Full-scale Accelerated Pavement Testing Research Articles

An exploratory framework for accelerated airport pavement testing using the geotechnical centrifuge

ABSTRACT Full-scale Accelerated Pavement testing (APT) has been regarded as an essential step to bridge the gap between research and practice for pavement design because it can fully mimic a large number of heavy wheel loading on pavements. Despite being able to test pavements in an accelerated manner compared to Long-term Performance Monitoring (LTPM), conducting one full-scale APT experiment is still demanding in terms of monetary cost, space, time, etc., and the accessibility to APT facilities is only available in a few countries nowadays. In this study, an exploratory APT study with a down-scaled pavement model in a high-g environment created by geotechnical centrifuge was performed with up to half a million simulated aircraft load repetitions. Through this test, it was proved that the centrifuge APT can reproduce the full-scale airfield pavement responses, including rutting, cracking, material fatigue, etc. The transient and permanent deflection of the pavement surface, variations in stress and strain states within the pavement structure over its lifespan can be well captured for analysis. This framework of centrifuge APT provides a new methodology for pavement testing and can significantly save the current cost and time of full-scale APT.

Permanent Deformation Monitoring and Remaining Life Prediction of Asphalt Pavement Combining Full-Scale Accelerated Pavement Testing and FEM

Permanent deformation (rutting) is one of the typical failure modes of asphalt pavement with a semirigid base in high-temperature areas. To address issues of pavement structure deformation and remaining life prediction, a method of combining accelerated pavement testing and finite element (FE) simulation was proposed. A modified Burgers model considering creep parameter damage was obtained using strain monitoring data and laboratory test values, which was performed in the FE model to analyze rutting development. The results showed that high temperature and heavy axle loads greatly influenced rutting development: the tested road was loaded 360,000 times at high temperature, contributing 50% to accumulated rutting; rutting increased by 90.7% under the condition of 50% overload under high-temperature seasons from the simulated results. Then, the ratio of the bulge area to the depression area (KR) was proposed to define the rutting deformation mechanism. The KR analysis results illustrated that rutting development was a transition process from compaction rutting to flow rutting. Finally, the relationship between the action times of axle load in the tested and in-service roads was established based on the rutting equivalence principle. When the action times of axle load reach approximately 25 million times (insufficient remaining life) for the investigated Hu-Ning highway, necessary maintenance measures should be taken to treat rutting deformation.

Analysis of Dynamic Load Characteristics of Accelerated Pavement Testing Equipment Based on Virtual Prototype Model

The purpose of this paper is to study the actual dynamic load characteristics of a full-scale Accelerated Pavement Test (APT) device called Natural Environment-Automatically Loaded Track (NE-ALT) during its operation. The NEALT uses hydraulic and support reaction forces to apply axle loads, which are somewhat different from real trucks. Therefore, in order to ensure the accuracy of the loading parameters of the device, it is necessary to analyze the dynamic load characteristics of the device during operation. In this paper, a virtual prototype model of the device was established, and the important parameters, including vehicle speed and axle load, were set. The dynamic axle load, dynamic load coefficient, and influential factors of the NE-ALT were analyzed using the model at different speeds, hydraulic pressures, and road roughness. The results have shown that the dynamic axle load accuracy was most affected by speed, followed by road roughness, and then hydraulic cylinder pressure. Compared with the real truck, its dynamic load stability was better than the real truck due to the restriction of the guide rail in the acceleration loading system and the method of hydraulic loading, and the larger the load, the more stable the load, which was different from the real truck. Therefore, in the design of accelerated pavement loading experiments, the dynamic axle load characteristics of equipment need to be considered. The results of this study can provide guidance for the further improvement and application of the NE-ALT.

