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- ItemMachine learning for additive manufacturing: Predicting materials characteristics and their uncertainty(Amsterdam [u.a.] : Elsevier Science, 2023) Chernyavsky, Dmitry; Kononenko, Denys Y.; Han, Jun Hee; Kim, Hwi Jun; van den Brink, Jeroen; Kosiba, KonradAdditive manufacturing (AM) is known for versatile fabrication of complex parts, while also allowing the synthesis of materials with desired microstructures and resulting properties. These benefits come at a cost: process control to manufacture parts within given specifications is very challenging due to the relevance of a large number of processing parameters. Efficient predictive machine learning (ML) models trained on small datasets, can minimize this cost. They also allow to assess the quality of the dataset inclusive of uncertainty. This is important in order for additively manufactured parts to meet property specifications not only on average, but also within a given variance or uncertainty. Here, we demonstrate this strategy by developing a heteroscedastic Gaussian process (HGP) model, from a dataset based on laser powder bed fusion of a glass-forming alloy at varying processing parameters. Using amorphicity as the microstructural descriptor, we train the model on our Zr52.5Cu17.9Ni14.6Al10Ti5 (at.%) alloy dataset. The HGP model not only accurately predicts the mean value of amorphicity, but also provides the respective uncertainty. The quantification of the aleatoric and epistemic uncertainty contributions allows to assess intrinsic inaccuracies of the dataset, as well as identify underlying physical phenomena. This HGP model approach enables to systematically improve ML-driven AM processes.
- ItemBreakdown of continuum models for spherical probe adhesion tests on micropatterned surfaces(Amsterdam [u.a.] : Elsevier Science, 2021) Bettscheider, Simon; Yu, Dan; Foster, Kimberly; McMeeking, Robert; Arzt, Eduard; Hensel, René; Booth, Jamie A.The adhesion of fibrillar dry adhesives, mimicking nature's principles of contact splitting, is commonly characterized by using axisymmetric probes having either a flat punch or spherical geometry. When using spherical probes, the adhesive pull-off force measured depends strongly on the compressive preload applied when making contact and on the geometry of the probe. Together, these effects complicate comparisons of the adhesive performance of micropatterned surfaces measured in different experiments. In this work we explore these issues, extending previous theoretical treatments of this problem by considering a fully compliant backing layer with an array of discrete elastic fibrils on its surface. We compare the results of the semi-analytical model presented to existing continuum theories, particularly with respect to determining a measurement system- and procedure-independent metric for the local adhesive strength of the fibrils from the global pull-off force. It is found that the discrete nature of the interface plays a dominant role across a broad range of relevant system parameters. Accordingly, a convenient tool for simulation of a discrete array is provided. An experimental procedure is recommended for use in conjunction with this tool in order to extract a value for the local adhesive strength of the fibrils, which is independent of the other system properties (probe radius, backing layer thickness, and preload) and thus is suitable for comparison across experimental studies.
- ItemThe impact of atmospheric boundary layer, opening configuration and presence of animals on the ventilation of a cattle barn(Amsterdam [u.a.] : Elsevier Science, 2020) Nosek, Štěpán; Kluková, Zuzana; Jakubcová, Michaela; Yi, Qianying; Janke, David; Demeyer, Peter; Jaňour, ZbyněkNaturally ventilated livestock buildings (NVLB) represent one of the most significant sources of ammonia emissions. However, even the dispersion of passive gas in an NVLB is still not well understood. In this paper, we present a detailed investigation of passive pollutant dispersion in a model of a cattle barn using the wind tunnel experiment method. We simulated the pollution of the barn by a ground-level planar source. We used the time-resolved particle image velocimetry (TR-PIV) and the fast flame ionisation detector (FFID) to study the flow and dispersion processes at high spatial and temporal resolution. We employed the Proper Orthogonal Decomposition (POD) and Oscillating Patterns Decomposition (OPD) methods to detect the coherent structures of the flow. The results show that the type of atmospheric boundary layer (ABL) and sidewall opening height have a significant impact on the pollutant dispersion in the barn, while the presence of animals and doors openings are insignificant under conditions of winds perpendicular to the sidewall openings. We found that the dynamic coherent structures, developed by the Kelvin-Helmholtz instability, contribute to the pollutant transport in the barn. We demonstrate that in any of the studied cases the pollutant was not well mixed within the barn and that a significant underestimation (up to by a factor 3) of the barn ventilation might be obtained using, e.g. tracer gas method. © 2020 The Authors
