the survey showed the advantages of use of multimodal NDE surveys in the comprehensiveness of condition assessment of concrete bridge decks.
The determination of water and salt distribution in brickwork and stonework is a frequent problem in cultural heritage protection. Conventional but reliable methods are usually based on the investigation of core samples and provide only punctual information. To avoid the destruction of valuable building fabric, a non-destructive approach using a combination of investigation methods is needed. A case study, demonstrating the possibilities of almost non-destructive testing methods and their combination is presented in this article.
Moisture ingress is one of major damaging factors for masonry buildings. As the complex resistivity (CR) is sensitive to textural properties as well as to the pore fluid chemistry of wet porous media, its non-destructive application can provide helpful information for conservators. In a comprehensive laboratory study it has been shown that CR might even be able to distinguish between salt content and saturation degree in only one measurement. The combined use of electrical and electromagnetic measurement techniques in two field-scale flooding experiments has shown some unexpected differences. Possible reasons are discussed and it is shown that bringing together the information of both methods leads to a clearer picture.
We present the results of a machine learning (ML)- inspired data fusion approach, applied to multi-sensory nondestructive testing (NDT) data. Our dataset consists of Impact-Echo (IE), Ultrasonic Pulse Echo (US) and Ground Penetrating Radar (GPR) measurements collected on large-scale concrete specimens with built–in simulated honeycombing defects. In a previous study we were able to improve the detectability of honeycombs by fusing the information from the three different sensors with the density based clustering algorithm DBSCAN. We demonstrated the advantage of data fusion in reducing the false positives up to 10% compared to the best single sensor, thus, improving the detectability of the defects. The main objective of this contribution is to investigate the generality, i.e. whether the conclusions from one specimen can be adapted to the other. The effectiveness of the proposed approach on a separate full-scale concrete specimen was evaluated.
Permeability estimation from induced polarization (IP) measurements is based on a fundamental premise that the characteristic relaxation time τ is related to the effective hydraulic radius reff controlling fluid flow. The approach requires a reliable estimate of the diffusion coefficient of the ions in the electrical double layer. Others have assumed a value for the diffusion coefficient, or postulated different values for clay versus clay-free rocks. We have examined the link between a widely used single estimate of τ and reff for an extensive database of sandstone samples, in which mercury porosimetry data confirm that reff is reliably determined from a modification of the Hagen-Poiseuille equation assuming that the electrical tortuosity is equal to the hydraulic tortuosity. Our database does not support the existence of one or two distinct representative diffusion coefficients but instead demonstrates strong evidence for six orders of magnitude of variation in an apparent Diffusion coefficient that is well-correlated with reff and the specific surface area per unit pore volume Spor. Two scenarios can explain our findings:
(1) the length scale defined by τ is not equal to reff and is likely much longer due to the control of pore-surface roughness or
(2) the range of diffusion coefficients is large and likely determined by the relative proportions of the different minerals (e.g., silica and clays) making up the rock. In either case, the estimation of reff (and hence permeability) is inherently uncertain from a single characteristic IP relaxation time as considered in this study.
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.
Monitoring of the absolute water content in porous materials based on embedded humidity sensors
(2018)
Moisture transport monitoring may indicate the onset of deterioration in porous building materials Prior to damage occurring. Most moisture measurement systems provide only qualitative values, require extensive calibration, or are destructive. Thus, non-destructive and calibration-free monitoring Systems are required. Our approach of moisture monitoring is to embed sensors that measure the relative humidity.
In our experiment, screed samples are monitored during the Hydration and evaporation process. Every test sample is equipped with 10 embedded sensors which measure the relative humidity across the sample thickness. Based on Hillerborg’s approach, the relative humidity is converted into the corresponding pore saturation. In our study, the free water is computed without knowledge of the Sorption isotherm. The free water in the pore system is predicted and validated. The predicted weight decrease corresponds conclusively to gravimetrically measured weights. The embedded sensors yield the absolute liquid water content and enable an experimental, non-destructive monitoring of liquid water in porous materials.