Testing and Evaluating the High-Temperature Rutting Development of Steel Deck Asphalt Pavement Using Full-Scale Accelerated Pavement Testing

Abstract Steel deck asphalt pavement (SDAP) significantly differs from traditional pavement in terms of substructure and service environment, so its rutting development is unique. Indoor tests and the finite element method cannot competently simulate service environment and accurately show the rutting development of SDAP. In this study, the rutting development of SDAP was evaluated using full-scale accelerated pavement testing (APT). First, a steel bridge with two different pavement structures was constructed and a heating system was installed to keep the high temperature. Second, three indoor tests—dynamic stability (DS), hardness number (HN), and indentation—were conducted to quantify the rutting resistance of pavement materials, and the Mobile Load Simulator 66 executed the APT. The indoor results showed that DS and HN correlated well with the APT rut depth. With the increase of APT loading cycles, the rutting depth, the ratio of sag area to uplift area, and the ratio of sag area to full areas were increased. Meanwhile, the rutting depth changing speed and the ratio of uplift area to full areas declined with the loading. A rutting depth prediction model (RPM) was proposed based on the number of loading cycles and the initial rutting depth at 5,000 loading cycles. The RPM applied well to the previous study’s test data, indicating that rut development can be evaluated by its early status.

Validation of a Novel Sensing Approach for Continuous Pavement Monitoring Using Full-Scale APT Testing

The objective of this paper is to present a novel approach for the continuous monitoring of pavement condition through the use of combined piezoelectric sensing and novel condition-based interpretation methods. The performance of the developed approach is validated for the detection of bottom-up fatigue cracking through full-scale accelerated pavement testing (APT). The innovative piezoelectric sensors are installed at the bottom of a thin 102 mm (4 in.) asphalt layer. The structure is then loaded until failure (up to 1 million loading cycles in this study). The condition-based approach, used in this work, does not rely on stain measurements and allows users to bypass the need for any structural or finite-element models. Instead, the data compression approach relies on variations in strain energy harvested by smart sensors to track changes in material and structural conditions. Falling weight deflectometer (FWD) measurements and visual inspections were used to validate the observations from the sensing system. The results in this paper present a first large-scale validation in pavement structures for a piezopowered sensing system combined with a new response-only based approach for data reduction and interpretation. The proposed data analysis method has demonstrated a very early detection capability compared to classical inspection methods, which unveils a huge potential for improved pavement monitoring.

Using Bender Elements to Investigate the Effect of a Multi-axial Geogrid on Aggregate Layer Stiffness

Geogrid inclusion in low-volume road applications has been shown to improve rutting performance. Although rutting performance and traditional instrumentation response data provide meaningful insights into pavement behavior, they do not provide a direct measurement of material behavior near the geogrid. Recently, the University of Illinois at Urbana-Champaign has developed field-deployable shear-wave transducers, that is, bender elements to measure the localized stiffness enhancement attributed to geogrid inclusion in unbound aggregate layers, which have been verified in laboratory and limited field applications. Bender element sensors were installed in a full-scale accelerated pavement test experiment at the U.S. Army Engineer Research and Development Center that included a recently developed multi-axial hexagonal geogrid. The sensors were installed directly on the geogrid and 10 cm above the geogrid in the unbound aggregate layer to measure the geogrid zone of influence. The test item was trafficked with a dual-wheel truck gear, and bender element measurements were made at select intervals throughout traffic application. To estimate the unbound aggregate moduli, the data were analyzed using two techniques: first arrival time and peak-to-peak arrival time. The bender element sensors were found to be sufficiently robust to survive installation, construction, and trafficking. Calculated modulus values 10 cm above the geogrid were found to be higher than those directly on the geogrid, which was an unexpected finding. However, a forensic investigation revealed moisture and fines migration into the bottom of the unbound aggregate layer, which could have dampened the shear-wave signal, resulting in lower calculated modulus values.

Calibration of Inverted Asphalt Pavement Rut Prediction Model, Based on Full-Scale Accelerated Pavement Testing.

