Mustafa Karaşahin

Investigation of fatigue behaviour of asphalt concrete pavements with fuzzy-logic approach

Fatigue life and deformation are intimately related phenomena and a model involving a relationship between them can best be derived by methods that explicitly take vagueness into account. In this paper, the theory of fuzzy sets, especially fuzzy modeling, is employed to represent fatigue life and deformation relations as a set of fuzzy rules. A fuzzy logic algorithm has been devised for estimating the fatigue life from deformation measurements. The main advantage of fuzzy models is their ability to describe the knowledge in a descriptive human-like manner in the form of simple rules using linguistic variables only. In this manner the classical power relationship between the fatigue life and deformation variable can be replaced by a set of fuzzy rule bases. The fuzzy approach is applied for test data obtained in Isparta city, Turkey.

Performance model for asphalt concrete pavement based on the fuzzy logic approach

AbstractAccurate pavement performance estimation is very important for the managing and maintaining of surface transportation infrastructure. In the present study, a new model for the prediction of present and future performance of flexible pavements is developed using the fuzzy logic approach. The database of the model is able to use numerical measurements and also linguistic statements. Many models developed in the literature neglect the parameters that have little bearing on performance. However, it is a well known fact that these parameters do have an effect on performance to some degree. Different parameters were considered in the model as accepted by the authorities, and as having little bearing on performance. For each parameter, a certain weight was appointed, and the parameters that affected performance were assigned greater weights while the others were assigned smaller weights. As a result, the current model in the fuzzy logic approach is more flexible than the current Pavement Serviceability I...

Chip Seal Adhesion Performance with Modified Binder in Cold Climates: Experimental Investigation

The purpose of this study was to evaluate chip seal performance with neat and polymer-modified asphalt cement. These chip seals were fabricated with various aggregate combinations to emphasize aggregate retention in cold climates with the accelerated chip seal simulation device. Three aggregate types at low temperatures were used to compare the aggregate retention performances of neat versus modified asphalt cement. A major finding of this research was that polymer modification of neat asphalt cement improved aggregate retention performance. In addition, results showed that a decrease in temperature causes increasing aggregate loss.

Investigation of ride comfort limits on urban asphalt concrete pavements

Abstract It is well known that pavement distress negatively affects the drivers and passengers of vehicles. Many studies report that foremost among these negative effects is the vibrations that form within the vehicle. Ride comfort depends on the human response to vibration and vehicle response to the road. The goal of this study was to investigate the effect of pavement condition index on ride comfort and to determine the threshold comfort limits for passenger cars on urban asphalt concrete pavements. The pavement condition index (PCI) was determined for pavement sections subject to different surface distress using the PAVER system. Ride (driving) speeds of 20, 30, 40 and 50 km/h were assessed on the same pavement sections to measure vibrational effects inside the vehicle and on the passenger seat. These measurements were then evaluated using the ISO 2631-1 standard in order to determine the a wz values. Using the logistic regression technique, predictive model that took into account linguistic concepts for estimating ride comfort levels based on PCI values was developed. With the aid of this mathematical model, comfort threshold values were determined for each driving speed within an interval of 0–100 PCI. The study results indicated that increasing driving speed was generally associated with higher PCI comfort thresholds.

Backcalculation of pavement layer thickness using data mining

Pavement deflection data are often used to evaluate a pavement’s structural condition nondestructively. Pavement layers are important parameters in view of bearing capacity. Pavement layer thickness may be known from the design project or site investigation. At the same time, using backcalculation analysis, flexible pavement layer thicknesses together with in situ material properties can also be backcalculated from the measured field data through appropriate analysis techniques. Data mining (DM) process has not been used as a backcalculation tool before. In this study, DM process is used in backcalculating the pavement layer thickness from deflections measured on the surface of the flexible pavements. Experimental deflection data groups from NDT are used to show the capability of the DM process in backcalculating the pavement layer thickness and compared each other. Performing the study, modeling with Kstar method gives fine results with respect to other DM modeling techniques. Backcalculation of pavement layer thickness using DM process has been carried out for the first time.

Prediction of the marshall stability of reinforced asphalt concrete with steel fiber using fuzzy logic

In this study, Marshall Stability MS of steel fiber reinforced asphalt concrete has been predicted using steel fiber rate 0%, 0.25%, 0.50%, 0.75%, 1.0%, 1.5%, 2.0% and 2.5%, bitumen content 5%, 5.5% and 6.0% and unit weights 2,465--2,515 gr/cm3 by Fuzzy Logic FL. Results have shown that developed FL model has a strong potential for predicting the MS of asphalt concrete without performing any experimental studies.

Investigation of chip seal performance under cold climate conditions

Abstract The chip seal is an economical type of asphalt pavement that was constructed for single- or double-layer aggregate-bitumen. Chip seals are applied to prime-sealed granular pavement surfaces in order to waterproof the surfaces of sub-layers, produce smooth and high-skid-resistance surfaces for vehicles and protect pavements against the detrimental effects of traffic and climate. Unlike bituminous hot mixtures, numerous factors can affect the performance of chip seal. One of the most important factors is climate. The aim of this study is to determine the performance variation of chip-sealed pavements under cold climate conditions. Three different chip-sealed roads in Erzurum, which is in one of the coldest regions of Turkey, were examined with non-destructive tests. Sand-patch, British pendulum, light weight deflectometer and dynamic cone penetrometer tests were performed. Chip-sealed pavements’ densities and surface temperature variation and base courses layer’s thicknesses were also measured, and deteriorations were observed and scored by researchers. Test results showed that flushing due to the higher temperatures during the short summer season, deficiency of the base course’s bearing capacity and moisture in the base course are the most important causes of deterioration in this type of chip seal, and the chip seals in this region must be resealed in <1 year because of the premature deterioration.

Effect of Aggregate Embedment On Chip Seal Retention Performance

The aim of this study is to evaluate chip seal retention performance with two type of aggregate depending on the various embedment depths using Accelerated Chip Seal Simulation Device (HSKSC). To simulate the worst condition in field for chip seal in respect to aggregate retention performance, the water was poured on the specimens and performance tests were conducted in water. Major findings of this research include that increasing the aggregate embedment significantly reduces the aggregate loss. However, it correspondingly reduced the macrotexture value of the chip seal which is very important parameter for chip seal service life.

Monitoring The Condition of Surfacing Seals With Nondestructive Tests at Field

Surfacing seal is an asphalt pavement type preferred because of its simplicity of application and economic viability. It enables waterproof surfaces for sub-layers and creates smooth and high skid resistance for vehicles. Therefore, surfacing seals constructed on unbound base are widely used such as New Zealand, Australia and South Africa. However the performance of surfacing seals can be affected by a number of factors. If these factors are not considered, they will need to be reconstructed after a very short period. In this study, performances of surfacing seals under heavy traffic were observed for 2 years, and routine tests were performed to determine the surfacing seal’s performance in relation to traffic and climate and to determine the kind of deteriorations which occurred. In this study variety of test such as sand-patch, British pendulum, density measurement with electromagnetic method, measuring surface temperature with thermal camera, light weight deflectometer, dynamic cone penetration test and layer thickness measurement were performed with ground penetrating radar technique. The results of the study show that loss of macro texture, and raveling and flushing are the most common types of deterioration especially at road sections with longitudinal slope. Furthermore, skid numbers decrease during the rainy seasons when the bearing capacity of layers also decreases, the trend of raveling deterioration decreases at roads with high traffic volume and average maximum surface temperature. However, it was determined that trend of flushing deterioration increase.

Asphalt concrete stability estimation from non-destructive test methods with artificial neural networks

The core drilling method has often been used to determine the current status of asphalt concretes. However, this method is destructive so causes damage to the asphalt concretes. In addition, this method causes localized points of weakness in the asphalt concretes and is time consuming. In recent years, non-destructive testing methods have been used for pavement thickness estimation, determination of elasticity modulus, and density and moisture measurements. In this study, the above-mentioned non-destructive and destructive tests with data obtained by applying the Marshall stability to the same asphalt concretes were estimated using the artificial neural networks approach.