The models from that project were designed to help NYSDOT implement the new AASHTO mechanistic-empirical pavement design guide (DARWin-ME™) while still being applicable with the existing NYSDOT Comprehensive Pavement Design Manual (CPDM). This project will expand on earlier research results, creating models of seasonal change in unbound (subbase and subgrade) layer moduli applicable across approximately 90 percent of the area of New York State.
Nuggets & Nibbles Newsletter Feature Article on Pavement Frost Models
Project Goals
- Expand the inference space of the models of seasonal change in unbound (subbase and subgrade) layer moduli for use in mechanistic pavement design.
- Revise and update the matrix of the soil and climatic zones important to pavement design in New York State.
- Using a practical set of evaluation tests at a site; determine an effective resilient modulus of subgrade for use in the 2000 NYSDOT Comprehensive Pavement Design Manual (CPDM), Chapter 4: New Pavement Design.
- Using a practical set of evaluation tests at a site, determine a predictive seasonal model of resilient modulus of unbound materials to be used in mechanistically-based new and reconstruction pavement design.
- Provide software tools and training for NYSDOT engineers to facilitate the implementation of this research.
Cornell Spring Thaw Predictor for Local Highway Agencies in New York State
New York State suffers from freeze-thaw cycles in the spring that cause significant damage to local pavements. Across the United States, spring load restriction periods (SLR's) restrict traffic and impose weight limits during the thaw-weakening season in order to reduce damage and better preserve pavements.
Some of the common SLR methods that have been used to determine the critical periods when the pavement is weak are either too simple or too complicated. The use of fixed dates determined by weather data, or simply waiting until after thawing has started, leads to preventable damage. Other, more complicated methods, can be very accurate, but require a large amount of detailed data which can be hard to obtain. Spring freeze-thaw periods change from year to year both by location within NYS, and in response to the composition of a pavement.
The CSTP tool uses the Cornell Pavement Frost Model (CPFM) as the engine behind the calculations used to predict freeze-thaw cycles in pavements. A 10-day spring thaw forecast using publicly available temperature data allow for accurate predictions of thawing and gives users sufficient warning time to plan for, and implement SLRs.
Predictor Tool (xls)
User Guide (pdf)
