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

由于基础设施老化和缺乏适当的维护，美国土木工程师学会(ASCE)给我们的国家基础设施，特别是河流结构(如桥梁)的评级为“D”级。虽然桥梁在交通网络中至关重要，但在极端和危险的洪水事件中，桥梁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的恒定流实验。这就造成了在无法进入的洪水期间获取全面的全尺度冲刷数据的困难，以及无法模拟那些河流中建筑物周围和上方快速变化的非恒定流和局部冲刷过程。该项目旨在开发一个受生物启发的、由低成本无线智能声纳传感器组成的冲刷监测网络，以模仿电鱼的自适应皮肤传感方法，用于全面监测桥墩周围的冲刷地形，并增强非恒定流水动力和泥沙输送模型，以预测高对流洪水波对建筑物周围的局部冲刷。研究结果将补充国家和地方防洪机构的现场数据，以评估当前的桥梁设计原则，并修改/修改设计标准以提高其安全性。现场将用于教职员工和学生发展创新的研究想法。该项目还将为亚利桑那土木工程大学注册的学生提供使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、计算模拟、大规模物理实验和现场监测来实现。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来监测桥梁冲刷。传感器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，还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，为研究现有设计标准的可行性提供有价值的数据，并为易发生极端洪水的桥梁提出新的设计考虑。独特的实验室和现场实时资料将更好地理解非恒定流中的桥梁冲刷。

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.