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Improved criteria for the material properties and mix proportions of concrete slabs to enhance the performance of concrete pavements at Incheon international airport (IA) in the Republic of Korea are suggested. Gimpo IA and Gimhae IA were selected for comparison with Incheon IA based on their facility status and annual flight processing capability. After Incheon IA, Gimpo IA and Gimhae IA have the second and third largest annual numbers of flights per unit area of runway, respectively. Criteria for aggregate and mix proportions were chosen for improvement because of durability cracks (the major form of pavement distress at Incheon IA) due to the poor quality of aggregates used and repeated freeze–thaw cycles. Compared with the other airports, the mix specifications of the concrete slab at Incheon IA showed lower contents of cement and liquid admixture, a higher abrasion rate of coarse aggregate and a larger content of fines in the aggregate. Improved criteria were established based on a comparison of results. Concrete specimens were fabricated using the improved criteria and the performance of the concrete pavement was evaluated by testing the air content and freeze–thaw resistance of 12 mixes with different contents of cement, liquid admixture and fines in the aggregate.

In this study, cracking patterns and widths were analytically investigated in a continuously reinforced bonded concrete overlay (CRBCO), as they developed due to temperature change and drying shrinkage, as the environmental load for the sustainable management of deteriorated concrete pavements. The parameters of the concrete damaged plasticity (CDP) model used for the nonlinear finite element analysis (FEA) of the continuously reinforced concrete pavement were determined through comparison of the FEA results with the field crack survey results so as to be used in the nonlinear FEA of the CRBCO pavement. The total temperature change, which combines the actual temperature change with the temperature change converted from the drying shrinkage, considering stress relaxation, was adopted in the FEA as the environmental load applied to the CRBCO pavement. The locations and movements of the reflection and transverse cracks in CRBCO were investigated via FEA. The reflection cracks occurred in the overlay at all of the joints of the existing pavement. Only one secondary crack, with a width that was 5–6 times narrower than that of the reflection cracks, occurred between adjacent reflection cracks under various conditions. Thus, the crack width of the CRBCO was predominantly affected by joint movement in the existing pavement. In addition, the crack widths predicted by the CDP model were narrower than those predicted using the elastic model by approximately 10%. Therefore, crack movement in a CRBCO pavement can be reasonably predicted by the CDP model.

The pavement condition index (PCI) is a tool for evaluating pavement performance and is based on the type and severity of surface distress. It is used to determine maintenance times, methods and location priorities. Most previous PCI prediction models have considered only pavement age or traffic volume as a variable, without consideration of other factors that affect pavement distress. In this study, data from 12 airports were analysed using reports published from 1994 to 2013. The airport pavements were divided into homogeneous zones according to their function and structure. For improved management of concrete airport pavements, a non-linear PCI model was developed for the homogeneous zones and tornado diagrams were used to analyse the sensitivity of the PCI according to the independent variables of the model. The results showed that the developed model can predict the PCI of homogeneous zones of concrete airport pavements more reasonably by considering various factors that affect pavement distress.

When spalling occurs at a concrete pavement joint, partial depth repair (PDR) is implemented by removing the damaged part of a slab and filling the space with repair materials. However, re-repair is frequently also required because additional distress develops at the boundary of the repaired area due to improper PDR size in addition to poor quality of materials and construction methods. For the sustainability of pavement structures, it is necessary to study the PDR size based on the mechanical theory. Therefore, in this study, the PDR size for spalling was suggested based on the results of laboratory and field tests conducted using the impact echo (IE) method. The dynamic modulus estimated in the laboratory using the IE and forced resonance methods were compared for concrete specimens subjected to repetitive freeze–thaw cycles. In addition, the correlations of the dynamic modulus estimated by the methods with the compressive strength and absorption coefficient were analyzed. As a result, the IE method, for which vibration could be estimated on the same side of the specimen where impaction was applied, was selected for use on the pavement surface. Furthermore, the short-time Fourier transform technique was used instead of the fast Fourier transform, which has been commonly used for nondestructive methods, to minimize the noise in the field and, consequently, to estimate the dynamic modulus more accurately. The dynamic modulus was estimated according to the distance from the spalling end using the IE method at the Korea Expressway Corporation test road to identify the damaged range in the slab based on the severity of spalling. The dynamic modulus, compressive strength, and absorption coefficient tests were conducted in the laboratory for specimens cored from the concrete slab where the field test was performed. Finally, the PDR size was suggested according to the severity of spalling based on the damaged range in the slab, as determined by the field test and laboratory test results.

This study investigated the distress conditions of test sections of concrete pavement that have been used for more than the design life of 20 years. The study was performed using data from a highwa...

