Open Access

Off-lattice Boltzmann methods increase the flexibility and applicability of lattice Boltzmann methods by decoupling the discretizations of time, space, and particle velocities. However, the velocity sets that are mostly used in off-lattice Boltzmann simulations were originally tailored to on-lattice Boltzmann methods. In this contribution, we show how the accuracy and efficiency of weakly and fully compressible semi-Lagrangian off-lattice Boltzmann simulations is increased by velocity sets derived from cubature rules, i.e. multivariate quadratures, which have not been produced by the Gauß-product rule. In particular, simulations of 2D shock-vortex interactions indicate that the cubature-derived degree-nine D2Q19 velocity set is capable to replace the Gauß-product rule-derived D2Q25. Likewise, the degree-five velocity sets D3Q13 and D3Q21, as well as a degree-seven D3V27 velocity set were successfully tested for 3D Taylor–Green vortex flows to challenge and surpass the quality of the customary D3Q27 velocity set. In compressible 3D Taylor–Green vortex flows with Mach numbers on-lattice simulations with velocity sets D3Q103 and D3V107 showed only limited stability, while the off-lattice degree-nine D3Q45 velocity set accurately reproduced the kinetic energy provided by literature.

In this contribution, we perform computer simulations to expedite the development of hydrogen storages based on metal hydride. These simulations enable in-depth analysis of the processes within the systems which otherwise could not be achieved. That is, because the determination of crucial process properties require measurement instruments in the setup which are currently not available. Therefore, we investigate the reliability of reaction values that are determined by a design of experiments. Specifically, we first explain our model setup in detail. We define the mathematical terms to obtain insights into the thermal processes and reaction kinetics. We then compare the simulated results to measurements of a 5-gram sample consisting of iron-titanium-manganese (FeTiMn) to obtain the values with the highest agreement with the experimental data. In addition, we improve the model by replacing the commonly used Van’t-Hoff equation by a mathematical expression of the pressure-composition-isotherms (PCI) to calculate the equilibrium pressure. Finally, the parameters’ accuracy is checked in yet another with an existing metal hydride system. The simulated results demonstrate high concordance with experimental data, which advocate the usage of approximated kinetic reaction properties by a design of experiments for further design studies. Furthermore, we are able to determine process parameters like the entropy and enthalpy.

Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.

Ausgehend von einer Sichtung aktueller Ergebnisse in der KI werden Faktoren identifiziert, die zur erfolgreichen Anwendung führen. Ein Abgleich mit den Gegebenheiten im Spitzen-sport führt zur Identifikation potenzieller Handlungsfelder.

Medien spielen eine Schlüsselrolle für die öffentliche Meinung und Akzeptanz neuer Technologien. Mit einer qualitativen Inhaltsanalyse journalistischer Artikel zum Elektrofahrrad wurden Akteure und ihre Einstellungen und Handlungen in Bezug auf das Elektrofahrrad untersucht. In die Analyse flossen 444 Artikel ausgewählter deutscher Qualitätsmedien aus dem Jahr 2018 ein. Die Untersuchung zeigt den gesellschaftlich relevanten Diskurs über Elektrofahrräder auf und bietet Anknüpfungspunkte für die Förderung von Individualmobilität und der Entwicklung zukunftsfähiger Mobilitätskonzepte.

Wie machen die das... kann angesichts der erstaunlichen Fähigkeiten mancher Lebewesen gefragt werden. Die Bionik fragt noch weiter …und wie kann man das nachmachen? Hier liegt ein Schwerpunkt dieses Lehrbuches, das die Bionik nicht nur an zahlreichen Beispielen erklärt, sondern auch eine Vorgehensweise für die Identifizierung biologischer Lösungen und deren Übertragung auf technische Anwendungen vermittelt. Basisinformationen der Biologie und Grundlagen der Konstruktionstechnik gewährleisten einen leichten Zugang zum Stoff. Mit dem 3D-Druck als Schlüsseltechnologie und der Thematisierung der Nachhaltigkeit geht das Buch zudem auf aktuelle Entwicklungen ein. Dieser ganzheitliche Blick auf die Bionik soll den Leser zur Durchführung bionischer Projekte befähigen und motivieren. (Verlagsangaben)

