Drones for enabling computational environmental flow dynamics studies

支持加拿大建筑环境的可持续性并保持其抵御自然灾害的能力，对于维持我们社区的福祉和繁荣是必要的。加拿大是世界第二大国家，地理位置多样，气候极端，其可持续建筑设计主要围绕能源效率和弹性(即承受气候负荷并在气候引起的中断后快速反弹的能力)。加拿大的建筑物每年消耗30%的总能源和50%的电力。然而，通过最优的弹性和可持续设计，有机会将建筑的能源消耗降低高达80%。可持续设计需要考虑和整合气候反应能力和复原力。因此，对气候和建筑环境之间复杂的相互作用进行清晰的理解和现实的建模是一个先决条件。这就需要前所未有的城市气候模型(风速、压力、湿度、温度等)。时间和空间分辨率都很高。在特定的建筑位置、通风口、窗/门开口处或长时间的街道水平上都需要瞬变气候参数。在风工程、环境和建筑能源模拟应用中，现实和实用的城市小气候数值模拟的主要挑战之一是城市暴露所涉及的几何(拓扑)的复杂性和地表类型的可变性。每种建筑形式和表面分类都是通过现场观察和公开信息单独手动输入到CAD模型中，这通常非常耗时且不太精确。例如，在结构或自然通风设计或建筑能量模拟期间，需要准确的场地和建筑特定信息来评估气候负荷(例如风)。这个项目的主要目标是开发一种自动化的场地特定的3D城市建模，用于城市气候研究。为此，将使用安装在无人机上的各种远程传感器来收集地形和表面数据。通过无人机安装的遥感进行准确的城市气候建模及其自动化，预计将改变可持续和有弹性的建筑设计的最先进水平。所要求的无人机系统还将有助于在不进行任何破坏性测试或功能中断的情况下对建筑物和桥梁进行结构健康监测、损坏检测。它还可进一步用于环境灾害监测应用，如龙卷风登陆、飓风登陆或城市洪水等极端事件期间的损失后评估。此外，该系统还可以用于优化城市地区的太阳能光伏部署。

Embracing sustainability and maintaining resiliency of Canada’s built environment against natural hazards is necessary to sustain the wellbeing and prosperity of our communities. Sustainable building design in Canada, the second largest country in the world with diverse geography characterized by climate extremes, mostly revolves around energy efficiency and resiliency (i.e. ability to withstand the climate loads and re-bounce quickly after climate induced interruptions). Buildings in Canada consume 30% of the total energy and 50% of the electricity on an annual basis. Through optimal resilient and sustainable design, however, there is an opportunity to reduce a building’s energy consumption by as high as 80%. Sustainable design entails consideration and integration of climate responsiveness and resiliency. Therefore, a clear understanding and realistic modelling of the complex interaction between the climate and the built-environment is a prerequisite. This necessitates unprecedented urban climate modeling (wind speed, pressure, humidity, temperature, etc.) at high temporal and spatial resolution. Transient climate parameters are required at a particular building location, ventilation inlet, window/door opening or at street level over a long duration. One of the major challenges in realistic and pragmatic numerical urban micro-climate modeling for wind engineering, environmental and building energy simulation application is the complexity of the geometry (topology) and the variability of surface types involved in urban exposures. Each building form and surface classification is individually and manually entered into a CAD model through on-site-observations and publicly available information, which are often very time consuming and less precise. Accurate site and building specific information are required to assess climate loads such as wind, for example, during structural or natural ventilation design or for building energy simulation. The main objective of this project is to develop an automated site specific 3D urban modeling useful for urban climate studies. For this purpose, various remote sensors installed on Unmanned Aerial Vehicle (UAV) will be used to collect topology and surface data. Accurate urban climate modeling and their automation through UAV mounted remote sensing is expected to transform the state-of-the-art in sustainable and resilient building design. The requested UAV system will also aid in structural health monitoring, damage detection of buildings and bridges without any destructive testing or interruption of functionality. It can be further used for environmental disaster monitoring applications such as post-damage assessment during extreme events such tornado touchdowns, hurricane landfalls or urban flooding. Furthermore, the system can be adapted for optimizing solar photovoltaic deployment in urban areas.