- ItemBayesian approach for auroral oval reconstruction from ground-based observations(Amsterdam [u.a.] : Elsevier Science, 2022) Wagner, D.; Neuhäuser, R.; Arlt, R.Naked eye observations of aurorae might be used to obtain information on the large-scale magnetic field of the Earth at historic times. Their abundance may also help bridge gaps in observational time-series of proxies for solar activity such as the sunspot number or cosmogenic isotopes. With information derived from aurora observations like observing site, time of aurora sighting and position on the sky we can reconstruct the auroral oval. Since aurorae are correlated with geomagnetic indices like the Kp index, it is possible to obtain information about the terrestrial magnetic field in the form of the position of the magnetic poles as well as the magnetic disturbance level. Here we present a Bayesian approach to reconstruct the auroral oval from ground-based observations by using two different auroral oval models. With this method we can estimate the position of the magnetic poles in corrected geomagnetic coordinates as well as the Kp index. The method is first validated on synthetic observations before it is applied to four modern geomagnetic storms between 2003 and 2017 where ground-based reports and photographs were used to obtain the necessary information. Based on the four modern geomagnetic storms we have shown, that we are able to reconstruct the pole location with an average accuracy of ≈2° in latitude and ≈11° in longitude. The Kp index can be inferred with a precision of one class. The future goal is to employ the method to historical storms, where we expect somewhat higher uncertainties, since observations may be less accurate or not favorably distributed.
- ItemLong term trends of mesopheric ice layers: A model study(Amsterdam [u.a.] : Elsevier Science, 2021) Lübken, Franz-Josef; Baumgarten, Gerd; Berger, UweTrends derived from the Leibniz-Institute Middle Atmosphere Model (LIMA) and the MIMAS ice particle model (Mesospheric Ice Microphysics And tranSport model) are presented for a period of 138 years (1871–2008) and for middle, high, and arctic latitudes, namely 58°N, 69°N, and 78°N, respectively. We focus on the analysis of mesospheric ice layers (NLC, noctilucent clouds) in the main summer season (July) and on yearly mean values. Model runs with and without an increase of carbon dioxide and water vapor (from methane oxidation) concentrations are performed. Trends are most prominent after ~1960 when the increase of both CO2 and H2O accelerates. It is important to distinguish between tendencies on geometric altitudes and on given pressure levels converted to altitudes (‘pressure altitudes’). Negative trends of (geometric) NLC altitudes are primarily due to cooling below NLC altitudes caused by CO2 increase. Increases of ice particle radii and NLC brightness with time are mainly caused by an enhancement of water vapor. Several ice layer and background parameter trends are similar at high and arctic latitudes but are substantially different at middle latitudes. This concerns, for example, occurrence rates, ice water content (IWC), and number of ice particles in a column. Considering the time period after 1960, geometric altitudes of NLC decrease by approximately 260 m per decade, and brightness increases by roughly 50% (1960–2008), independent of latitude. NLC altitudes decrease by approximately 15–20 m per increase of CO2 by 1 ppmv. The number of ice particles in a column and also at the altitude of maximum backscatter is nearly constant with time. At all latitudes, yearly mean NLC appear at altitudes where temperatures are close to 145±1 K. Ice particles are present nearly all the time at high and arctic latitudes, but are much less common at middle latitudes. Ice water content and maximum backscatter (βmax) are highly correlated, where the slope depends on latitude. This allows to combine data sets from satellites and lidars. Furthermore, IWC and the concentration of water vapor at βmax are also strongly correlated. Nearly all trends depend on a lower limit applied for βmax, e.g., IWC and occurrence rates. Results from LIMA/MIMAS are in very good agreement with observations.
