Minnesota Road Research Facility Research Articles

Evaluating the Short-term Performance of Spray-on Rejuvenators using a Modified Bending Beam Rheometer Test Methodology

Spray-on rejuvenation is a preventive maintenance strategy that highway agencies use to prolong the service life of asphalt pavements. This process involves applying rejuvenators on the surface of asphalt pavement to reverse the stiffening caused by aging. However, with several rejuvenators available on the market, it can be challenging to select specific products without understanding their effects at the mixture level. In this study, 12 different spray-on rejuvenators were applied on two different test sections (each with multiple test cells) at the Minnesota Road Research Facility. To assess the short-term (1–2 months) performance of rejuvenators, bending beam rheometer (BBR) test beams were prepared from the surface of the field-extracted cores, and a creep stiffness test was performed. The creep stiffness was measured at three different temperatures to evaluate the effectiveness of rejuvenators at these temperatures. The BBR test was not used to assess the low-temperature cracking resistance; instead, it was simply used to measure the beams’ linear viscoelastic property (i.e., the creep stiffness). Results indicated that the effect of rejuvenation is more evident at higher temperatures (20°C in this case). Besides, specific unexpected effects of rejuvenator products were observed. One of the test sections included extensive microcracks visible on the surface (presumably because of construction-related issues). Some of the rejuvenators closed these microcracks, leading to a “bridging” effect and increasing the stiffness of the BBR beams. This study provides a reference for evaluating the effect of spray-on treatments at the asphalt mixture level, which can assist roadway agencies in decision-making.

Joint performance and faulting of ultra-thin and thin structural-fiber reinforced concrete pavements

ABSTRACT Structural fibers contribute to the overall performance of concrete pavements by mitigating various distresses. To understand the influence of structural fibers on the pavement structural responses and distresses, the Minnesota Department of Transportation (MnDOT) constructed two ultra-thin (3 and 4 in. thick) and three thin (5 and 6 in. thick) fiber reinforced concrete cells along with one plan concrete control test cell at the Minnesota Road Research (MnROAD) facility in 2017. These test cells have 6 ft x 6 ft concrete slabs and were constructed on the granular base layer. While the structural designs of these cells were intended for roads with low to moderate traffic volume, the cells were subjected to accelerated loading to complete the study in a short period of time. This paper summarizes the design and construction of the six test cells and provides a comprehensive discussion on the joint performance behavior and transverse joint faulting trends, emphasizing the influence of the fibers on the abovementioned. It was found that fibers can improve joint performance and decrease faulting in thin concrete pavements. Regarding the ultra-thin pavements, no conclusion was possible to be drawn on the contribution of the fibers.

Redevelopment of Artificial Neural Networks for Predicting the Response of Bonded Concrete Overlays of Asphalt for use in a Faulting Prediction Model

Transverse joint faulting is a common distress in bonded concrete overlays of asphalt pavements (BCOAs), also known as whitetopping. However, to date, there is no predictive faulting model available for these structures. Therefore, the intended research is to develop a predictive faulting model for BCOAs. In addition, it is important to be able to account for conditions unique to BCOA when characterizing the response in a faulting prediction model. To address this, computational models were developed using a three-dimensional finite element program, ABAQUS, to accurately predict the response of these structures. These models account for different depths of joint activation, as well as full and partial bonding between the concrete overlay and existing asphalt pavement. The models were validated with falling weight deflectometer (FWD) data from existing field sections at the Minnesota Road Research Facility (MnROAD) as well as at the University of California Pavement Research Center (UCPRC). A fractional factorial analysis was executed using the computational models to generate a database to be used in the development of the predictive models. The predictive models, based on artificial neural networks (ANNs), are used to rapidly estimate the structural response at the joint in BCOA to environmental and traffic loads so that these responses can be incorporated into the design process. The structural response obtained using the ANNs is related to damage using the differential energy concept. Future work includes the implementation of the ANNs developed in this study into a faulting prediction model for designing BCOA.

