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Paper des Monats
- ja (1)
We introduce a novel adaptive Gaussian Process Regression (GPR) methodology for efficient construction of surrogate models for Bayesian inverse problems with expensive forward model evaluations. An adaptive design strategy focuses on optimizing both the positioning and simulation accuracy of training data in order to reduce the computational cost of simulating training data without compromising the fidelity of the posterior distributions of parameters. The method interleaves a goal-oriented active learning algorithm selecting evaluation points and tolerances based on the expected impact on the Kullback-Leibler divergence of surrogated and true posterior with a Markov Chain Monte Carlo sampling of the posterior. The performance benefit of the adaptive approach is demonstrated for two simple test problems.
Structural health monitoring (SHM) using ultrasonic-guided waves (UGWs) enables continuous monitoring of components with complex geometries and provides extensive information about their structural integrity and their overall condition. Composite overwrapped pressure vessels (COPVs) used for storing hydrogen gases at very high pressures are an example of a critical infrastructure that could benefit significantly from SHM. This can be used to increase the periodic inspection intervals, ensure safe operating conditions by early detection of anomalies, and ultimately estimate the remaining lifetime of COPVs. Therefore, in the digital quality infrastructure initiative (QI-Digital) in Germany, an SHM system is being developed for COPVs used in a hydrogen refueling station. In this study, the results of a lifetime fatigue test on a Type IV COPV subjected to many thousands of load cycles under different temperatures and pressures are presented to demonstrate the strengths and challenges associated with such an SHM system. During the cyclic testing up to the final material failure of the COPV, a sensor network of fifteen surface-mounted piezoelectric (PZT) wafers was used to collect the UGW data. However, the pressure variations, the aging process of the COPV, the environmental parameters, and possible damages simultaneously have an impact on the recorded signals. This issue and the lack of labeled data make signal processing and analysis even more demanding. Thus, in this study, semi-supervised, and unsupervised deep learning approaches are utilized to separate the influence of different variables on the UGW data with the final aim of detecting and localizing the damage before critical failure.
The main advantage of air-coupled ultrasonic testing is the absence of a liquid couplant, which can damage some materials. However, most air-coupled testing scenarios have the challenge of low signals and a signal-to-noise ratio (SNR) several orders of magnitude lower than with couplant-assisted tech-niques. Since this challenge of small SNR also exists in radar technology, the pulse compression used there was adapted and applied to the physical conditions of air-coupled ultrasonic testing. This paper presents ultrasonic transmission measurements on a carbon-fibre-reinforced polymer plate using two experimental setups: 1) a thermoacoustic transmitter and an optical microphone and 2) a pair of ferroe-lectret transducers as transmitter and receiver. Thermoacoustic transmitters convert electrical energy to heat, which causes the air to expand thus producing acoustic waves. The optical microphone is based on a Fabry-Perot interferometer. Ferroelectrets are charged cellular polymers, having piezoelectric proper-ties and excellent acoustic matching to air. Both thermoacoustic transmitters and ferroelectrets are non-linear regarding the relationship between the excited sound pressure and the excitation voltage. Due to these physical boundary conditions, unipolar coding was used to modulate the excitation signals. Vari-ous codes were tested, and parameters of the excitation pulses were varied to find the optimal combina-tion for each experimental setup. The application of pulse compression to the combination of thermo-acoustic transmitter and optical microphone increased the signal-to-noise ratio by up to 16 dB and for the ferroelectret transducers by up to 23 dB.
Die Fließfähigkeit von Metallpulvern gilt als wichtige Pulvereigenschaft für den additiven Aufbau mittels Laser, wobei bisher wenige Arbeiten die Auswirkungen im Laserpulverauftragschweißen (Engl.: Directed Energy Deposition DED-LB) untersuchen. Arbeiten, die sich mit den Pulvereigenschaften für Pulverbettverfahren beschäftigen, zeigen Korrelationen zwischen Partikelgrößenverteilung und Fließeigenschaften mit der Bauteildichte und den mechanischen Eigenschaften. Sie bewerten insbesondere Pulverbettdichte und -stabilität. In der vorliegenden Arbeit werden daher die Eigenschaften zweier Pulverfraktionen (20 µm – 63 µm und 63 µm – 150 µm) des austenitischen Stahls AISI 316L und deren freien Ausfluss im Vergleich zur Pulverdichte untersucht. Die Untersuchungen zeigen, dass die feinere Pulverfraktion eine um 14,5 % höhere Durchflussrate erzielt als die gröbere Fraktion. korreliert die Ergebnisse zur inneren Porosität und Partikelgrößenverteilung.