The repair method for pavements should be selected considering the structural capacity of sublayers, in addition to the conditions observed at the pavement surface, to reduce the recurrence of distress in the repaired area. However, it is practically impossible to include the structural capacity of sublayers in the database of the pavement management system (PMS) because this would require additional tests in all expressway sections. Therefore, an artificial neural network model for predicting the indirect tensile strength (ITS) of the intermediate layer of all asphalt pavement sections in an expressway was developed in this study, taking the international roughness index, rut depth, surface distress, and equivalent single axle load as independent variables. The ITS of specimens cored from target sections was measured in the laboratory, and the PMS data for the target sections were collected. The ITS was predicted by conducting a feedforward process prior to the training step. When the error between the predicted and measured ITSs exceeded the allowable error, the model was repetitively trained using the resilient backpropagation method until the error fell within the acceptable boundary. The model was validated by analyzing the correlations between the ITSs predicted from the data of the training and test sets. Finally, the model was complemented by the corresponding minimum and maximum values of the ITS measured at the target section.

The design of overlay pavement in Korea, using the American empirical method, does not consider the unique Korean climate, pavement material, and traffic conditions. Therefore, in this study, a mechanistic–empirical design catalog for bonded concrete overlays (BCO) that are appropriate for Korean pavement conditions was developed. First, the thickness of the new pavement slab was determined through the Korean pavement design method, which uses a mechanistic–empirical design program according to the traffic volume of the region with the worst climatic conditions in Korea. Then, finite element analysis models of new jointed concrete and BCO pavements were developed to determine the BCO thickness by adjusting it until the stress–strength ratio of an existing slab of BCO pavement was equal to that of a new concrete pavement slab. By repeating this procedure, a design catalog was developed for the sustainable management of concrete pavement according to the traffic volume, elastic modulus, and thickness of the existing slab after milling. The appropriateness of the BCO thickness predicted by the design catalog was verified by comparing it with that predicted by other design methods.

In this study, strain gages were installed at the centre, edge, and corner of concrete pavement slabs of Incheon International Airport based on the slab depth, whereas thermometers were positioned ...

A method for designing an airport concrete pavement (ACP) that can withstand environmental loads as well as traffic loads is presented. Information on ACPs for which double dual tandem landing gears were used for design aircrafts was collected and the stresses induced on the slabs when environmental loads and traffic loads were simultaneously applied were predicted with the finite-element analysis program FeaFaa. In addition, a maximum tensile stress regression model of ACP slabs was developed using the statistical analysis program SPSS. When environmental and traffic loads were simultaneously applied, the maximum tensile stress obtained with the finite-element method was significantly different from that obtained using Westergaard's equation of edge loading only in traffic loads. Therefore, the fatigue model in the US Federal Aviation Administration's AC 150/5320-6E design method was corrected to be appropriate for this study. Using the stress regression model developed in this study and the corrected fatigue model, the thickness and joint spacing of existing ACP slabs were redesigned and compared with existing airport pavements. Previously, only the thickness of a slab was designed and the joint spacing was empirically determined. However, from the results of this study, a slab's thickness and joint spacing can be designed mechanistically.

The objective of this study was to verify the effect of fiber grid reinforcement on the long-term performance of asphalt overlay pavements by performing field investigation, laboratory test, and finite element analysis. Crack, rutting, roughness, and other miscellaneous distresses of fiber-grid-reinforced overlay sections and ordinary overlay sections were compared. Pavement conditions of fiber grid overlay sections before and after the overlay were also compared. Cores were obtained from the fiber-grid-reinforced and ordinary sections to measure bonding shear strength between the intermediate and overlay layers. Fracture energy, displacement after yield, and shear stiffness of the cores were also obtained by analyzing the test results. Finite element analysis was performed by using the test results to validate the effect of the fiber grid reinforcement on the long-term performance of asphalt overlay pavements. Rutting and fatigue cracking were predicted for three cases: 1) fiber grid was not used; 2) glass fiber grid was used; and 3) carbon fiber grid was used. The cracking ratio of fiber-grid-reinforced sections was much smaller than that of ordinary sections. The results of field investigation, laboratory test, and finite element analysis showed that the fiber grid reinforcement improved the long-term performance of asphalt overlay pavements. Keywords: Asphalt pavement, Fiber grid reinforcement, Overlay pavement, Finite element analysis, Bonding shear strength

In this study, a remodeling index (RMI) prediction model was developed to determine and prioritize target sections for large-scale repair works of deteriorated expressway concrete pavements in Korea. The unit sections that represent the distribution of the structural condition of entire analyzed sections were selected for jointed concrete pavement (JCP) and continuously reinforced concrete pavement (CRCP), and the RMI of the representative sections was rated by a panel of members. The model that predicts the RMI of aging JCP and CRCP after a few years hereafter was developed using the RMI obtained by the panel rating as a dependent variable, and the pavement conditions, pavement age, traffic volume, and weather conditions of the corresponding sections were considered as independent variables. The RMI sensitivity was analyzed according to each independent variable, and the appropriateness of the RMI prediction model was verified by comparing the RMIs in 2016 predicted in 2014 (future RMI in two years) with those in 2016 predicted in 2016 (present RMI). The entire aging expressway concrete-pavement sections were divided into homogeneous sections of suitable lengths for remodeling works by applying the RMI prediction model to each unit section. The priority for remodeling works was determined among the highly ranked homogeneous sections using the predicted RMI. The actual pavement conditions of a target section in which the remodeling priority had the highest rank were verified.

