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In this study, nanoscopic particles of magnesium Fluoride (MgF2) and calcium fluoride (CaF2) also known as nano metal fluorides (NMFs), were evaluated for their potential to improve wood durability. Even though these fluorides are sparingly soluble, their synthesis in the form of nano-sized particles turns them into promising candidates for wood preservation. Their distinct property of low-water solubility is proposed to maintain long-lasting protection of treated wood by reducing the leaching of fluoride. Analytical methods were used to characterize the synthesized NMFs and their distribution in treated wood specimens. Transmission electron microscopy images showed that these fluoride particles are smaller than 10 nm. In nano metal fluoride (NMF) treated specimens, aggregates of these particles are uniformly distributed in the wood matrix as confirmed with scanning electron microscopy images and their corresponding energy-dispersive X-ray spectroscopy maps. The fluoride aggregates form a protective layer around the tracheid walls and block the bordered pits, thus reducing the possible flow path for water absorption into wood. This is reflected in the reduced swelling and increased hydrophobicity of wood treated with NMFs. The biocidal efficacy of NMFs was tested against brown-rot fungi (Coniophora puteanaand Rhodonia placenta), white-rot fungus (Trametes versicolor), and termites (Coptotermes formosanus). The fungal and termite tests were performed in accordance with the EN 113 (1996) and EN 117 (2012) standards, respectively. Prior to fungal tests, the NMF treated wood specimens were leached according to the EN 84 (1997)standard. Compared to untreated specimens, the NMF treated wood specimens have a higher resistance to decay caused by brown-rot fungi, white-rot fungus, and termites. Although all NMF treatments in wood reduce the mass loss caused by fungal decay, only the combined treatment of MgF2 and CaF2 has efficacy against both brown-rot fungi and white-rot fungus. Similarly, wood treated with the combined NMF formulation is the least susceptible to attack by C. formosanus.It is proposed that combining MgF2 and CaF2changes their overall solubility to promote the release of fluoride ions at the optimal concentration needed for biocidal efficacy against fungi and termites. In this thesis, it was proven that even after leaching, sufficient fluoride was present to protect NMF treated wood from fungal decay. This shows that NMFs are robust enough for above ground contact outdoor applications of wood, where permanent wetness cannot be avoided according to Use Class 3.2, as per the EN 335 (2013) standard. Also, they pose a low risk to human health and the environment because they are sparingly soluble. Since NMFs significantly reduce the decay of wood, the CO2 fixed in it will be retained for longer than in unpreserved wood. Overall, the novel results of this study show the potential of NMFs to increase the service life of building materials made from non-durable wood.
Feuchte, sei es Material- oder Gasfeuchte, ist eine wichtige Messgröße bei der Qualitätsbeurteilung von Kunststoffen, landwirtschaftlichen Erzeugnissen, Energieträgern, Arzneimitteln, industriell und medizinisch verwendeten Gasen. Deswegen gibt es ein Interesse Feuchtemesserfahren hinsichtlich Präzision, Wiederholbarkeit, Rückführbarkeit und Stabilität kontinuierlich zu verbessern. Ein bewährtes Messprinzip für diese Aufgabe wurde bereits 1959 von Keidel entwickelt und basiert auf der Absorption und Elektrolyse von Wasserdampf. Der einfache Aufbau dieses Prinzips besteht aus einem Sensorelement, einer Gleichspannungsquelle, einem Digitalmultimeter und einen geregelten Gasstrom über den Sensor. Nach dem Faraday’schen Gesetz der Elektrolyse korreliert bei dem Messprinzip die Ladungsmenge mit der elektrolysierten Wassermasse. Jedoch bedarf es in der heutigen Zeit einer Validierung der Sensoren, weil durch gezielte Miniaturisierung weniger aktive Fläche vorhanden ist und somit das Faraday’sche Gesetz nicht vollständig anwendbar ist. In dieser Arbeit wurden coulometrische Sensoren mit einer planaren Elektrodenstruktur hinsichtlich der Einflüsse von unterschiedlichen Gasen, der Gastemperatur und dem -druck untersucht. Zusätzlich wurde eine neuartige Sensorbeschichtung basierend auf einer ionischen Flüssigkeit getestet. Des Weiteren wurde ein Messgerät für die abgestufte Bestimmung der Materialfeuchte und Wasseraktivität entwickelt und dessen messtechnischer Einsatz untersucht.
