CAREER: Understanding the Role of Buoyancy Flow for Accurate and Robust Scale Modeling of Upward Flame Spread

职业：了解浮力流在向上火焰蔓延的精确且稳健的比例建模中的作用

• 批准号: 1942282
• 负责人: Ya-Ting Liao
• 金额: $ 50万
• 依托单位: Case Western Reserve University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1942282&HistoricalAwards=false
• 关键词: CAREER; Understanding; Role; Buoyancy; Flow

This project will study how fire behaviors change with scale. Laboratory-scale tests are often used in fundamental research and in technical standards to characterize the burning behaviors of materials. However, key fire behaviors change when moving from small laboratory scale to larger real-world scales found in structures or forest fires. This scalability problem is a long-standing challenge in fire science, one that limits generalizability of laboratory testing. Filling this knowledge gap will improve the relevance of standard safety tests and lead to safer structures and products. Ultimately this will save lives, money, and property for society. This project employs experiments, numerical simulations, and theoretical modeling to control, study, and predict fire behavior at various scales. The focus will be on a phenomenon called buoyancy flow, which varies significantly with scale. The developed scaling models will be validated against real-world testing databases maintained by industry collaborators. This project will also help cultivate the next generation of academic and industry leaders. This will be achieved via interactive public demonstrations of fire dynamics and via promotion of technical standards in college curricula. One of the key factors influencing fire scalability is buoyancy flow. This project will focus on the effects of buoyancy flow on upward flame spread over solids. In this fire scenario, the fuel sample is oriented vertically, along the direction where buoyancy flow varies significantly. The coupling between solid fuel and gaseous flame is sensitive to such buoyancy flow variations, making scalability even more challenging. By nature, buoyancy flow is caused by a density gradient in a gravity field. By systematically varying these phenomena, buoyancy flow can be manipulated. First, the effect of density will be studied by varying pressure and diluents of ambient gas in a combustion chamber. Second, the effect of hyper-gravity will be studied using a 17.7m-diameter centrifuge. Experiments will be augmented by calibrated numerical modeling. The small-scale data, where buoyancy flow is artificially enhanced, will be compared to large-scale data from collaborators, where buoyancy flow is naturally up-scaled with fire size. Dimensional analysis will be performed to identify the invariant dimensionless variable groups. Finally, a new scaling model will be proposed to bridge small and large fires by incorporating buoyancy flow. This will allow creation of fire models that make fewer assumptions than ever before. This will also dramatically increase the applicability of lessons from lab-scale experiments as well as allowing re-interpretation of past reduced-scale experiments.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.

这个项目将研究火灾行为是如何随着规模的变化而变化的。实验室规模的测试通常用于基础研究和技术标准中，以表征材料的燃烧行为。然而，当从小型实验室规模转移到建筑或森林火灾中发现的更大的现实世界规模时，关键的火灾行为会发生变化。这种可扩展性问题是火灾科学中一个长期存在的挑战，它限制了实验室测试的通用性。填补这一知识空白将提高标准安全测试的相关性，并导致更安全的结构和产品。最终，这将为社会挽救生命、金钱和财产。本项目采用实验、数值模拟和理论建模来控制、研究和预测不同尺度的火灾行为。重点将放在浮力流现象上，浮力流随尺度变化很大。开发的缩放模型将根据行业合作者维护的真实测试数据库进行验证。该项目还将有助于培养下一代学术和行业领袖。这将通过火动力学的互动公开演示和通过在大学课程中推广技术标准来实现。影响火灾可扩展性的关键因素之一是浮力流动。这个项目将集中在浮力流动对向上火焰在固体上传播的影响。在此火灾场景中，燃料样品垂直定向，沿着浮力流动变化较大的方向。固体燃料和气体火焰之间的耦合对这种浮力流动变化很敏感，这使得可扩展性更具挑战性。从本质上讲，浮力流动是由重力场中的密度梯度引起的。通过系统地改变这些现象，可以控制浮力流动。首先，将通过改变燃烧室中环境气体的压力和稀释剂来研究密度的影响。其次，将使用直径17.7米的离心机研究超重力的影响。校正后的数值模拟将扩大实验。人工增强浮力流的小规模数据将与合作者提供的大规模数据进行比较，在大规模数据中，浮力流随火灾规模自然放大。将进行量纲分析，以确定不变的无量纲变量组。最后，提出了一种新的尺度模型，通过结合浮力流来桥接小火灾和大火灾。这将允许创建比以往任何时候都更少的假设的五个模型。这也将极大地提高实验室规模实验的适用性，并允许重新解释过去的缩小规模的实验。该奖项反映了美国国家科学基金会的法定使命，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。