Showing papers by "Karim Chatti published in 2001"

Effective Layer Temperature Prediction Model and Temperature Correction via Falling Weight Deflectometer Deflections

Abstract: Surface deflections and backcalculated layer moduli of flexible pavements are significantly affected by the temperature of the asphalt concrete (AC) layer. The correction of these deflections and moduli to a reference temperature requires the determination of an effective temperature of the AC layer. In light of this, a new temperature prediction model for determination of the AC temperature on the basis of a database approach is presented, and temperature correction factors for AC modulus are developed. Temperature datum points (n = 317) and deflection profiles (n = 656) were collected from the six in-service test sites in Michigan. Temperature datum points (n = 197) from three of the test sites were used to develop the temperature prediction model, and data from the remaining sites were used for validation. The temperature prediction model developed has an R2 value greater than 90 percent and an F-statistic significantly greater than 1.0. For further validation of the temperature prediction model, tempe...

Development of a preventive maintenance strategy for minimizing roughness-related pavement damage

Abstract: The Michigan Department of Transportation (MDOT) uses several measures of pavement performance in managing its pavement network, including the distress index (DI) and the ride quality index (RQI). Currently, decisions on when and where to take rehabilitation or preventive maintenance action are mainly based on the DI. The RQI is used only in a passive or reactive fashion: When DI reaches the threshold for poor ride quality, a decision to rehabilitate the road is made. MDOT is currently funding a research study to develop RQI thresholds for each pavement type (rigid, flexible, or composite) aimed at retarding pavement damage caused by roughness-generated, dynamic (impact) loading. These thresholds correspond to the RQI value at which pavement damage is accelerated by high dynamic loads. Given these new RQI thresholds, extending the service life of the pavement by taking preventive maintenance action in the form of smoothing of the pavement surface (by way of milling, grinding, or adding a thin overlay) bec...

Simple dynamic backcalculation procedure for falling weight deflectometer testing of rigid pavements

Abstract: A simple and direct method for backcalculation of the dynamic subgrade stiffness and damping coefficients from falling weight deflectometer (FWD) deflection basins is presented. The method can also be used to detect a stiff layer underneath the pavement system. The method consists first of decomposition of the transient deflection signal of each sensor into a series of harmonic motions by the fast Fourier transform algorithm. Then, for each frequency of interest, the real and imaginary components of the displaced volume underneath the slab are calculated from the complex deflection basin. The dynamic force-displacement relationship is decomposed into real and imaginary parts, leading to a simple system of equations that can easily be solved for the coefficient of the subgrade reaction (k) and the radiation damping coefficient (c). The method was verified by using FWD test data from six different sites in Michigan. In addition, the backcalculated k-values were compared with those obtained by the AASHTO-rec...

Development of Roughness Thresholds for Preventive Maintenance Using PMS Data from In-Service Pavements

Abstract: In this paper, 462 pavement sections from thirty-seven projects in Michigan were analyzed to investigate the interaction between pavement surface roughness and distress. The main hypothesis of this research is that an increase in roughness leads to higher dynamic axle loads, which in turn can lead to a tangible acceleration in pavement distress. If this relationship is established, then it will be possible to plan a preventive maintenance (PM) action to smooth the pavement surface. Such a PM action is bound to extend the service life of the pavement by several years. The objectives of this research were to: (1) test the above hypothesis; (2) develop a roughness threshold; and (3) determine the optimal timing of the PM action. The selected projects include thirteen rigid, fifteen flexible and nine composite pavements. The Ride Quality Index (RQI) and Distress Index (DI) were used as measures of surface roughness and distress, respectively. The analysis showed good relationships between dynamic load-related distress and roughness for rigid and composite pavements (R² = 0.739 and 0.624); however for flexible pavements there was significant scatter (R² = 0.375). A logistic function was used to fit the data. Roughness thresholds were determined as the RQI-values corresponding to peak acceleration in distress. These were determined to be 64 for rigid pavements and 51 for composite pavements. A model for selecting the optimal timing of PM action was developed based on the reliability concept. The model uses actual RQI growth rates from 1382 rigid-pavement sections.

Development of roughness thresholds for preventive maintenance of pavements based on dynamic loading considerations

Abstract: All road surfaces are inherently rough even when new, and they become increasingly rougher with age depending on pavement type, traffic volume, and environment. This process is the result of the interaction between vehicles and pavements. Accordingly, it is reasonable to assume that there is a threshold value in roughness where dynamic load increases sharply leading to acceleration in pavement damage. If this threshold value exists, it could be a useful preventive maintenance (PM) tool, whereby a PM action, such as smoothening the pavement surface, is taken to extend the service life of a given pavement for several years. In this paper, the relationship between dynamic axle load and road roughness was developed to determine such roughness threshold. For this analysis, actual surface profiles of 335 in-service pavement sections from 37 projects in Michigan were used to generate dynamic axle load using the TruckSim truck simulation program. Results of this analysis shows good correlation between dynamic axle load and roughness (R-sq. of 0.85-0.95). Based on these relationships, roughness threshold values were determined for rigid, flexible and composite pavements. Rigid pavements have higher threshold than flexible and composite pavements. These results agree with those obtained using MDOT PMS distress data.

Dynamic analysis of rigid pavements with different subgrade support models

Abstract: The accuracy of any slab-on-grade model is strongly dependent on the foundation model used. Therefore, using an accurate structural model for the concrete slab system does not guarantee an accurate response for the slab-subgrade system. This means that characterizing the subgrade support correctly is essential in order to obtain accurate predictions of the rigid pavement response. Most existing finite-element programs for rigid pavements use the Winkler model as the primary model for subgrade characterization. This paper presents the development of an expanded version of the DYNASLAB computer program with the addition of a frequency-dependent Winkler foundation and a layered foundation model. Using the DYNASLAB program, several dynamic analyses were conducted to compare the results from the two foundation models.