Bruce Dietrich

Modeling Crack Deterioration of Flexible Pavements: Comparison of Recurrent Markov Chains and Artificial Neural Networks

Pavement cracking and rutting are two of the most critical distress types manifested on flexible pavements, and they often govern the overall pavement condition. Hence, many models have been developed for forecasting the deterioration of the crack condition accurately, with the traditionally preferred technique being the use of a regression relationship developed from laboratory or field statistical data, or both. However, it becomes tedious for regression techniques to predict crack performance accurately and robustly in the presence of the multitude of tributary factors, material nonlinearity, and uncertainty involved in the cracking process. With the advancement of modeling techniques, two innovative breeds of models, neural networks and recurrent Markov chains, have drawn increasing attention from researchers for their use in modeling complex phenomena such as pavement cracking. This paper compares the ability of neural networks and recurrent Markov chains to model crack performance, using the Florida...

Measuring Resilient Modulus of Granular Materials in Flexible Pavements

A comparison study from the experimental results of the falling weight deflectometer (FWD) backcalculated modulus values, laboratory-measured resilient modulus values under field and laboratory conditions, and laboratory limerock bearing ratio values for granular materials in flexible pavements is presented. Based on the measured results, a case study was conducted to illustrate the use of laboratory resilient modulus for pavement design through the AASHTO flexible pavement design procedure. The results indicated that the average laboratory resilient moduli at optimum compacted conditions were 1.1 times higher than the average laboratory determined resilient moduli under in situ conditions. The FWD backcalculated moduli were about 1.8 times higher than the laboratory resilient moduli for the granular materials. The laboratory optimum moisture content was comparable to the field-measured in situ moisture content, although the average laboratory-determined maxi mum dry density was slightly higher than the average field-measured in situ dry density. The flexible pavement design could be based on the resilient modulus values found in the laboratory.

Development of Procedure for Automated Segmentation of Pavement Rut Data

To effectively manage pavements, it is necessary to know the current pavement condition. The Florida Department of Transportation uses an automated road profiler system to survey pavement condition. This system uses ultrasonic technology and is able to collect rut data at a high speed with tolerable accuracy. The system software processes the raw data into a density of 62 data points per kilometer. For pavement management applications, a summary of the rut data would be more useful than simply a list of them along the road. Thus, the objective of this study was to find a better way to reduce the amount of data and maintain the attributes as much as possible. To achieve the goal, an SAS (Statistical Analysis Software) segmentation program based on the cumulative difference approach (CDA) was developed to process the rut data. With this program a road may be divided into a number of segments within which the rut depth is relatively uniform. The average of the rut depths within this segment may represent the rut depth value of the whole segment. The data reduction rate and the sum of squared errors (SSE) were used in a case study as the indicators to compare the results from different user-specified constraints and to illustrate the usefulness of the CDA in rut data reduction. It may be concluded that the CDA is an effective method for rut data reduction in pavement management applications.

Influence of Base Clearance on Subgrade Resilient Modulus of Florida Roadway Pavements

The resilient modulus of pavement subgrade materials is an essential parameter for mechanistically based flexible pavement design procedures. “Base clearance” is defined as the clearance between the ground-water level and the pavement base layer within a pavement system. A high pavement moisture content, which is strongly influenced by the base clearance, causes detrimental effects on the resilient modulus of pavement subgrades. The determination of a pavement base clearance is one of the most important steps toward setting up grade lines in a roadway design. This paper presents an experimental study to evaluate the effects of base clearance on the resilient modulus of pavement subgrades. Full-scale dynamic pavement tests were conducted in test pits to simulate vehicle dynamic impact on field pavements. The level of base clearance was adjusted by raising or lowering the water level within the pavement layer in the pit. Ten types of Florida subgrade material were tested at different base clearances for this study. The dynamic plate load test results were compared with the resilient modulus obtained from the laboratory triaxial test by using layer theory. The differences between the resilient modulus from the laboratory test and the plate load test were typically about 20%. Resilient modulus measured from the laboratory triaxial test could be used to predict the resilient deformation of the pavement subgrade layers. The experimental results showed that, at lower base clearances, the high pavement moisture content caused a significant reduction of the resilient modulus of pavement subgrade layers. The resilient modulus of subgrade materials decreases with the decrease of base clearance.

Computer program for network level determination of pavement layer thicknesses

To address the need for developing a database of pavement layer thicknesses to support pavement management, the Florida Department of Transportation (FDOT) funded a project with the Texas Transportation Institute that developed a computer program called TERRA for analyzing Ground Penetrating Radar (GPR) data in a production environment. TERRA is an acronym for Thickness Evaluation of Roads by RAdar. It incorporates user-specified decision criteria for automated detection of layer interfaces. Tests to verify peak tracking capability demonstrated that the program is able to handle gradual or sudden changes in the patterns of the interface reflections as well as gaps in the data. Verification of the thickness predictions against core data from sites surveyed with radar showed acceptable accuracy for uncalibrated estimates of surface thickness. In particular, the average of the absolute differences between the means of predicted and measured surface thicknesses was found to be 0.30 inches. Because of the absence of measured base thicknesses, it was not possible to verify the base predictions on the sites tested. It is recommended that this be done by FDOT at a future date as part of its GPR implementation efforts.

