Suchergebnisse

Abstract. A tailing dam accident can cause serious ecological
disaster and property loss. Simulation of a tailing dam accident in advance
is useful for understanding the tailing flow characteristics and assessing
the possible extension of the impact area. In this paper, a
three-dimensional (3-D) computational fluid dynamics (CFD) approach was
proposed for reasonably and quickly predicting the flow routing and impact
area of mud flow from a dam failure across 3-D terrain. The Navier–Stokes
equations and the Bingham–Papanastasiou rheology model were employed as the
governing equations and the constitutive model, respectively, and solved
numerically in the finite volume method (FVM) scheme. The volume-of-fluid
(VOF) method was used to track the interface between the tailings and air.
The accuracy of the CFD model and the chosen numerical algorithm were
validated using an analytical solution of the channel flow problem and a
laboratory experiment on the dam-break problem reported in the literature.
In each issue, the obtained results were very close to the analytical
solutions or experimental values. The proposed approach was then applied to
simulate two scenarios of tailing dam failures, one of which was the
Feijão tailing dam that failed on 25 January 2019, and the simulated
routing coincided well with the in situ investigation. Therefore, the
proposed approach does well in simulating the flow phenomenon of tailings
after a dam break, and the numerical results can be used for early warning
of disasters and emergency response.

While previous studies largely focus on extreme events, little is known about the behaviors of mild weather, a positive and pleasant condition occurring frequently, directly associated with outdoor activities, and highly relatable to the public. Here we examine the climatological characteristics and long-term trends of mild weather over China during 1971–2014, as well as the possible linkage with the El Niño−Southern Oscillation. It is found that, on average, China experiences 94.5 days (25.4% of all days) of mild weather in a year, and the annual number of mild days increased by 1.02% per decade (3.73 days per decade) during 1971–2014, especially in summer (1.54% per decade), spring (1.49% per decade), and autumn (1.03% per decade). We also find that most parts of China have been experiencing increasing mild weather in 1971–1998 but decreasing in 1998–2014. Clustering analysis reveals six subregions that exhibit distinct mild weather behaviors. In particular, harsh seasons (i.e., summer of southern China and winter of northern China) are becoming even less pleasant. Besides these secular trends, it is also noticed that El Niño event in the preceding winter is followed by less pleasant spring and summer and more pleasant autumn and winter in most areas of China. The results reported here have significant implications for urban planners and governmental policymakers.