Intelligent decision support for marine oil spill response in harsh environments

恶劣环境下海上溢油应急响应智能决策支持

• 批准号: RGPIN-2020-05002
• 负责人: Chen, Bing
• 金额: $ 6.41万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717486
• 关键词: Intelligent; decision; support; marine; oil

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.

海洋石油泄漏（例如，2010年BP溢出）不仅会对环境和社会经济造成显着负面影响，而且对海洋生物和人类健康构成了长期危害。对溢出的反应是时间敏感，动态，多方面和复杂的过程，具体取决于各种因素，例如油量/特性，位置，环境条件，响应资源和人类判断/行为。成功在很大程度上取决于如何利用信息和资源的有效性，以及如何最佳和快速地做出决策和行动。在加拿大北极/北大西洋等加拿大海上地区，严酷的海洋环境（低温，海洋，海冰等）进一步挑战。由于技术/逻辑困难，安全性和快速的石油运动，机会的响应窗口非常短。最近在纽芬兰离岸的三起泄漏事件证明了这一点。因此，充满动态和有效的响应决策支持是非常需要的，但仍然缺乏研究和实践。此外，人为因素/错误在溢出事故中贡献了60-80％，但没有良好地低估其对溢出反应的影响。因此，该研究是通过开发智能海洋石油漏油响应决策支持系统（IMOS-DSS）来帮助解决这些挑战的，重点是：1）全面审查和开发海洋溢油I-Base（石油/溢出数据库和响应知识库）； 2）智能药物和人为分析有助于溢出模拟； 3）深度学习辅助响应过程仿真 - 优化耦合，通过倒液实验（掠夺，分离，治疗和处置）支持； 4）人工智能协助海洋漏油反应决定支持； 5）虚拟现实辅助可视化，用于海洋溢油响应决策。最常用的响应选项（并且仅在加拿大合法允许），倾斜过程将主要针对实验室实验，以支持过程仿真和优化工作。系统验证和评估将通过NL的当地泄漏响应者的课堂和海上培训练习进一步进行。拟议的计划将1）产生新的/高级知识和方法，以满足提高加拿大及其响应能力的紧急需求； 2）丰富和改善环境应急管理和决策的理论和技术； 3）通过跨学科，公平，多元化和包容（EDI）研究/培训环境来培训下一代专业人员和研究人员； 4）帮助我的团队和大学在船舶溢油研究中的全球定位，以扩大国际合作/影响，并在全球应用成果； 5）通过支持负责任的行业发展和保护我们的海洋环境，从而带来显着的短期/长期利益。