The present work is intended to make a contribution to the monitoring of civil engineering structures. The detection of damage to structures is based on the evaluation of spatially and temporally distributed hybrid measurements. The acquired data can be evaluated purely geometrically or physically. It is preferable to do the latter, since the cause of damage can be determined by means of geometrical-physical laws in order to be able to intervene in time and ensure the further use of the structures. For this reason, the continuum mechanical field equations in conjunction with the finite element method and hybrid measurements are combined into a single evaluation method by the adjustment calculation. This results in two challenges.
The first task deals with the relationship between the finite element method and the method of least squares. The finite element method solves certain problem classes, which are described by a system of elliptical partial differential equations. Whereas the method of least squares solves another class of problems, which is formulated as an overdetermined system of equations. The striking similarity between both methods is known since many decades. However, it remains unresolved why this resemblance exists. The contribution is to clarify this by examining the variational calculus, especially with regard to its methodological procedure. Although the well-known Gauss-Markov model within the method of least squares and the finite element method solve inherently different problem classes, it is shown that both methods can be derived by following the same methodological steps of the variational calculus. From a methodical viewpoint, this implies that both methods are not only similar, but actually the same. In addition, it is pointed out where a possible cross-connection to other methods exists.
The second task introduces a Measurement- and Model-based Structural Analysis (MeMoS) by integrating the finite element method into the adjustment calculation. It is shown in numerical examinations how this integrated analysis can be used for parameter identification of simple as well as arbitrarily shaped structural components. Based on this, it is examined with which observation types, with which precision and at which location of the structure these measurements must be carried out in order to determine the material parameters as precisely as possible. This serves to determine an optimal and economic measurement set-up. With this integrated analysis, a substitute model of a geometrically complex structure can also be determined. The issue of the detection and localisation of damage within a structure is studied by means of this structural analysis. The Measurement and Model-based Structural Analysis is validated using two different test setups, an aluminum model bridge and a bending beam.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel
patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
In the event of moisture deterioration, rapid detection and localization is particularly important to prevent further deterioration and costs. For building floors, the layered structure poses a challenging obstacle for most moisture measurement methods. But especially here, layer-specific information on the depth of the water is crucial for efficient and effective repairs. Ground Penetrating Radar (GPR) shows the potential to generate such depth information. Therefore, the present work investigates the suitability of GPR in combination with machine learning methods for the automated classification of the typical deterioration cases (i) dry, (ii) wet insulation, and (iii) wet screed.
First, a literature review was conducted to identify the most common methods for detecting moisture in building materials using GPR. Here, it especially became clear that all publications only investigated individual time-, amplitude- or frequency features separately, without combining them. This was seen as a potential aspect for innovation, as the multivariate application of several signal features can help to overcome individual weaknesses and limitations.
Preliminary investigations carried out on drying screed samples confirmed the profitable use of multivariate evaluations. In addition to the general suitability and dependencies of various features, first limitations due to possible interference between the direct wave and the reflection wave could be identified. This is particularly evident with thin or dry materials, for which the two-way travel times of the reflected radar signals become shorter.
An extensive laboratory experiment was carried out, for which a modular test specimen was designed to enable the variation of the material type and thickness of screed and insulation, as well as the simulation of moisture deteriorations. The data collected revealed clear differences between dry and deteriored structures within measured B-scans. These deviations were to be detected with the newly introduced B-scan features, which evaluate the statistical deviation of A-scan features within a survey line. In this way, deteriorations to unknown floor structures are recognized, regardless of the material parameters present. In a subsequent training and cross-validation process of different classifiers, accuracies of over 88 \% of the 504 recorded measurements (252 different experimental setups) were achieved. For that, the combination of amplitude and frequency features, which covered all relevant reflections of the radar signals, was particularly beneficial. Furthermore, the data set showed only small differences between dry floors and deteriored screeds for the B-scan features, which could be attributed to a homogeneous distribution of the added water in the screeds. The successfully separation of these similar feature distributions raised the suspicion of overfitting, which was examined in more detail by means of a validation with on-site data.