This study investigates the establishment and calibration method of the rut depth (RD) prediction model of inverted asphalt pavements (IAPs), based on full-scale accelerated pavement testing (APT), which facilitates the accurate and reliable design or maintenance of IAPs. A power function is adopted for the prediction model construction of the rut progression before the failure stage, based on the typical permanent deformation progression curve of flexible pavements. The APT loading history is divided into units, according to the difference in physical conditions, providing the basis for a cumulative RD analysis and model calibration. The nonlinear incremental recursive (IR) principle is applied in the RD analysis to consider the influence of the nonlinear material property, performance deterioration, and loading history on the RD development. Further, the rut shift function relating prediction models obtained from laboratory tests and full-scale APT is established to introduce the APT data in the calibration process. Accordingly, the mechanistic-empirical RD prediction model calibration method, based on APT and the IR principle, is proposed and applied in a case study of a IAP RD prediction model calibration. Four 3.5 m × 4 m IAP test sections S1-S4 are constructed and instrumented and 700,000- and 900,000-wheel loads are applied on test sections S1-S2 and S3-S4, respectively, using the heavy vehicle simulator. The test data from the different APT load units are utilized for the model calibration, and the resultant prediction errors range from -2.16 mm to 1.18 mm. The calibrated model can also be used for the RD prediction of IAPs with other design schemes, by updating the corresponding material-related coefficients and the finite element model, which is essential for the design and maintenance of IAPs. The proposed calibration method could be a useful reference for the establishment of flexible pavement performance prediction models.

Reduction of carbon footprint of roads construction thanks to the Pavement Optimisation with hexagonal geogrids

There is a growing demand on reduction of greenhouse gases emission from all branches of industry. Roads construction is responsible for a substantial part of building industry carbon footprint. One of the ways to reduce its carbon footprint is the use of Pavement Optimisation (PO) with hexagonal geogrids technology. This technology utilizes the phenomenon of aggregate stabilisation by interlock within apertures of geogrid. When aggregate is placed and compacted on a layer of geogrid, a geogrid/aggregate composite – called Mechanically Stabilised Layer (MSL) - is created. Stiff geogrid ribs resist particle movement reducing layer deformation, which increases its stiffness. Increased stiffness of aggregate can be utilized in design, and has a substantial influence on pavement life. This provides the possibility to reduce the thickness of a pavement, including thickness of asphalt. Thinner pavement will require less materials, workforce, time and energy. It will be cheaper, and its construction will result in lesser emission of CO2. This paper presents the overview of Pavement Optimisation technology and results of full scale accelerated pavement tests confirming the influence of hexagonal geogrids. Case studies of projects with optimised pavements and calculations of carbon footprint savings achieved thanks to the use of PO are presented.

Development of a Fatigue Damage Model for Roller Compacted Concrete Pavement Based on In Situ Saw-Cut Beams and Accelerated Pavement Performance

As a durable, economical, and low-maintenance concrete material, roller compacted concrete (RCC) is steadily becoming the preferred choice for many pavement applications. However, the fatigue models in current pavement thickness design procedures have generally been found to over-predict the RCC pavement fatigue damage under in situ heavy truck loading. In this study, a comprehensive beam fatigue test experiment was performed using field saw-cut RCC slab samples from two full-scale accelerated pavement testing (APT) sections to investigate the fatigue behavior of in situ RCC pavements. This is the first research study to investigate the fatigue behavior of field RCC beam samples prepared and constructed with a high-density asphalt-type paver and a vibratory roller. The results indicate that a well-compacted RCC pavement can achieve higher flexural strength and exhibit better fatigue life than conventional concrete pavement. Based on the beam fatigue test results and in situ fatigue performance of APT test sections, an RCC fatigue-life model was developed, providing a more accurate solution for estimating the allowable number of load repetitions of RCC pavements subjected to vehicular fatigue loading. This model could be used in RCC thickness design procedures to determine the optimum RCC design thickness and long-term fatigue performance of RCC pavements for roadway application.

