Collaborative Research:CPS:Medium:SMAC-FIRE: Closed-Loop Sensing, Modeling and Communications for WildFIRE

合作研究：CPS：中：SMAC-FIRE：野火的闭环传感、建模和通信

基本信息

批准号：
2209695
负责人：
Arnold Swindlehurst
金额：
$ 104.91万
依托单位：
University of California-Irvine
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2209695&HistoricalAwards=false
关键词：
Collaborative Research CPS Medium SMAC

项目摘要

Increases in temperatures and drought duration and intensity due to climate change, together with the expansion of wildlife-urban interfaces, has dramatically increased the frequency and intensity of forest fires, and has had devastating effects on lives, property, and the environment. To address this challenge, this project’s goal is to design a network of airborne drones and wireless sensors that can aid in initial wildfire localization and mapping, near-term prediction of fire progression, and providing communications support for firefighting personnel on the ground. Two key aspects differentiate the system from prior work: (1) It leverages and subsequently updates detailed three-dimensional models of the environment, including the effects of fuel type and moisture state, terrain, and atmospheric/wind conditions, in order to provide the most timely and accurate predictions of fire behavior possible, and (2) It adapts to hazardous and rapidly changing conditions, optimally balancing the need for wide-area coverage and maintaining communication links with personnel in remote locations. The science and engineering developed under this project can be adapted to many applications beyond wildfires including structural fires in urban and suburban settings, natural or man-made emergencies involving radiation or airborne chemical leaks, "dirty bombs" that release chemical or biological agents, or tracking highly localized atmospheric conditions surrounding imminent or on-going extreme weather events.The system developed under this project will enable more rapid localization and situational awareness of wildfires at their earliest stages, better predictions of both local, near-term and event-scale behavior, better situational awareness and coordination of personnel and resources, and increased safety for fire fighters on the ground. Models ranging from simple algebraic relationships based on wind velocity to more complex time-dependent coupled fluid dynamics-fire physics models will be used to anticipate fire behavior. These models are hampered by stochastic processes such as the lofting of burning embers to ignite new fires, that cause errors to grow rapidly with time. This project is focused on closing the loop using sensor data provided by airborne drones and ground-based sensors (GBS). The models inform the sensing by anticipating rapid growth of problematic phenomena, and the subsequent sensing updates the models, providing local wind and spot fire locations. Closing this loop as quickly as possible is critical to mitigating the fire’s impact. The system we propose integrates advanced fire modeling tools with mobile drones, wireless GBS, and high-level human interaction for both the initial attack of a wildfire event and subsequent on-going support.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.

由于气候变化而引起的温度，干旱持续时间和强度的增加，以及野生动物城市界面的膨胀，已经大大增加了森林火灾的频率和强度，并且对生命，财产和环境产生了破坏性的影响。为了应对这一挑战，该项目的目标是设计一个机载无人机和无线传感器网络，这些网络可以帮助最初的野火定位和映射，近期对火灾进展的近期预测，并为地面上的消防人员提供通信支持。两个关键方面将系统与先前的工作区分开：（1）它利用并随后更新了详细的环境三维模型，包括燃料类型和水分状态和水分状态，地形和大气/风条件的影响，以提供最及时，最准确的防火行为预测，以及与范围隔离的范围，以范围内的范围，以弥补范围，以弥补的范围，以危险的范围弥补，并且在范围内进行了广泛的范围，并且可以弥补往来的范围，并且可以弥补往来的范围。位置。该项目下开发的科学和工程可以适应以外的许多应用，包括野火，包括城市和郊区环境中的结构性火灾，涉及辐射或机载化学物质泄漏的自然或人工紧急情况，“肮脏的炸弹”释放化学物质或生物学剂，或者在经常发生的范围内的高度稳定的环境中释放化学物质或生物学的环境。野火在最早的阶段，更好地预测当地，事件规模的行为，更好的情境意识和人与资源的协调以及地面消防员的安全性。从基于风速度的简单代数关系到更复杂的时间依赖性耦合流体动力学生理模型的模型将用于预测火灾行为。这些模型受到随机过程的阻碍，例如燃烧的余烬抬起以点燃新火灾，这会导致错误随时间而迅速增长。该项目的重点是使用机载无人机和地面传感器（GB）提供的传感器数据关闭循环。这些模型通过预期有问题现象的快速增长来告知传感器，随后的传感更新了模型，提供了当地的风和射击位置。尽快关闭此循环对于减轻火灾的影响至关重要。我们提出的系统将高级火建模工具与移动无人机，无线GB和高级人类互动集成到野火事件的初步攻击和随后的持续支持。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛的影响审查审查的审查标准来通过评估来通过评估来获得的支持。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Historical spatiotemporal changes in fire danger potential across biomes

生物群落潜在火灾危险的历史时空变化

DOI：
10.1016/j.scitotenv.2023.161954
发表时间：
2023
期刊：
Science of The Total Environment
影响因子：
9.8
作者：
Baijnath-Rodino, Janine A.;Le, Phong V.V.;Foufoula-Georgiou, Efi;Banerjee, Tirtha
通讯作者：
Banerjee, Tirtha

Revisiting “bursts” in wall-bounded turbulent flows

DOI：
10.1103/physrevfluids.8.044606
发表时间：
2023-01
期刊：
Physical Review Fluids
影响因子：
2.7
作者：
S. Chowdhuri;T. Banerjee
通讯作者：
S. Chowdhuri;T. Banerjee

Features of turbulence during wildland fires in forested and grassland environments

森林和草原环境野火期间的湍流特征

DOI：
10.1016/j.agrformet.2023.109501
发表时间：
2023
期刊：
Agricultural and Forest Meteorology
影响因子：
6.2
作者：
Desai, Ajinkya;Heilman, Warren E.;Skowronski, Nicholas S.;Clark, Kenneth L.;Gallagher, Michael R.;Clements, Craig B.;Banerjee, Tirtha
通讯作者：
Banerjee, Tirtha

Cell-Free UAV Networks With Wireless Fronthaul: Analysis and Optimization

DOI：
10.1109/twc.2023.3294908
发表时间：
2024-03
期刊：
IEEE Transactions on Wireless Communications
影响因子：
10.4
作者：
Carles Diaz-Vilor;A. Lozano;H. Jafarkhani
通讯作者：
Carles Diaz-Vilor;A. Lozano;H. Jafarkhani

Quantifying the effectiveness of shaded fuel breaks from ground-based, aerial, and spaceborne observations

DOI：
10.1016/j.foreco.2023.121142
发表时间：
2023-09
期刊：
Forest Ecology and Management
影响因子：
3.7
作者：
J. Baijnath-Rodino;Alexandre Martinez;R. York;E. Foufoula‐Georgiou;A. Aghakouchak;T. Banerjee
通讯作者：
J. Baijnath-Rodino;Alexandre Martinez;R. York;E. Foufoula‐Georgiou;A. Aghakouchak;T. Banerjee