Ingenieurwissenschaften und zugeordnete Tätigkeiten
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By means of a small-scale truss bridge, the ability of the Measurement- and Model-based Structural Analysis to detect and localize damage was examined. Although there was no noteworthy difficulty in detecting damage, it turned out that damage localization responds sensitively to systematic influences, i.e. non-modelled properties of the mechanical model. Therefore, another experiment is being conducted to re-examine the Measurement- and Model-based Structural Analysis. For this purpose, the bending test is carried out as it has been already theoretically respectively numerically discussed. In this attempt, the systematic influences such as residual stress are kept as low as possible.
Die Messung von Flüssigkeitskonzentrationen in Rohrsystemen ist von großem Interesse für viele unterschiedliche Anwendungen. Die meisten Messsysteme sind jedoch nicht in der Lage, die Flüssigkeit direkt im Rohr zu untersuchen und es muss eine zusätzliche Vorrichtung, wie z.B. einem Bypass, angebracht werden, welche den Kontakt zwischen Flüssigkeit und Sensor ermöglicht.
Um den Einbauaufwand gering zu halten und die Strömungseigenschaften des Rohres nicht zu beeinflussen, wird ein neuartiges Messsystem entwickelt, welches als Teil der Rohrwand ausgeführt werden kann. Dieses neuartige System ist angelehnt an die Idee der phononischen Kristallen (PnK). PnK’s bestehen im Allgemeinen aus einem Matrixmaterial, in welchem Streuzentren periodisch angeordnet sind. Dies führt beim Eintreffen einer akustischen Welle in definierten Frequenz-bereichen, sogenannter Bandlücken, zu zunehmender destruktiven Interferenz. Wird innerhalb einer solchen Bandlücke durch Einbringen einer flüssigkeitsgefüllten Kavität ein Resonanzverhalten erzeugt, kann dies genutzt werden, um die Flüssigkeit zu analysieren.
Im Rahmen von Voruntersuchung wird zunächst das akustische Verhalten des PnK’s, welcher für die Sensorentwicklung genutzt werden soll, unter Vernachlässigung der Flüssigkeit ausführlich untersucht. Hierbei werden zunächst die Bandlücken ermittelt und das Übertragungsverhalten betrachtet. Dieses wird im Anschluss experimentell überprüft.
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.
Additive Manufacturing (AM) of metals has become industrially viable for a large variety of applications, including aerospace, automotive and medicine. Powder bed techniques such as Selective Laser Melting (SLM) based on layer-by-layer deposition and laser melt enable numerous degrees of freedom for the geometrical design. Developing during the manufacturing process, residual stresses may limit the application of SLM parts by reducing the load bearing capacity as well as induce unwanted distortion depending on the boundary conditions specified in manufacturing.
The residual stress distribution in the bulk of IN718 elongated prisms produced by SLM was studied non-destructively by means of neutron diffraction. The samples with different scanning strategies, i.e. hatching length, were measured in as-build condition (on a build plate) and after removal from the build plate.
The absolute values of all stress components decreased after removal from the build plate. Together with surface scan utilizing a coordinate-measuring machine (CMM), it is possible to link the stress release to the sample distortion. Obtained results indicated different residual stress states for each of the transversal, longitudinal and normal component depending on the thermal gradient in the respective direction.
Vor allem in den letzten Jahren ist das Interesse der Industrie an der additiven Fertigung deutlich gestiegen. Die Vorteile dieser Verfahren sind zahlreich und ermöglichen eine ressourcenschonende, kundenorientierte Fertigung von Bauteilen, welche zur stetigen Entwicklung neue Anwendungsbereiche und Werkstoffe führen. Aufgrund der steigenden Anwendungsfälle, nimmt auch der Wunsch nach Betriebssicherheit unabhängig von anschließenden kostenintensiven zerstörenden und zerstörungsfreien Prüfverfahren zu. Zu diesem Zweck werden im Rahmen des von der BAM durchgeführten Themenfeldprojektes „Prozessmonitoring in Additive Manufacturing“ verschiedenste Verfahren auf ihre Tauglichkeit für den in-situ Einsatz bei der Prozessüberwachung in der additiven Fertigung untersucht. Hier werden drei dieser in-situ Verfahren, die Thermografie, die optische Emissionsspektroskopie und die Schallmissionsanalyse für den Einsatz beim Laser-Pulver-Auftragschweißen betrachtet.
Explosive spalling is caused by, among others, the thermohydraulic spalling mechanism. During this process, vaporization, dehydration, moisture-transport and condensation processes interact. As a result, a drying and dehydration zone as well as a saturated zone, known as a moisture clog, are observed inside the unilaterally-heated concrete. The presented research is focused on the experimental investigation of the underlying thermohydraulic processes.
