Determination of Immediate Claystone Scour Potential

Details

• Creators:
  Stelwagon, Kate ; Senseney, Christopher T
• Corporate Creators:
  University of Colorado Boulder
• Corporate Contributors:
  Colorado. Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Scour
  • Clay
  • Corrosion
  • Cohesive soils
  • Procedures
  • Bridge decks
  • Mathematical prediction
  • Fluid dynamics
• Publication/ Report Number:
  CDOT-2025-09
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States ; Colorado
• Edition:
  Final Report
• Corporate Publisher:
  Colorado. Department of Transportation
• Abstract:
  The leading cause of bridge failure globally is scour. Scour occurs when water flowing beneath a bridge excavates and carries away portions of the streambed. Traditional scour prediction methodologies were designed for course-grained or “cohesionless” materials. Different scour mechanisms exist for course-grained and fine-grained materials. This study explores a new scour prediction methodology called SRICOS-EFA and compares it with scour predictions made by HEC-RAS and HEC-18, the standard scour prediction methodologies. This study focuses on scour prediction in fine-grained or “cohesive” materials, specifically Colorado claystone samples from Clear Creek in Wheat Ridge, Colorado. Results from this investigation indicate that SRICOS-EFA may not be an accurate method of estimating scour for Colorado claystone specifically. This result should be considered within the context of the limited number of samples that were tested under the scope of this study. Recommendations for a computational fluid dynamics model and potential next steps within standard procedures are discussed.
• Format:
  PDF
• Funding:
  R223.03
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/87979/dot_87979_DS1.pdf
• File Type:
  [PDF - 6.44 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:e9497a86f57032fa55a7a2efd69e5d42950f48228a13678578612007e596f0c084d8f9a7cb955a73108cf2e8897c2763ac2f8c68a3f3463c3b0d4d33ad00b428