Towards a sustainable monitoring: A self-powered smart transportation infrastructure skin

Sustainable monitoring of traffic using clean energy supply has always been a significant problem for engineers. In this study, we proposed a self-powered smart transportation infrastructure skin (SSTIS) as an innovative and bionic system for the traffic classification of a smart city. This system incorporated the self-powered flexible sensors with net-zero power consumption based on the Triboelectric Nanogenerator (TENG) and an intelligent analysis system based on artificial intelligence (AI). The feasibility of the SSTIS was tested using the full-scale accelerated pavement tests (APT) and the long-short term memory (LSTM) deep learning model with a vehicle axle load classification accuracy up to 89.06%. This robust SSTIS was later tested on highway and collected around 869,600 pieces of signals data. The generative adversarial networks (GAN) WGAN-GP (Wasserstein GAN - Gradient Penalty) was used for data augmentation, due to the imbalanced data of different vehicle types in actual traffic. The overall accuracy for on-road vehicle type classification improved to 81.06% using the convolutional neural network ResNet. Finally, we developed a mobile traffic signal information monitoring system based on cloud platform and Android framework, which enabled engineers to obtain the vehicle axle-load information mobilely. This study is the emerging design and engineering application of the self-powered flexible sensors for smart traffic monitoring, which provides a significant advance for intelligent transportation and smart cities in future.

Airport Pavement Stiffness Monitoring and Assessment of Mechanical Stabilization using Bender Element Field Sensor

The bender element (BE) field sensor is a newly developed embedded pavement instrumentation that measures shear wave velocity to estimate constructed layer moduli of unbound aggregate bases and subbases. This paper presents findings related to monitoring stiffness characteristics of airport pavement base courses instrumented with BE field sensors and tested under full-scale accelerated pavement testing during Construction Cycle 9 (CC9) of the National Airport Pavement Test Facility (NAPTF) by the U.S. Federal Aviation Administration (FAA). The CC9 aggregate base courses were constructed following FAA’s P-209 specification for a geosynthetic experiment using a biaxial geogrid installed at the bottom of the 8-in. (203-mm) thick base in the north test section, while the control pavement in the south test section was built without a geogrid. Two BE field sensors were installed in the north and south test sections approximately 1 in. (25 mm) above the base–subbase interface. Multiple stages of aircraft gear loads, including static dual-gear, dynamic slow-roll (moving wheel), and dynamic proof-roll, were applied to the test sections. BE field sensor data collected throughout multiple loading stages were used to investigate the stiffness characteristics of the pavement base. These preliminary tests conducted at the NAPTF CC9 experiment revealed the effects of static and dynamic aircraft gear loads on the stiffness of the aggregate base layer and how confinement influenced the moduli of the geogrid-stabilized base. Further, previously observed anti-shakedown effects caused by vehicle load wander could be quantified through changing base course modulus and deformation behavior from the BE field sensor data analysis.

Analysis of the dynamic responses of asphalt pavement based on full-scale accelerated testing and finite element simulation

This paper proposes a method of combining full-scale accelerated pavement testing (APT), indoor experiments, and finite element (FE) simulations to analyze and predict the dynamic response of a typical pavement structure with an SMA overlay. First, APT was performed under different loads from various axle weights, temperatures and speeds, and the longitudinal strain was selected as the analysis index. Indoor experiments considering the size effect were used to correct the parameters of the viscoelastic constitutive model. Then, the FE model was validated based on the consistency of the time-history curve and the proximity of the peaks of the dynamic response. Next, dynamic response analysis results indicate that the pavement structure in the influence range of the wheel track is in the strain alternating state of “compression-tension-compression”. Increased axle weight and temperature causes an increase in the longitudinal strain at the bottom of the underlayer asphalt, while the situation is reversed for the loading speed. Moreover, the longitudinal strain decreases after pavement overlaying, and the greater the axle weight loading is, the more obvious this trend. The FE analysis method further shows that the compressive stress is mainly concentrated under the wheel track, and it increases and then decreases from the center of the wheel track in the transverse distribution. The shear stress and strain increase and then decrease from the center of the wheel track. As the heavy load increases, the longitudinal strain increases nonlinearly with increasing axial loads, while the maximum shear stress increases linearly. In addition, the simulation results under a high loading speed illustrate that the effect of the loading speed change on the strain is noticeable.

