RII Track-4: Partnership Between the University of Wyoming and the Missoula Fire Sciences Laboratory in Multi-Scale Wildland Fire Research

RII Track-4：怀俄明大学与米苏拉火灾科学实验室在多尺度荒地火灾研究方面的合作

• 批准号: 2033379
• 负责人: Erica Belmont
• 金额: $ 19.03万
• 依托单位: University of Wyoming
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2033379&HistoricalAwards=false
• 关键词: RII; Track; Partnership; Between; University

Wildland fire modeling entails prediction of ignition, spread, emissions, and other fire characteristics. Accurate predictive modeling can lead to better land management decisions, climate modeling, and public health management. Such modeling is a challenging endeavor, however, due to myriad complexities including variability in fuel composition, fuel geometry, and environmental conditions such as wind speed and humidity. Field- and laboratory-based experimental measurements are utilized to develop sub-models, such as models of quantities and types of emissions produced from fires, and validation of integrated models. This NSF RII Track-4 Fellowship will enable the University of Wyoming (UW) PI and her graduate student to visit the Missoula Fire Sciences Laboratory (MFL) in Missoula, MT, over the next two years in order to engage with MFL researchers in multi-scale wildland fire-related experiments and modeling. Specifically, the UW researchers will work with MFL researchers to evaluate and improve a model for wildland fire emissions that the UW researchers have developed and tested at a small, laboratory scale to-date. This model allows for the prediction of emissions as a function of factors such as fire fuel composition and environmental conditions, including ambient oxygen level and humidity. This Fellowship will allow the UW researchers to work with MFL researchers to test this model under larger-scale and more complex, but well-characterized, fire conditions.The RII Track-4 Fellowship will offer the UW team access to world-class facilities and collaborators to scale their research and test a research hypothesis regarding wildland fire emissions over different scales. The hypothesis is that aerosol emissions formation can be predicted by coupling quantification of key influential effects on emissions formation at micro-scales and accurate prediction of relevant variables in full-scale fires. Effects of biomass composition and fire environment on aerosol emissions have been demonstrated at the micro-scale at UW, and findings will be tested at larger scales where conditions are less tightly controlled than in micro-scale experiments. At larger scales, additional factors such as heat and mass transport limitations and complex entrainment of ambient gases into combustion products may confound the measurement of such effects, making experimentation on well-defined and well-controlled platforms critical to elucidation of these factors. The MFL has not only the facilities to enable the UW researchers to perform these scaled-up experiments, but also fire science experts with whom collaboration will be invaluable to ensuring maximal relevance of this work to current and future wildland fire modeling efforts. The UW team will work with MFL research engineers with expertise in fire experimentation using platforms including a burn box platform and a wind tunnel platform in which the combustion environment can be well-controlled and well-characterized. Additionally, the UW team with work with MFL research engineers with expertise in fire and smoke modeling to ensure the relevance of the UW team’s work to emissions modeling efforts.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.

野火建模需要预测点火，蔓延，排放和其他火灾特征。准确的预测建模可以带来更好的土地管理决策、气候建模和公共卫生管理。然而，由于燃料成分、燃料几何形状以及风速和湿度等环境条件的变化等多种复杂性，这种建模是一项具有挑战性的奋进。实地和实验室的实验测量被用来开发子模型，如火灾产生的排放量和类型的模型，以及综合模型的验证。NSF RII Track-4奖学金将使怀俄明州大学（UW）PI和她的研究生能够在未来两年内访问位于蒙大拿州米苏拉的米苏拉火灾科学实验室（MFL），以便与MFL研究人员进行多尺度荒地火灾相关实验和建模。具体来说，华盛顿大学的研究人员将与MFL的研究人员合作，评估和改进一个荒地火灾排放模型，该模型是华盛顿大学的研究人员迄今为止在小型实验室规模上开发和测试的。该模型允许预测排放量作为火灾燃料成分和环境条件（包括环境氧气水平和湿度）等因素的函数。该奖学金将使华盛顿大学的研究人员与MFL的研究人员合作，在更大规模和更复杂，但特征良好的火灾条件下测试该模型。RII Track-4奖学金将为华盛顿大学的团队提供世界一流的设施和合作者，以扩大他们的研究规模，并测试有关不同尺度野火排放的研究假设。该假设是，可以通过量化微观尺度上对排放物形成的关键影响效应和准确预测全面火灾中的相关变量来预测气溶胶排放物的形成。生物质组成和火灾环境对气溶胶排放的影响已在华盛顿大学的微观尺度上得到证明，并将在更大的尺度上测试结果，其中条件控制不那么严格，而不是在微观尺度实验。在更大的尺度上，其他因素，如热量和质量传输的限制和复杂的夹带环境气体进入燃烧产物可能会混淆这种影响的测量，使实验上定义明确，控制良好的平台上阐明这些因素至关重要。MFL不仅拥有使UW研究人员能够进行这些扩大实验的设施，而且还有火灾科学专家，与他们的合作对于确保这项工作与当前和未来的荒地火灾建模工作的最大相关性将是非常宝贵的。UW团队将与具有火灾实验专业知识的MFL研究工程师合作，使用包括燃烧箱平台和风洞平台在内的平台，其中燃烧环境可以得到很好的控制和表征。此外，UW团队与MFL研究工程师合作，在火灾和烟雾建模方面具有专业知识，以确保UW团队的工作与排放建模工作的相关性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。