A Feasibility Study of Road Culvert/Bridge Deck Deicing Using Geothermal Energy

Khosravi, Mohammad; Turner, Ethan; Sherazi, Syed Haider Ali; Plymesser, Kathyrn; Matteson, Kirsten; Pourakbar, Mehran; Nazemi, Neda; Dadgostari, Faraz; Toomani, Pooria; McKittrick, Ladean

doi:10.21949/1529

i

A Feasibility Study of Road Culvert/Bridge Deck Deicing Using Geothermal Energy

2025-08-01
By Khosravi, Mohammad ; Turner, Ethan ; Sherazi, Syed Haider Ali

File Language:

English

[PDF - 17.90 MB]

Details

Creators:

Khosravi, Mohammad ; Turner, Ethan ; Sherazi, Syed Haider Ali ; Plymesser, Kathyrn ; Matteson, Kirsten ; Pourakbar, Mehran ; Nazemi, Neda ; Dadgostari, Faraz ; Toomani, Pooria ; McKittrick, Ladean
Corporate Creators:

Montana State University (Bozeman, Montana)
Corporate Contributors:

United States. Department of Transportation. Federal Highway Administration ; Montana Department of Transportation. Research Programs
Subject/TRT Terms:
Publication/ Report Number:

FHWA/MT-25-002/9890-784
DOI:

https://doi.org/10.21949/1529
Resource Type:

Tech Report
Geographical Coverage:

United States ; Montana
Edition:

Final Report (July 2020-August 2025)
Corporate Publisher:

Montana. Department of Transportation. Research Programs
Abstract:

Montana's severe winters challenge bridge infrastructure with snow, ice, and concrete deterioration. Traditional deicing methods are often insufficient, harmful, and costly. This research explored using shallow geothermal energy for sustainable bridge deck deicing. Through lab tests, simulations, and machine learning, the system showed it could keep bridge surfaces above freezing at -10°C with 10°C inlet fluid. Higher inlet temperatures improved performance in colder conditions. The system also reduced thermal strain, potentially extending bridge life. A machine learning framework aids future site selection and cost-benefit analyses. This research supports the Montana Department of Transportation in implementing geothermal deicing systems, improving safety, reducing maintenance, and promoting sustainable infrastructure.
Format:

PDF
Funding:

9890-784
Download URL:

https://rosap.ntl.bts.gov/view/dot/86319/dot_86319_DS1.pdf
File Type:

[PDF - 17.90 MB]
Collection(s):

Artificial Intelligence Deployment Center of Excellence (AI COE) ; US Transportation Collection
Main Document Checksum:

urn:sha-512:d22cee3b1d661cd2bf4c750ade3ddb9b18fc872e1c25c28a0f557c890d9be1cc8c66ad4aa64c574d962f18d9bbdf0b599a60c8d6307c431560c07f3d41302c36

File Language:

English

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