Instrumentation response of full-scale thin airfield pavements

ABSTRACT Instrumentation response data from full-scale accelerated pavement testing have been used to inform pavement design models and enhance service life predictions to ensure long-term operating conditions. However, some aircraft, i.e. military aircraft, may have a requirement to operate under relatively short-term conditions on airfields that are constructed below optimal conditions. Accordingly, the objective of this study was to construct, traffic, and collect instrumentation data from airfield pavement test sections constructed with asphalt thicknesses below existing military standards. Three asphalt thicknesses and two base course strengths were evaluated using two different aircraft simulators each at two tire inflation pressures. Earth pressure cells, single-depth deflectometers, and asphalt strain gauges were used to collect response data. Instrumentation response data were sensitive to increases in asphalt layer thickness, i.e. an increase in asphalt layer thickness generally resulted in an improvement in measured response albeit in relatively thin asphalt layers. Instrumentation response data were more sensitive to tire inflation pressure changes at higher loading conditions when compared to lower loading conditions. Finally, a layered elastic analysis using a non-uniform tire pressure distribution was found to provide a better approximation of measured earth pressure cell response than that of a typically assumed uniform pressure distribution.

Three-dimensional contact stresses of a slick solid rubber tyre on a rigid surface

The main aim of this paper is to quantify the three-dimensional contact stresses imposed by a single slow-moving (or rolling) slick solid rubber tyre on a relatively rough contact surface, such as stiff asphalt concrete or airport concrete surfacing layers. The results indicated the tyre-contact patch of a slick solid rubber tyre to be of rectangular shape for a vertical tyre loading range between 20 kN and 100 kN. The rectangular tyre contact shape was confirmed with static paper prints, as well as an electronically measured contact patch with the stress-in-motion pad device. The study included load calibration using a mass load scale, and a stress-in-motion device. These were used with an existing full-scale accelerated pavement test device, referred to as the heavy vehicle simulator. In addition, simplistic multi-layer linear elastic modelling was used to quantify differences between stress and strain responses of two types of two relatively 'stiff' based pavements, such as an asphalt concrete base and Portland cement concrete base, on similar subbase and subgrade layers. Notable differences were obtained, which could potentially influence further detailed studies on the performance of full-scale slick solid rubber tyres on typical multi-layered pavements.

Pavement Optimisation With Aggregate Base Or Asphalt Layers Stabilised With Hexagonal Geogrids

The use of hexagonal geogrids in pavement structures results in the increase of the life of designed structure.This offers the possibility to reduce the thickness of layers without reduction of pavement life, or to increase the traffic capacity of a pavement without the need to increase its thickness. This way of using geogrids in pavements design was introduced to the pavement industry by one producer of hexagonal geogrids as a Pavement Optimisation (PO) concept.It can be transformed into both economic and environmental benefits, and obviously results in savings of natural resources and reduction of carbon footprint of a project. PO with geogrids can be used both in the newly designed pavement structures, and in the asphalt overlays of the existing old pavements. Asphalt overlays enhancement with a geogrid either increases the fatigue life of overlays or allows the reduction of overlays thickness to achieve the same pavement life. In new pavements, stabilisation of aggregate base with geogrids increases the stiffness of aggregate, which increases the performance of a whole pavement. This paper presents several tests results, which confirm beneficial effects of using hexagonal geogrids in asphalt overlays and aggregate base layers, from laboratory to full scale accelerated pavement tests. Also, modifications of Mechanistic-Empirical pavement design method, which allow to implement the geogrid benefits into the design process, are discussed. Finally, case studies of pavements – newly designed and reconstructed – optimised with hexagonal geogrids are presented.

