Overview
Project No. | 1032 |
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Contract No. | 693JK32450004CAAP |
Research Award Recipient | University of Dayton 300 College Park Dayton, OH 45469 |
AOR/TTI | Ben Kendrick Nusnin Akter Meg OConnor |
Researcher Contact Info | Hui Wang, Assistant Professor, Civil and Environmental Engineering Phone: 937-229-3847 Fax: 937-229-2756 Email: hwang12@udayton.edu Co-PIs: Homero Castaneda, Texas A&M University (TAMU) hcastaneda@tamu.edu; Hao Wang, Rutgers University (RU), hw261@soe.rutgers.edu; Lei Wang, University of Cincinnatti (UC), wang4li@ucmail.uc.edu |
Technology Demonstrated | TBD |
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Commercialized (in whole/part) | TBD |
Commercial Partner | Empty Value |
Net Improvement | Empty Value |
Project Status | Active |
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Start Fiscal Year | 2024 (09/30/2024) |
End Fiscal Year | 2026 (03/29/2026) |
PHMSA $$ Budgeted | $774,996.00 |
Main Objective
The main objective is to develop an integrated framework for creating a dynamic, risk-model-compatible pipeline data repository. The developed methodology will be validated through field testing on selected pipeline sections, incorporating feedback from subject matter experts and users to ensure alignment with industry best practices and standards. The outcome will be an integral and reliable tool for pipeline risk assessment, improving data management, mitigating risks, and enhancing the integrity and safety of pipeline systems.
Public Abstract
This project aims to develop a novel framework and integrated solution for creating a dynamic and risk-model-compatible pipeline data repository. Leveraging a multidisciplinary research team, the project will utilize publicly available sources, including climatalogical data, geological/geohazard data, and remote sensing data from government agencies such as NOAA, USGS, and NASA via open-source platforms. The proposed framework will integrate this extensive data with existing pipeline databases, encompassing a wide range of pipeline inspection methodologies, soil surveys, and emerging technologies. This project will actively engage subject matter experts, including practitioners, standards organizations, and pipeline operators, to ensure alignment with industry best practices and requirements.
Anticipated Results: The resulting data framework and repository will be meticulously designed to facilitate efficient data collection, cleaning, updating, and fusion at scale, with a focus on seamless integration into existing risk models. By promoting digital transformation within the pipeline industry and harnessing the full potential of data from both public and private sectors, the proposed database framework will improve pipeline data management practices, mitigate risks, and enhance the integrity of pipeline systems.
Potential Impact on Safety: The outcome of the project will positively impact pipeline safety by promoting digital transformation of pipeline industry via developing a framework and methodology to make full use of available data and will lead to minimizing the risk and maximizing the integrity of all pipeline systems.
Relevant Files & Links
Quarterly/Annual Status Reports
Quarterly Report 1
Quarterly Report 2