Contribution of MnROAD Research to Improvements in Concrete Pavement Technology from 1994–2019

By the late 1980s several states, including Minnesota, began to wonder if American Association of State Highway Official (AASHO) based asphalt and concrete pavement designs were still valid, given the significant changes in traffic loads, materials and construction practices over time. This interest in validating current designs, as well as seeking improved and more efficient designs and materials, led to the creation of the Minnesota Road Research facility, known as MnROAD. Construction of the first phase of test sections at MnROAD took place from 1991 to 1994, and it was open to traffic loading commencing on July 15, 1994. Since 1994, three phases of pavement research have been, and continue to be, conducted at MnROAD. In its first 25 years of operation, an overwhelming amount of pavement research and development has been accomplished at MnROAD. The focus of this paper is to describe many of the more unique and significant findings that have improved concrete pavement technology not only in Minnesota, but throughout the U.S. and other parts of the world. The contributions are categorized into the following areas: design, materials, construction, rehabilitation, pavement monitoring and evaluation, and full-scale testing. In each of the areas, the significant contributions are described and relevant references are cited. The positive contributions of MnROAD toward concrete pavement knowledge and technology have been recognized, and as a result, the MnROAD facility will continue to operate successfully into the future under the National Road Research Alliance (NRRA).

Nondestructive Full Coverage Asphalt Stripping Detection Using 3D Radar

Since subsurface stripping extent is important for maintaining the road network, Minnesota Department of Transportation (MnDOT) uses forensic measures such as coring. The destructive nature and lack of coverage provided by this accepted method makes finding nondestructive methods for detecting stripping of in situ asphalt pavements an important need for MnDOT and many other agencies. Stripping between hot mix asphalt layers can cause premature failure of pavements. Knowledge of the lateral location, depth and extent of stripping can affect the timing and type of pavement preservation, maintenance, or rehabilitation. This paper reports on use of a DX1821 antenna to collect data at a frequency step of 20 MHz ranging from 50 MHz to 3050 MHz with a dwell time of 7.52 μs using a GeoScope Mk IV control unit on a full-scale asphalt pavement constructed at the National Center for Asphalt Technology (NCAT) test track with built-in stripping. Signals from the known stripped and non-stripped locations were used to evaluate statistical and energy based approaches. It is shown that a maximum energy ratio method, an approach that has been successfully applied to acoustic emission applications in the past, can improve signal clarity for stripping detection using ground penetrating radar (GPR). These results are confirmed using highway speed measurements at the Minnesota Road Research Facility with core validation.

Performance of Chip Seal Treatments in Two Different Climatic Regions

Over time, new pavements deteriorate because of the effect of traffic loads and the environment. Pavement preservation treatments, such as chip seals, are a cost-effective alternative for extending the service life of the pavement without incurring in costly rehabilitation or reconstruction activities. Chip seals are preservation treatments that can help protect the pavement structure, reduce the rate of pavement deterioration, improve skid resistance, and address minor surface problems. As part of the National Center for Asphalt Technology and Minnesota Road Research Facility Pavement Preservation Study, chip seal test sections were placed on low-traffic-volume roads in Alabama and Minnesota. The two locations were selected to represent different climate conditions. Lee County Road 159 in Auburn, Alabama, is subjected to warm, wet, no-freeze climate, while County State Aid Highway (CSAH 8) is located in a cold, wet, freeze area in Pease, Minnesota. Treatments have been in service for approximately 6 years in the southern sections, and 2 years in the northern sections. During this time, cracking, roughness, rutting, and macrotexture data were collected periodically to evaluate pavement performance. The results determined that cracking is a predominant form of distress for these treatments. While the treatments are not expected to address rutting or roughness, the results indicated little variation in the case of the southern treatments, and an increasing trend in international roughness index in the northern sections, likely related to the appearance of thermal cracking. Macrotexture data may be used to assess the functional life of the treatments.

Artificial Neural Networks for Predicting the Response of Unbonded Concrete Overlays in a Faulting Prediction Model

Transverse joint faulting is a common distress in unbonded concrete overlays (UBOLs). However, the current faulting model in Pavement mechanistic-empirical (ME) is not suitable for accurately predicting the response of UBOLs. Therefore, to develop a more accurate faulting prediction model for UBOLs, the first step was to develop a predictive model that would be able to predict the response (deflections) of these structures. To account for the conditions unique to UBOLs, a computational model was developed using the pavement-specific finite element program ISLAB, to predict the response of these structures. The model was validated using falling weight deflectometer (FWD) data from existing field sections at the Minnesota Road Research Facility (MnROAD) as well as sections in Michigan. A factorial design was performed using ISLAB to efficiently populate a database of fictitious UBOLs and their responses. The database was then used to develop predictive models, based on artificial neural networks (ANNs), to rapidly estimate the structural response of UBOLs to environmental and traffic loads. The structural response can be related to damage through the differential energy concept. Future work will include implementation of the ANNs developed in this study into a faulting prediction model for designing UBOLs.

