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Insulating Pavements to Extend Service Life

  • Rajib B. Mallick
  • Aaron Sakulich
  • Bao-Liang Chen
  • Sankha Bhowmick
Part of the RILEM Bookseries book series (RILEM, volume 8)

Abstract

Temperature fluctuations in asphalt pavements can increase the potential for rutting and cracking distresses. One way of countering this problem is to insulate a pavement from the extremes of air temperature and to also use a high reflectivity surface in warmer climates to reduce the absorption of solar radiation. This paper presents modeling and simulation results of the application of these concepts. Pavements with and without insulation layers were modeled in low temperature (Juneau, AK) and high temperature (Houston, TX) cities. A high reflectivity surface was also modeled in Houston. Temperature and solar radiation data for an entire year were analyzed for each city and the data corresponding to lowest and highest temperature (respectively) were utilized in the low and high temperature city pavement models. Results indicate that high temperatures were significantly reduced and that low temperatures were increased, depending on the thermal conductivity and thickness of the insulation layer. The presence of a highly reflective layer was also found to be very effective in reducing high temperatures in pavements. The positive effects of high temperature reduction on the service life of pavements was found to be significant, and the use of conventional materials of sufficient thickness was found to be feasible. Based on these findings, an ideal pavement section is suggested as one with an insulation layer near the surface, which could also serve as a moisture prevention layer; with a high reflectivity surface; and which is economical, durable, and capable of retaining its properties.

Keywords

Insulation Layer Phase Change Material Bridge Deck National Renewable Energy Laboratory Lightweight Aggregate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© RILEM 2013

Authors and Affiliations

  • Rajib B. Mallick
    • 1
  • Aaron Sakulich
    • 1
  • Bao-Liang Chen
    • 1
  • Sankha Bhowmick
    • 2
  1. 1.Worcester Polytechnic InstituteWorcesterUSA
  2. 2.University of Massachusetts DartmouthNorth DartmouthUSA

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