National Academy of Sciences | 150 Year Anniversary

Questions? Call 800-624-6242

| Items in cart [0]

The National Academies Press

Rights & Permissions

topleft topright

NCHRP Report 669: Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays (2010)
National Cooperative Highway Research Program (NCHRP)

Citation Manager

Zhou, Fujie, Lytton, Robert L, Hu, Sheng, Luo, Rong, Tsai, Fang-Ling, Lee, Sang Ick, Transportation Research Board. "Traffic Data Collection." NCHRP Report 669: Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays. Washington, DC: The National Academies Press, 2010.

Please select a format:

BibTeX EndNote RefMan


Page
10
bottomleft bottomright
Page
10
Front Matter (R1-R11)
Organization of the Report (1-1)
Material Properties (2-2)
Calibration to Field Data (3-3)
Use in Design (4-4)
Available Reflection Cracking Models (5-5)
Selection of a Reflection Cracking Model (6-6)
Process of Constructing a Calibrated Reflection Cracking Model (7-7)
Collection of Pavement Structure Data (8-9)
Traffic Data Collection (10-10)
Axle Load Distribution Factor (11-12)
Categorizing Traffic Load (13-13)
Finite Element Method for Calculating SIF (14-16)
Method of Predicting SIF (17-18)
Modeling of Cumulative Axle Load Distribution (19-19)
Probability Density on Tire Patch Length (20-25)
Reflection Cracking Amount and Severity Model (26-26)
Calibration of Field Reflection Cracking Model (27-27)
System Identification Process (28-28)
Parameter Adjustment and Adaption Algorithm (29-29)
Calibrating Reflection Cracking Model of Test Sections (30-32)
Heat Transfer in Pavement (33-33)
The Bottom Boundary Condition (34-34)
Stiffness, Tensile Strength, Compliance, and Fracture Properties of Mixtures (35-35)
Artificial Neural Network Algorithms for Witczak's Complex Modulus Models (36-37)
Models of Paris and Erdogan's Law Fracture Coefficients A and n (38-38)
Computational Method for Crack Growth Due to Traffic (39-40)
Computational Method for Viscoelastic Thermal Stresses (41-41)
Computation-to-Field Calibration Coefficients (42-43)
Validation of the Calibration Coefficients (44-47)
Mechanistic Prediction of Crack Growth (48-48)
Calibration of Calculated Overlay Life to the Observed Distress (49-49)
Predictions of Overlay Reflection Cracking (50-54)
Calibration of the Computational Model to Field Data (55-55)
Suggested Research (56-57)
References (58-59)
Appendices (60-60)
Abbreviations used without definitions in TRB publications (61-61)

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 10
10 Table 3. Distribution of LTPP test sections by states. Climate No. of Climate No. of Climate No. of State State State Zone Sections Zone Sections Zone Sections Alabama WNF 14 Massachusetts WF - South Dakota WF 3 Alaska WF 4 Michigan WF 12 Tennessee WF/WNF 4/1 Arizona DNF 11 Minnesota WF 21 Texas DF/ WNF 2/28 Arkansas WNF 2 Mississippi WNF 13 Utah DF - California DNF/WNF 5/3 Missouri WF 23 Vermont WF 4 Colorado DF 9 Montana DF - Virginia WF/WNF 1/3 Connecticut WF 6 Nebraska DF/ WF - Washington DF 1 Delaware WF 1 Nevada DF/DNF - West Virginia WF - D.C. WF 1 New Hampshire WF 1 Wisconsin WF 20 Florida WNF 2 New Jersey WF 21 Wyoming DF - Georgia WNF 2 New Mexico DF/DNF - Alberta WF 4 Idaho DF/WF - New York WF 4 British Columbia DF - Illinois WF 13 North Carolina WF/WNF 2/11 Manitoba WF 9 Indiana WF 14 Ohio WF 3 New Brunswick WF 1 Iowa WF 10 Oklahoma WF/WNF 1/11 Nova Scotia WF - Kansas WF 13 Oregon WNF 1 Ontario WF 3 Kentucky WF 2 Pennsylvania WF 7 Quebec WF 9 Maine WF 6 Rhode Island WF - Saskatchewan DF 4 Maryland WF 14 South Carolina WNF 1 - - - shift coefficients, C1 and C2). The method of making this con- order to have reliable and values for the S-shaped curves version is explained in Appendix G. These six properties of the that were fitted to the distress data, at least three separate and master curve of extracted binders were measured and reported sequential observations of distress were required. In some in SHRP studies (4) and tabulated in Appendix G. This infor- cases, no distress data were recorded on the old pavement mation was used together with the calculated temperature to surface prior to overlay and a mathematical method had to be determine the input to the ANN models of Witczak's 1999 (2) devised to estimate the original amount of cracking which and 2006 (3) models of the complex modulus. was subject to reflection. The mathematical method used was The overlay test sections in Texas and New York City con- the Systems Identification method which is described in tributed high quality data and the unique feature of having detail subsequently in this chapter and also in Appendix L. the overlays reinforced by geosynthetic interlayers. Traffic Data Collection Pavement Distress Data Collection Traffic data is a key element for the design and analysis of The pavement distress data included the total length and a HMA overlay structure or a new pavement structure. For severity of the cracks in the old pavement surface prior to the compatibility with the MEPDG, traffic was described by the placement of the overlay and the length and severity of the actual load distribution (spectrum) for each axle type (single, cracks reflected through the overlay. Only transverse cracks tandem, tridem, or quadrem axle) for each vehicle (truck) were considered as reflection cracks in each test section. In class or number of tires (single or dual).