To investigate these, a test methodology based on X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) was developed. Thereby, the X-ray CT scans are carried out simultaneously during the application of a defined unilateral-heating regime on a specially-constructed specimen. This miniaturized specimen, equipped with a double-layer casing, reproduces the condition within a planar, unilaterally-heated building component.
A preliminary test methodology and the first experimental results were presented at the 5th International Workshop on Concrete Spalling in Borås, Sweden (2017). The contribution for the upcoming workshop presents an improved version of this test methodology and new results for a high-performance concrete (HPC) mixture exposed to temperatures up to 500 °C. Regarding the CT measurements, a higher time-resolution of 15 min was achieved and a quantification of the moisture changes was implemented. Due to an increase in signal quality of the NMR measurements, a pore-size specific moisture distribution can now be resolved. This allows to conclude about the moisture reconfiguration between small gel pores and larger interhydrate pores. Additionally, the NMR measurement are no longer limited to first 2.5 cm below the heated surface but a one-dimensional moisture distribution can now be estimated over the whole 10 cm long specimen.
The presented results demonstrate that the combination of X-ray CT and NMR measurements enables to image and quantify the thermally-induced moisture transport and reconfiguration from small gel pores up to macro pores. This provides important insights into the thermohydraulic damage mechanism and leads to a better understanding of spalling avoidance strategies, like the addition of polypropylene fibres.
In special cases of angle beam ultrasonic measurement – e.g. defect detection in hot solids as well as flow measurement of liquid gases or energy storage mediums – the applied transducer has to withstand extreme temperatures. Since the irradiation angle into the specific material is determined not only by wedge design, but also by the speed of sound in both the wedge material and the tested object, the developer must take into account the speed of the wave propagation in a wedge material over the whole temperature range of transducers application.
In this study we investigate the temperature dependence of the speed of longitudinal wave propagation in 10 different materials in the range from -200 °C to 400 °C. The investigated materials belong to different material classes (ceramics, glass, as well as ferrous and non-ferrous metals) and are all temperature-resistant up to at least 600 °C, and therefore applicable as wedge materials in an ultrasonic transducer for use at extreme temperatures.
Modern wind turbine rotor blades consist of sandwich shell segments made from glass fiber reinforced polymers. During manufacturing, defects can arise which could lead to failure of the whole component under dynamic mechanical and thermal loads. Hence during operation defects can arise which, if detected, can be repaired locally and in-situ by applying repair patches instead of taking the whole rotor blade down and repair it remotely. This method is much more time and cost effective, since the shut-down time of the energy converter is limited to a minimum. These repair patches can, however, also lead to new defects if not applied optimally. Therefore, it is necessary to control the quality of the repair patches to ensure the best possible restoration of structural integrity of the component. As a rotor blade is an object with a large aspect ratio, X-ray laminography is predestined to provide 3D information of the objective volume. To enhance the amount of information gained from laminographic reconstruction, we use in this study a photon counting and energy discriminating X-ray detector and apply a material decomposition algorithm to the data. By inherently separating the incident spectra within the detection process into two distinct energy bins, the basis material decomposition can provide material resolved images. Choosing glass and epoxy resin as basis materials and numerically solving the inverse dual-energy equation system, the reconstructed laminographic datasets contain highly valuable information about the distribution of the basis materials within the structure. Furthermore, cross- artifacts arising from the limited angle of the projection data can be reduced by this method which allows to investigate structures that were hidden underneath the artefacts.
Defect recognition in CFRP components using various NDT methods within a smart manufacturing process
(2018)
The manufacturing process of carbon fiber reinforced polymer (CFRP) components is gaining a more and more significant role when looking at the increasing amount of CFRPs used in industries today. The monitoring of the manufacturing process and hence the reliability of the manufactured products, is one of the major challenges we need to face in the near future. Common defects which arise during manufacturing process are e.g. porosity and voids which may lead to delaminations during operation and under load. To find irregularities and classify them as possible defects in an early stage of the manufacturing process is of high importance for the safety and reliability of the finished products, as well as of significant impact from an economical point of view. In this study we compare various NDT methods which were applied to similar CFRP laminate samples in order to detect and characterize regions of defective volume. Besides ultrasound, thermography and eddy current, different X-ray methods like radiography, laminography and computed tomography are used to investigate the samples. These methods are compared with the intention to evaluate their capability to reliably detect and characterize defective volume. Beyond the detection and evaluation of defects, we also investigate possibilities to combine various NDT methods within a smart manufacturing process in which the decision which method shall be applied is inherent within the process. Is it possible to design an in-line or at-line testing process which can recognize defects reliably and reduce testing time and costs? This study aims to show up opportunities of designing a smart NDT process synchronized to the production based on the concepts of smart production (Industry 4.0). A set of defective CFRP laminate samples and different NDT methods were used to demonstrate how effective defects are recognized and how communication between interconnected NDT sensors and the manufacturing process could be organized.
For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring), which have not been researched to an extent that allows to guarantee the adherence to strict quality and safety standards.
In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques.