EAGER: Fiber Sensors Networks for Crude Oil Migration Monitoring In Ocean

EAGER：用于海洋原油运移监测的光纤传感器网络

• 批准号: 1054652
• 负责人: Kevin Peng Chen
• 金额: $ 20万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1054652&HistoricalAwards=false
• 关键词: EAGER; Fiber; Sensors; Networks; Crude

Abstract1054652 (EAGER)Peng ChenUniversity of PittsburgThe Deepwater Horizon oil spills in the Gulf of Mexico has become the most damaging environmental catastrophe in the US history. The failures for scientists and engineers to promptly stop the rupture and to swiftly evaluate the environmental damage highlight a number of daunting technical challenges related to deepwater resource exploration, pollution monitoring, and ecological conservation. In this EAGAR project, a distributed sensing network based on fiber optical sensing technology is investigated and designed for in-situ measurement of subsurface oil distribution and migration. Fiber grating sensors will be fabricated in short sections of high-attenuation fibers. Each fiber sensor will be coated with oil-affinitive porous nano-materials. Once it encounters oil droplets, the porous materials will absorb oil droplet, which leads to the increase of refractive index change and absorption in porous layers. Using wavelength division multiplexing, a large number of fiber sensors can be monitored by a single interrogation instrument.The proposed research will provide powerful and low-cost sensing tools to monitor three-dimensional oil pollution distribution and migration under ocean currents. The effectiveness of the clean-up efforts and long-term impact of oil spills to ocean ecology can be rapidly evaluated, rectified, and improved. This project will also impact the sustainability education at the University of Pittsburgh by providing unique teaching opportunities to students in terms of technological skills, professional ethnics, and environmental responsibilities.

墨西哥湾深水地平线石油泄漏事件已成为美国历史上最具破坏性的环境灾难。科学家和工程师未能及时阻止破裂并迅速评估环境损害，突出了与深水资源勘探、污染监测和生态保护有关的一些艰巨的技术挑战。EAGAR项目研究和设计了一种基于光纤传感技术的分布式传感网络，用于地下石油分布和运移的现场测量。光纤光栅传感器将在高衰减光纤的短节中制造。每个光纤传感器将被涂上亲油的多孔纳米材料。一旦遇到油滴，多孔材料将吸收油滴，导致多孔层的折射率变化和吸收增加。利用波分复用技术，一台光纤传感器可以监测多个光纤传感器，为海洋环境下油污染物三维分布和迁移监测提供了一种低成本、高性能的传感手段。清理工作的有效性和溢油对海洋生态的长期影响可以迅速评估、纠正和改善。该项目还将影响匹兹堡大学的可持续发展教育，为学生提供技术技能，职业道德和环境责任方面的独特教学机会。