Assessing Variability of Surface Distress Surveys in Canadian Long-Term Pavement Performance Program

2001 ◽  
Vol 1764 (1) ◽  
pp. 112-118 ◽  
Author(s):  
Stephen N. Goodman
Keyword(s):  
Pavement Performance ◽  
Surface Distress

“Off-the-Wall” Pavement Distress Variability Study

1998 ◽  
Vol 1643 (1) ◽  
pp. 62-70 ◽  
Author(s):  
Jerome F. Daleiden ◽  
Amy L. Simpson
Keyword(s):  
Data Collection ◽  
Pavement Performance ◽  
Human Errors ◽  
Projection System ◽  
Pavement Distress ◽  
Sophisticated Equipment ◽  
Surface Distress ◽  
The Impact ◽  
Variability Study

Variability of pavement surface distress data collection has always been an area of significant concern. When conducting evaluations of distress data manually (with raters observing pavements in question, interpreting what they see, and recording on paper) the process is subject to human errors. To minimize the impact of such human errors on these important pavement performance data, sophisticated equipment has been developed to eliminate as much of the human intervention as possible. Such technology is not without its own limitations of precision and bias. With both methodologies being used for the collection of surface distress data for the long-term pavement performance (LTPP) program, questions regarding precision and bias have been identified. In attempting to define the variability of the data for incorporation in stochastic analyses, it has become apparent how diverse and complex these distress data truly are. To adequately quantify the precision and bias, a detailed experiment was designed to evaluate the errors inherent in the different distress data collection methodologies. The facet of the experiment reported targets the variability of human distress surveyors and the biases associated with conducting surveys from film, using a slightly different projection system. Specifically, a collection of surveyors was assembled to establish the variability associated with experienced raters versus novice raters, engineers versus engineering technicians, and teams versus individuals.

Use of Long-Term Pavement Performance Data to Develop Traffic Defaults in Support of Mechanistic-Empirical Pavement Design Procedures

2003 ◽  
Vol 1855 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Weng On Tam ◽  
Harold Von Quintus
Keyword(s):  
Pavement Design ◽  
Vehicle Classification ◽  
Pavement Performance ◽  
Traffic Data ◽  
Design Procedures ◽  
Load Spectra ◽  
State Highway ◽  
Pavement Structures ◽  
Empirical Design

Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under NCHRP require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.

Comprehensive Evaluation of Rutting of Warm-Mix Asphalt Utilizing Long-Term Pavement Performance Specific Pavement Studies

2020 ◽  
Vol 2674 (7) ◽  
pp. 272-283 ◽  
Author(s):  
Biswajit K. Bairgi ◽  
A.S.M. Asifur Rahman ◽  
Rafiqul A. Tarefder ◽  
Matias M. Mendez Larrain
Keyword(s):  
Comprehensive Evaluation ◽  
Field Investigation ◽  
Warm Mix Asphalt ◽  
Pavement Performance ◽  
Laboratory Evaluation ◽  
Production Temperature ◽  
Wheel Tracking Test ◽  
Modified Binder ◽  
Wheel Tracking

Warm-mix asphalt (WMA) technologies allow binder softening for compaction benefits. Lower production temperature also causes reduced short-term aging in WMA. Considering the long-term implication of the reduced aging and binder softening, WMA is being questioned about its rutting characteristics. As such, this study evaluates different WMA technologies for rutting characteristics in comparison to traditional hot-mix asphalt (HMA) through laboratory and field investigation. The study utilized the long-term pavement performance (LTPP) project in the state of New Mexico called Specific Pavement Study-10 (SPS-10), which was designed to evaluate the WMA performances. The LTPP SPS-10 section includes: (i) control HMA, (ii) foaming, (iii) Evotherm, (iv) Cecabase 1, and (v) Cecabase 2 mixtures. Cecabase 2 mixture consists of a polymer-modified binder (PG 70-28+), whereas other mixtures consist of PG 70-28 binder. The aggregate type, properties, and gradations are the same in all the sections. Laboratory evaluation of rutting was conducted through the Hamburg wheel tracking test. Long-term field rutting was evaluated through Mandli’s pavement profile scanner, a laser-based distress evaluation technology. The study found that WMA with foaming, Evotherm, or Cecabase shows slightly higher rutting compared with the control HMA; however, all the sections satisfied laboratory and field rutting criteria. The use of a polymer-modified binder in WMA significantly improves the rutting characteristics.

Seed Modulus Generation Algorithm for Backcalculation of Flexible Pavement Moduli

2005 ◽  
Vol 1905 (1) ◽  
pp. 117-127 ◽  
Author(s):  
T. F. Fwa ◽  
Thakur Swapna Rani
Keyword(s):  
Closed Form ◽  
Flexible Pavements ◽  
Flexible Pavement ◽  
Pavement Performance ◽  
Program Performance ◽  
Generation Algorithm ◽  
User Input ◽  
Pavement Structures ◽  
Performance Project

The seed moduli chosen for backcalculation analysis of multilayer flexible pavements can have significant impacts on the performance of backcalculation software and, sometimes, the final solutions of the backcalculated moduli. Practically all backcalculation programs provide internally generated seed moduli for backcalculation analysis. However, as the internally generated seed moduli do not always produce satisfactory results, the use of user-input seed moduli is generally encouraged. With the aim of providing useful guidance in the choice of seed moduli, a seed modulus generation algorithm, 2L-BACK, for multilayer flexible pavements based on a closed-form modulus backcalculation solution for two-layer flexible pavement structures was developed. The proposed algorithm does not require any subjective judgment by the user. An evaluation analysis of the effectiveness of the proposed procedure is presented by the use of two types of backcalculation software, MICHBACK and EVERCALC, and is based on measured and computed data for flexible pavement segments from the Long-Term Pavement Performance project. A comparison was made of the backcalculation program performance and the computed moduli of solutions obtained from internally generated seed moduli and those obtained from seed moduli generated by the proposed algorithm. It was found that the proposed seed modulus generation algorithm led to enhanced program performance of MICHBACK with respect to convergence characteristics and the accuracies of the backcalculated solutions. In comparison, the corresponding improvements for the case of EVERCALC were less. The proposed seed modulus generation algorithm does not suffer from the location and pavement type transferability constraints of most regression-based seed modulus generation methods. The results of the study suggest that the algorithm can be effectively incorporated into backcalculation software for multilayer flexible pavements.

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