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Efficient multiscale simulation approaches for lightweight compact and foamed fiber-reinforced components
No full textTo reduce the weight of structural components, foamed fiber-reinforced materials promise gains beyond established composites, particularly for bending loading. One of the main barriers to the wider use of FIM has been the inability to predict the properties of FIM parts with sufficient precision up to now. Based on experimental data, we present a multiscale modeling framework for challenging industry-level structural components. First, we identify a suitable effective medium theory that captures the effect of the pores on the mechanical behavior without the need to model them in the microstructural simulations. Afterwards, an effective macroscopic material model is constructed by generating so-called "materials cards", which are later used to interpolate effective properties. The material card entries are determined from homogenization problems solved on representative volume elements with resolved fibers, whose generation accounts for the local fiber-length distribution and fiber orientations. Thereby, the novelty of our approach is the extension of material cards to account for both matrix porosity and the fiber orientation. Results of the effective model of the tri-phasic composite are within the experimental spread. Eventually, applications in detailed structural 3D simulation pipelines using commercial tools like Moldflow and Abaqus emphasize the versatility of our framework for real-world applications.38
Evaluation of the Impact of the Cable Model on the Distance Protection Performance in a Submarine Transmission System
No full text137142Distance protection is widely used to protect transmission systems due to its simplicity and selectivity. The line sequence impedances, which are required for setting the distance relay before its field implementation, depend on the chosen cable models. This paper assesses the accuracy of distance protection for a power system comprising both land and submarine cables. A comparison is made between two approaches for calculating the line sequence impedances of the cables, one with DIgSILENT PowerFactory and one entirely based on the manufacturer’s data. The findings from the fault tests conducted on the power system under study show that the distance relay performs better when the line sequence impedances are calculated using the cable manufacturer’s specifications. While PowerFactory allows the specification of the cross-section layers as provided by the manufacturer, its internal routines neglect some parameters used for the sequence impedance calculations, ultimately compromising their accuracy. When computing the sequence impedances used for the relay settings, the obtained results underline the need to accurately model the actual cross-section layers of transmission cables in order to obtain a better performance of the distance protection
Hybrid Spectral Data Compression for Efficient and Interpretable Bosch Process Monitoring
No full text396Virtual Metrology (VM) is used to estimate wafer-level process outcome using in-situ data, which helps in reducing metrology cost and time. In cyclical plasma etching processes such as Bosch etching, Optical Emission Spectroscopy (OES) provides high-dimensional, temporally resolved data that is rich in process information but computationally burdensome. We propose a hybrid data compression framework for OES data (3648 Channels, 25 Hz) using discrete wavelet transform (DWT) filtering, principal component analysis (PCA), and functional PCA (fPCA). The resulting compressed embedding is interpretable, compact, and predictive, enabling accurate VM while preserving plasma physics insights. Experiments on 100 wafers etched through 100 Bosch cycles demonstrate that the embedding achieves strong data compression (<0.001% of the total volume) and supports accurate prediction of etch depth, outperforming baselines
Venom variation among the three subspecies of the North African mountain viper Vipera monticola Saint Girons 1953
No full text152160The North African mountain viper (Vipera monticola) is a medically relevant venomous snake distributed in Morocco, Algeria, and Tunisia. Three subspecies of V. monticola, exhibiting differences in morphotypes and dietary regimes, are currently recognised: V. m. monticola, V. m. atlantica, and V. m. saintgironsi. Through the application of snake venomics, we analysed the venoms of specimens of Moroccan origin belonging to each of the three subspecies. Snake venom metalloproteinases (svMP), snake venom serine proteases (svSP), C-type lectin and C-type lectin-related proteins (CTL), and phospholipases A2 (PLA2) were predominant, with PLA2 being the most abundant toxin family overall. Disintegrins (DI) and cysteine-rich secretory proteins (CRISP) were exclusive to V. m. monticola and V. m. atlantica, while L-amino-acid oxidases (LAAO) were only found in V. m. saintgironsi. The differences detected in the venom profiles, as well as in presence/absence and relative abundances of toxin families, indicate the occurrence of intraspecific venom variation within V. monticola. The identified patterns of venom similarity between subspecies seem to align more with their phylogenetic relationships than with the reported differences in their feeding habits.22
Design and Analysis of Filter assemblies for the LSTM Instrument