Half-Cell-Potential Mapping (HP) is the most popular non-destructive testing (NDT) method for the detection of active corrosion in reinforced concrete. HP is influenced by parameters such as moisture and chloride gradients in the component. The sensitivity to the spatially small, but dangerous pitting is low. In this study we show how additional measurement information can be used with multi-sensor data fusion to improve the detection performance and to automate data evaluation. The fusion is based on supervised machine learning (SML). SML are methods that recognize relationships in (sensor) data based on given labels. We use SML to distinguish "defective" and "intact" labeled areas in our dataset. It consists of 18 measurement - each contains HP, ground radar, microwave moisture and Wenner resistance data. Exact labels for changing environmental conditions were available in a laboratory study on a reinforced concrete slab, which deteriorated controlled and accelerated. The deterioration progress was monitored continuously and corrosion was generated targeted at a predefined location. The detection results are quantified and statistically evaluated. The SML results shows a significant improvement over the best single method (HP).
Four cement-based and four calcium-sulphate-based screed types are investigated. The samples have a diameter of 300 mm and a height of 35 or 70 mm. Up to ten humidity sensors are embedded directly during the concreting of the screed samples. Thus, the humidity over the sample height is monitored during hardening, hydration, evaporation, and oven drying. Furthermore, the screed samples are weighted during every measurement to determine the total mass and the corresponding moisture loss.
To define the pore system precisely, mercury intrusion porosimetry as well as gas adsorption is performed. According to the data, the entire pore volume distribution is known. The measured pore diameters range from 0.8 nm to 100 μm and the total porosity of the examined screeds ranges between 11 % and 22 %.
Based on these measurement data, moisture transport, pore saturation as well as sorption isotherms and their hysteresis may be calculated quantitatively as described by Strangfeld et al.
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.
Relaxation phenomena observed in the electrical low-frequency range (approximately 1 mHz-10 kHz) of natural porous media like sandstones is often assumed to be directly related to the dominant (modal) pore throat sizes measured, for instance, with mercury intrusion porosimetry. Attempts to establish a universally valid relationship between pore size and peak Spectral Induced Polarization (SIP) relaxation time have failed, considering sandstones from very different origins and featuring great variations in textural and chemical compositions as well as in geometrical pore space properties. In addition working with characteristic relaxation times determined in Cole-Cole or Debye decomposition fits to build the relationship have not been successful. In particular, samples with narrow pore throats are often characterized by long SIP relaxation times corresponding to long “characteristic length scales” in these media, assuming that the diffusion coefficients along the electrical double layer were constant. Based on these observations, three different types of SIP relaxation can be distinguished. We present a new way of assessing complex pore spaces of very different sandstones in a multi-methodical approach to combine the benefits of mercury intrusion porosimetry, micro-computed tomography, and nuclear magnetic resonance. In this way, we achieve much deeper insight into the pore space due to the different resolutions and sensitivities of the applied methods to both pore constrictions (throats) and wide pores (pore bodies). We experimentally quantify pore aspect ratios and volume distributions within the two pore regions. We clearly observe systematic differences between three SIP relaxation types identified previously and can attribute the SIP peak relaxation times to measured characteristic length scales within our materials. We highlight selected results for a total of nine sandstones. It seems that SIP relaxation behavior depends on the size difference of the narrow pore throats to the wide pore bodies, which increases from SIP Type 1 to Type 3.
The moisture content of the subfloor has to be determined before installation to avoid damages of the floor covering. Only if the readiness for layering is reached, an installation without damages can be expected in all cases. In general, three different approaches exist to measure the residual water content: determination of the moisture content, determination of the water release, or determination of the corresponding relative humidity. All three approaches are tested in laboratory at eight different screed types including two different samples thicknesses in each case. The moisture content and the water release are measured by sample weighing, the corresponding relative humidity is measured by embedded sensors. All three approaches are compared and correlated to each other. The evaluations show only weak correlation and, in several cases, contradicting results. Samples are considered as being ready for layering and not-being ready for layering at the same time, depending on the chosen approach. Due to these contradicting results, a general threshold for the risk of damage cannot be derived based on these measurements. Furthermore, the experiment demonstrates that the measurement of corresponding relative humidity is independent of the considered screed type or screed composition. This makes the humidity measurement to very promising approach for the installation of material moisture monitoring systems in the future.
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%.