Background: Coniferous woods (Abies nordmanniana (Stev.) Spach, Abies procera Rehd, Picea abies (L.) H.Karst, and Picea pungens Engelm.) could contain useful secondary metabolites to produce sustainable packaging materials, e.g., by substitution of harmful petrol-based additives in plastic packaging. This study aims to characterise the antioxidant and light-absorbing properties and ingredients of different coniferous wood extracts with regard to different plant fragments and drying conditions. Furthermore, the valorisation of used Christmas trees is evaluated. Methods: Different drying and extraction techniques were applied with the extracts being characterised by determining the total phenolic content (TPC), total antioxidant capacity (TAC), and absorbance in the ultraviolet range (UV). Gas chromatography coupled with mass spectrometry (GC-MS) and an acid–butanol assay (ABA) were used to characterise the extract constituents. Results: All the extracts show a considerably high UV absorbance while interspecies differences did occur. All the fresh and some of the dried biomass extracts reached utilisable TAC and TPC values. A simplified extraction setup for industrial application is evaluated; comparable TAC results could be reached with modifications. Conclusion: Coniferous woods are a promising renewable resource for preparation of sustainable antioxidants and photostabilisers. This particularly applies to Christmas trees used for up to 12 days. After extraction, the biomass can be fully valorised by incorporation in paper packaging.

The motor protein myosin drives a wide range of cellular and muscular functions by generating directed movement and force, fueled through adenosine triphosphate (ATP) hydrolysis. Release of the hydrolysis product adenosine diphosphate (ADP) is a fundamental and regulatory process during force production. However, details about the molecular mechanism accompanying ADP release are scarce due to the lack of representative structures. Here we solved a novel blebbistatin-bound myosin conformation with critical structural elements in positions between the myosin pre-power stroke and rigor states. ADP in this structure is repositioned towards the surface by the phosphate-sensing P-loop, and stabilized in a partially unbound conformation via a salt-bridge between Arg131 and Glu187. A 5 Å rotation separates the mechanical converter in this conformation from the rigor position. The crystallized myosin structure thus resembles a conformation towards the end of the two-step power stroke, associated with ADP release. Computationally reconstructing ADP release from myosin by means of molecular dynamics simulations further supported the existence of an equivalent conformation along the power stroke that shows the same major characteristics in the myosin motor domain as the resolved blebbistatin-bound myosin-II·ADP crystal structure, and identified a communication hub centered on Arg232 that mediates chemomechanical energy transduction.

The development of metals tailored to the metallurgical conditions of laser-based additive manufacturing is crucial to advance the maturity of these materials for their use in structural applications. While efforts in this regard are being carried out around the globe, the use of high strength eutectic alloys have, so far, received minor attention, although previous works showed that rapid solidification techniques can result in ultrafine microstructures with excellent mechanical performance, albeit for small sample sizes. In the present work, a eutectic Ti-32.5Fe alloy has been produced by laser powder bed fusion aiming at exploiting rapid solidification and the capability to produce bulk ultrafine microstructures provided by this processing technique. Process energy densities between 160 J/mm³ and 180 J/mm³ resulted in a dense and crack-free material with an oxygen content of ~ 0.45 wt.% in which a hierarchical microstructure is formed by µm-sized η-Ti4Fe2Ox dendrites embedded in an ultrafine eutectic β-Ti/TiFe matrix. The microstructure was studied three-dimensionally using near-field synchrotron ptychographic X-ray computed tomography with an actual spatial resolution down to 39 nm to analyse the morphology of the eutectic and dendritic structures as well as to quantify their mass density, size and distribution. Inter-lamellar spacings down to ~ 30–50 nm were achieved, revealing the potential of laser-based additive manufacturing to generate microstructures smaller than those obtained by classical rapid solidification techniques for bulk materials. The alloy was deformed at 600 °C under compressive loading up to a strain of ~ 30% without damage formation, resulting in a compressive yield stress of ~ 800 MPa. This study provides a first demonstration of the feasibility to produce eutectic Ti-Fe alloys with ultrafine microstructures by laser powder bed fusion that are suitable for structural applications at elevated temperature.

West Africa is one of the least developed regions in the world regarding the energy availability and energy security. Located close to the equator West Africa receives high amounts of global horizontal irradiance (GHI). Thus, solar power and especially photovoltaic (PV) systems seem to be a promising solution to provide electricity with low environmental impact. To plan and to dimension a PV power system climatological data for global horizontal irradiance (GHI) and its variability need to be taken into account. However, ground based measurements of irradiances are not available continuously and cover only a few discrete locations.