Grant: Discovery Grants Program - Individual
Carleton University
$40,600.00
Model-assisted non-destructive monitoring of reinforcement corrosion in concrete structures
EF 2012-13
Résumé
The deterioration of reinforced concrete (RC) structures due to steel corrosion is a major concern for infrastructure owners and operators. Therefore, accurate monitoring of reinforcement corrosion in concrete structures using non-destructive tests (NDTs) is critically important for assessing their durability and long-term performance, and for prioritizing and budgeting maintenance/repair operations. Although significant progress has been made during the last two decades, existing NDTs still lack the necessary accuracy and reliability to detect and to characterize steel corrosion in RC structures. The challenges associated with these methods can be explained by (1) the black-box nature of RC, (2) highly variable and complex nature of the chemical and physical properties of concrete, (3) dense reinforcement detailing in structural members, and (4) inherent problems associated with the corrosion measurement techniques. The main goal of the proposed research is to use inverse modelling and optimization techniques that combine spatially sparse field measurement data with the strength of numerical modelling to develop an innovative approach to the monitoring of steel corrosion in RC structures. Accurate numerical simulations that are based on inverse modelling and optimization algorithms combined with relatively infrequent, and hence inexpensive, non-destructive measurements has the potential to revolutionize the corrosion monitoring of RC infrastructure. The proposed research is expected to pave the way to the development of the next generation of corrosion measurement devices for RC structures. These new model-assisted NDTs will have a significant impact on the early detection of corrosion-induced structural safety issues and will considerably reduce costs by helping engineers more accurately manage, prioritize and budget maintenance/repair operations. The students involved in these projects will be equipped to contribute to the safety assessment of Canada's critical infrastructure.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
298291-2009
Name nom
Isgor, Burkan
Department département
Civil and Environmental Engineering
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2009
Award amount
40600
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1061
Committee name en
Civil Engineering - A
Committee name fr
Génie civil - A
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
1105
Research subject group en
Structural engineering
Research subject group fr
Génie des structures
Research subject en
Structural materials
Research subject fr
Matériaux de structure
Partie
4
Nb partie
5
Application title
Model-assisted non-destructive monitoring of reinforcement corrosion in concrete structures
Keyword
NSERC
Application summary
The deterioration of reinforced concrete (RC) structures due to steel corrosion is a major concern for infrastructure owners and operators. Therefore, accurate monitoring of reinforcement corrosion in concrete structures using non-destructive tests (NDTs) is critically important for assessing their durability and long-term performance, and for prioritizing and budgeting maintenance/repair operations. Although significant progress has been made during the last two decades, existing NDTs still lack the necessary accuracy and reliability to detect and to characterize steel corrosion in RC structures. The challenges associated with these methods can be explained by (1) the black-box nature of RC, (2) highly variable and complex nature of the chemical and physical properties of concrete, (3) dense reinforcement detailing in structural members, and (4) inherent problems associated with the corrosion measurement techniques. The main goal of the proposed research is to use inverse modelling and optimization techniques that combine spatially sparse field measurement data with the strength of numerical modelling to develop an innovative approach to the monitoring of steel corrosion in RC structures. Accurate numerical simulations that are based on inverse modelling and optimization algorithms combined with relatively infrequent, and hence inexpensive, non-destructive measurements has the potential to revolutionize the corrosion monitoring of RC infrastructure. The proposed research is expected to pave the way to the development of the next generation of corrosion measurement devices for RC structures. These new model-assisted NDTs will have a significant impact on the early detection of corrosion-induced structural safety issues and will considerably reduce costs by helping engineers more accurately manage, prioritize and budget maintenance/repair operations. The students involved in these projects will be equipped to contribute to the safety assessment of Canada's critical infrastructure.
