Reference number : GC-2017-Q1-01928, amendment number : , agreement type : G, recipient legal name : Arjomandi, Kaveh (University of New Brunswick)|Arjomandi, Kaveh (Université du Nouveau-Brunswick), recipient country : CA, recipient province : nan, recipient city : New Brunswick|Nouveau-Brunswick, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Infrastructure around the world deteriorates as a result of aging, operational conditions, environmental loads, and sudden extreme events such as earthquakes. In Canada the civil infrastructure in poor and very poor conditions has been estimated to have a replacement cost of $141 billion. My research program concentrates on reducing the overall cost of development, maintenance, operation, and replacement of infrastructure by improving the process of health and reliability assessment of existing structures, known as Structural Health Monitoring (SHM). 
I will develop structural health monitoring techniques to a level of accuracy that enables them to be applied as tools supporting strategic, tactical and operational planning decisions for maintenance, repair, and replacement of large scale public and private assets. My initial focus is on bridges, but the intent is to develop methods that also apply to buildings, transmission towers, wind mills, and dam structures. 
Most previous research in SHM considers a single method as the sole monitoring technique. My program focuses on developing a holistic approach to structural health monitoring through the integration of hybrid data from various monitoring methods. The core method in my program is Operational Modal Analysis (OMA), an output-only method that has shown significant success in the SHM of bridges, buildings, wind mills, and dams. My goal is to develop methodologies for the integration of OMA with complementary approaches such as static input-output methods in order to improve the accuracy and efficiency of the monitoring process. I will focus on theoretical developments of OMA, multi-model identification, damage identification, and reliability assessment of structures using SHM data. Numerical studies, laboratory experiments, and full-scale tests will be used to verify the results. 
My research program is expected to have significant impact on the fundamental research in structural health monitoring, operational modal analysis, and structural damage models. Additionally, my program is expected to contribute to the application development of SHM and in particular the OMA method, with a focus on large-scale monitoring systems. Activities described in this Discovery Grant application will help private and public entities that are responsible for safety and operation of civil engineering infrastructure to improve the efficiency and frequency of detailed structural assessments. This will assist them to optimize the operational procedures as well as the maintenance and replacement strategies., program purpose french : Infrastructure around the world deteriorates as a result of aging, operational conditions, environmental loads, and sudden extreme events such as earthquakes. In Canada the civil infrastructure in poor and very poor conditions has been estimated to have a replacement cost of $141 billion. My research program concentrates on reducing the overall cost of development, maintenance, operation, and replacement of infrastructure by improving the process of health and reliability assessment of existing structures, known as Structural Health Monitoring (SHM). 
I will develop structural health monitoring techniques to a level of accuracy that enables them to be applied as tools supporting strategic, tactical and operational planning decisions for maintenance, repair, and replacement of large scale public and private assets. My initial focus is on bridges, but the intent is to develop methods that also apply to buildings, transmission towers, wind mills, and dam structures. 
Most previous research in SHM considers a single method as the sole monitoring technique. My program focuses on developing a holistic approach to structural health monitoring through the integration of hybrid data from various monitoring methods. The core method in my program is Operational Modal Analysis (OMA), an output-only method that has shown significant success in the SHM of bridges, buildings, wind mills, and dams. My goal is to develop methodologies for the integration of OMA with complementary approaches such as static input-output methods in order to improve the accuracy and efficiency of the monitoring process. I will focus on theoretical developments of OMA, multi-model identification, damage identification, and reliability assessment of structures using SHM data. Numerical studies, laboratory experiments, and full-scale tests will be used to verify the results. 
My research program is expected to have significant impact on the fundamental research in structural health monitoring, operational modal analysis, and structural damage models. Additionally, my program is expected to contribute to the application development of SHM and in particular the OMA method, with a focus on large-scale monitoring systems. Activities described in this Discovery Grant application will help private and public entities that are responsible for safety and operation of civil engineering infrastructure to improve the efficiency and frequency of detailed structural assessments. This will assist them to optimize the operational procedures as well as the maintenance and replacement strategies., agreement title english : Integration of Hybrid Inspection Data into Structural Health Monitoring, agreement title french : Integration of Hybrid Inspection Data into Structural Health Monitoring, agreement number : RGPIN, agreement value : 110000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada