- Program Areas
- Installation Energy and Water
- Environmental Restoration
- Munitions Response
- Resource Conservation and Resiliency
- Natural Resources
- Infrastructure Resiliency
- Air Quality
- Weapons Systems and Platforms
Developing Smart Infrastructure for a Changing Arctic Environment Using Distributed Fiber-Optic Sensing Methods
Dr. Jonathan Ajo-Franklin | Lawrence Berkeley National Laboratory
Permafrost environments are a unique setting for built infrastructure, an environment in which small thermal perturbations can have dramatic impacts on structural stability ranging from foundation settling to catastrophic failure of roads, bridges, and runways due to thermokarst generation. A substantial global temperature change is expected within the next century with a higher degree of variability predicted in arctic regions (approximately 4°C) where substantial Department of Defense (DoD) resources are currently located. The non-linear coupling of future changes in air temperature, surface insolation, and surface/subsurface hydrology to soil mechanics generates a high degree of uncertainty as to the environmental changes that built infrastructure will actually experience.
The objective of this project is to develop and validate a fiber-optic geophysical sensing package capable of providing real-time information on subsurface conditions relevant to infrastructure performance and failure in permafrost environments. The system will consist of a combination of three fiber-based distributed sensing methods—distributed temperature sensing (DTS), distributed strain sensing (DSS), and distributed acoustic sensing (DAS)—designed to be embedded in, or near, built infrastructure and to detect regions of progressive permafrost thaw induced by subsurface flow, surface water accumulation, or changes in system thermal behavior. Seismic noise generated by infrastructure utilization (e.g., planes, automobiles, and railway activity) will be measured by DAS and inverted to generate real-time shear modulus profiles across the length of the installed component. Pre-failure deformation will be measured using DSS, allowing characterization of the early phases of consolidation. These profiles will be coupled to DTS-detected thermal perturbations to identify zones likely to be experiencing thawing and to flag such regions for inspection before infrastructure failure occurs. The resulting information will be provided on a quasi-real time basis to system decision-makers for incorporation into maintenance planning.
The project will use a three-step effort to evaluate the fiber-optics based geophysical sensing package for infrastructure monitoring. Researchers will initially investigate the data quality and repeatability provided by DAS/DSS/DTS arrays and then develop surface wave inversion methodologies suitable for reliable real-time monitoring. The project will culminate with a field test of the prototype monitoring system in a controlled subsurface thaw experiment. After the field test validates system performance, researchers will develop a prototype interpretation/decision making framework to allow utilization of the monitoring system by a broader set of practitioners. The primary novel scientific contribution is the fusion of existing fiber-optics sensing technologies (e.g., DAS/DSS/DTS) with passive surface wave inversion to allow analysis of the thaw state of soil beneath built infrastructure in cold regions.
The system to be developed will provide a scalable enabling tool for making arctic infrastructure more “aware” of environmental changes before costly failures occur. Commodity fiber installation is relatively inexpensive in comparison to traditional sensor networks and the use of ambient noise sources for seismic inversion will make the analysis approach independent of the campaign deployment of seismic sources. Transforming traditional roads, runways, and rail lines into smart infrastructure should allow DoD’s investment in future facilities to adapt to changes in the constantly evolving permafrost environment without the expensive and personnel- intensive effort of continuous inspections. (Anticipated Project Completion - 2018)