For this purpose, investigations were carried out at five different locations in Germany, using the identical measurement method like in the laboratory. By extracting drilling cores, it was possible to determine the deterioration case for each measurement point and thus generate a corresponding reference. However, numerous data had to be sorted out before classification, since disturbances due to underfloor heating, screed reinforcements, steel beams or missing insulation prevented comparability with the laboratory experiments. Validation of the remaining data (72 B-scans) achieved only low accuracy with 53 \% correctly classified deterioration cases. Here, the previously suspected overfitting of the small decision boundary between dry setups and deteriored screeds within the laboratory proved to be a problem. The generally larger deviations within (also dry) on-site B-scans were thus frequently misclassified as screed deterioration. In addition, there were sometimes strongly varying layer thicknesses or changing cases of deterioration within a survey line, which caused additional errors due to the local limitation of the drilling core reference. Nevertheless, individual on-site examples also showed the promising potential of the applied signal features and the GPR method in general, which partly allowed a profound interpretation of the measurements. However, this interpretation still requires the experience of trained personnel and could not be automated using machine learning with the available database. Nevertheless, such experience and knowledge can be enriched by the findings of this work, which provide the basis for further research.
Future work should aim at building an open GPR data base of on-site moisture measurements on floors to provide a meaningful basis for applying machine learning. Here, referencing is a crucial point, whose limitations with respect to the moisture present and its distribution can easily reduce the potential of such efforts. The combination of several reference methods might help to overcome such limitations. Similarly, a focus on monitoring approaches can also help to reduce numerous unknown variables in moisture measurements and increase confidence in the detection of different deterioration cases.
Additive manufacturing technologies provide unique possibilities in the production of topologically optimized, near-net shape components. The main limiting factors affecting the structural integrity of Laser Powder Bed Fusion (LPBF) parts are manufacturing defects and residual stress (RS) because both of them are virtually inevitable. Taking into account the complex thermal history of LPBF materials, a prediction of the material behavior is not possible without experimental data on the microstructure, defect distribution, and RS fields. Therefore, this thesis aims to understand the factors that influence the LPBF Ti-6Al-4V material performance the most, covering both the production and the post-processing steps of manufacturing.
Indeed, a parametric study on the influence of manufacturing process and post-processing on RS, defects and microstructure was performed. It was found that the volumetric energy Density (EV), commonly used for the LPBF process optimization, does neither consider the pore shapes and distribution, nor the influence of individual parameters on the volume fraction of pores.
Therefore, it was recommended not to use EV without great care. It was shown that the Position on the base plate has a great impact on the amount of RS in the part.
The micromechanical behavior of LPBF Ti-6Al-4V was also studied using in-situ Synchrotron X-ray diffraction during tensile and compression tests. Diffraction elastic constants (DEC), connecting macroscopic stress and (micro) strain, of the LPBF Ti-6Al-4V showed a difference
from the DEC of conventionally manufactured alloy. This fact was attributed to the peculiar microstructure and crystallographic texture. It was therefore recommended to determine experimentally DECs whenever possible.
Low Cycle Fatigue (LCF) tests at a chosen operating temperature were performed to evaluate the effect of post-treatment on the mechanical performance. Through the information on the microstructure, the mesostructure, and the RS, the LCF behavior was (indirectly) correlated to the process parameters. It was found that the fatigue performance of LPBF samples subjected to hot isostatic pressing is similar to that of hot-formed Ti-6Al-4V. The tensile RS found at the
surface of LPBF as-built samples decreased the fatigue life compared to the heat-treated samples. The modification of the microstructure (by heat treatment) did not affect the Fatigue performance in the elastic regime. This shows that in the absence of tensile RS, the manufacturing defects solely control the failure of LPBF components and densification has the strongest effect on the improvement of the mechanical performance.