No full textLSTM, funded by the EU and ESA, is part of Copernicus, the European Union's Earth observation program for global monitoring. It is one of the six new missions, expanding the capabilities of the current Copernicus space component. The Copernicus Land Surface Temperature Monitoring, LSTM, mission carries a high spatial-temporal resolution thermal infrared sensor to provide observations of land-surface temperature. The mission responds to priority requirements of the agricultural user community for improving sustainable agricultural productivity at field-scale in a world of increasing water scarcity and variability. Land-surface temperature measurements and derived evapotranspiration are key variables to understand and respond to climate variability, manage water resources for agricultural production, predict droughts, and to address land degradation, natural hazards such as fires and volcanoes, coastal and inland water management as well as urban heat island issues [1]. The LSTM satellite is designed and build by Airbus DS in Madrid, while the development and production of the advanced technology instrument is carried out by Airbus DS in Toulouse. The detector plane filter (DPF) assemblies for the SWIR and VIS detector and the filter assembly for intermediate plane filters VNIR (IPF-VNIR) are developed, manufactured, integrated, and tested by Fraunhofer IOF. Optic Balzers Jena (OBJ) is the responsible subcontractor for the VNIR/SWIR filter assemblies and will provide the optical filter coatings. The design of filter assemblies for the detector plane filters of SWIR detector (DPF-SWIR) is developed. The filter assemblies consist of a lower frame and upper frame. Four single filter substrates coated with the bandpass filter layers are integrated into the lower frame. The upper and lower mask apertures are integrated into the upper and lower frame. The design of DPF-SWIR filter assemblies was analyzed by finite element (FE) analysis. The mechanical loads of sine and random vibration and shock are calculated. The modal analysis shows the meet of requirements of first eigenfrequency. The mechanical loads of interface imperfections are analyzed. The thermal loads are also analyzed, in combination with interface mechanical loads. In sum 21 load cases are investigated
Feasibility Study of Combining Data from Different Sources Within Artificial Intelligence Models to Reduce the Need for Constant Velocity Joint Test Rig Runs
No full textWithin this paper, the feasibility of reducing test rig runs in constant velocity joint (CVJ) development by combining data from different sources (simulation and test rig) for artificial intelligence (AI) models has been investigated. Therefore, a case study on CVJ efficiency prediction using a random forest regressor, a decision-tree-based algorithm, was conducted using a data set of 95,798 points derived from both test rigs (52,486 points) and multi-body simulations (43,312 points). The amount of test rig data in the training data set of the regression model was iteratively reduced from 100% to 12.5% to investigate the need of expensive test rig data. Additionally, clustering models related to KMeans-algorithm were performed, to achieve further improvements of the AI models and more information about the data. Furthermore, regression and clustering models were performed with data dimensionally reduced by principal component analysis (PCA) to improve model complexity and performance. The number of principal components for the regression model was reduced from 65 to 5 components to investigate their influence on the models predictions. The study showed that combining data from different sources has a positive impact on the predictions of AI models and the confidence of their results, even though the R2-Score of the trained regression models did not change significantly, ranging from 0.927% to 0.9497%.14
A Literature Review: Problem Definition and Identification Donation Blockchain
No full text6267This literature review addresses the challenges of traditional donation systems which are intended to be solved through the use of blockchain technology. The study examines existing literature that aim to improve donation processes by leveraging blockchain’s attributes of transparency, decentralization, and automation through smart contracts. Using a framework, the review analyzes current research to assess the landscape and identify strengths, weaknesses, and research gaps in donation systems using blockchain. The review highlights blockchain’s potential to improve trust, efficiency, and accountability in donation ecosystems, while identifying areas for further research and development
Erhöhung der Zuverlässigkeit elektronischer Baugruppen durch eine verbesserte Vorhersage der Alterungsbeständigkeit von Vergussmassen und Klebstoffen unter zyklisch-thermischer Beanspruchung
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Digital und nachhaltig die Zukunft meistern: Wie Unternehmen den Wert der Twin Transformation realisieren können
No full textDie Twin Transformation Studie 2.0 zeigt, wie Unternehmen durch die Verknüpfung von Digitalisierung und Nachhaltigkeit messbare Mehrwerte erzielen. Praxisbeispiele und der Twin Transformation Value Canvas bieten konkrete Handlungsempfehlungen
Wafer-scale epitaxial growth of AlN (0001) on heteroepitaxial diamond (111)
No full textWurtzite-type aluminum nitride (AlN) films were deposited by magnetron sputtering epitaxy (MSE) on wafer-scale diamond layers, which in turn were grown heteroepitaxially by plasma-enhanced chemical vapor deposition applying bias-enhanced nucleation on an Ir seed layer. The seed was fabricated on Si (111) wafers with an yttria-stabilized zirconia buffer layer by MSE. Analysis by x-ray diffraction has confirmed fully epitaxial growth throughout the entire stack. Due to diamond's high thermal conductivity, which makes it an effective heat sink, this stack constitutes an important step toward monolithically integrated high-efficiency III-nitride-diamond power electronics.128