应用基于复合bsamzier曲线的火锋可微参数表示的真实野火生长模拟

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Irene González, Carlos Carrillo, Ana Cortés, Tomàs Margalef
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引用次数: 0

摘要

对荒地城市界面(WUI)地区森林火灾的演变建模仍然是森林火灾模拟领域的一个主要挑战。大多数现有的森林火灾蔓延模拟器都是基于火灾边界的多边形表示,这往往无法捕捉到这些地区火灾行为的复杂性。基于椭圆波传播(EWP)的模拟器依赖于这种类型的森林火灾周界表示,也就是说,它们将火灾周界表示为由直线连接的一系列点,其中火锋的演变通过评估每个周界点的传播来执行,传播方向使用每个点的法向量方向作为传播方向。为此,基于ewp的模拟器已经建立在Richard模型之上,该模型使用火线的可微分参数表示。然而,由于基于ewp的模拟器使用多边形表示,它们不能利用使用参数表示火灾周长的数学潜力,这可能会损害模拟的准确性。为了解决这些限制,我们提出了一种新的使用复合bsamzier曲线(CBC)的火灾前沿参数表示。提议的野火周长表示提高了火灾形状的平滑和圆润的现实性。该方案的第一个实现是在保留原有法向量计算方法的基础上完成的。这种方法被称为使用邻域的复合bsamzier曲线(CBCN)。然而,也提出了一种改进的方法,其中使用了一种更准确的法向量方向计算方法,该方法与火灾前沿的曲率对齐,从而改进了火灾动力学的整体建模。这种先进的建议被称为使用微分的复合bsamzier曲线(CBCD)。这两种提出的方法都已集成到FARSITE中,这是一个著名的基于ewp的森林火灾蔓延模拟器。在理想场景和两个实际案例中对传统的多边形表示(LIN)和基于cbc的新方法(CBCN和CBCD)进行了测试。结果表明,任何基于CBCD的表示都可以生成更真实的火灾形状,并且增强了模拟器模拟WUI区域火灾蔓延的能力,其中CBCD是获得最佳结果的提议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Realistic wildfire growth simulations applying a differentiable parametric representation of the fire front based on Composite Bézier curves
Modelling the evolution of a forest fire in Wildland Urban Interface (WUI) areas is still a major challenge in the field of forest fire simulation. Most existing forest fire spread simulators are based on polygonal representations of the fire perimeter, which often fail to capture the complexities of fire behaviour in these areas. Elliptical Wave Propagation (EWP) based simulators rely on this type of forest fire perimeter representation, that is, they represent the fire perimeter as a series of points connected by straight lines where the evolution of the fire front is performed by evaluating the spread of each perimeter point using as the spread direction the direction of the normal vector at each of them. To this end, EWP-based simulators have been built on top of the Richard model, which uses a differentiable parametric representation of the fire front. However, due to the polygonal representation used by EWP-based simulators, these cannot exploit the mathematical potential of using a parametric representation of the fire perimeter, which could compromise the accuracy of the simulations.
To address these limitations, we propose a novel parametric representation of the fire front using Composite Bézier Curves (CBC). The proposed wildfire perimeter representation improves the realism of the fire shapes being smooth and rounded. The first implementation of this proposal was done keeping the original method of normal vector calculation. This approach has been called Composite Bézier Curves using Neighbours (CBCN). However, an improved methodology has also been proposed where a more accurate method for calculating the normal vector directions is used, which is aligned with the curvatures of the fire front, thereby improving the overall modelling of fire dynamics. This advanced proposal has been called Composite Bézier Curves using Differentials (CBCD). Both proposed methodologies have been integrated into FARSITE, a well-known EWP-based forest fire spread simulator. Traditional polygonal representation (LIN) and the new CBC-based approach (CBCN and CBCD) were tested in ideal scenarios and two real cases. The obtained results show that any CBC-based representation generates more realistic fire shapes and they also enhance the simulator’s ability to model fire spread in WUI areas, with CBCD being the proposal that obtains the best results.
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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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