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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.
One of the main problems in the assessment of the operability, stability and contamination potential of tailings facilities is the lack of data on subsurface materials, properties and structures. One key task in the use of geophysics is the selection of the proper methods for a given site/problem combination. Interpretation of the acquired and processed physical data (e.g. electrical resistivity distribution) into something useful for site assessment (e.g. contamination distribution) is another. In the TAILSAFE project (funded by the European Commission) we have worked with partners on the use of geophysics for tailings facilities inspection. DC and complex resistivity, ground penetrating radar, and spectral analysis of surface waves and multichannel analysis of surface waves have been used on dams and beaches. In most cases, our methods provided useful information on the subsurface structure, but the translation of geophysical values into geotechnical or other parameters is still challenging.
Over the last 15 years significant advancements in induced polarization (IP) research have taken place, particularly with respect to spectral IP (SIP), concerning the understanding of the mechanisms of the IP phenomenon, the conduction of accurate and broadband laboratory measurements, the modelling and inversion of IP data for imaging purposes and the increasing application of the method in near-surface investigations. We summarize here the current state of the science of the SIP method for near-surface applications and describe which aspects still represent open issues and should be the focus of future research efforts. Significant progress has been made over the last decade in the understanding of the microscopic mechanisms of IP; however, integrated mechanistic models involving different possible polarization processes at the grain/pore scale are still lacking. A prerequisite for the advances in the mechanistic understanding of IP was the development of improved laboratory instrumentation, which has led to a continuously growing data base of SIP measurements on various soil and rock samples. We summarize the experience of numerous experimental studies by formulating key recommendations for reliable SIP laboratory measurements. To make use of the established theoretical and empirical relationships between SIP characteristics and target petrophysical properties at the field scale, sophisticated forward modelling and inversion algorithms are needed. Considerable progress has also been made in this field, in particular with the development of complex resistivity algorithms allowing the modelling and inversion of IP data in the frequency domain. The ultimate goal for the future are algorithms and codes for the integral inversion of 3D, time-lapse and multi-frequency IP data, which defines a 5D inversion problem involving the dimensions space (for imaging), time (for monitoring) and frequency (for spectroscopy). We also offer guidelines for reliable and accurate measurements of IP spectra, which are essential for improved understanding of IP mechanisms and their links to physical, chemical and biological properties of interest. We believe that the SIP method offers potential for subsurface structure and process characterization, in particular in hydrogeophysical and biogeophysical studies.
Complex resistivity (CR) behavior of building material - first results of field scale measurements
(2008)
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).
Charakterisierung von Feuchte- und Salzbelastungen in Baumaterial durch Impedanzspektroskopie
(2006)
Complex resistivity (CR) behavior of building material - first results of field scale measurements
(2008)
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.
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.
Es werden Ergebnisse von 1H-NMR-Relaxometrie-Messungen an Salzbeton und einem alkali-aktivierten Material, die im Rahmen des Themenfeldprojektes Seal Waste Safe durchgeführt werden, vorgestellt. Dabei wird die zeitliche Entwicklung von ausgewählten Merkmalen der ermittelten T2-Relaxationszeitenverteilungen während der Hydratation betrachtet. Als Referenz zur Identifikation von charakteristischen Hydratationsereignissen dienen der Vicat-Nadeleindringversuch und Wärmeflusskalorimetrie.
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.
This contribution summarizes actual developments and draft fundamental teaching topics in the field of nondestructive testing in civil engineering (NDT-CE). It is based on the first memorandum on teaching and research in the field of NDT-CE at German speaking universities and provides an overview of the academic education and highlights possible focuses, especially in teaching but also takes into account noteworthy developments and topics in research in the field of NDT-CE.
Suggestions are given for the development and advancement of the teaching curricula in regards to a comprehensive and sound professional education of students in civil engineering and adjacent disciplines.
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.