TY - JOUR A1 - Zhang, Zhuodong A1 - Wieland, Ralf A1 - Reiche, Matthias A1 - Funk, Roger A1 - Hoffmann, Carsten A1 - Li, Yong A1 - Sommer, Michael T1 - Wind modelling for wind erosion research by open source computational fluid dynamics JF - Ecological informatics : an international journal on ecoinformatics and computational ecolog N2 - The open source computational fluid dynamics (CFD) wind model (CFD-WEM) for wind erosion research in the Xilingele grassland in Inner Mongolia (autonomous region, China) is compared with two open source CFD models Gerris and OpenFOAM. The evaluation of these models was made according to software technology, implemented methods, handling, accuracy and calculation speed. All models were applied to the same wind tunnel data set. Results show that the simplest CFD-WEM has the highest calculation speed with acceptable accuracy, and the most powerful OpenFOAM produces the simulation with highest accuracy and the lowest calculation speed. Gerris is between CFD-WEM and OpenFOAM. It calculates faster than OpenFOAM, and it is capable to solve different CFD problems. CFD-WEM is the optimal model to be further developed for wind erosion research in Inner Mongolia grassland considering its efficiency and the uncertainties of other input data. However, for other applications using CFD technology, Gerris and OpenFOAM can be good choices. This paper shows the powerful capability of open source CFD software in wind erosion study, and advocates more involvement of open source technology in wind erosion and related ecological researches. KW - Computational fluid dynamics KW - Wind modelling KW - Open source KW - Wind erosion KW - Gerris KW - OpenFOAM KW - SAMT Y1 - 2011 U6 - https://doi.org/10.1016/j.ecoinf.2011.02.001 SN - 1574-9541 VL - 6 IS - 5 SP - 316 EP - 324 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Zhang, Zhuo-dong A1 - Wieland, Ralf A1 - Reiche, Matthias A1 - Funk, Roger A1 - Hoffmann, Carsten A1 - Li, Yong A1 - Sommer, Michael T1 - A computational fluid dynamics model for wind simulation: model implementation and experimental validation JF - Journal of Zhejiang University : an international journal ; Science A, Applied physics & engineering : an international applied physics & engineering journal N2 - To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was conducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear implementation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale. KW - Wind model KW - Computational fluid dynamics (CFD) KW - Wind erosion KW - Wind tunnel experiments KW - Spatial analysis and modelling tool (SAMT) KW - Open source Y1 - 2012 U6 - https://doi.org/10.1631/jzus.A1100231 SN - 1673-565X VL - 13 IS - 4 SP - 274 EP - 283 PB - Zhejiang University Press CY - Hangzou ER - TY - JOUR A1 - Garrels, Tim A1 - Khodabakhsh, Athar A1 - Renard, Bernhard Y. A1 - Baum, Katharina T1 - LazyFox: fast and parallelized overlapping community detection in large graphs JF - PEERJ Computer Science N2 - The detection of communities in graph datasets provides insight about a graph's underlying structure and is an important tool for various domains such as social sciences, marketing, traffic forecast, and drug discovery. While most existing algorithms provide fast approaches for community detection, their results usually contain strictly separated communities. However, most datasets would semantically allow for or even require overlapping communities that can only be determined at much higher computational cost. We build on an efficient algorithm, FOX, that detects such overlapping communities. FOX measures the closeness of a node to a community by approximating the count of triangles which that node forms with that community. We propose LAZYFOX, a multi-threaded adaptation of the FOX algorithm, which provides even faster detection without an impact on community quality. This allows for the analyses of significantly larger and more complex datasets. LAZYFOX enables overlapping community detection on complex graph datasets with millions of nodes and billions of edges in days instead of weeks. As part of this work, LAZYFOX's implementation was published and is available as a tool under an MIT licence at https://github.com/TimGarrels/LazyFox. KW - Overlapping community detection KW - Large networks KW - Weighted clustering coefficient KW - Heuristic triangle estimation KW - Parallelized algorithm KW - C++ tool KW - Runtime improvement KW - Open source KW - Graph algorithm KW - Community analysis Y1 - 2023 U6 - https://doi.org/10.7717/peerj-cs.1291 SN - 2376-5992 VL - 9 PB - PeerJ Inc. CY - London ER -