For the sustainable management of pavements, predicting the condition of the pavement structure using a consistent and accurate method is necessary. The intermediate layer situated immediately below the surface layer has the greatest effect on the condition of the pavement structure. As a result, to accurately predict the condition of a pavement structure, the mechanistic properties of the intermediate layer are very important. Fracture toughness (FT)—a mechanistic property of the intermediate layer—is an important factor in predicting the distress that develops on the pavement surface. However, measuring FT consistently is practically impossible by coring asphalt pavement over the entire pavement section. Therefore, an artificial neural network (ANN) model—developed by using pavement surface conditions and traffic volume—can predict the FT of the intermediate layer of expressway asphalt pavements. Several ANN models have been developed by applying various optimizers, ANN structures, and preprocessing methods. The optimal model was selected by analyzing the predictive performance, error stability, and distribution of the developed models. The final selected model showed small stable errors, and the distributions of the predicted and measured FTs were similar. Furthermore, FT limits were set with outliers. Future asphalt pavement conditions can be predicted throughout the expressway network by using the proposed model without coring samples.

In this study, a method to identify the representative section (RS) which can represent the pavement conditions of entire aged concrete expressway pavement (CEP) sections for the large-scale remodeling project, was developed based on pavement management system (PMS) data and an optimized approach. To fulfill this objective, various PMS data sets on the target section (TS) of concrete expressway pavement that exceeded 20 years of design life were collected with 100m intervals. Then, the first version of the optimized 100 RSs, which was a reasonable amount of data for analysis of aged CEP condition, was selected based on the different severity levels of surface damage and international roughness index (IRI) data. Secondly, another crucial PMS factor: the alkali-silica reaction (ASR) severity level, was considered and substituted partially in the previously selected 100 RSs to provide additional and reasonable representative characteristics. Finally, the characteristics of the RS were evaluated and verified by considering whether the various distress size rankings of the RS were uniformly distributed within the entire distress size ranking of the total jointed concrete pavement (JCP) and continuously reinforced concrete pavement (CRCP) TS. It was found that the RS selection approach and corresponding criteria proposed in this study, based on the optimization approach, could be successfully used to determine the future large-scale remodeling priority of the old concrete expressway pavements.

In this study, the feasibility of introducing calcite-forming bacteria into concrete pavements to improve their mechanical performance was investigated. Lysinibacillus sphaericus WJ-8, which was isolated in a previous study and is capable of exhibiting high urease activity and calcite production, was used. When analyzed via scanning electron microscopy (SEM) and X-ray diffraction, WJ-8 showed a significant amount of calcite precipitation. The compressive strength of cement mortar mixed with WJ-8 cells and nutrient medium (urea with calcium lactate) increased by 10% compared with that of the controls. Energy dispersive x-ray spectroscopy analyses confirmed that the increase in strength was due to the calcite formed by the WJ-8 cells.

This paper presents a methodology to estimate the stress-strain relationship of an unbound aggregate base using linear viscoelastic theory. Current Mechanistic-Empirical (ME) pavement design procedure adopts the resilient modulus concept to explain the behavior of granular materials for flexible pavement design. The resilient modulus is a stress dependent material property of granular materials that is different from strength. Although California Bearing Ratio (CBR) test results (i.e., stress and strain) can be used to estimate the strength of a granular material, it is not possible to estimate the resilient modulus directly. Therefore, it is necessary to estimate stress along with strain changes. The convolution integral enables the stress to be estimated from the given strain changes only if the relaxation modulus is measured. Aggregate specimens prepared from two different sources in Georgia were subjected to the relaxation modulus test. From the test data, the time-dependent stress due to a known strain rate was computed as a convolution integral of the strain. The computed stress-strain relationship was compared with that from the resilient modulus (MR) test. The results indicate that the stress-strain relationships from the MR test and the convolution integral are similar with nearly the same slopes when horizontal stress is assumed to be approximately 45% of vertical stress. This observation supports the use of the proposed methodology by state highway agencies to validate the MR test results for quality control and quality assurance of aggregate base material selection for pavement design and construction.

This study examined the pavement distress data obtained from the field as well as the effects of the soil cover depth, joint position and reinforced slab length on the behaviour of concrete pavement using the finite element method. An ultimate strength model with a similarity of 1/2 was designed and constructed. Finite element analysis incorporating an implicit direct numerical integration scheme was conducted to obtain an optimal design for the pavement structure above a box culvert. An accelerated pavement test was conducted for validation, in which a realistic traffic load was imposed on the pavement model constructed in the laboratory. The strain histories were measured at each section and compared with those of numerical analysis. The optimal joint position and reinforced slab length that can minimise the damage to the pavement structure above a box culvert were also determined.