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arXiv 0802.1615physics.ao-phphysics.comp-ph
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实时数据驱动的野外火灾模拟

Real-Time Data Driven Wildland Fire Modeling

Jonathan D. Beezley, Soham Chakraborty, Janice L. Coen, Craig C. Douglas, Jan Mandel, Anthony Vodacek, Zhen Wang

摘要:

我们正在开发一个基于半经验关系的荒地火灾模型,该模型估计了地面火灾的蔓延速度和锋面后的热量释放,再加上WRF,天气研究和预报大气模式。水平集方法识别火灾前沿。数据同化使用幅度和位置校正使用变形集合卡尔曼滤波器。我们将使用火灾的热图像进行观察,并将其与基于模型状态的合成图像进行比较。

英文摘要:

We are developing a wildland fire model based on semi-empirical relations that estimate the rate of spread of a surface fire and post-frontal heat release, coupled with WRF, the Weather Research and Forecasting atmospheric model. A level set method identifies the fire front. Data are assimilated using both amplitude and position corrections using a morphing ensemble Kalman filter. We will use thermal images of a fire for observations that will be compared to synthetic image based on the model state.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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