Post-Earthquake Aerial Reconnaissance of Geotechnical Engineering Systems

东北(2011)、克赖斯特彻奇(2011)和坎特伯雷(2010)地震影响了两个以在地震工程方面取得开创性进展而闻名的国家；然而，这两个国家都经历了极端程度的破坏。这些事件令人痛心地提醒我们，要确保我们能够设计出真正有弹性的社区，我们还需要吸取许多教训。震后勘察任务对于促进我们对自然灾害及其对岩土系统的影响的了解所需的以经验为基础的学习进程是绝对重要的。虽然震后勘察提供了丰富的学习经验，但由于人工收集易腐烂的大型数据集的效率低下、与部署团队相关的高成本、可获得性限制和安全考虑，目前的做法存在缺陷。无人驾驶自主飞行器(UAAV)使用最新的技术和计算工具，将使工程师能够收集更高质量、更客观、更易腐烂的关于勘察任务中岩土系统性能的数据集。该项目为使用无人机技术对岩土系统进行极端事件侦察铺平了道路。与基于无人机的事后侦察相关的社会效益是显著的，包括在灾害袭击我们国家之前更有效地从国外的灾害中学习，更有效的事后反应导致更具弹性的民用基础设施系统，以及受影响地区更快的经济复苏。在使用高度机动性和传感器丰富的无人机的基础上，计划建立一个变革性的事后侦察和决策框架。无人机技术的采用代表了事后勘察的范式转变，因为它使岩土工程师能够更有效地收集更大、更高质量和更客观的勘察数据。该平台还将有能力处理大量收集的数据集，以(A)在区域范围内自动检测和绘制损坏特征图；(B)使用激光雷达增强的图像生成更准确的地表变形和几何图形的三维地图。此外，无人机与现场部署的无线传感器通信的能力将被调查，并收集额外的场地特征数据。为此，该项目旨在证明，无人机和无线地震检波器网络可以进行面波测量，使用无人机落下的重量来估计横波速度，并将条件表征到比侦察团队目前可行的更深的地方。无人机通信平台还将有效地将地理参考数据传播到专家社区，专家社区可以分析数据并向地面侦察团队提供专家建议。

The Tohoku (2011), Christchurch (2011), and Canterbury (2010) Earthquakes affected two nations known for their pioneering advances in earthquake engineering; yet both nations experienced extreme levels of destruction. These events are poignant reminders that many lessons are yet to be learned to ensure we can engineer truly resilient communities. Post-earthquake reconnaissance missions are absolutely vital to the experience-based learning process required to advance our understanding of natural hazards and their impact on geotechnical systems. While post-earthquake reconnaissance has provided a wealth of learning experiences, current practices suffer from drawbacks due to inefficiencies in manual collection of large perishable datasets, high costs associated with deployment of teams, accessibility limitations, and safety considerations. Unmanned Autonomous Aerial Vehicles (UAAVs), using the latest technological and computational tools available, will enable engineers to collect higher quality, more objective, and more extensive perishable datasets on the performance of geotechnical systems during reconnaissance missions. This project paves the way for the use of UAAV technology for extreme-event reconnaissance of geotechnical systems. The societal benefits associated with UAAV-based post-event reconnaissance are significant and include more effective learning from disasters abroad before they hit our nation, more efficient post-event responses leading to more resilient civil infrastructure systems, and quicker economic recovery of affected regions. A transformative framework for post-event reconnaissance and decision making is planned based on the use of highly-mobile and sensor-rich UAAVs. Adoption of UAAV technology represents a paradigm shift in post-event reconnaissance because it allows geotechnical engineers to more efficiently collect large, higher quality, and more objective reconnaissance data. The platform will have the ability to also process large collected datasets to (a) automatically detect and map damage features at a regional scale; and (b) generate more accurate 3D maps of surface deformations and geometry using LIDAR-enhanced imagery. In addition, the UAAV's ability to communicate with field-deployed wireless sensors and collect additional site characterization data will be investigated. Towards this end, the project aims to prove that the UAAV and a network of wireless geophones can execute surface wave measurements to estimate shear wave velocity using weights dropped by the UAAV and characterize conditions to greater depths than currently feasible by reconnaissance teams. The UAAV communication platform will also efficiently disseminate geo-referenced data to a community of experts who can analyze the data and provide expert advice to ground-based reconnaissance teams.