Richard W. Miller

Estimation of Remaining Service Life of Flexible Pavements from Surface Deflections

Remaining service life (RSL) has been defined as the anticipated number of years that a pavement will be functionally and structurally acceptable with only routine maintenance. The Kansas Department of Transportation (KDOT) employs a comprehensive pavement management system with a network optimization system (NOS) that uses the RSL concept. In support of NOS, annual condition surveys are conducted. Currently, KDOT uses an equation to compute RSL of flexible pavements based on surface conditions and deflection from the last sensor of a falling-weight deflectometer. However, a rolling-wheel deflectometer (RWD) can be used to collect deflection data at network-level. Thus, a model that can calculate RSL of pavements in terms of center deflection (the only deflection measured by RWD) is desired for NOS. In this study, FWD deflection data, collected with a Dynatest 8000 FWD on the KDOT network from 1998 to 2006, were analyzed. Nonlinear regression procedure in the Statistical Analysis Software and Solver in Microsoft Excel were also used. The results showed a sigmoidal relationship exists between RSL and center deflection. Sigmoidal RSL models have very good fits and can be used to predict RSL at the network level based on the center deflection from FWD or RWD. Sigmoidal equivalent fatigue crack models have also shown good fits, but with some scatter that can be attributed to the nature and quality of the data used to develop these models. Predicted and observed equivalent transverse crack values do not match well, though the difference is insignificant from a practical point of view.

Assessment of image-based data collection and the AASHTO provisional standard for cracking on asphalt-surfaced pavements

The network-level pavement management system of the Kansas Department of Transportation (KDOT) is known as the Network Optimization System (NOS). For input, KDOT manually collects data on cracking severity and extent on its network annually. In this study, pavement surface images were collected and analyzed to evaluate the impact of AASHTO provisional standard PP 44-01 for asphalt-surfaced pavement-cracking data collection on NOS. The study covered approximately 262 km (164 mi) of in-service bituminous and composite pavements in Kansas. Nearly 50,000 images of the pavement surface were obtained for manual and automated evaluation of pavement condition. Two different processes of image analysis were compared with existing results from the KDOT annual survey. Transverse and fatigue crack severity and extent were manually interpreted following KDOT crack-rating algorithms for all sections. In addition, the sections were analyzed with an automated crack identification procedure following PP 44-01. The images corresponding to approximately a 5% sample rated by KDOT were identified. Comparative data were available for a manual distress survey on 5% samples (by KDOT) and image-based manual and automated interpretation on the 5% and 100% samples. Statistical analysis shows good agreement between the 5% sample and 100% sample results from the manual survey and image-based manual interpretation, respectively, for both crack types. This implies that a 5% pavement sample is adequate for describing crack severity and extent in NOS. Severity of fatigue cracks from the images was more difficult to rate, probably because of the descriptive nature of severity levels in the NOS algorithm. Agreement between the results from the manual image analysis on both 5% and 100% pavement samples and the KDOT manual survey is acceptable. However, the automated image analysis technique following the provisional AASHTO standard tends to overestimate severity of cracking.

Network Level Testing for Pavement Structural Evaluation Using a Rolling Wheel Deflectometer

Structural evaluation can be very useful at the network level of pavement management for project prioritization purposes. However, due to expenses involved in data collection and analysis, pavements are not tested for structural capacity at the network level. Rolling wheel deflectometer (RWD), which measures surface deflections at highway speed, is an alternate, faster method of pavement deflection testing for network level data collection. This study was initiated to assess the feasibility of using RWD for network level pavement deflection measurements. RWD deflection data was collected under an 80-kN axle load and at about highway speed on non-interstate highways in northeast Kansas in July 2006. Falling-wheel deflectometer (FWD) data on these roads, collected from 1998 to 2006, were also used for comparison. The computed effective structural numbers from both FWD and RWD deflection data were compared. The results show that the deflections measured by RWD and the center (first sensor) deflections from FWD are statistically similar. The effective structural numbers computed from the FWD and RWD deflection measurements are also statistically similar. Thus RWD appears to be a valuable tool for structural capacity evaluation of pavements at the network level.

Costs and Benefits of Thin Surface Treatments on Bituminous Pavements in Kansas

This study investigated the benefits and costs of commonly used thin surface treatments for maintenance of bituminous pavements in Kansas. Cost and performance data were collected from the Kansas Pavement Management Information System for all treatments applied from 1992 to 2006. Results show that seal coats have a short average service life on Interstate highways. The average life on non-Interstate highways is about 4 years. This life is slightly lower than that for other thin surface treatments, including hot-mix asphalt (HMA) overlays. Seal coats also have a significantly lower equivalent uniform annual cost than do all other thin surface treatments in Kansas. A comparison of pavement benefit values before and after application showed that seal coat could not mitigate distresses better than other methods, especially thin HMA overlays. However, its performance is quite similar to that of the modified slurry seal.

ASSESSMENT OF AASHTO PROVISIONAL STANDARDS FOR PROFILE DATA COLLECTION AND INTERPRETATION

The Kansas Department of Transportation (KDOT) currently uses a comprehensive, network-level pavement management system (PMS) known as the network optimization system (NOS). Annual condition surveys for roughness, rutting, and faulting generate important inputs for NOS. Recently, AASHTO published provisional standards for condition surveys to harmonize data collection efforts among the states. To study the effects of these provisional standards on KDOT NOS, profile data were collected on about 320 km (201 mi) of Kansas highways according to these standards. The comparison data came from KDOTs annual condition survey with KDOT standards. The roughness values, in terms of international roughness index, were computed and aggregated for 20 test sections; rut depths were computed and compared for 16 test sections; and the fault values were computed and compared for 4 test sections. Various statistical analyses compared the results from the algorithms, according to KDOT NOS and AASHTO provisional standards. The roughness measurements and subsequent analysis using AASHTO provisional standard PP 37-00 and current KDOT methodology tend to produce statistically similar results. This may indicate that the PP 37-00 standard can be adopted for NOS without any major changes in current practice. The four-level stratification for rut-depth severity suggested by AASHTO PP 38-00 compares reasonably well with the current NOS practice. Both algorithms compared well for 3 composite pavement test sections and on 7 of 13 bituminous sections. On these sections, the effects of 0.16-km (0.1-mi) and 0.1-km (0.0625-mi) aggregation are insignificant. The dissimilarities on other sections may result from the outer sensors in the five-sensor configuration required by AASHTO PP 38-00. However, significant differences were found in calculated fault values from the two methods, even after some modification to PP 39-00.

Network-level flexible pavement structural evaluation

The Kansas Department of Transportation has a comprehensive pavement management system known as network optimisation system (NOS). Annual condition surveys are conducted for NOS. Currently, the structural number (SN) of flexible pavements is computed using the American association of state highway and transportation officials equation based on the centre and fifth sensor deflections of a falling weight deflectometer (FWD). However, a rolling wheel deflectometer (RWD) can be used to collect deflection data at the network-level. This study was conducted to see whether the SN of flexible pavements can be obtained from this RWD deflection and NOS condition survey results. In this study, FWD deflection data, collected from 1998 to 2006, were analysed. Multiple regression analysis was done. The results showed that there is a negative relationship between SN and centre deflection. Equations can be used to calculate SN based on FWD (or RWD) centre deflections and network-level condition survey results. The SN is more sensitive to centre deflection than the total pavement thickness.