Collaborative Research: RAPID: Rapid computational modeling of wildfires and management with emphasis on human activity

准确的野火蔓延短期预测对于向人们提供信息、将生命损失降至最低以及通过有效的扑救活动减少野火的损失和成本至关重要。在拉海纳大火造成破坏之后，改善这些进程至关重要。在忘记细节之前，关键是要确定影响野火蔓延的所有因素，并确定如何将这些因素纳入快速预测过程。这个项目将在计算科学和建模方面培训博士生。该项目将涉及来自毛伊岛上的‘Aina数据管家计划’的高中生和社区大学生。该项目将开发有可能在未来的野火中拯救人类生命和基础设施的野火模型，使用水平集方法和汉密尔顿-雅各比方程来模拟在居民区野火活动期间和之后与人类活动相耦合的野火传播。虽然水平集方法在野火模拟和与用于实时分析的数据同化方法的耦合方面相对著名，但需要了解它们与人类活动的相互作用，特别是在涉及野火事件发生后立即疏散和财产保护的情况下。这项研究的一个成果将是一个新的模型，以提供对野火响应的复杂算法和数学基础的理解，这些基础可以在像拉海纳火灾这样的几乎实时的灾难情况下帮助分配资源。该项目将展示如何立即部署这一模式，以避免导致悲剧的瓶颈，以及在火灾管理技术中实施范式转换解决方案所需的技术进步。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Accurate short-term predictions of wildfire spread are essential to inform people, minimize the loss of lives and mitigate damage and cost of wildfire through effective suppression activities. It is critical to improve on these processes in the aftermath of the devastation of the Lahaina Fires. Before details are forgotten, it is critical to identify all the factors influencing wildfire spreads and to determine how to incorporate them into the rapid prediction process. This project will train Ph.D. students in computational science and modeling. This project will involve high school and community college students from the `Aina Data Stewards program on Maui. This project will develop wildfire models that have the potential to save human lives and infrastructure in future wildfires using level-set methods and Hamilton-Jacobi equations to model wildfire spread coupled to human activity during and after wildfire activity in residential zones. While level-set methods are relatively well known for wildfire modeling with coupling to data assimilation methods for real-time analysis, there is need to understand their interaction with human activity especially as it relates to evacuation and protection of property immediately after a wildfire event. A product of this research will be a new model to provide an understanding of the complex algorithmic and mathematical basis for wildfire response that can aid in resource allocation in a virtually real-time disaster situation such as the Lahaina firestorm. This project will show how to immediately deploy this model to avert the bottlenecks leading to tragedy and the required technological advances necessary to implement paradigm-shifting solutions in fire management techniques.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.