Calibration of pavement ME rutting model for geogrid stabilized roadways

Many transportation agencies started implementing Mechanistic-Empirical (ME) approach for designing and analyzing new and rehabilitated pavements. Although the widely popular empirical design approach based on 1993 AASHTO Design Guide is still in practice, the need for performance-based design and accurate prediction of pavement distresses throughout the service life led to the adoption of the ME approach. The two major steps associated with the ME approach are the computation of pavement stress–strain responses using mechanistic analysis and estimation of pavement distresses using empirical analysis. Layered Elastic Analysis (LEA) or Finite Element Analysis (FEA) is normally utilized for mechanistic analysis whereas regression analysis is typically used for empirical analysis. Although the empirical models (i.e., transfer functions) were calibrated using the Long Term Pavement Performance (LTPP) dataset, these models do not consider the benefits of geogrid stabilization. Research and field studies had shown improvement in pavement performance when the pavement is stabilized with geogrids. This paper aims at incorporating the effect of geogrid in one of the distress models – more specifically, the rutting model – of AASHTOWare Pavement ME. Model calibration factors were developed based on the recent full-scale accelerated pavement test conducted at the research facility of the US Army Corps of Engineers. Two types of punched and drawn triangular aperture geogrids were utilized in the full-scale test. Pavement surface deformations measured during the trafficking period were used for calibrating the rutting model. The calibrated rutting model was validated with the LTPP and Louisiana Transportation Research Center (LTRC) dataset.

Analysis of airfield composite pavement rutting using full-scale accelerated pavement testing and finite element method

Rutting is a typical distress of hot-mix asphalt (HMA) overlays on airfield composite pavements (ACPs). An approach is needed that can provide comprehensive and reliable evaluation of ACP rutting characteristics. In this study, we developed a finite element model (FEM) that was based on parameters derived from laboratory and field tests performed in China. The FEM exhibited satisfactory accuracy after validated by the full-scale accelerated pavement testing (APT) [1]. The test results indicate that a typical dual-wheel rutting profile of ACP exhibits a non-uniform W-shaped deformation with double peaks in a two-stage development process. Variations in temperature, driving states, and interface bonding conditions influence ACP rutting characteristics significantly in terms of increasing deformations (uplift and sag) and changing profiles (with double peaks or single peak). The aircraft load level and overlay thickness only affect the degree and scope of rutting deformations. Rut depth has a power-function relationship with temperature and load cycles, but has a linear relationship with tire pressure and overlay thickness. The uplift coefficients are stable between approximately 0.26 and 0.29 when the influential factors are varied.

Alternate Method of Pavement Assessment Using Geophones and Accelerometers for Measuring the Pavement Response

Pavement instrumentation with embeddable in-situ sensors has been a feasible approach to determine pavement deteriorations. Determining pavement deflections during the passage of the load is a promising strategy to determine the overall performance of the pavement. There are different devices that apply loads to the pavements and measure the deflection basin, these include static, vibratory, or impulse loadings. Most commonly used are the static loading like Benkelman beam and impulse loading like the Falling Weight Deflectometer (FWD). However, these techniques are costly and the measurements are recorded infrequently, i.e., once per year or two years. This study focuses on the use of geophones and accelerometers to measure the surface deflections under traffic loading. To develop a method to measure pavement deflections, the sensors were submitted first to laboratory tests, and then tested in situ, in a full scale accelerated pavement test. In the laboratory, the sensors were submitted to different types of loading using a vibrating table. These tests were used to determine the noise and sensitivity of the sensors, and then to evaluate their response to signals simulating pavement deflections under heavy vehicles. The sensor response was compared with measurements of a reference displacement sensor. Different processing techniques were proposed to correct the measurements from geophones and accelerometers, in order to obtain reliable deflection values. Then, the sensors were evaluated in a full scale accelerated test, under real heavy axle loads. Tests were performed at different loads and speeds, and the deflection measurements were compared with a reference anchored deflection sensor. The main advantage of using accelerometers or geophones embedded in the pavement is to enable continuous pavement monitoring, under real traffic. The sensor measurements could also be used to determine the type of vehicles and their corresponding speeds. The study describes in detail the signal analysis needed to measure the pavement deflections accurately. The measurements of pavement deflection can be then used to analyze the pavement behavior in the field, and its evolution with time, and to back-calculate pavement layer properties.

