Progression of Aggregate Loss on Porous Asphalt
L.Y. Pan (TU Delft - Electrical Engineering, Mathematics and Computer Science)
G. Jongbloed – Mentor (TU Delft - Delft Institute of Applied Mathematics)
L. Schouten – Mentor (Rijkswaterstaat)
K. Anupam – Graduation committee member (TU Delft - Pavement Engineering)
P. Chen – Graduation committee member (TU Delft - Statistics)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Porous asphalt resides on most top layers of Dutch roads. Scheduling maintenance for these roads is generally dependent on several factors, but ravelling, the loss of aggregates in the top layers, is the main reason for maintenance on Dutch roads. With the recent framework of the DOS-LCMS scheme generating values for aggregate loss in percentages, a prediction for the remaining lifetime of a road section surfaced with porous asphalt with respect to ravelling can be performed. The lifespan for porous asphalt layers is dependent on the most suffered 25% of the section on the respective 100 meter length.
The current threshold is set at 10%, implying that road sections of 100 meter need maintenance if more than 25% of the road (75th percentile) measures aggregate loss over 10%. The present work approximates these 75th percentiles throughout the years using parametric and non-parametric approaches, whereafter the estimates of the 75th percentiles are used to construct smooth monotonic increasing convex curves. These curves, which are in fact functions built on P-splines, are then used to perform extrapolation and hence predict the dates on which the threshold is going to be surpassed. The study reveals problems in the raw data which is particularly prominent in the sequence of 75th percentiles, frequently showing a lack of monotonicity and convexity. Putting the monotonicity and convexity constraints on a more granular level were found to be helpful for the predictions and improved the consistency of lifetime predictions over consecutive years.