Ingenieurwissenschaften und zugeordnete Tätigkeiten
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In this presentation, the results of the determination of the diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 are presented. The analysis is based on high-energy synchrotron diffraction experiments performed at the Deutsches Elektronen-Synchrotron. It is shown that the characteristic microstructure of laser powder bed fused Inconel 718 impacts the elastic anisotropy and therefore the diffraction and single-crystal elastic constants. Finally, the consequences on the diffraction-based residual stress determination of laser powder bed fused Inconel 718 are discussed.
AbstractIn this study, we compare the residual stress state in a laser powder bed fusion (PBF‐LB/M) AlSi10Mg alloy in the as‐built (AB) condition with that after two different heat treatments (265 °C for 1 h, HT1; and 300 °C for 2 h, HT2). The bulk residual stress (RS) is determined using synchrotron X‐ray diffraction (SXRD), and near‐surface profiles are determined using laboratory energy‐dispersive X‐ray diffraction (EDXRD). The EDXRD results do not reveal any notable difference between the conditions at a depth of 350 μm, suggesting that the machining process yields a comparable residual stress state in the near‐surface regions. On the other hand, the SXRD results show that HT1 is more effective in relieving the bulk RS. It is observed that HT1 reduces the RS state in both the aluminium matrix and the silicon network. In addtion, HT2 does not have a significant impact on relaxing the RS as‐built state of the matrix, although it does induce a reduction in the RS magnitudes of the Si phase. It is concluded that the heat treatment stress relieving is effective as long as the Si‐network is not disaggregated.
The stress-induced tetragonal to monoclinic (t-m) zirconia phase transformation can provide a certain degree of plasticity to Ceria-stabilized (Ce-TZP) zirconia-based composites. Characterizing and monitoring this phase transition on a millimeter-size range, within the bulk and in-situ remains a challenge. In this work, the mechanical behavior of Ce-TZP based composite was studied in tension, combining microscopy and synchrotron Xray refraction techniques. In contrast with microscopy methods, which only provide surface information, X-ray refraction radiography (SXRR) allowed the visualization of all the transformation bands, over the entire length and thickness of tested specimens, opening up new avenues for in-situ stress-induced t-m transformation studies.
Various software products for the simulation of industrial X-ray radiography have been developed in recent years (e.g., aRTist 2, CIVA CT, Scorpius XLab, SimCT, Wilcore) and their application potential has been shown in numerous works. However, full systematic approaches to characterise a specific CT system for these simulation software products to obtain a truthful digital twin are still missing. In this contribution, we want to present two approaches to obtain realistic grey values in X-ray projections in aRTist 2 simulations based on measured projections. In aRTist 2, the displayed grey value of a pixel is based on the energy density incident on that pixel.
The energy density is calculated based on the X-ray tube spectrum, the attenuation between source and detector as well as an energy-dependent sensitivity curve of the detector. The first approach presented in this contribution uses the sensitivity curve as a free modelling parameter. We measured the signal response at different thicknesses of Al EN-AW6082 at different tube voltages (i.e., different tube spectra). We then regarded the grey values displayed by these projections as a data regression respectively an optimisation problem and obtained the sensitivity curve that is best able to reproduce the measured behaviour in aRTist 2. The resulting sensitivity curve does not necessarily hold physical meaning but is able to simulate the real system behaviour in the simulation software.
The second approach presented in this contribution is to estimate the sensitivity curve based on assumptions about the characteristics of the scintillation detector (e.g., scintillator material, scintillator thickness and signal processing characteristics). For this approach, a linear response function (linear relationship between the deposited energy per pixel and the resulting grey value) is assumed. If the detector characteristics, which affect the simulated deposited energy, are properly modelled, the slope and offset of the response function to match the measured grey values should be the same for different tube spectra. As the offset is constant and given by the grey values measured at no incident radiation, the slope is the remaining parameter to evaluate the success of the detector modelling. We therefore adapted the detector characteristics by changing the detector setup until the slope was nearly the same for all measured tube spectra. We are aware that the resulting parameters of the scintillator material and thickness might not be the real ones, but with those modelling parameters we are able to simulate realistic grey values in aRTist 2. Both of those approaches could potentially be a step forward to a full systematic approach for a digital twin of a real CT system in aRTist 2.
