Estimating Service Life of In Situ Flexible Pavements in Louisiana Using Pavement Management System Data

Author(s):  
Ahmed Abdel-Khalek ◽  
Mostafa A. Elseifi ◽  
Julius Codjoe ◽  
Christophe Fillastre
Author(s):  
T. S. Vepa ◽  
K. P. George ◽  
A. Raja Shekharan

The evaluation of remaining life is necessary to make optimal use of the structural capacity of in-service pavements. It simply represents the useful life left in the pavement until a failure condition is reached. Knowledge of remaining life facilitates decision making in regard to strategies for reconstruction-rehabilitation of roads, thereby leading to the efficient use of existing resources. Several methods proposed or used by various agencies to estimate the remaining lives of pavements are reviewed. They are classified under two categories: functional and structural. Making use of the Mississippi Department of Transportation pavement management system data base, survivor curves are developed for seven classes of flexible pavements with from thin to thick structures. By using these survivor curves a novel method for estimating remaining life is proposed. The reasonableness of the selected methods is examined by putting them to use in calculating the remaining lives of each of eight rigid and flexible pavement sections, all of them from the Mississippi global positioning system sections of the Strategic Highway Research Program–Long-Term Pavement Performance project (LTPP). With the structural details, falling weight deflectometer deflection data, and the distress information compiled from the LTTP information management system data base, the authors use two and four methods for rigid and flexible pavements, respectively, to determine the remaining lives. The remaining lives calculated by two methods for rigid pavements are comparable. Three of four methods for flexible pavements also generated comparable remaining lives. The authors were encouraged by the results and recommend that the survivor curve approach be explored further for network-level remaining life calculations. The reliabilities of various techniques currently available for the remaining life calculation are discussed.


Author(s):  
L. B. Wang ◽  
JinYoung Park ◽  
Sonya H. Hill

Pavement warranty is an innovative contracting procedure increasingly adopted by highway agencies. Many states view implementing warranties as a way to protect their investment in pavement construction. The major benefit of pavement warranty is enhanced pavement performance. However, establishing warranty criteria and monitoring the performance of warranted pavement are two technical issues that must be resolved. This paper presents the discoveries of a research project supported by FHWA to investigate the effectiveness of using the pavement management system (PMS) to monitor the performance of pavement under warranty. It has been discovered that most states establish their warranty specifications on the basis of performance data from their PMS database by using statistical analyses, expert opinions, and adaptation of other states’ specifications. They also use the PMS data to monitor the performance of both warranty and nonwarranty pavements because the essential data, like ride, cracking, and rutting, are available in the database and are convenient for use. This paper also documents the unique features of the warranty specifications, including the warranty period, performance indicators, data collection methods, performance thresholds, remedial actions, and how the PMS database can be used to track the performance of pavements under warranty in five states: Indiana, Wisconsin, Ohio, Florida, and Michigan. Some comparisons of the performances of the warranted pavements and those of nonwarranted pavements of similar conditions are also presented. The survey indicated that an integrated PMS that links the materials and traffic database would offer better efficiency to monitor and analyze the performance of both warranty and nonwarranty pavements.


2020 ◽  
Vol 8 (5) ◽  
pp. 3230-3232

The pavement management system deals with a pavement condition assessment. Rating of pavement can be done on the pavement condition assessment. Structural and functional distress is responsible for the failure of pavements. In this work, significant functional distresses which occur in flexible pavements are considered for the rating and assessment of road sections. The functional distress considered are Raveling, Potholes, Shoving, Patching, Depression, and Rutting as these are common and frequently occurred in the flexible pavements. The study of these distresses is done by authors. The measurement of distresses is done as per guideline given by the Indian Road Congress 1982 is used. For the condition, assessment guideline provided in Maintenance Management of Primary, Secondary, and Urban Roads, IRC, 2004, is used. Total five road section in the Pune region is considered for the study. All are flexible pavements. As Per assessment, it is observed that out of five segments, segment I and II are in fair to good condition, segment III is in very good condition. Segment IV and V are in very good and good condition, respectively.


The pavement management system deals with maintenance, repair, and rehabilitation of pavements. Pavement Condition evaluation is one of the critical steps in the pavement management system. It required distresses identification and measurement on the pavement surface. Structural distresses are an essential component in the pavement condition evaluation. To take decisions precisely, it is necessary to develop the relationship between various distresses. In this study, the relationship between structural distresses in flexible pavements has been analyzed. The primary structural distresses as longitudinal cracking, transverse cracking, Fatigue cracking, Block cracking, and deflection has been considered for the study. The correlation between all the distresses has been analysis. For correlation analysis, the Pearson Correlation Coefficient is used. The values of the Pearson correlation coefficient indicate that there is a strong positive relationship betweenthe distresses. Furthermore, to develop a prediction model, the regression analysis has been done. The values of the coefficient of regression indicate that the relationship is linear and positive between the structural distresses.


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