Prediction of Pavement Deterioration Based on FWD Results


Book Description

Prediction models for pavement deterioration of major roads in Miyazaki Pre-fecture, Japan, using falling weight deflectometer (FWD) data are presented. The models would be incorporated in a pavement management system (PMS), for the prefecture, which is under development. At first, a relation between Japanese maintenance control index (MCI) and cumulative equivalent single axle loads (CESAL) was established. MCI was computed using variables that were automatically measured by a vehicle mounted with laser beam, cameras and profilometers. AASHO performance equation provided the basis for the development of these new models. Strength (deflection) factor was introduced into the coefficient that controls the slope of the performance curve through multiple regression analysis. Given FWD deflection and CESAL, these models could predict the trend of future pavement deterioration. This method increases the range of applicability of FWD data and may complement pavement condition rating systems that provide a measure of current pavement conditions only.




Nondestructive Testing of Pavements and Backcalculation of Moduli


Book Description

As with the previous two symposia, the 32 papers from the June/July, 1999, Seattle symposium present advances in the nondestructive testing of pavements using conventional falling weight deflectometer techniques and other promising techniques such as ground penetrating radar, rolling weight deflecto




The Applicability of Published Pavement Deterioration Models for National Roads


Book Description

The growing interest in pavement management systems (PMSs), both in South Mrica and internationally, has been in response to a shift in importance from the construction of new roads to the maintenance of the existing paved network coupled with increasingly restrictive road funding. In order to develop a balanced expenditure programme for the national roads of South Africa there is a need to predict the rate of deterioration of a pavement and the nature of the changes in its condition so that the timing, type and cost of maintenance needs could be estimated. Internationally these expected changes in pavement condition are predicted by pavement deterioration models, which normally are algorithms developed mathematically or from a study of pavement deterioration. Since no usable pavement deterioration models existed locally, it was necessary to evaluate overseas literature on pavement deterioration prediction models with the aim of identifying models possibly applicable to the national roads of South Africa. Only deterioration models developed from the deterioration results of inservice pavements under a normal traffic spectrum were evaluated. Models developed from accelerated testing were avoided since these models virtually eliminated long?term effects (these are primarily environmental but also include effects of the rest periods between loads), and that the unrepresentative traffic loading regimes can distort the behaviour of the pavement materials, which is often stress dependent. Models developed from the following studies were evaluated: AASHO Road Test The Kenya study Brazil-UNDP study (HDM-ill models) Texas study Of all the above models studied that were developed from major studies it was concluded that the incremental models developed during the Brazil study, were the most appropriate for further evaluation under South African conditions. A sensitivity analysis was conducted on the HDM-III models to evaluate their sensitivity to changes in the different parameters comprising each model. The results obtained from the sensitivity analysis indicate that the incremental roughness prediction model incorporated into the HDM-III model tends to be insensitive to changes in most parameters. Accuracy ranges for input data were, however, also identified for parameters which indicated an increase in sensitivity in certain ranges. The local applicability of the HDM-III deterioration models were finally evaluated by comparing HDM-III model predictions with the actually observed deterioration values of a selected number of national road pavement sections. To enable the above comparison, a validation procedure had to be developed according to which the format of existing data could be transformed to that required by the HDM-ill model, as well as additional information be calculated. From the comparison it was concluded that the HDM-III models are capable of accurately predicting the observed deterioration on South African national roads, but that for most models calibration is needed for local conditions. Guidelines regarding recommended calibration factor ranges for the different HDM-ill models are given. Finally it is recommended that the HDM-III models should be considered for incorporation into a balanced expenditure programme for the national roads of South Africa.




Development of Deterioration Models for Street Pavement in Dallas-Fort Worth Metroplex


Book Description

Accurate prediction of pavement deterioration is vital for an efficient and cost-effective allocation of available budgets for keeping an agency's road networks operating at a desirable level. Currently, most cities in the Dallas-Fort Worth Metroplex area are using the software PAVERTM and the associated performance models to predict future conditions as they do not have available reliable prediction models. However, the problem with this type of modeling is that the models are not calibrated to local conditions.The Pavement Deterioration Prediction models that have been developed in this research will help any pavement management agencies within DFW Metroplex area to identify and predict the future pavement performance for any planning period. The models were developed based on the available data collected by the city's pavement management department for the DFW Metroplex area. In this research, a family modeling approach has been used as this method reduces the number of independent variables in performance modeling to a single variable (age in this research) by enabling the development of models in each pavement family. Separate models are also developed for areas with expansive and non-expansive subgrade soil. A total of eleven models are developed for the areas non-expansive subgrade soil area and nine models for the areas with expansive subgrade soil. Deterministic models that are developed are applicable to cities with available historical data on PCI or IRI. The developed probabilistic models are applicable to cities with a current pavement condition data, but no less than the last two consecutive years.