The importance of mineral filler on construction specifications

Studies have been conducted to date to demonstrate how the dust content in hot-mix-asphalt (HMA) should be accounted for in construction specifications. It may be detrimental to pavement performance if a high change in the dust content from the actual target value is not captured during HMA production. A study was conducted to determine whether the present composite pay factor (CPF) in Florida reflects the laboratory predicted loss in cracking performance. Resilient modulus, creep and strength tests, along with the University of Florida fracture mechanics model were used on 18 Superpave mixtures. Based on the analysis conducted, it was found that the current CPF in Florida did not reflect the expected loss in performance. The results showed that a 2% increase in dust can be at least as or more detrimental than 0.7% reduction in the asphalt content. However, this was not reflected in the weighted factor assigned to dust in the CPF equation. In this research, a framework to identify performance-based acceptance procedures was also presented. Ideally, this framework can be used to develop or modify construction specifications so that the expected performance of HMA can be assessed accordingly.

Florida’s Return on Investment from Pavement Research and Development

The Florida Department of Transportation (DOT) recently implemented an innovative pavement management forecasting methodology, Floridas Analysis System for Targets (FAST). FAST uses bottom-up, section-level forecasts to develop regional and systemwide network pavement condition forecasts and evaluates the effects of alternative resurfacing funding scenarios. FAST is calibrated and validated annually with the latest section-level pavement condition data. This calibration provides the ability to assess the latest impacts of changes in pavement materials, processes, and construction methods and management. FAST allows the Florida DOT to leverage its pavement management database to address funding limitations by ensuring that transportation dollars are efficiently allocated. FAST enables engineers and managers to predict more accurately the condition of the highway system in a manner that allows managers to establish the level of funding necessary for projected resurfacing needs. For two decades, the Florida DOT has worked on an initiative to improve the durability of its pavement sections. Floridas experience with FAST has shown an excellent return on investment for research and development into pavement materials, processes, construction methods and management, and pavement management technology. As a result of the adoption of Superpave®, changes to open graded friction courses, changes to the Florida DOT construction quality control program, and a consistent resurfacing program, Floridas pavements are lasting longer, and Florida DOT management is able to reallocate resources. This tool has enabled the Florida DOT to reduce its resurfacing program and reallocate approximately

Interpretation of Transverse Profiles to Determine the Source of Rutting Within an Asphalt Pavement System

3 billion in nonessential resurfacing funds over the next 10 years to projects to increase capacity.

Use of ground-penetrating radar for asphalt thickness determination

The transverse profilograph has been recognized as one of the most accurate devices for the measurement of rut depth. However, interpretation of surface transverse profile measurements poses a major challenge in determining the contributions of the different layers to rutting. A literature review has shown that the actual rutting mechanism can be estimated from a surface transverse profile for determination of the relative contribution of the layers to rutting. Unfortunately, much of the research yielded no verification or data. In addition, some techniques presented cannot be used if the rut depth is not well pronounced. Other techniques may be costly and time-consuming. The present research developed an approach that integrates (a) falling weight deflectometer and core data along with 3.6-m transverse profile measurements to assess the contributions of different pavement layers to rutting and (b) identifies the presence (or absence) of instability within the asphalt surface layer. This approach can be used regardless of the magnitude of the rut depth. On the basis of the analysis conducted, absolute rut depth should not be used to interpret the performance of the asphalt mixture. In addition, continued instability may not result in an increase in rut depth because the rutted basin broadens as traffic wander compacts or moves the dilated portion of the mixture. The approach developed appears to provide a reasonable way to distinguish between different sources of rutting. The conclusions drawn from analysis of the approach agreed well with observations from the trench cuts taken from four sections.

FORECASTING OF PAVEMENT CRACK PERFORMANCE WITH ADAPTIVE FILTER MODEL

A computer program, called TERRA (Thickness Evaluation of Roads by RAdar) was recently developed for estimating pavement layer thicknesses from ground penetrating radar (GPR) data. This program incorporates decision criteria for automated detection of layer interfaces, computation of layer thicknesses and a segmentation algorithm for delineating segments based on layer thicknesses. The Florida Department of Transportation (FDOT) initiated the present field study for an initial assessment of TERRA. Radar and core data were collected from several flexible pavement sections of Floridas roadway system. These sites were selected to represent the present Florida in-place mixes (Superpave and Marshall mixtures) and different asphalt layer thicknesses, which varied from approximately 50 to 300 mm (2 to 12 in). Radar data were collected at both highway speeds and in stationary mode. This paper presents a description of the data collection effort as well as the subsequent analysis and findings.