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  • 1
    Publication Date: 2022-03-21
    Type: info:eu-repo/semantics/article
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  • 2
    Publication Date: 2022-03-21
    Type: info:eu-repo/semantics/article
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  • 3
    Publication Date: 2022-08-05
    Description: Vlasov solvers that operate on a phase‐space grid are highly accurate but also numerically demanding. Coarse velocity space resolutions, which are largely unproblematic in particle‐in‐cell (PIC) simulations, can lead to numerical heating or oscillations in continuum Vlasov methods. To address this issue, we present a new dual Vlasov solver which is based on an established positivity preserving advection scheme for the update of the distribution function and an energy conserving partial differential equation solver for the kinetic update of mean velocity and temperature. The solvers work together via moment fitting during which the maximum entropy part of the distribution function is replaced by the solution from the partial differential equation solver. This numerical scheme makes continuum Vlasov methods competitive with PIC methods concerning computational cost and enables us to model large scale reconnection in Earth's magnetosphere with a fully kinetic continuum method. The simulation results agree well with measurements by the MMS spacecraft.
    Description: Key Points: A moment fitting continuum Vlasov solver is presented that preserves positivity of the distribution function and conserves total energy. The method behaves well at low velocity space resolutions, making it competitive with PIC methods concerning computational cost. There is good agreement of the simulations with measurements of magnetic reconnection by the MMS spacecraft.
    Description: Helmholtz Association (亥姆霍兹联合会致力) http://dx.doi.org/10.13039/501100009318
    Description: https://vlasov.tp1.ruhr-uni-bochum.de/data/paper-JGR-2021
    Keywords: ddc:550 ; ddc:538.7
    Language: English
    Type: doc-type:article
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  • 4
    Publication Date: 2023-05-22
    Description: Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated over large areas. Although OpenStreetMap (OSM) offers great potential to assess risk at a detailed building-by-building level, the completeness of OSM building footprints is still heterogeneous. We present an approach to close this gap by means of crowd-sourcing based on the mobile app MapSwipe, where volunteers swipe through satellite images of a region collecting user feedback on classification tasks. For our application, MapSwipe was extended by a completeness feature that allows to classify a tile as “no building”, “complete” or “incomplete”. To assess the quality of the produced data, the completeness feature was applied to four regions. The MapSwipe-based assessment was compared with an intrinsic approach to quantify completeness and with the prediction of an existing model. Our results show that the crowd-sourced approach yields a reasonable classification performance of the completeness of OSM building footprints. Results showed that the MapSwipe-based assessment produced consistent estimates for the case study regions while the other two approaches showed a higher variability. Our study also revealed that volunteers tend to classify nearly completely mapped tiles as “complete”, especially in areas with a high OSM building density. Another factor that influenced the classification performance was the level of alignment of the OSM layer with the satellite imagery.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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