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Grant: Discovery Grants Program - Individual

Université d'Ottawa

$26,000.00

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

FY 2023-24

Summary
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.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2022-05116
Name nom
Dragomirescu, Elena
Department département
Civil Engineering
Organization id
28
Institution établissement
Université d'Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
26000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
601
Area of application group en
Construction, urban and rural planning
Area of application group fr
Construction, urbanisme et aménagement rural
Area of application en
Structural engineering
Area of application fr
Génie des charpentes
Research subject code
1000
Research subject group en
Civil engineering
Research subject group fr
Civil engineering
Research subject en
Génie civil
Research subject fr
Génie civil
Application title
Towards a new generation of smart long-span bridges with auto-detection systems for nonlinear dynamic response and local deterioration under wind effect
Keyword
Coupled flutter for long-span bridges; Damage identification methods; Machine learning algorithms; Modal properties of long-span bridges; Non-linear response of damaged long-span bridges; Stochastic structural dynamics; Wind-induced damage simulation
Application summary
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.