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The role of MBSE in the exploration and exploitation of sustainable development Die rolle von MBSE fur die nachhaltige forschung und entwicklung
No full text175186The present study analyses how to manage and integrate internal and external knowledge sources in sustainable product-, service- and system development with MBSE. To do so, the study employs a qualitative research approach. The data sample consists of eighteen experts from research and industry in the field of MBSE and sustainability. Together, the results indicate that MBSE enables both exploration and exploitation of sustainability-centered knowledge sources. MBSE was most often recognized to support ecologic and economic sustainability. Social sustainability was least often recognized. A comparison of expert answers revealed, discrepancies in the perceived scope of the sustainability performance of MBSE
TENSILE PROPERTY PREDICTION OF LONG FIBER THERMOPLASTIC COMPOSITES MANUFACTURED BY LFT-D-IM PROCESS
No full textThe objective of the study is to predict tensile properties for long fiber thermoplastic composites manufactured by direct compounding of long fiber thermoplastic followed by injection molding (LFT-D-IM). Tensile properties of discontinuous fiber thermoplastic composites are influenced by factors of fiber's length, content, and orientation. Injection molding of a composite melt results in fiber orientation distribution while flow properties of the melt are influenced by fiber's length and content. After consolidation, tensile properties of the composite are determined by the factors in view of micromechanics. Consequently, the composite exhibits locally different fiber orientation and resulting tensile property distribution. To predict the distribution, the strategy combined (1) prediction of polymer-melt-flow-induced fiber orientation by thermo-viscoelastic flow analysis, (2) flow analysis - FEA mapping, and (3) micromechanics-based mechanical property prediction. To verify, tensile modulus at specimen scale were compared. For simulation, tensile modulus were calculated by structural analysis for tensile testing of dog-bone specimens whose properties from (3) were applied on their finite elements. For experiment, long glass fiber/polyamide 66 (LGF/PA66) composite plates were manufactured by LFT-D-IM from which dog-bone specimens were prepared and tensile modulus were measured. The measured and predicted tensile modulus showed good agreement at various locations of the composite plate
The Prospective COVID-19 Post-Immunization Serological Cohort in Munich (KoCo-Impf): Risk Factors and Determinants of Immune Response in Healthcare Workers
No full textAntibody studies analyze immune responses to SARS-CoV-2 vaccination and infection, which is crucial for selecting vaccination strategies. In the KoCo-Impf study, conducted between 16 June and 16 December 2021, 6088 participants aged 18 and above from Munich were recruited to monitor antibodies, particularly in healthcare workers (HCWs) at higher risk of infection. Roche Elecsys® Anti-SARS-CoV-2 assays on dried blood spots were used to detect prior infections (anti-Nucleocapsid antibodies) and to indicate combinations of vaccinations/infections (anti-Spike antibodies). The anti-Spike seroprevalence was 94.7%, whereas, for anti-Nucleocapsid, it was only 6.9%. HCW status and contact with SARS-CoV-2-positive individuals were identified as infection risk factors, while vaccination and current smoking were associated with reduced risk. Older age correlated with higher anti-Nucleocapsid antibody levels, while vaccination and current smoking decreased the response. Vaccination alone or combined with infection led to higher anti-Spike antibody levels. Increasing time since the second vaccination, advancing age, and current smoking reduced the anti-Spike response. The cumulative number of cases in Munich affected the anti-Spike response over time but had no impact on anti-Nucleocapsid antibody development/seropositivity. Due to the significantly higher infection risk faced by HCWs and the limited number of significant risk factors, it is suggested that all HCWs require protection regardless of individual traits.15
Site-selective substitution and resulting magnetism in arc-melted perovskite ATiO3-δ (A = Ca, Sr, Ba)
No full text67786786Magnetic properties in perovskite titanates ATiO3-δ (A = Ca, Sr, Ba) were investigated before and after arc melting. Crystal structure analysis was conducted by powder synchrotron X-ray diffraction with Rietveld refinements. Quantitative chemical element analysis was carried out by X-ray photoelectron spectroscopy. Magnetic measurements were conducted by vibrating sample magnetometer and X-ray magnetic circular dichroism (XMCD). The magnetic properties are found to be affected by impurities of 3d elements such as Fe, Co, and Ni. Depending on the composition and crystal structure, the occupation of the magnetic ions in perovskite titanates is selectively varied, which is interpreted to be the origin of the different magnetic behaviors in arc-melted perovskite titanates ATiO3-δ (A = Ca, Sr, Ba). In addition, both formation of oxygen vacancies and the reduction of Ti4+ to Ti3+ during arc-melting also play a role as proven by XMCD. Nevertheless, preferential site occupation of magnetic impurities is dominant in the magnetic properties of arc-melted perovskite ATiO3-δ (A = Ca, Sr, Ba).1061
Application of Machine Learning Methods for Process Optimization in Electronic Packaging Processes
