MoDOT pavement preservation research program volume III, development of pavement family and treatment performance models.

Details

• Creators:
  Richardson, David N. ; Lusher, Michael
• Corporate Creators:
  Missouri University of Science and Technology. Dept. of Civil, Architectural, and Environmental Engineering
• Corporate Contributors:
  United States. Federal Highway Administration ; Missouri University of Science and Technology. Center for Transportation Infrastructure and Safety
• Subject/TRT Terms:
  • Pavement maintenance
  • Research
  • Pavement management systems
  • Maintenance management
  • Guidelines
  • Minimization
  • Costs
  • Pavement performance
  • Roughness
  • Mathematical models
• Publication/ Report Number:
  cmr 16-004
• Resource Type:
  Tech Report
• Geographical Coverage:
  Missouri
• Corporate Publisher:
  Missouri. Dept. of Transportation. Division of Construction and Materials
• Abstract:
  Pavement performance models describe the deterioration behavior of pavements. They are essential in a pavement management ; system if the goal is to make more objective, reliable, and cost-effective decisions regarding the timing and nature of pavement ; maintenance activities. The general objective of Task 2 was to develop performance models for a variety of pavement families and ; pavement preservation treatments used by the Missouri Department of Transportation (MoDOT). Using the data collected in Task ; 1, linear least-squares regression techniques were used to generate deterministic models that predict the International Roughness ; Index (IRI), the pavement condition measure most widely used today. Family IRI-prediction models were developed for full-depth ; asphalt (FDA), concrete (PCC), and composite (Comp) pavements. Treatment IRI-prediction models were developed for 1-in. ; overlays on FDA pavements, chip seals on FDA pavements, and 3.75-in. overlays on PCC pavement. Predictor variables ; consistently shown to be highly significant in predicting IRI for both FDA and Comp pavements were initial IRI (IRIo or the IRI ; value right after treatment) and pavement surface age (SA). The majority of the PCC pavement sections selected were so old that ; IRIo could not be determined (or estimated with any confidence), therefore SA was the dominant predictor variable in the PCC ; pavement family model. Terminal IRI (IRIt ; which was the IRI just prior to a treatment) was also a significant predictor of IRI and ; was directly or indirectly included in the FDA and Comp family and treatment models. Additional significant IRI predictors ; (depending on the model) were the climate parameters DT32 (days/year that air temperature was below freezing), FT (freeze/thaw ; cycles per year), and DP01 (days/year that precipitation was at least 0.1–in.), subgrade soil parameters P200 (percent passing the ; #200 sieve) and Pclay (percent clay-size soil), and LstTrtThk (the last treatment thickness).
  More +
• Format:
  PDF
• Funding:
  TRyy1141 (Task 2) ; 39112 ; DTRT06-G-0014
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29576/dot_29576_DS1.pdf
• File Type:
  [PDF - 2.68 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:1316e435c48f29d2de70f9ec76f941dc49dc7924ab775f6405a8b14367029546