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In the present paper, the fracture toughness of a polyurethane (PUR) foam (manufactured by Necumer GmbH, Germany, under the commercial designation Necuron 651) is experimentally and numerically investigated in order to examine its dependence on the specimen sizes. As a matter fact, to the best knowledge of the present authors, such an analysis is still missing in the technical literature. To perform the experimental campaign, notched PUR foam beams, with different geometrical sizes, are tested under three‐point bending loading, and the Modified Two‐Parameter Model (recently proposed by some of the present authors) is employed to measure the fracture toughness. Subsequently, such an experimental campaign is numerically simulated by applying a micromechanical model, implemented in a non‐linear finite element homemade code. Finally, the results obtained are compared with some experimental data available in the literature, related to the same PUR foam. Highlights: The fracture toughness of a polyurethane foam is experimentally investigated.Notched PUR foam beams, with different sizes, are tested under three‐point bending.The Modified Two‐Parameter Model is employed to measure the fracture toughness.A numerical simulation is performed with a non‐linear finite element model.The results are compared with some experimental data available in the literature. [ABSTRACT FROM AUTHOR]

Temporally and spatially resolved data on wind power generation are very useful for studying the technical and economic aspects of this variable renewable energy at local and regional levels. Due to the lack of disaggregated electricity data from onshore and offshore turbines in Germany, it is necessary to use numerical simulations to calculate the power generation for a given geographic area and time period. This study shows how such a simulation model, which uses freely available plant and weather data as input variables, can be developed with the help of basic atmospheric laws and specific power curves of wind turbines. The wind power model is then applied to ensembles of nearly 28,000 onshore and 1500 offshore turbines to simulate the wind power generation in Germany for the years 2019 and 2020. For both periods, the obtained and spatially aggregated time series are in good agreement with the measured feed-in patterns for the whole of Germany. Such disaggregated simulation results can be used to analyze the power generation at any spatial scale, as each turbine is simulated separately with its location and technical parameters. This paper also presents the daily resolved wind power generation and associated indicators at the federal state level. [ABSTRACT FROM AUTHOR]