PFI:AIR - TT: A Novel Platform for Optimizing Fire Suppression System Performance

这个PFI：空气技术翻译项目专注于翻译在喷雾测量和分析方面的最新发现，以改进灭火系统设计和提高公共安全。消防知识的空白会导致设计保守，这不仅会限制消防系统的性能，而且会在形式、功能和成本方面限制建筑的整体性能。拟议的平台通过将喷雾测量和分析方面的最新发现与日益流行的建筑信息建模(BIM)环境相结合，提供了前所未有的评估喷头性能的能力。建筑师和工程师使用BIM环境来协调各种设计、工程、施工甚至检查活动。建筑信息建模已经用于传达消防安装细节和评估水力计算，以确保在发生火灾时以足够的压力将水输送到喷头。然而，这些模型没有对实际的喷雾扩散以及与建筑环境的相关相互作用进行功能性能预测。拟议的BIM插件将通过提供严格分析和系统优化所需的工具，对基于性能的喷水灭火系统设计具有足够的保真度。与现有的计算流体力学框架不同，将这种喷雾分析功能集成到BIM框架中，开辟了动态功能分析的新世界，具有独特的方便、快速和精确的特点。此外，在BIM等流行、可用、方便的工程平台上实施这种喷雾分析功能，预计将促进广泛的利益相关者采用，建立市场生存能力，并探索各种用例。应该指出的是，关于消防喷水灭火系统的基本工程问题即使在使用了100年后仍然没有得到回答。虽然新的设计是常规构思的，但没有预测能力来回答喷雾成分的基本问题(即喷雾是什么？)以及分散(即它去了哪里？)，这阻碍了创新。虽然已知喷头喷头图案细节(例如，动量、体积流量和液滴大小的空间随机分布)控制着灭火性能，但设计过程中喷头描述的逼真度不会超过给定喷头类型的全球覆盖区域规范。相比之下，这项拟议的技术试图捕捉所有喷雾细节，以完整地描述其组成。具体地说，该技术提供了复杂的空间-随机初始喷雾表示，由每个喷头模型唯一地生成，由激光诊断捕获，根据概率分析框架进行表征，并记录在喷头数据库中。这种虚拟喷雾表示被用来提供集成到BIM框架中的新的计算效率的轨迹分析，以提供对建筑表面喷雾模式的高保真、超实时预测。这些喷雾图案为喷水灭火系统设计人员确定灭火系统的安装细节提供了有用的信息。除了该项目预期的这些技术进步外，本科生和研究生还将在由工程师、计算机科学家、大学生和教职员工组成的团队中获得宝贵的创业和技术开发经验。工业界和大学的合作团队将使用该大学最近开发的专利技术，同时接触包括建筑设计师、工程师和建筑师在内的潜在客户，以促进新的消防设计技术的采用。

This PFI: AIR Technology Translation project focuses on translating recent discoveries in spray measurement and analysis to improve fire suppression system designs and enhance public safety. Fire suppression knowledge gaps can result in design conservatism that not only limits fire suppression system performance but also limits the overall building performance in form, function, and cost. The proposed platform provides an unprecedented capability to evaluate sprinkler performance by integrating recent discoveries in spray measurements and analysis with the increasingly popular Building Information Modeling (BIM) environment used by architects and engineers to coordinate a wide variety of design, engineering, construction, and even inspection activities. Building Information Modeling is already used to communicate fire protection installation details and to evaluate hydraulic calculations ensuring water is delivered at sufficient pressure to the sprinkler head in the event of a fire. However, these models fall short of functional performance predictions of the actual spray dispersion and associated interactions with the built environment. The proposed BIM plugin would possess sufficient fidelity for performance-based design of sprinkler systems by providing the tools needed for rigorous analysis and system optimization. Distinct from the available computational fluid dynamics framework, integrating this spray analysis capability within the BIM framework opens a new world of dynamic functional analysis that is uniquely convenient, fast, and precise. Further, implementation of this spray analysis capability on a popular, usable, convenient engineering platform such as BIM is expected to facilitate widespread stakeholder adoption, establishment of market viability, and exploration of the full spectrum of use cases. It should be noted that basic engineering questions regarding fire sprinkler systems remain unanswered even after 100 years of use. While new designs are routinely conceived, no predictive capability is available to answer essential questions of spray composition (i.e. what is the spray?) and dispersion (i.e. where does it go?), which impedes innovation. While the sprinkler spray pattern details (e.g. spatio-stochastic distributions of momentum, volume flux, and drop size) are known to govern fire suppression performance, the fidelity of the spray descriptions in the design process do not reach beyond global coverage area specifications for a given sprinkler type. In contrast, this proposed technology seeks to capture all of the spray details to completely describe its composition. Specifically, the proposed technology provides a complex spatio-stochastic initial spray representation, generated uniquely by each sprinkler model, captured by laser diagnostics, characterized in terms of a probabilistic analytical framework, and recorded into a sprinkler database. This virtual spray representation is used to inform a novel computational efficient trajectory analysis integrated into the BIM framework to provide high fidelity super-real time predictions of spray patterns on building surfaces. These spray patterns provide useful information for sprinkler system designers to determine installation details for the suppression system. In addition to these technical advancements expected from this project, undergraduate and graduate students will receive valuable entrepreneurship and technology development experience working on a team consisting of engineers, computer scientists, university students, and faculty. The team of industrial and university collaborators will work with recently patented technology developed at the university while reaching out to potential customers including building designers, engineers, and architects to promote adoption of the new fire suppression design technology.