Monitoring Hazard to Critical Infrastructure from Increased Seismic Activity in or near Injection Wells

SPONSOR:  MICHIGAN SPACE GRANT CONSORTIUM

PI:  Thomas Oommen

The recent earthquakes in or near active injection wells in Youngstown, Ohio (Mw 3.9, 2011), Raton Basin, Colorado (Mw 5.3, 2011), and Prague, Oklahoma (Mw 5.6, 2011) have alerted the scientific community to the possibility that these earthquakes are caused by human activity. Although studies have not unequivocally established the human influence on this, it is evident that there is an increase in seismic activity near some injection wells and perhaps in some hydraulic fracturing operations.

This increase in seismic activity raises a significant question: How does this seismic activity affect the critical infrastructure ( dams, highways, railways, pipelines, and others) in its vicinity? The objective of this proposal is to do a prelimina,y study on the applicability of satellite based high resolution optical imaging and Synthetic Aperture Radar (SAR) to evaluate the effects of induced seismic events on the integrity of critical infrastructure in the vicinity of injection wells.

Thomas Oommen
Thomas Oommen

Sustainable Geotechnical Asset Management along the Transportation Infrastructure Environment using Remote Sensing

Sponsor: US Department of Transportation

PI: Thomas Oommen

The objective of this study is to establish a sustainable framework for Geotechnical Asset Management (GAM) using remote sensing data that can be used by the state departments of transportation across the US in order to identify and mitigate the failure of geotechnical assets proactively along the transportation infrastructure environment. Developing a sustainable GAM to enable more proactive infrastructure risk assessment is critical for strategic investment and long term management of the United State’s transportation infrastructure.

Remote sensing techniques, such as Interferometric Synthetic Aperture Radar (InSAR) and Light Detection and Ranging (LiDAR) provide great opportunities to measure ground movements precisely. Additionally, high resolution optical images complement observations from InSAR and LiDAR. Applying these techniques to the transportation environment can help to monitor and manage the stability of the geotechnical assets and would significantly reduce the level of effort currently needed to survey and inspect these assets.

A copy of this report can be found on the National Transportation Library website.

Thomas Oommen
Thomas Oommen

Evaluating the Use of Unmanned Aerial Vehicles for Transportation Purposes

Sponsor: Michigan Department of Transportation

PI: Colin Brooks

Advances in unmanned aerial vehicle (UAV) technology have enabled these tools to become easier to use and afford. In a budget-limited environment, these flexible remote sensing technologies can help address transportation agency needs in operations, maintenance, and asset management while increasing safety and decreasing cost.

This project tested and evaluated five main UAV platforms with a combination of optical, thermal, and LiDAR sensors to assess critical transportation infrastructure and issues such as bridges, confined spaces, traffic flow, and roadway assets.

A State of the Practice report was completed, and a series of lab testing were accomplished to ensure practicality and safe operations. Field demonstrations were completed at bridges, pump stations, and conferences. The project team gave a series of technical demonstrations at the Intelligent Transportation Systems World Congress in Detroit in September, 2014, enabling outreach to a wide domestic and international audience who gained understanding of the advanced research that MDOT is funding. These demonstrations showed that UAV technologies provide many advantages to helping MDOT cost-effectively assess, manage, and maintain its resources, providing benefit to staff and the traveling public.

A copy of this report can be found on the Michigan Department of Transportation website.

Colin N. Brooks
Colin N. Brooks
Tess Ahlborn
Tess Ahlborn
Timothy Havens
Timothy Havens
Thomas Oommen
Thomas Oommen

Remote Sensing Based Assessment System for Evaluating Risk to Transportation Infrastructure Following Wildfires

Sponsor:  University of Arkansas

PI:  Thomas Oommen

Photo courtesy of FEMA

Michigan Tech will aid in developing an empirical model to predict the probability of mudflow/rockslide and a Remote Sensing Based Decision Support System to evaluate the risk to transportation infrastructure following wildfires.

The empirical modeling will include developing a probabilistic model using logistic regression that relates the remote sensing inputs to the occurrence and non-occurrence of mudflows/rockslides.  The remote sensing derived parameters for logistic regression will include soil suction, soil volumetric water content, soil temperature, soil density, predominant mineral type, clay content, etc.

The RSBDSS will be built upon the existing decision support system that is being developed for Phase 5 Geotechnical Asset Management project (PI: Thomas Oommen).  Specifically, following the development of the RSBDSS, input parameters obtained from existing data or newly collected remote sensing data will be entered into the logistic regression model to determine the amount of risk associated with mudflows or rockslides following wildfire events.  This RBDSS is anticipated to aid highway managers in determining the risk to transportation infrastructure, which would help in developing plans for required road closures and ensuring safety of the users of transportation infrastructure.

