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

加拿大的主要悬索桥是在1920-1940年间建造的，现在它们的寿命即将结束。桥梁可以通过维护、维修和更换损坏的结构构件来延长使用期限。然而，这些结构的复杂性使得很难决定哪些部件必须修复或更换。因此，目前的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伤，还可以指示潜在受影响的结构构件。创新的SI工具将基于HQP为训练机器学习(ML)算法生成的海量损伤和风致疲劳数据库而开发。通过为不同长度的悬索桥调整多个校准步骤，将确保SI工具的成功应用。此次校准所需的设计和监测数据由加拿大公共服务和采购局(PSPC)提供，该机构负责监督加拿大大部分悬索桥的服务。一旦与悬索桥的SHM现场数据进行验证，SI工具将能够预测未来的损伤和风疲劳，当连接到任何类似的悬索桥SHM系统时。一个新的知识进展是发展了一种新的桥梁结构单元的非线性损伤模型，该模型将修改频率传递函数，以考虑每个结构单元的阻尼项和刚度项的非线性损伤减少。该方法采用积分有限条法(IFSM)，其中PI具有专业知识，而不是依赖于常规几何属性折减的有限元方法，因此不能真实地模拟损伤。拟议研究方案的短期目标是检测连接土著社区的老化的利亚德河大桥的严重损坏，并协助PSPC监测和修复/更换决定。长期目标是实施一个集中式自动损伤检测系统，该系统将允许PSPC及其合作伙伴远程访问任何仪表化和监测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的桥梁结构构件。一个由19名HQP(6PhD、7MASc和6UG)组成的多元化和包容性团队将通过与以下渥太华办事处合作制定的选择标准注册参加该计划：土著事务办公室、黑人健康跨学科中心和妇女参与科学和工程委员会，以便HQP队列的隐私和多样性得到尊重。拟议的计划将受益于与ML算法专家D.Inkpen博士和SHM桥梁数据解释专家D.Lau博士的跨学科合作监督。因此，HQP将通过参与计划的活动获得跨学科的技术技能和软技能。

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.