Collaborative Research: CDI-Type II--Integrated Weather and Wildfire Simulation and Optimization for Wildfire Management

合作研究：CDI-Type II——天气与野火综合模拟及野火管理优化

• 批准号: 0941432
• 负责人: Xiaolin Hu
• 金额: $ 29.55万
• 依托单位: Georgia State University Research Foundation, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-11-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0941432&HistoricalAwards=false
• 关键词: Collaborative; Research; CDI; Type; II

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Wildfires cause great destruction including the loss of life and damage to property, infrastructure and the environment. The complexity of wildfire management arises from the uncertain dynamic interactions and dependencies among multiple system components. These include highly dynamic and nonlinear wildfire behaviors, weather conditions, and firefighting resource management. In previous research, these components have been largely treated in isolation in their own fields. To achieve effective wildfire management, decision-making support tools that integrate all these components as a whole are needed. The objective of this project is to develop new models and computation methods that integrate weather prediction, wildfire simulation, data assimilation and stochastic optimization for effective wildfire response management. In doing so, the project will make two key paradigm-shifting advances in wildfire modeling and management: 1) coupled weather and wildfire modeling and data assimilation for two-way interactive dynamic weather-wildfire prediction, and 2) Integrated wildfire simulation and stochastic optimization for wildfire containment. The project focuses on computational thinking for understanding the complexity in the natural systems of weather and wildfire behavior, and in the man-made system of firefighting resources management. Due to the stochastic and multiscale nature of the problem data associated with these systems, the project also involves data assimilation and parallel/distributed computational methods for robust weather and wildfire behavior predictions. The results of this project will aid in wildfire management to alleviate losses caused by wildfires through robust firefighting resource management decisions. The collaboration with the Texas Forest Service will enable validation and transfer of the resulting knowledge, systems and tools to real wildfire management. The results of the research will also benefit other emergency response applications such as those in homeland security. The project will provide interdisciplinary training to both undergraduate and graduate students and will develop a web-based education and training simulation environment. The project will also strengthen and complement existing K-12 outreach programs at Georgia State University (GSU), University of Oklahoma (OU), and Texas A&M University (TAMU) for minority students, and will make a concerted effort to broaden the participation of underrepresented students in research and education. Results of the research will be presented at conferences and published in refereed journals.

该奖项是根据2009年的《美国复苏与再投资法》（公法111-5）资助的。婚后造成巨大破坏，包括丧生和财产，基础设施和环境的损失和损害。野火管理的复杂性来自多个系统组件之间不确定的动态相互作用和依赖性。这些包括高度动态和非线性野火行为，天气状况和消防资源管理。在先前的研究中，这些组成部分在自己的领域很大程度上被孤立地进行了处理。为了实现有效的野火管理，需要将所有这些组件整体整合的决策支持工具。该项目的目的是开发新的模型和计算方法，以整合天气预测，野火模拟，数据同化和随机优化，以进行有效的野火响应管理。在此过程中，该项目将在野火建模和管理方面取得两个关键的范式转移进步：1）耦合的天气和野火建模和数据同化，用于双向交互式动态天气野火预测，以及2）集成的野火仿真和野火遏制的随机仿真。该项目着重于了解天然天气和野火行为系统的复杂性以及人造的消防资源管理系统中的复杂性。由于与这些系统相关的问题数据的随机性和多阶段性质，该项目还涉及数据同化以及适用的天气和野火行为预测的平行/分布式计算方法。该项目的结果将有助于野火管理，从而通过强大的消防资源管理决策来减轻野火造成的损失。与得克萨斯州森林服务部的合作将使所得的知识，系统和工具验证和转移真正的野火管理。该研究的结果还将受益于其他应急申请，例如国土安全部。该项目将为本科生和研究生提供跨学科的培训，并将开发基于网络的教育和培训模拟环境。该项目还将加强和补充佐治亚州立大学（GSU），俄克拉荷马大学（OU）和德克萨斯A＆M大学（TAMU）的现有K-12外展计划，并为少数族裔学生提供一致的努力，并努力扩大人物不足的学生从事研究和教育的参与。该研究的结果将在会议上介绍，并在裁判期刊上发表。