Use of Falling Weight Deflectometer Data for Assessing Pavement Structural Evaluation Values


Book Description

Structural evaluation can be very useful at the network level for project prioritization purposes. In the project priority ranking procedure of the Kansas Department of Transportation (KDOT), a pavement rating attribute, Pavement Structural Evaluation (PSE), is used. These ratings are subjective. his study outlines an approach based on the classical multiple regression analysis resulting in a better estimation of the PSE values using the results from the Falling Weight Deflectometer (FWD) tests and network-level distress survey. The regression models proposed in this study predict the decrease in PSE values by taking into account the FWD data, age, thickness, and distress levels of pavements, and very closely approximate the current PSE ratings obtained at the district level.




Significant Findings from Full-scale Accelerated Pavement Testing


Book Description

"TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 433: Significant Findings from Full-Scale Accelerated Pavement Testing documents and summarizes significant findings from the various experimental activities associated with full-scale accelerated pavement testing (f-sAPT) programs that have taken place between 2000 and 2011. The report also identifies gaps in knowledge related to f-sAPT and where future research may be needed. NCHRP Synthesis 433 is designed to expand the f-sAPT base of knowledge documented in NCHRP Syntheses 325 and 235, both with the same title of Significant Findings from Full-Scale Accelerated Pavement Testing. f-sAPT is the controlled application of a wheel loading, at or above the appropriate legal load limit, to a pavement system to determine pavement response in a compressed time period. The acceleration of damage is achieved by one or more of the following factors: increased repetitions, modified loading conditions, imposed climatic conditions, and thinner pavements with a decreased structural capacity which have shorter design lives"--







Maintenance and Safety of Aging Infrastructure


Book Description

This book presents the latest research findings in the field of maintenance and safety of aging infrastructure. The invited contributions provide an overview of the use of advanced computational and/or experimental techniques in damage and vulnerability assessment as well as maintenance and retrofitting of aging structures and infrastructures such







Pavement Deterioration Modeling Using Historical Roghness Data


Book Description

Pavement management systems and performance prediction modeling tools are essential for maintaining an efficient and cost effective roadway network. One indicator of pavement performance is the International Roughness Index (IRI), which is a measure of ride quality and also impacts road safety. Many transportation agencies use IRI to allocate annual maintenance and rehabilitation strategies to their road network. The objective of the work in this study was to develop a methodology to evaluate and predict pavement roughness over the pavement service life. Unlike previous studies, a unique aspect of this work was the use of non-linear mathematical function, sigmoidal growth function, to model the IRI data and provide agencies with the information needed for decision making in asset management and funding allocation. The analysis included data from two major databases (case studies): Long Term Pavement Performance (LTPP) and the Minnesota Department of Transportation MnROAD research program. Each case study analyzed periodic IRI measurements, which were used to develop the sigmoidal models.The analysis aimed to demonstrate several concepts; that the LTPP and MnROAD roughness data could be represented using the sigmoidal growth function, that periodic IRI measurements collected for road sections with similar characteristics could be processed to develop an IRI curve representing the pavement deterioration for this group, and that pavement deterioration using historical IRI data can provide insight on traffic loading, material, and climate effects. The results of the two case studies concluded that in general, pavement sections without drainage systems, narrower lanes, higher traffic, or measured in the outermost lane were observed to have more rapid deterioration trends than their counterparts. Overall, this study demonstrated that the sigmoidal growth function is a viable option for roughness deterioration modeling. This research not only to demonstrated how historical roughness can be modeled, but also how the same framework could be applied to other measures of pavement performance which deteriorate in a similar manner, including distress severity, present serviceability rating, and friction loss. These sigmoidal models are regarded to provide better understanding of particular pavement network deterioration, which in turn can provide value in asset management and resource allocation planning.