98,612 research outputs found
Bayesian Species Delimitation Can Be Robust to Guide-Tree Inference Errors
distribution, and reproduction in any medium, provided the original work is properly cited
Centrality Scaling of the Distribution of Pions
From the preliminary data of PHENIX on the centrality dependence of the
spectrum in at midrapidity in heavy-ion collisions, we show that
a scaling behavior exists that is independent of the centrality. It is then
shown that degrades with increasing exponentially with a
decay constant that can be quantified. A scaling distribution in terms of an
intuitive scaling variable is derived that is analogous to the KNO scaling. No
theoretical models are used in any part of this phenomenological analysis.Comment: 4 pages RevTex, 5 figures include
An integrated wind risk warning model for urban rail transport in Shanghai, China
The integrated wind risk warning model for rail transport presented has four elements:
Background wind data, a wind field model, a vulnerability model, and a risk model. Background
wind data uses observations in this study. Using the wind field model with effective surface
roughness lengths, the background wind data are interpolated to a 30-m resolution grid. In the
vulnerability model, the aerodynamic characteristics of railway vehicles are analyzed with CFD
(Computational Fluid Dynamics) modelling. In the risk model, the maximum value of three
aerodynamic forces is used as the criteria to evaluate rail safety and to quantify the risk level under
extremely windy weather. The full model is tested for the Shanghai Metro Line 16 using wind
conditions during Typhoon Chan-hom. The proposed approach enables quick quantification of real-
time safety risk levels during typhoon landfall, providing sophisticated warning information for
rail vehicle operation safety
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