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

美国土木工程师协会（ASCE）给我们的国家基础设施，特别是河流结构（如桥梁），一个“D”级，因为老化的基础设施的下降状态和缺乏适当的维护。尽管桥梁在交通网络中起着至关重要的作用，但它们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的稳定流实验。这导致难以在不可接近的洪水期间获得全面的全尺寸冲刷数据，并且无法模拟快速变化的非定常流和这些流内结构周围和上方的局部冲刷过程。本项目旨在开发一个由低成本无线智能声纳传感器组成的仿生冲刷监测网络，模拟电鱼的自适应皮肤传感方法，用于桥梁桥墩周围的综合冲刷地形监测，并增强非定常水流动力和泥沙输运模型，用于预测建筑物周围强对流洪水引起的局部冲刷。研究结果将为国家和地方防洪机构提供实地数据的补充，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。这些实地站点将用于教师和学生发展创新的研究思路。该项目还将为亚利桑那大学土木工程专业的学生提供一个使用实时数据研究桥梁冲刷的机会。该项目的目标将通过发展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，部署低成本的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，以在洪水事件期间收集实时桥梁冲刷数据。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，并为容易发生极端洪水的桥梁提供新的设计考虑因素。独特的实验室和实时现场数据将更好地理解非定常流场下桥梁冲刷。

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.