Die Analyse der Bauteilqualität zeigt einen geringen Einfluss der Korngrößenverteilung auf die Porosiät der DED-LB aufgebauten Quader.
Hochbelastete Stahlbauteile lassen sich durch Auftragen von Kobalt-Chrom Legierungen vor Verschleiß schützen. Die plötzliche Änderung der Materialeigenschaften führt jedoch zu Spannungen und Rissen im Anbindungsbereich. Daraus resultierende Abplatzungen stellen eine Gefahr für die Funktionsfähigkeit der Maschine und damit für Mensch und Umwelt dar. Um die Belastbarkeit der Schutzschicht zu verbessern, kann die Anbindung durch einen gradierten Materialübergang optimiert werden. Diese funktional gradierten Materialien können mittels pulverbasiertem Directed Energy Deposition aufgetragen werden. Die Methodik zum Aufbau und zur Qualitätssicherung solcher Materialien wurde in vorangegangenen Arbeiten für dickwandige Geometrien gezeigt. Für dünnwandige Geometrien ist die Anwendbarkeit bisher unzureichend untersucht worden. Diese Arbeit zeigt am Beispiel einer dünnwandigen gradierten Schneckengeometrie die Einsatzfähigkeit der Methodik. Dafür wird die Gefügestruktur der Gradierung auf Fehler untersucht und der Härteverlauf gemessen. Außerdem wird die relative Dichte anhand eines bereits trainierten neuronalen Netzes vorhergesagt und mit einer Porositätsuntersuchung verglichen.
Quantifying uncertainties in subsurface properties and stratigraphy can lead to better understanding of the ground conditions and enhance the design and assessment of geotechnical structures. Several studies have utilized Cone Penetration Test (CPT) data and employed Bayesian and Machine Learning methods to quantify the geological uncertainty, based on the Robertson’s soil classification charts and the Soil Behaviour Type Index (Ic). The incorporation of borehole data can reduce the stratigraphic uncertainty. Significant challenges can arise, however, mainly due to the intrinsic differences between field and laboratory-based soil classification systems, which can potentially lead to inconsistent soil classification. To this end, this study proposes a multivariate Gaussian Process model that utilizes site-specific data and: i) jointly models multiple categorical (USCS labels) and continuous (Ic) variables, ii) learns a (shared) spatial correlation structure and the betweenoutputs covariance, and iii) produces two types of dependent classification outputs. The results indicate that the integration of geotechnical and geological information into a unified model can provide more reliable predictions of the subsurface stratification, by allowing simultaneous interpretation of USCS and Ic profiles. Importantly, the model demonstrates the potential to integrate multiple variables of different types, aiming to contribute to the development of a methodology for joint modeling of geotechnical, geological and geophysical data.
How structural health monitoring can be embedded in a digital quality infrastructure: an example.
(2024)
The digital Quality Infrastructure (QI) initiative “QI-Digital” in Germany is focusing on implementing new technologies and approaches to ensure that the task of quality assurance is more efficient and ready for the digital and green transformation of the economy. The implementation of quality control key elements, such as Smart Standards, Digital Certificates and QI-cloud solutions shall contribute to solving the socio-economic, ecological, and technological challenges of our time. Hydrogen is a key energy carrier and has the potential to play a significant role in the energy transition, especially in mobility. An essential factor for the broad acceptance of hydrogen-based mobility is the availability of refueling stations that operate reliably and safely. Using the example of a Hydrogen Refueling Station (HRS) built within the QI-Digital initiative, the Federal Institute for Material Research and Testing (BAM) aims to establish a real laboratory where modern measurement techniques and new digital methods are implemented to enhance operational safety, availability, and economic efficiency and render the technology more attractive for the industry.
