Towards a new generation of smart long-span bridges with auto-detection systems for nonlinear dynamic response and local deterioration under wind effect

新一代智能大跨度桥梁，具有非线性动力响应和风效应下局部劣化自动检测系统

• 批准号: RGPIN-2022-05116
• 负责人: Dragomirescu, Elena
• 金额: $ 1.89万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749463
• 关键词: Towards; new; generation; smart; long

The main suspension bridges in Canada are approaching the end of their life span, as these were built during 1920-1940. The service of a bridge can be extended through maintenance, repairs and replacement of damaged structural elements. However, the complexity of these structures makes it difficult to decide which element must be repaired or replaced. Thus, the current Program will develop a Structural Intelligent (SI) Tool which will detect the damage in real-time when connected to the Structural Health Monitoring (SHM) system of each bridge, also indicating the potentially affected structural elements. The innovative SI Tool will be developed based on a vast damage and wind-induced fatigue database generated by HQP for training Machine Learning (ML) algorithms. The successful application of the SI Tool will be ensured through multiple calibration steps adjusted for suspension bridges of different lengths. Design and monitoring data necessary for this calibration are made available by Public Services and Procurement Canada (PSPC), who oversees the service of most of the suspension bridges in Canada. Once validated with SHM field data of a suspension bridge, the SI Tool will be able to predict future damage and wind-fatigue, when linked to any similar suspension bridge SHM system. A novel advance in knowledge is developing a new non-linear damage model for bridge structural elements, which will modify the frequency transfer functions to account for the non-linear damage reduction in damping and stiffness terms for each structural bridge element. The implementation will be done in Integrated Finite Strip Method (IFSM), where the PI has expertise, instead of FEM which relies on conventional geometric properties reduction, thus cannot realistically simulate damage. The short-term objectives of the proposed Research Program are to detect the critical damage of the aging Liard River Bridge, which connects indigenous communities, and to assist PSPC in monitoring and repairing/replacement decisions. The long-term objective is to implement a centralized auto-detection damage system which will allow PSPC and their partners to access remotely the structural condition of any instrumented and monitored suspension bridge and to decide towards repairing or replacement of the signaled damaged bridge structural elements. A diverse and inclusive team of 19 HQP (6PhD, 7MASc and 6UG) will enroll in this Program through selection criteria developed in collaboration with uOttawa offices of: Indigenous Affairs Office, Interdisciplinary Centre for Black Health and Women in Science and Engineering Committee, such that the privacy and the diversity of the HQP cohort are respected. The proposed Program will benefit of interdisciplinary co-supervisions with Dr. D. Inkpen, expert in ML algorithms and Dr. D. Lau, expert in SHM bridge data interpretation. Thus, the HQP will gain interdisciplinary technical skills and soft skills through participation in planned activities.

加拿大的主要吊桥均建于 1920 年至 1940 年，其使用寿命已接近尾声。通过维护、修理和更换损坏的结构元件可以延长桥梁的使用寿命。然而，这些结构的复杂性使得很难决定必须修理或更换哪个元件。因此，当前计划将开发一种结构智能（SI）工具，当连接到每座桥梁的结构健康监测（SHM）系统时，该工具将实时检测损坏情况，并指示可能受影响的结构元件。创新的 SI 工具将基于 HQP 生成的庞大损伤和风致疲劳数据库来开发，用于训练机器学习 (ML) 算法。 SI Tool的成功应用将通过针对不同长度的悬索桥调整的多个校准步骤来确保。加拿大公共服务和采购部 (PSPC) 提供了校准所需的设计和监测数据，该机构负责监督加拿大大多数悬索桥的服务。一旦使用悬索桥的 SHM 现场数据进行验证，当与任何类似的悬索桥 SHM 系统连接时，SI 工具将能够预测未来的损坏和风疲劳。知识方面的一项新进展是为桥梁结构元件开发一种新的非线性损伤模型，该模型将修改频率传递函数，以考虑每个结构桥梁元件的阻尼和刚度项的非线性损伤减少。实施将采用集成有限条法（IFSM）进行，PI具有专业知识，而不是依赖于传统几何属性简化的有限元法，因此无法真实地模拟损坏。拟议研究计划的短期目标是检测连接土著社区的老化利亚德河大桥的严重损坏情况，并协助 PSPC 进行监测和修复/更换决策。长期目标是实施一个集中式自动检测损坏系统，该系统将使 PSPC 及其合作伙伴能够远程访问任何装有仪表和监控的悬索桥的结构状况，并决定修复或更换已发出信号的损坏桥梁结构元件。由 19 名 HQP（6PhD、7MASc 和 6UG）组成的多元化和包容性团队将通过与渥太华大学办公室合作制定的选择标准参加该计划：原住民事务办公室、黑人健康跨学科中心和科学与工程领域的女性委员会，以便HQP 群体的隐私和多样性受到尊重。拟议的计划将受益于 ML 算法专家 D. Inkpen 博士和 SHM 桥梁数据解释专家 D. Lau 博士的跨学科共同监督。因此，总部将通过参与计划的活动获得跨学科的技术技能和软技能。