Thomas Oommen
Thomas Oommen

Implementation of Unmanned Aerial Vehicles (UAVs) for Assessment of Transportation Infrastructure – Phase II

Sponsor:  Michigan Department of Transportation

PI:  Colin Brooks

Through Phase I of MDOT’s “Evaluating the Use of Unmanned Aerial Vehicles for Transportation Purposes” project, the Michigan Tech combined project team was successfully able to plan, demonstrate, and document UAV capabilities in the assessment of transportation assets.

With the rapid development of UAV’s, MDOT has requested additional research concerning their use for transportation asset management.  The work plan of the MTU combined team includes:

TASK 1:

  • Collect data from the UAV platform using sensing technology in near-time (as real-time as can be achieved) demonstrating, developing, and implementing storage capabilities of large amounts of data, usage of data, and application development that complements current data usage and application at MDOT.
  • Provide data collection from UAVs to the MDOT Data, Use, Analysis, and Process (DUAP) project that meets the quality, low latency delivery and data format requirements.
  • Provide a report that describes and recommends optional methods to store and distribute potentially large imaging, point cloud, and 3D surface datasets created through UAV-based data collection.

TASK 2:

  • Demonstrate, develop, and implement high-accuracy simultaneous thermal/photo/video/Light Detection and Ranging (LIDAR) measurement using a high-fidelity sensor-fused UAV positioning approach.

TASK 3:

  • Demonstrate the capabilities to complete aerial remote sensing data collections to meet MDOT mapping and construction monitoring needs.  Coordinate with MDOT Survey Support to identify pilot projects and meet data delivery needs satisfying MDOT requirements for spatial data collection as it pertains to data density, absolute and relative 3D positional accuracy.

TASK 4:

  • Demonstrate, develop and implement uses of data collection from UAV(s) and sensors for operations, maintenance, design, and asset management.

TASK 5:

  • Demonstrate, develop and implement enhanced testing of UAV-based thermal imaging for bridge deck structural integrity.
  • Compare data collected from UAV sensors to current data collected and systems used at MDOT for highway assets/operations.

TASK 6:

  • Demonstrate, develop, and implement systems management and operations uses.

TASK 7:

  • Provide a benefit/cost analysis and performance measures that define the return on investment as a result of deploying UAVs and related sensory technologies for transportation purposes.

TASK 8:

  • Secure a Federal Aviation Administration (FAA) Certificate of Authorization (COA) to complete the tasks and deliverables.
Colin N. Brooks
Colin N. Brooks
Tess Ahlborn
Tess Ahlborn
Timothy Havens
Timothy Havens
Thomas Oommen
Thomas Oommen
Kuilin Zhang
Kuilin Zhang

Rail Embankment Stabilization Needs on the Hudson Bay Railway

SPONSOR:  HUDSON BAY RAILWAY

PI:  Thomas Oommen

Hudson Bay Railway (HBR)is a key trade link that connects domestic origins and destinations in Canada and the United States with the export origins and destinations in Europe through the Port of Churchill. Over the last 80 years, the deterioration of the HBR embankment due to thawing discontinuous permafrost, combined with poor geotechnical properties of the muskeg soil has caused significant challenges in maintaining the HBR line. Warming climate has further added to this challenge, causing major concern for the owner of the line, Omnitrax. Developing sustainable methods to reliably identify, monitor, and mitigate issues along the transportation infrastructure in cold regions is critical for safe and efficient operations.

The objectives of this research are:

1. Defining a rating system for severity of railway conditions in permafrost affected areas.

2. Designing a “Best Practices Guide” to diagnose, document and perform corrective actions addressing each severity rating.

3. Creating a long term solution for embankment stability.

Thomas Oommen
Thomas Oommen

 

Sustainable Geotechnical Asset Management along the Transportation Infrastructure Environment Using Remote Sensing

Sponsor:  USDOT Research and Innovative Technology Administration (RITA)

PI:  Thomas Oommen

The objective of this proposed study is to establish a sustainable framework for Geotechnical Asset Management (GAM) using remote sensing data that can be used by the state departments of transportation across the US in order to identify and mitigate the failure of geotechnical assets proactively along the transportation infrastructure environment. Developing a sustainable GAM to enable more proactive infrastructure risk assessment is critical for strategic investment and long term management of the United State’s transportation infrastructure. Remote sensing techniques, such as Interferometric Synthetic Aperture Radar (InSAR) and Light Detection and Ranging (LiDAR) provide great opportunities to measure ground movements precisely. Additionally, high resolution optical images complement observations from InSAR and LiDAR. Applying these techniques to the transportation environment can help to monitor and manage the stability of the geotechnical assets and would significantly reduce the level of effort currently needed to survey and inspect these assets.

Thomas Oommen
Thomas Oommen
Colin N. Brooks
Colin N. Brooks
Pasi Lautala
Pasi Lautala
Stan Vitton
Stan Vitton