2022, Christian Müller, Manar Samri, René Hensel, Eduard Arzt, Martin H. Müser

Viscoelasticity is well known to cause a significant hysteresis of crack closure and opening when an elastomer is brought in and out of contact with a flat, rigid counterface. In contrast, the idea that adhesive hysteresis can also result under quasi-static driving due to small-scale, elastic multistability is relatively new. Here, we study a system in which both mechanisms act concurrently. Specifically, we compare the simulated and experimentally measured time evolution of the interfacial force and the real contact area between a soft elastomer and a rigid, flat punch, to which small-scale, single-sinusoidal roughness is added. To this end, we further the Green's function molecular dynamics method and extend recently developed imaging techniques to elucidate the rate- and preload-dependence of the pull-off process. Our results reveal that hysteresis is much enhanced when the saddle points of the topography come into contact, which, however, is impeded by viscoelastic forces and may require sufficiently large preloads. A similar coaction of viscous- and multistability effects is expected to occur in macroscopic polymer contacts and be relevant, e.g., for pressure-sensitive adhesives and modern adhesive gripping devices.

2021, Hermann, Erik

[No abstract available]

2017, Piniewski, Mikołaj, Szcześniak, Mateusz, Kardel, Ignacy

There is considerable concern that the water resources of Central and Eastern Europe region can be adversely affected by climate change. Projections of future water balance and streamflow conditions can be obtained by forcing hydrological models with the output from climate models. In this study, we employed the SWAT hydrological model driven with an ensemble of nine bias-corrected EURO-CORDEX climate simulations to generate future hydrological projections for the Vistula and Odra basins in two future horizons (2024–2050 and 2074–2100) under two Representative Concentration Pathways (RCPs). The data set consists of three parts: (1) model inputs; (2) raw model outputs; (3) aggregated model outputs. The first one allows the users to reproduce the outputs or to create the new ones. The second one contains the simulated time series of 10 variables simulated by SWAT: precipitation, snow melt, potential evapotranspiration, actual evapotranspiration, soil water content, percolation, surface runoff, baseflow, water yield and streamflow. The third one consists of the multi-model ensemble statistics of the relative changes in mean seasonal and annual variables developed in a GIS format. The data set should be of interest of climate impact scientists, water managers and water-sector policy makers. In any case, it should be noted that projections included in this data set are associated with high uncertainties explained in this data descriptor paper.

2019, Geitner, Robert, Fritzsch, Robby, Bocklitz, Thomas W., Popp, Jürgen

In the package corr2D two-dimensional correlation analysis is implemented in R. This paper describes how two-dimensional correlation analysis is done in the package and how the mathematical equations are translated into R code. The paper features a simple tutorial with executable code for beginners, insight into the calculations done before the correlation analysis, a detailed look at the parallelization of the fast Fourier transformation based correlation analysis and a speed test of the calculation. The package corr2D offers the possibility to preprocess, correlate and postprocess spectroscopic data using exclusively the R language. Thus, corr2D is a welcome addition to the toolbox of spectroscopists and makes two-dimensional correlation analysis more accessible and transparent.

2019, Todtenberg, Nicole, Kraemer, Rolf

Bluetooth was firstly announced in 1998. Originally designed as cable replacement connecting devices in a point-to-point fashion its high penetration arouses interest in its ad-hoc networking potential. This ad-hoc networking potential of Bluetooth is advertised for years - but until recently no actual products were available and less than a handful of real Bluetooth multi-hop network deployments were reported. The turnaround was triggered by the release of the Bluetooth Low Energy Mesh Profile which is unquestionable a great achievement but not well suited for all use cases of multi-hop networks. This paper surveys the tremendous work done on Bluetooth multi-hop networks during the last 20 years. All aspects are discussed with demands for a real world Bluetooth multi-hop operation in mind. Relationships and side effects of different topics for a real world implementation are explained. This unique focus distinguishes this survey from existing ones. Furthermore, to the best of the authors’ knowledge this is the first survey consolidating the work on Bluetooth multi-hop networks for classic Bluetooth technology as well as for Bluetooth Low Energy. Another individual characteristic of this survey is a synopsis of real world Bluetooth multi-hop network deployment efforts. In fact, there are only four reports of a successful establishment of a Bluetooth multi-hop network with more than 30 nodes and only one of them was integrated in a real world application - namely a photovoltaic power plant. © 2019 The Authors