In this work, two X-ray refraction based imaging methods, namely, synchrotron X-ray refraction radiography (SXRR) and synchrotron X-ray refraction computed tomography (SXRCT), are applied to analyze quantitatively cracks and porosity in metallic materials.
SXRR and SXRCT make use of the refraction of X-rays at inner surfaces of the material, e.g., the surfaces of cracks and pores, for image contrast. Both methods are, therefore, sensitive to smaller defects than their absorption based counterparts X-ray radiography and computed tomography. They can detect defects of nanometric size.
So far the methods have been applied to the analysis of ceramic materials and fiber reinforced plastics. The analysis of metallic materials requires higher photon energies to achieve sufficient X-ray transmission due to their higher density. This causes smaller refraction angles and, thus, lower image contrast because the refraction index depends on the photon energy. Here, for the first time, a conclusive study is presented exploring the possibility to apply SXRR and SXRCT to metallic materials. It is shown that both methods can be optimized to overcome the reduced contrast due to smaller refraction angles. Hence, the only remaining limitation is the achievable X-ray Transmission which is common to all X-ray imaging methods. Further, a model for the quantitative analysis of the inner surfaces is presented and verified.
For this purpose four case studies are conducted each posing a specific challenge to the imaging task. Case study A investigates cracks in a coupon taken from an aluminum weld seam. This case study primarily serves to verify the model for quantitative analysis and prove the sensitivity to sub-resolution features. In case study B, the
damage evolution in an aluminum-based particle reinforced metal-matrix composite is analyzed. Here, the accuracy and repeatability of subsequent SXRR measurements is investigated showing that measurement errors of less than 3% can be achieved. Further, case study B marks the fist application of SXRR in combination with in-situ tensile loading. Case study C is out of the highly topical field of additive manufacturing. Here, porosity in additively manufactured Ti-Al6-V4 is analyzed with a special interest in the pore morphology. A classification scheme based on SXRR measurements is devised which allows to distinguish binding defects from keyhole pores even if the defects cannot be spatially resolved. In case study D, SXRCT is applied to the analysis of hydrogen assisted cracking in steel. Due to the high X-ray attenuation of steel a comparatively high photonenergy of 50 keV is required here. This causes increased noise and lower contrast in the data compared to the other case studies. However, despite the lower data quality a quantitative analysis of the occurance of cracks in dependence of hydrogen content and applied mechanical load is possible.
Data fusion for multi-sensor nondestructive detection of surface cracks in ferromagnetic materials
(2018)
Fatigue cracking is a dangerous and cost-intensive phenomenon that requires early detection. But at high test sensitivity, the abundance of false indications limits the reliability of conventional materials testing. This thesis exploits the diversity of physical principles that different nondestructive surface inspection methods offer, by applying data fusion techniques to increase the reliability of defect detection. The first main contribution are novel approaches for the fusion of NDT images. These surface scans are obtained from state-of-the-art inspection procedures in Eddy Current Testing, Thermal Testing and Magnetic Flux Leakage Testing. The implemented image fusion strategy demonstrates that simple algebraic fusion rules are sufficient for high performance, given adequate signal normalization. Data fusion reduces the rate of false positives is reduced by a factor of six over the best individual sensor at a 10 μm deep groove. Moreover, the utility of state-of-the-art image representations, like the Shearlet domain, are explored. However, the theoretical advantages of such directional transforms are not attained in practice with the given data. Nevertheless, the benefit of fusion over single-sensor inspection is confirmed a second time. Furthermore, this work proposes novel techniques for fusion at a high level of signal abstraction. A kernel-based approach is introduced to integrate spatially scattered detection hypotheses. This method explicitly deals with registration errors that are unavoidable in practice. Surface discontinuities as shallow as 30 μm are reliably found by fusion, whereas the best individual sensor requires depths of 40–50 μm for successful detection. The experiment is replicated on a similar second test specimen. Practical guidelines are given at the end of the thesis, and the need for a data sharing initiative is stressed to promote future research on this topic.
This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling
channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
A workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established.
Synchrotron computed tomography (CT) was used to correlate the packing
density with the particle size and particle shape. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary
information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The Deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to
find reliable principal stress directions.