SPR-4714: Use of Machine Learning Methods to Obtain a Reliable Predictive Model for Resilient Modulus of Subgrade Soil

This research will use machine learning to develop/train data model(s) for predicting the resilient modulus of soil in the state of Indiana. The developed model(s) will reduce the need for routine iterative laboratory testing conducted for obtaining the resilient modulus of soil, which is complicated, resource intensive, time consuming, and expensive. In addition, based on the developed model(s), recommendations will be provided for future sampling locations.

Language

• English

Project

• Status: Completed
• Funding: $63841
• Contract Numbers:

  SPR-4714

• Sponsor Organizations:

  Purdue University/Indiana Department of Transportation JHRP

  Purdue University
  1284 Civil Engineering Building, Room 4154
  West Lafayette, IN  United States  47907-1284
• Principal Investigators:

  Khoshnevisan, Sara

  Norouzi, Mehdi

• Start Date: 20221001
• Expected Completion Date: 20240930
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Machine learning; Modulus of resilience; Soils; Subgrade (Pavements)
• Geographic Terms: Indiana
• Subject Areas: Geotechnology; Highways;

Filing Info

• Accession Number: 01856072
• Record Type: Research project
• Source Agency: Indiana Department of Transportation
• Contract Numbers: SPR-4714
• Files: RIP, STATEDOT
• Created Date: Aug 24 2022 4:04PM