Accelerated Pavement Testing of Perpetual Pavement Test Sections under Heavy Aircraft Loading at FAA’s National Airport Pavement Test Facility

Abstract Six flexible pavements were constructed for construction cycle 7 (CC7) at the Federal Aviation Administration (FAA) National Airport Pavement Test Facility in Atlantic City, New Jersey. Four test sections on the north side measure 200 mm (LFP-4), 250 mm (LFP-3), 300 mm (LFP-2), and 375 mm (LFP-1) that are made of hot mix asphalt (HMA) over an aggregate subbase (thickness varying between 850 and 1,025 mm) resting on a subgrade with a California bearing ratio of 5.5. The fifth test section, LFC-5, is conventional flexible pavement with 125 mm of HMA over aggregate base and subbase, and the LFC-6 structure is the same as LFC-5 except that the crushed stone base layer is replaced with asphalt-stabilized drainable base. The objective of CC7 tests is to develop perpetual pavement design criterion and to validate or refine the fatigue model for HMA in airport pavement thickness design software FAARFIELD. The HMA fatigue model is based on the ratio of dissipated energy change (RDEC). Four fiber optic strain plates were installed to measure transverse and vertical strains at top and transverse strains at bottom within the HMA layer. Full-scale accelerated pavement tests were performed. Traffic test load parameters were six-wheel gear, 245-kN wheel load (gear load 1,470 kN), and 4-kmph speed. Pavement performance was monitored using crack maps, straight edge rut depth, and surface profile measurements. LFC-5 and LFP-4 showed significant fatigue cracks and rutting. LFP-1 and LFP-2 performed well with no signs of cracking. This article presents a discussion on the RDEC fatigue model, pavement thickness design, pavement material characterization test results, pavement instrumentation, accelerated pavement tests under heavy aircraft gear loads, and pavement responses measured using embedded sensors. The test section performance shows that, under loading conditions used in the study, by increasing HMA thickness from 25.4 to 30.5 cm, fatigue cracking was eliminated for the duration of testing (38,000 passes).

Instrumented flexible pavement responses under aircraft loading

ABSTRACT The FAA National Airport Pavement Test Facility (NAPTF) is a full-scale accelerated pavement testing facility located in Atlantic City International Airport, New Jersey. Six flexible and three rigid test sections were built, instrumented and trafficked by Boeing 777 and 747 gears as part of construction cycle one. One flexible test section with an asphalt-stabilised base over a low-strength subgrade was considered in this study. All dynamic sensors, including pressure cells, strain gauges and multi-depth deflectometers were evaluated. A multistep procedure for evaluating the dynamic sensors was developed, and it included data reliability, repeatability, changes in the pavement responses under the Boeing 777 and 747 gears, and comparison with a three-dimensional (3D) finite element (FE) mechanistic model. The mechanistic model was found to predict the pavement responses with good reliability, whenever representative layer moduli are used. The study also found that 60% of the sensors produced acceptable or marginal responses and 40% produced unacceptable responses; therefore, it is recommended to consider this sensor survival rate when instrumenting future test sections. The rutting performance and pavement responses over time were evaluated; the test section was shown to have relatively similar performance and pavement responses under the Boeing 777 and 747 gears.