Grant: Discovery Grants Program - Individual
Memorial University of Newfoundland
$88,000.00
Intelligent decision support for marine oil spill response in harsh environments
EF 2021-22
Résumé
Marine oil spills (e.g., 2010 BP spill) can not only cause significantly negative impacts on the environment and socio-economy but constitute a long-term hazard to marine life and human health. The response to a spill is a time-sensitive, dynamic, multifaceted and complex process, depending on various factors e.g., oil quantity/properties, location, environmental conditions, response resources, and human judgement/behaviours. The success much relies on how efficiently and effectively the information and resources can be utilized and how optimally and quickly the decision and actions can be made. It is further challenged by harsh marine environments (low temperature, rough sea, sea ice, etc.) prevailing in Canadian offshore areas such as the Arctic/Northern Atlantic oceans. The response window of opportunity is very short due to technical/logistic difficulties, safety, and rapid oil movement. This has been evidenced by three recent spills in Newfoundland offshore. Thus, dynamic and efficient response decision support is much desired but still lacking of research and practice. Furthermore, human factors/errors contribute 60-80% in spill accidents but without good understating of their effects on spill response. Therefore, the research is to help address these challenges by developing an intelligent Marine Oil Spill response Decision Support System (iMOS-DSS) for harsh environments with focuses on: 1) comprehensive review and development of marine oil spill i-Base (oil/spill databases and a response knowledge base); 2) intelligent agent and human factor analysis aided spill simulation; 3) deep learning aided response process simulation-optimization coupling supported by decanting experiments (skimming, separation, treatment, and disposal); 4) artificial intelligence aided marine oil spill response decision support; and 5) virtual reality aid visualization for marine oil spill response decision making. The most commonly used response option (and only legally allowed in Canada), decanting process, will be mainly targeted for lab experiment to support process simulation and optimization work. System validation and evaluation will be further conducted via local spill responders' classroom and at-sea training exercises in NL. The proposed program will 1) produce new/advanced knowledge and methodologies to address urgent needs in improving response capabilities in Canada and beyond; 2) enrich and improve the theories and technologies of environmental emergency management and decision making in general; 3) train next-generation professionals and researchers through a cross-disciplinary, equitable, diverse and inclusive (EDI) research/training environment; 4) help position my group and university globally in marine oil spill research to expand international collaborations/impacts and apply the outcomes worldwide; and 5) bring significant short-/long-term benefits by supporting responsible development of industry and protecting our marine environments.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Newfoundland and Labrador, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2020-05002
Name nom
Chen, Bing
Department département
Engineering and Applied Science, Faculty of - Engineering and Applied Science, Faculty of
Organization id
89
Institution établissement
Memorial University of Newfoundland
Province en
Newfoundland and Labrador
Province fr
Terre-Neuve-et-Labrador
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2020
Award amount
88000
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
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
402
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Oceans, seas and estuaries
Area of application fr
Océans, mers et estuaires
Research subject code
1501
Research subject group en
Environmental engineering
Research subject group fr
Génie de l'environnement
Research subject en
Water quality, pollution
Research subject fr
Qualité de l'eau, pollution
Installment
inst:2
Partie
1
Nb partie
5
Application title
Intelligent decision support for marine oil spill response in harsh environments
Keyword
NSERC
Application summary
Marine oil spills (e.g., 2010 BP spill) can not only cause significantly negative impacts on the environment and socio-economy but constitute a long-term hazard to marine life and human health. The response to a spill is a time-sensitive, dynamic, multifaceted and complex process, depending on various factors e.g., oil quantity/properties, location, environmental conditions, response resources, and human judgement/behaviours. The success much relies on how efficiently and effectively the information and resources can be utilized and how optimally and quickly the decision and actions can be made. It is further challenged by harsh marine environments (low temperature, rough sea, sea ice, etc.) prevailing in Canadian offshore areas such as the Arctic/Northern Atlantic oceans. The response window of opportunity is very short due to technical/logistic difficulties, safety, and rapid oil movement. This has been evidenced by three recent spills in Newfoundland offshore. Thus, dynamic and efficient response decision support is much desired but still lacking of research and practice. Furthermore, human factors/errors contribute 60-80% in spill accidents but without good understating of their effects on spill response. Therefore, the research is to help address these challenges by developing an intelligent Marine Oil Spill response Decision Support System (iMOS-DSS) for harsh environments with focuses on: 1) comprehensive review and development of marine oil spill i-Base (oil/spill databases and a response knowledge base); 2) intelligent agent and human factor analysis aided spill simulation; 3) deep learning aided response process simulation-optimization coupling supported by decanting experiments (skimming, separation, treatment, and disposal); 4) artificial intelligence aided marine oil spill response decision support; and 5) virtual reality aid visualization for marine oil spill response decision making. The most commonly used response option (and only legally allowed in Canada), decanting process, will be mainly targeted for lab experiment to support process simulation and optimization work. System validation and evaluation will be further conducted via local spill responders' classroom and at-sea training exercises in NL. The proposed program will 1) produce new/advanced knowledge and methodologies to address urgent needs in improving response capabilities in Canada and beyond; 2) enrich and improve the theories and technologies of environmental emergency management and decision making in general; 3) train next-generation professionals and researchers through a cross-disciplinary, equitable, diverse and inclusive (EDI) research/training environment; 4) help position my group and university globally in marine oil spill research to expand international collaborations/impacts and apply the outcomes worldwide; and 5) bring significant short-/long-term benefits by supporting responsible development of industry and protecting our marine environments.