2016, Surrey, Alexander, Schultz, Ludwig, Rellinghaus, Bernd

Nanosized or nanoconfined hydrides are promising materials for solid-state hydrogen storage. Most of these hydrides, however, degrade fast during the structural characterization utilizing transmission electron microscopy (TEM) upon the irradiation with the imaging electron beam due to radiolysis. We use ball-milled MgH2 as a reference material for in-situ TEM experiments under low-dose conditions to study and quantitatively understand the electron beam-induced dehydrogenation. For this, valence electron energy loss spectroscopy (VEELS) measurements are conducted in a monochromated FEI Titan3 80–300 microscope. From observing the plasmonic absorptions it is found that MgH2 successively converts into Mg upon electron irradiation. The temporal evolution of the spectra is analyzed quantitatively to determine the thickness-dependent, characteristic electron doses for electron energies of both 80 and 300 keV. The measured electron doses can be quantitatively explained by the inelastic scattering of the incident high-energy electrons by the MgH2 plasmon. The obtained insights are also relevant for the TEM characterization of other hydrides.

2023, Rastogi, Abhishake, Mathé, Peter

We study linear ill-posed inverse problems with noisy data in the framework of statistical learning. The corresponding linear operator equation is assumed to fit a given Hilbert scale, generated by some unbounded self-adjoint operator. Approximate reconstructions from random noisy data are obtained with general regularization schemes in such a way that these belong to the domain of the generator. The analysis has thus to distinguish two cases, the regular one, when the true solution also belongs to the domain of the generator, and the ‘oversmoothing’ one, when this is not the case. Rates of convergence for the regularized solutions will be expressed in terms of certain distance functions. For solutions with smoothness given in terms of source conditions with respect to the scale generating operator, then the error bounds can then be made explicit in terms of the sample size.

2022, Tavakoli, Mohammadreza, Faraji, Abdolali, Vrolijk, Jarno, Molavi, Mohammadreza, Mol, Stefan T., Kismihók, Gábor

Attaining those skills that match labor market demand is getting increasingly complicated, not in the last place in engineering education, as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Anticipating and addressing such dynamism is a fundamental challenge to twenty-first century education. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. In this paper, we propose a novel, Artificial Intelligence (AI) driven approach to the development of an open, personalized, and labor market oriented learning recommender system, called eDoer. We discuss the complete system development cycle starting with a systematic user requirements gathering, and followed by system design, implementation, and validation. Our recommender prototype (1) derives the skill requirements for particular occupations through an analysis of online job vacancy announcements

2009, Koepler, O., Balke, W.-T., Köncke, B., Tönnies, S.

[No abstract available]

2015, Dworak, Volker, Huebner, Michael, Selbeck, Joern

Most of the relevant technology related to precision agriculture is currently controlled by Global Positioning Systems (GPS) and uploaded map data; however, in sensitive areas with young or expensive plants, small robots are becoming more widely used in exclusive work. These robots must follow the plant lines with centimeter precision to protect plant growth. For cases in which GPS fails, a camera-based solution is often used for navigation because of the system cost and simplicity. The low-cost plant camera presented here generates images in which plants are contrasted against the soil, thus enabling the use of simple cross-correlation functions to establish high-resolution navigation control in the centimeter range. Based on the foresight provided by images from in front of the vehicle, robust vehicle control can be established without any dead time; as a result, off-loading the main robot control and overshooting can be avoided.