No full textEpoxy resins are commonly used as encapsulation materials in electronic packaging processes. Fluctuations in the materials lead to both changes in processability and to varying quality. Ideally, these variations should be identified, and measures taken as quickly as possible to reduce scrap parts and thus costs. A promising optimization approach for encapsulation processes are machine learning models, which have already shown good results in quality predictions, especially for injection molding. Subsequent quality measurements are avoided with good quality prediction models. With this type of models, not only predictions can be made, but also optimal parameter combinations can be found. In this paper, models for predicting quality criteria warpage and residual enthalpy of the epoxy molding compound were set up, trained and validated. Time series of in-situ sensors were used, from which relevant features were extracted and which, together with machine parameters, provide a dataset for prediction. The most promising prediction models are random forest regression and gradient boosting regression. They predict warpage with an accuracy of 90 % to 91 % and the residual enthalpy with an accuracy of 95 %. Subsequently, optimization models of the machine parameters were set up. All relevant target variables were considered in a cost function, through the minimization of which an optimal parameter set was found. The gradient boosted tree and Bayesian optimization were determined to be the most promising models, as they lead to the lowest values of the respective cost function
Right-Angle D-Band Differential Microstrip to Waveguide Transition with Irises
No full text710A right-angle transition from differential microstrip line to rectangular waveguide is proposed that operates in D-band and does not require a backshort. By utilization of a resonant patch and multiple irises within the waveguide that act as a matching network, a relative bandwidth of 35% is achieved. Simulations and measurements are performed and the influence of manufacturing tolerances is investigated
ExRec: Experimental Framework for Reconfigurable Networks Based on Off-the-Shelf Hardware
No full text6672In order to meet the increasingly stringent throughput and latency requirements in datacenter networks, several innovative network architectures based on reconfigurable optical topologies have been proposed. Examples include demand-oblivious reconfigurable topologies such as RotorNet (SIGCOMM 2017), Opera (NSDI 2020), and Sirius (SIGCOMM 2021), as well as demand-aware topologies such as ProjecToR (SIGCOMM 2016). All these architectures feature attractive performance properties using specific prototypes. However, reproducing these experiments is often difficult due to missing hardware and publicly available software. This paper presents a flexible framework for reconfigurable networks based on off-the-shelf hardware, which supports experimentation and reproducibility at a small scale. We describe how our framework, ExReC, can be instantiated with different configurations, allowing us to emulate existing architectures and to study their trade-offs. Finally, we demonstrate the application of our approach to different use cases and workloads, including distributed machine learning training
Influence of Hydrogen on Crack Growth Resistance of Steels for Energy Infrastructure Applications
No full text4148The aim of this study was to develop a methodology to investigate hydrogen effects on crack growth resistance in low alloy ferritic steels using cathodic hydrogen precharging with the focus on stable crack growth in pressure vessel steel grade P355NH. Inert gas fusion measurements (IGF) were performed to determine hydrogen uptake and estimate diffusion behavior. Numerical calculations allowed a first prediction of the concentration profile in compact tension specimens. To assess the influence of internal hydrogen on crack growth resistance, fatigue precracking was performed and J-Δa-curves were measured. Accelerated fatigue crack growth was observed for high stress intensities and low frequencies. In the J-Δa-analysis, the crack growth resistance in hydrogen charged material was reduced in contrast to uncharged specimens. However, no unstable crack growth was perceivable. In conclusion, the steel remains predominately ductile with the applied charging conditions.7
Full Octave Continuously Tunable SiGe Bipolar LC-VCO in Ku-Band
No full text277280In this paper a signal generation concept is presented with frequency tuning ranges of more than one octave in the Ku-Band. On the MMIC a fundamental cross-coupled ultra-wideband Ku-Band LC-VCO is integrated along with a simple buffer and a frequency divider for PLL stabilization. The chip is fabricated in Infineon's BiCMOS production technology B11HFC which offers HBTs with an fT of 250 GHz and fmax of 370 GHz. The chip has a power consumption of only 106 mW and uses an area of 0.52 mm2. The VCO reaches an absolute frequency tuning range (FTR) of 12.1 GHz (relative FTR=75.1%) at a center frequency of 16.1 GHz. The phase noise at 1 MHz offset is as low as -104 dBc/Hz. The output level is around 0 dBm
Impact of Printing Parameters on Green Density Homogeneity in Lithography-based Metal Manufacturing
No full textLithography-based metal manufacturing (LMM) is an emerging technology for the 3D production of metal parts with high dimensional accuracy and outstanding surface quality. To reliably reproduce these properties, a better understanding of parameter characteristics correlation is necessary. One of the most important characteristics of the printed part is the green density and its distribution within the building volume. This study investigates the printing parameters degree of powder filling of the feedstock, layer thickness, coating speed, coating mode and size of the material roll, with the help of a Design of Experiment (DoE). The green parts are getting characterised by dimensions, weight and density, the latter one determined by using the principle of Archimedes. Also, the strength of the green part is investigated. As the densification during sintering works as a magnifying glass for imperfections and differences in green density of the green parts, all samples get sintered and analysed on their density and shrinkage afterwards