Early detection of fatigue cracks and accurate measurements of the crack growth play an important role in the maintenance and repair strategies of steel structures exposed to cyclic loads during their service life. Observation of welded connections is especially of high relevance due to their higher susceptibility to fatigue damage. The aim of this contribution was to monitor fatigue crack growth in thick welded specimens during fatigue tests as holistically as possible, by implementing multiple NDT methods simultaneously in order to record the crack initiation and propagation until the final fracture. In addition to well-known methods such as strain gauges, thermography, and ultrasound, the crack luminescence method developed at the Bundesanstalt für Materialforschung und -prüfung (BAM), which makes cracks on the surface particularly visible, was also used. For data acquisition, a first data fusion concept was developed and applied in order to synchronize the data of the different methods and to evaluate them to a large extent automatically. The resulting database can ultimately also be used to access, view, and analyze the experimental data for various NDT methods. During the conducted fatigue tests, the simultaneous measurements of the same cracking process enabled a comprehensive comparison of the methods, highlighting their individual strengths and limitations. More importantly, they showed how a synergetic combination of different NDT methods can be beneficial for implementation in large-scale fatigue testing but also in monitoring and inspection programs of in-service structures - such as the support structures of offshore wind turbines.
Self-healing polymers have been developed to improve durability and reduce costs associated with maintenance during service. The addition of thermoplastics to thermosets to produce mendable polymers appears as a promising selfhealing technique. In this study, poly (ethylene-co-methacrylic acid) (EMAA) was added to epoxy resin and the effects of EMAA addition on epoxy properties were evaluated. Specimens with two different contents of thermoplastic and particles sizes were manufactured. A two-level full factorial experimental design was used to evaluate the effect of particle size and particle content on properties of epoxy modified with addition of EMAA. Tensile tests and dynamic mechanical analysis (DMA) were used and the evaluated responses were tensile strength, modulus of elasticity, and glass transition temperature (Tg). X-ray computed tomography (XCT) was used to investigate particle size and concentration after manufacturing. It was found that the particle concentration has greater effects on stress–strain behavior of epoxy while Tg was not significantly affected by neither of the analyzed entrance variables.
This paper outlines significant advancements in our previously developed aerial gas tomography system, now optimized to reconstruct 2D tomographic slices of gas plumes with enhanced precision in outdoor environments. The core of our system is an aerial robot equipped with a custom-built 3-axis aerial gimbal, a Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor for CH4 measurements, a laser rangefinder, and a wide-angle camera, combined with a state-of-the-art gas tomography algorithm. In real-world experiments, we sent the aerial robot along gate-shaped flight patterns over a semi-controlled environment with a static-like gas plume, providing a welldefined ground truth for system evaluation. The reconstructed cross-sectional 2D images closely matched the known ground truth concentration, confirming the system’s high accuracy and reliability. The demonstrated system’s capabilities open doors for potential applications in environmental monitoring and industrial safety, though further testing is planned to ascertain the system’s operational boundaries fully.
This paper explores combining a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor and a video camera to create a virtual gas camera for methane leak detection. This provides a low-to-zero-cost extension of typical TDLAS gas tomography systems. A prototype setup mounted on a ground robot is evaluated. Results acquired using a simulated methane leak show the feasibility of the virtual gas camera, accurately detecting methane leaks by overlaying concentrations onto a visual image. While the acquisition time is significantly longer than for traditional gas cameras, potential enhancements are discussed. The study concludes that the virtual gas camera is feasible and useful, despite its longer acquisition time. It serves as a valuable software-only addition to typical TDLAS gas tomography systems, offering quickly-available on-site data augmentation for visual leak assessment at low-to-zero cost.
This study explores the acceleration of material design in the concrete industry, focusing on improving carbonation resistance, a key factor in the durability of concrete structures. Traditional tests for carbonation resistance are lengthy, but with the construction industry aiming for sustainable production, finding a balance between carbonation resistance and CO2 footprint is crucial. Our research employs two innovative methods: 1. Applying the Sequential Learning App for Materials Discovery (SLAMD), an AI materials design framework, to an extensive dataset of real-world concrete compositions to selectively test materials that meet market demands: maximum durability, optimal eco-durability, and the best cost-durability trade-off. 2. Investigating 1H Nuclear Magnetic Resonance (NMR) relaxometry as a quick alternative for characterizing carbonation behavior, as it saves time compared to traditional tests and assesses the complete material's pore space. Specific NMR features are then integrated into the material design model, with the model's performance compared against traditional approaches. The results of our study are compelling, demonstrating that materials can be precisely tailored to meet specific requirements with minimal data points. This marks a significant stride in the concrete industry, indicating that NMR-based, low-fidelity surrogate characterizations, combined with a focused, data-driven design approach, can substantially accelerate the development of durable, sustainable concrete mixtures.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field material characterization by X-ray imaging is presented. The principle of X-ray Computed Tomography (XCT) is explained. The multiple examples of application of quantitative analysis by XCT are reported, such as additive manufacturing, Li-ion battery, concrete research.