In this work, we present an approach to establish a Structural Health Monitoring (SHM) system on a high-pressure buffer inside HRS and show how it could be embedded into a digital QI. The high-pressure buffers are essential components of the plant which are currently inspected periodically without regard to their operating history. Focusing on the transition to a continuous and digitally supported monitoring of the component’s integrity during operation the novel inspection scheme will be linked to a completely digitalized component-related documentation and tested using digital certificates. This allows the operational safety and, if necessary, the remaining useful lifetime to be assessed on an ongoing basis and to be a valuable contribution to increasing sustainability.
Long-term dry interim storage may adversely affect the mechanical properties of spent fuel rods, possibly resulting in a reduced resilience during handling or transport after storage. The cladding is the first barrier for the spent fuel pellets. An established method for characterising the cladding material is the ring compression test (RCT), in which a small, cylindrical sample of the cladding tube is subjected to a compressive load. Radial hydrides may precipitate in zirconium-based alloys (Zircaloy) under pre-storage drying and during slow cooling, which result in embrittlement of the cladding material and eventually a possible sudden failure of cladding integrity under additional mechanical loads. The focus of the presented research is on the development of appropriate nu-merical methods for predicting the mechanical behaviour and identification of limiting conditions to prevent brittle fracture of Zircaloy claddings. A modelling approach based on cohesive zones is ex-plained which is able to reproduce the propagation of cracks initiated at radial hydrides in the zir-conium matrix. The developed methods are applied to defueled samples of cladding alloy ZIRLO®, which were subjected to a thermo-mechanical treatment to reorient existing circumferential hy-drides to radial hydrides. A selected sample showing sudden load drops during a quasi-static ring compression test is analysed by means of fracture mechanics for illustrative purposes. Based on the developed fracture mechanics approach, not only the deformation behaviour but also the fail-ure behaviour of irradiated as well as unirradiated Zircaloy claddings with radial hydrides under RCT loading conditions can be adequately described.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a nondestructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. We study our proposed testing method along experiments carried out on a custom research PBF-LB/M machine using infrared (IR) cameras.
Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
Das Laserstrahl-Lichtbogen-Hybridschweißverfahren kombiniert Laserstrahl- und Lichtbogenschweißverfahren in einem gemeinsamen Schmelzbad. Das Verfahren wurde Ende der 70er Jahre entwickelt, um die Synergieeffekte der Schweißprozesse effektiv zu nutzen. Durch die hohe Strahlungsintensität des Laserstrahls werden hohe Einschweißtiefen erreicht. Es ist möglich, die Anzahl der Schweißlagen zu reduzieren und somit die thermische Belastung des Grundwerkstoffes zu senken, da der Wärmeeintrag verringert wird. Die Überbrückung von Spalten und Kantenversatz kann durch die Zufuhr eines geschmolzenen Zusatzdrahtes durch das MSG-Verfahren erreicht werden. Der Zusatzdraht kann zudem das metallurgische Gefüge positiv beeinflussen. Daher ist das Laser-Hybridschweißverfahren ideal für das einlagige Schweißen von Dickblechen und wird bereits erfolgreich in der Schiffbauindustrie zum Schweißen von Blechen mit einer Dicke von bis zu 15 mm verwendet. Obwohl Hochleistungslaser heutzutage bereits im Multi-Kilowatt-Bereich verfügbar sind, sind sie für den industriellen Einsatz nur auf Stahlbleche mit einer Dicke von max. 15 mm geeignet. Hohe Abkühlgeschwindigkeiten, gravitationsbedingtes Austropfen beim einlagigen Schweißen von Dickblechen, Prozessinstabilitäten bei höheren Laserleistungen und Schweißnahtimperfektionen wie Rissbildung sind einige Faktoren, die den Einsatz von Laser-Hybridschweißtechnologien aktuell begrenzen. Ohne eine Badstütze ist eine Verringerung der Schweißgeschwindigkeit und somit der Abkühlgeschwindigkeit aufgrund unzulässiger Wurzelüberhöhungen oder gravitationsbedingtem Austropfen nicht möglich. Bei herkömmlichen Badstützen ist es allerdings erforderlich, dass sie mechanisch befestigt und die Wurzel entfernt oder nachbearbeitet werden muss. In dieser Arbeit wird als Alternative das innovative Konzept der elektromagnetischen Schweißbadsicherung vorgestellt und die Fähigkeiten dieses Verfahrens erläutert.