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 Ma={0.5;1.0;1.5;2.0} 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.

Data emerged as a central success factor for companies to benefit from digitization. However, the skills in successfully creating value from data – especially at the management level – are not always profound. To address this problem, several canvas models have already been designed. Canvas models are usually created to write down an idea in a structured way to promote transparency and traceability. However, some existing data science canvas models mainly address developers and are thus unsuitable for decision-makers and communication within interdisciplinary teams. Based on a literature review, we identified influencing factors that are essential for the success of data science projects. With the information gained, the Data Science Canvas was developed in an expert workshop and finally evaluated by practitioners to find out whether such an instrument could support data-driven value creation.

The actomyosin system generates mechanical work with the execution of the power stroke, an ATP-driven, two-step rotational swing of the myosin-neck that occurs post ATP hydrolysis during the transition from weakly to strongly actin-bound myosin states concomitant with Pi release and prior to ADP dissociation. The activating role of actin on product release and force generation is well documented; however, the communication paths associated with weak-to-strong transitions are poorly characterized. With the aid of mutant analyses based on kinetic investigations and simulations, we identified the W-helix as an important hub coupling the structural changes of switch elements during ATP hydrolysis to temporally controlled interactions with actin that are passed to the central transducer and converter. Disturbing the W-helix/transducer pathway increased actin-activated ATP turnover and reduced motor performance as a consequence of prolonged duration of the strongly actin-attached states. Actin-triggered Pi release was accelerated, while ADP release considerably decelerated, both limiting maximum ATPase, thus transforming myosin-2 into a high-duty-ratio motor. This kinetic signature of the mutant allowed us to define the fractional occupancies of intermediate states during the ATPase cycle providing evidence that myosin populates a cleft-closure state of strong actin interaction during the weak-to-strong transition with bound hydrolysis products before accomplishing the power stroke.

Models of basic psychological needs have been present and popular in the academic and lay literature for more than a century yet reviews of needs models show an astonishing lack of consensus. This raises the question of what basic human psychological needs are and if this can be consolidated into a model or framework that can align previous research and empirical study. The authors argue that the lack of consensus arises from researchers describing parts of the proverbial elephant correctly but failing to describe the full elephant. Through redefining what human needs are and matching this to an evolutionary framework we can see broad consensus across needs models and neatly slot constructs and psychological and behavioural theories into this framework. This enables a descriptive model of drives, motives, and well-being that can be simply outlined but refined enough to do justice to the complexities of human behaviour. This also raises some issues of how subjective well-being is and should be measured. Further avenues of research and how to continue building this model and framework are proposed.

This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks.

For a sustainable development the electricity sector needs to be decarbonized. In 2017 only 54% of the West African households had access to the electrical grid. Thus, renewable sources should play a major role for the development of the power sector in West Africa. Above all, solar power shows highest potential of renewable energy sources. However, it is highly variable, depending on the atmospheric conditions. This study addresses the challenges for a solar based power system in West Africa by analyzing the atmospheric variability of solar power. For this purpose, two aspects are investigated. In the first part, the daily power reduction due to atmospheric aerosols is quantified for different solar power technologies. Meteorological data at six ground-based stations is used to model photovoltaic and parabolic trough power during all mostly clear-sky days in 2006. A radiative transfer model is combined with solar power model. The results show, that the reduction due to aerosols can be up to 79% for photovoltaic and up to 100% for parabolic trough power plants during a major dust outbreak. Frequent dust outbreaks occurring in West Africa would cause frequent blackouts if sufficient storage capacities are not available. On average, aerosols reduce the daily power yields by 13% to 22% for photovoltaic and by 22% to 37% for parabolic troughs. For the second part, long-term atmospheric variability and trends of solar irradiance are analyzed and their impact on photovoltaic yields is examined for West Africa. Based on a 35-year satellite data record (1983 - 2017) the temporal and spatial variability and general trend are depicted for global and direct horizontal irradiances. Furthermore, photovoltaic yields are calculated on a daily basis. They show a strong meridional gradient with highest values of 5 kWh/kWp in the Sahara and Sahel zone and lowest values in southern West Africa (around 4 kWh/kWp). Thereby, the temporal variability is highest in southern West Africa (up to around 18%) and lowest in the Sahara (around 4.5%). This implies the need of a North-South grid development, to feed the increasing demand on the highly populated coast by solar power from the northern parts of West Africa. Additionally, global irradiances show a long-term positive trend (up to +5 W/m²/decade) in the Sahara and a negative trend (up to -5 W/m²/decade) in southern West Africa. If this trend is continuing, the spatial differences in solar power potential will increase in the future. This thesis provides a better understanding of the impact of atmospheric variability on solar power in a challenging environment like West Africa, characterized by the strong influence of the African monsoon. Thereby, the importance of aerosols is pointed out. Furthermore, long-term changes of irradiance are characterized concerning their implications for photovoltaic power.

4GREAT is an extension of the German Receiver for Astronomy at Terahertz frequencies (GREAT) operated aboard the Stratospheric Observatory for Infrared Astronomy (SOFIA). The spectrometer comprises four different detector bands and their associated subsystems for simultaneous and fully independent science operation. All detector beams are co-aligned on the sky. The frequency bands of 4GREAT cover 491-635, 890-1090, 1240-1525 and 2490-2590 GHz, respectively. This paper presents the design and characterization of the instrument, and its in-flight performance. 4GREAT saw first light in June 2018, and has been offered to the interested SOFIA communities starting with observing cycle 6.