用于实时预测的可解释野火蔓延模型

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

森林火灾是自然生态系统的重要组成部分,但其频率和强度的增加会对社会、经济和环境造成破坏性影响。因此,我们亟需能够对火灾演变和人类干预进行实时评估的可靠数字工具。这项工作开发了一个可解释的、基于物理学的模型,将作为更广泛的野火预测工具的核心。建模方法涉及对燃烧动力学和热能传递(当地植被高度的平均值)的简化描述,并产生了一个计算成本低廉的微分方程系统,该系统提供了温度和可燃物二维场的时空演变。该模型的关键部分包括对穿过植被的平均风速的估算,以及对地面倾斜度影响的考虑。预测结果成功地与有关可燃物体积密度、含水量以及风和坡度综合影响的基准文献结果进行了比较。模拟似乎从质量上正确地描述了火线从同质或异质冠层中的局部着火点开始的传播、斜火线碰撞产生的加速以及火线在燃料断裂带处的偏移或停止。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An interpretable wildfire spreading model for real-time predictions

Forest fires are a key component of natural ecosystems, but their increased frequency and intensity have devastating social, economic, and environmental implications. Thus, there is a great need for trustworthy digital tools capable of providing real-time estimates of fire evolution and human interventions. This work develops an interpretable, physics-based model that will serve as the core of a broader wildfire prediction tool. The modeling approach involves a simplified description of combustion kinetics and thermal energy transfer (averaged over local plantation height) and leads to a computationally inexpensive system of differential equations that provides the spatiotemporal evolution of the two-dimensional fields of temperature and combustibles. Key aspects of the model include the estimation of mean wind velocity through the plantation and the inclusion of the effect of ground inclination. Predictions are successfully compared to benchmark literature results concerning the effect of flammable bulk density, moisture content, and the combined influence of wind and slope. Simulations appear to provide qualitatively correct descriptions of firefront propagation from a localized ignition site in a homogeneous or heterogeneous canopy, of acceleration resulting from the collision of oblique firelines, and of firefront overshoot or arrest at fuel break zones.

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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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