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Title:

Statistical Analysis Framework to Evaluate Asphalt Concrete Overlay Reflective Cracking Performance

Accession Number:

01838525

Record Type:

Component

Availability:

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Order URL: http://worldcat.org/issn/03611981

Abstract:

The purpose of this paper is to provide a robust process to statistically analyze reflective cracking field performance data. There is often a lack of consistency and transparency in statistical analysis of pavement field performance data, which may not satisfy ANOVA or regression modeling assumptions. Twelve full-scale asphalt concrete (AC) overlay pavement test sections located at the MnROAD test facility are used to demonstrate the statistical framework. The percentage of cracking reported at joint locations (%RC) is used to represent reflective cracking performance, and its relationships to pre-overlay load transfer efficiency (LTE), truck traffic, overlay thickness, and common performance indices determined from laboratory tests are investigated. The three laboratory tests considered in this study are the disk-shaped compact tension (DCT), semi-circular bend (SCB) and overlay tester (OT). Logistic regression models are used for estimation. Predictive abilities of various models are compared in relation to the percentage odds (%odds) of reflective cracking. Model output is binary: it estimates not the relative amount of reflective cracking but instead the probability of a given pavement structure cracking. Varying ability to perform asphalt mixture laboratory performance testing is assumed. One such model, where no laboratory performance testing variables are included, shows that a one-unit increase (1-in.) in AC overlay thickness may result in approximately a third decrease in the %odds of reflective cracking. A logistic regression model developed that considers laboratory performance data from DCT, SCB, and OT results in the optimal model balancing best fit and best prediction properties without overfitting.

Supplemental Notes:

Katie Haslett https://orcid.org/0000-0002-3494-1066 © National Academy of Sciences: Transportation Research Board 2022.

Language:

English

Authors:

Haslett, Katie

ORCID 0000-0002-3494-1066

Dave, Eshan

ORCID 0000-0001-9788-2246

Sias, Jo

ORCID 0000-0001-5284-0392

Linder, Ernst

ORCID 0000-0002-9658-2329

Pagination:

pp 132-146

Publication Date:

2022-5

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Volume: 2676
Issue Number: 5
Publisher: Sage Publications, Incorporated
ISSN: 0361-1981
EISSN: 2169-4052
Serial URL: http://journals.sagepub.com/home/trr

Media Type:

Web

Features:

References (14)

Subject Areas:

Highways; Materials; Pavements

Files:

TRIS, TRB, ATRI

Created Date:

Mar 11 2022 3:02PM