Flood Induced Bridge Scour Prediction Using Bio-Inspired Smart Sensor Network

美国土木工程师协会（ASCE）为我们的国家基础设施，特别是建筑结构（例如，桥梁），“D”级，因为老化的基础设施和缺乏适当的维护状态下降。虽然桥梁在交通网络中至关重要，但其在极端和危险洪水事件中的实时行为在很大程度上是未知的，特别是因为桥梁冲刷预测是基于实验室中的恒定流实验。这导致难以获得全面的全尺寸冲刷数据，在无法访问的洪水和无法模拟快速变化的非定常流和局部冲刷过程周围和以上的这些流中结构。该项目旨在开发一个由低成本无线智能声纳传感器组成的生物启发冲刷监测网络，以模仿电鱼的自适应皮肤传感方法，用于桥墩周围的全面冲刷地形监测，并增强非定常水流动力学和泥沙输运模型，用于预测结构周围高度对流洪水波引起的局部冲刷。研究结果将为州和地方防洪机构提供现场数据的补充，以评估当前的桥梁设计原则，并修订/修改设计标准，以提高其安全性。该领域的网站将用于教师和学生开发创新的研究思路。该项目还将为亚利桑那大学土木工程系的学生提供一个利用实时数据研究桥梁冲刷的机会。 该项目的目标将通过开发一个创新的冲刷监测网络、计算机模拟、大规模物理实验和实地监测来实现。该项目将开发一种算法，部署低成本高密度声纳传感器阵列，用于监测桥梁冲刷。传感网络将在现场进行测试和安装，以收集洪水事件期间的实时桥梁冲刷数据。此外，将开发一个先进的计算模型来模拟局部冲刷过程。该项目预计将推进洪水中桥墩的冲刷监测技术，为检查现有设计标准的可行性提供有价值的数据，并为易受极端洪水影响的桥梁提出新的设计考虑因素。独特的实验室和实时现场数据将更好地了解非稳定流期间桥梁冲刷的情况。

The American Society of Civil Engineers (ASCE) has given our national infrastructure, especially instream structures (e.g., bridges), a "D" grade because of the declining state of aging infrastructure and lack of appropriate maintenance. Although bridges are critical in transportation network, their real-time behavior during extreme and hazardous flood events is largely unknown, particularly, because bridge scour prediction is based on steady flow experiments in laboratory. This contributes to the difficulties to acquire comprehensive full-scale scour data during inaccessible flood flows and inability to simulate rapidly varied unsteady flow and local scour processes around and over those in-stream structures. This project aims to develop a bio-inspired scour monitoring network consisting of low-cost wireless smart sonar sensors to mimic the electric fish's adaptive skin sensing methods for comprehensive scour topography monitoring around bridge piers, and enhance an unsteady flow hydrodynamic and sediment transport model for predicting local scour due to highly convective flood waves around structures. The results will supplement field data for the state and local flood control agencies to evaluate current bridge design principles and revise/modify the design criteria to improve its safety. The field sites will be used for faculty and students to develop innovative research ideas. The project will also provide students enrolled in the University of Arizona Civil Engineering an opportunity to study bridge scour using real-time data. This project's objectives will be achieved through the development of an innovative scour monitoring network, computational simulations, large-scale physical experiments, and field monitoring. The project will develop an algorithm to deploy low cost high-density sonar sensor array for monitoring bridge scour. The sensing network will be tested and installed in the field to collect real-time bridge scour data during flood events. Additionally, an advanced computational model will be developed to simulate the local scour processes. The project expects to advance the scour monitoring technologies for bridge piers in flood flow, provide valuable data to examine the feasibility of existing design criteria, and recommend new design considerations for bridges prone to extreme flood flows. The unique laboratory and real-time field data will better the understanding of bridge scour during unsteady flow.