- ItemSmall-scale structures in noctilucent clouds observed by lidar(Amsterdam [u.a.] : Elsevier Science, 2020) Schäfer, Britta; Baumgarten, Gerd; Fiedler, JensNoctilucent clouds (NLC) are mesospheric ice clouds occurring in the summer hemisphere at high latitudes and an altitude of about 83km. This region is the coldest of the earth's atmosphere and is characterized by the presence of wave interaction and dissipation. The processes involved here lead to a variety of structures and instabilities that become visible in noctilucent clouds and are observed by different instruments. In this work high-resolution lidar measurements are used to give a wide overview of the structures at small scales below the Brunt–Väisälä period of ∼5min. For the first time a large amount of NLC profiles from lidar with a temporal resolution of 1s is analyzed in detail, covering about 1400h during the summer from 2011 to 2018. A new categorization focusing on small-scale structures is introduced, and occurrence statistics for these categories in the season of 2014 are performed. Both wave structures with periods below 10min and thin layers of <100m thickness are commonly found. When taking simultaneous wind measurements into account, we find that structures often are advected by the wind. © 2020 The Authors
- ItemUse of polymers as wavenumber calibration standards in deep-UVRR(Amsterdam [u.a.] : Elsevier Science, 2022) Pistiki, Aikaterini; Ryabchykov, Oleg; Bocklitz, Thomas W.; Rösch, Petra; Popp, JürgenDeep-UV resonance Raman spectroscopy (UVRR) allows the classification of bacterial species with high accuracy and is a promising tool to be developed for clinical application. For this attempt, the optimization of the wavenumber calibration is required to correct the overtime changes of the Raman setup. In the present study, different polymers were investigated as potential calibration agents. The ones with many sharp bands within the spectral range 400–1900 cm−1 were selected and used for wavenumber calibration of bacterial spectra. Classification models were built using a training cross-validation dataset that was then evaluated with an independent test dataset obtained after 4 months. Without calibration, the training cross-validation dataset provided an accuracy for differentiation above 99 % that dropped to 51.2 % after test evaluation. Applying the test evaluation with PET and Teflon calibration allowed correct assignment of all spectra of Gram-positive isolates. Calibration with PS and PEI leads to misclassifications that could be overcome with majority voting. Concerning the very closely related and similar in genome and cell biochemistry Enterobacteriaceae species, all spectra of the training cross-validation dataset were correctly classified but were misclassified in test evaluation. These results show the importance of selecting the most suitable calibration agent in the classification of bacterial species and help in the optimization of the deep-UVRR technique.
- ItemDevelopment of an electrochemical sensor for in-situ monitoring of reactive species produced by cold physical plasma(Amsterdam [u.a.] : Elsevier Science, 2021) Nasri, Zahra; Bruno, Giuliana; Bekeschus, Sander; Weltmann, Klaus-Dieter; von Woedtke, Thomas; Wende, KristianThe extent of clinical applications of oxidative stress-based therapies such as photodynamic therapy (PDT) or respiratory chain disruptors are increasing rapidly, with cold physical plasma (CPP) emerging as a further option. According to the current knowledge, the biological effects of CPP base on reactive oxygen and nitrogen species (RONS) relevant in cell signaling. To monitor the safety and the biological impact of the CPP, determining the local generation of RONS in the same environment in which they are going to be applied is desirable. Here, for the first time, the development of an electrochemical sensor for the simple, quick, and parallel determination of plasma-generated reactive species is described. The proposed sensor consists of a toluidine blue redox system that is covalently attached to a gold electrode surface. By recording chronoamperometry at different potentials, it is possible to follow the in-situ production of the main long-lived reactive oxygen and nitrogen species like hydrogen peroxide, nitrite, hypochlorite, and chloramine with time. The applicability of this electrochemical sensor for the in-situ assessment of reactive species in redox-based therapies is demonstrated by the precise analysis of hydrogen peroxide dynamics in the presence of blood cancer cells.
- ItemFunctional surface microstructures inspired by nature – From adhesion and wetting principles to sustainable new devices(Amsterdam [u.a.] : Elsevier Science, 2021) Arzt, Eduard; Quan, Haocheng; McMeeking, Robert M.; Hensel, RenéIn the course of evolution nature has arrived at startling materials solutions to ensure survival. Investigations into biological surfaces, ranging from plants, insects and geckos to aquatic animals, have inspired the design of intricate surface patterns to create useful functionalities. This paper reviews the fundamental interaction mechanisms of such micropatterns with liquids, solids, and soft matter such as skin for control of wetting, self-cleaning, anti-fouling, adhesion, skin adherence, and sensing. Compared to conventional chemical strategies, the paradigm of micropatterning enables solutions with superior resource efficiency and sustainability. Associated applications range from water management and robotics to future health monitoring devices. We finally provide an overview of the relevant patterning methods as an appendix.