Establishing the Interlayer Structural Response for Unbonded Concrete Overlays of Existing Concrete Pavements

An improved mechanistic empirical design procedure for unbonded concrete overlays of existing concrete pavements (UBOLs) should account for the effect of the interlayer on the structural response of the pavement. One approach is to use the Totsky model to characterize the interlayer. The Totsky model treats the interlayer as a bed of springs between two plates and is currently incorporated into the rigid pavement finite element software ISLAB. A difficulty encountered in implementing this model is that there are currently no guidelines as to what the interlayer k-value should be for different types of interlayers. The interlayer can be constructed of new or aged asphalt (open or dense graded) or a nonwoven geotextile fabric. To establish the k-values that accurately characterize each of these materials, an ISLAB model of a laboratory test was created so the k-values could be established by matching the measured and calculated difference between the deflections in the overlay and existing pavement. To supplement the use of the laboratory data in establishing the Totsky interlayer k-value, an analysis was carried out using falling weight deflectometer (FWD) data from UBOLs at the Minnesota Road Research Facility (MnROAD). Analyses were then performed to determine if the difference between k-values for different interlayer materials are statistically significant, and if the results from the laboratory analysis match those obtained from the MnROAD field data. The Totsky k-value recommended for use when modeling the response of an UBOL with an asphalt interlayer is 3500 psi/in and 425 psi/in for a fabric interlayer.

Development of Artificial Neural Networks for Predicting the Response of Bonded Concrete Overlays of Asphalt for Use in a Faulting Prediction Model

Transverse joint faulting is a common distress in bonded concrete overlays of asphalt pavements (BCOAs), also known as whitetopping. However, to date, there is no predictive faulting model available for these structures. To account for conditions unique to BCOA, a computational model was developed using a three-dimensional finite element program, ABAQUS, to predict the response of these structures. The model was validated with falling weight deflectometer (FWD) data from existing field sections at the Minnesota Road Research Facility (MnROAD) as well as at the University of California Pavement Research Center (UCPRC). A large database of analyses was then developed using a fractional factorial design. The database is used to develop predictive models, based on artificial neural networks (ANNs), to rapidly estimate the structural response at the joint in BCOA to environmental and traffic loads. The structural response will be related to damage using the differential energy concept. Future work includes the implementation of the developed ANNs in this study into a faulting prediction model for designing BCOA.

Statistical Model to Detect Voids for Curled or Warped Concrete Pavements

A statistical classifier was developed to interpret falling weight deflectometer data for the detection of voids under jointed concrete pavement slabs. The classifier was trained with the Seasonal Monitoring Program sections in the Long-Term Pavement Performance (LTPP) database and data from the Minnesota Road Research Facility. A two-level cross-validation process was used to assess the performance of existing void detection methods, according to a threshold of a single variable, and the least absolute shrinkage and selection operator (LASSO) classifier, which is based on several variables. Simple void detection methods based on the normalized 9,000-lb deflection were found to perform better than void detection methods based on variable deflection analysis. The LASSO classifier outperformed any of the existing void detection techniques. The LASSO classifier was validated through two field trials in Pennsylvania and an LTPP general pavement section in which significant faulting had developed.

Comparison of response for three different composite pavement sections to environmental loads

Composite pavement structures are constructed mainly either as Portland cement concrete (PCC)-over-PCC or hot mix asphalt (HMA)-over-PCC. Several successful in-service projects have been reported in Europe. The design and construction of these sections in the United States, however, still require effort. The current study includes the analysis of the response of three different composite pavement sections to the environmental loads. These sections were constructed in May of 2010 at the Minnesota Road Research Facility. The sections are constructed in three individual cells, Cell 70, a HMA-over-PCC with recycled concrete aggregate (RCA), Cell 71, exposed aggregate concrete (EAC)-over-RCA and Cell 72, EAC-over-economical concrete. All cells were heavily instrumented with thermocouples, moisture sensors, and static and dynamic strain gauges. This study characterises the structural response of HMA-over-PCC pavements and also PCC-over-PCC to the environmental loads.

Dynamic Viscoelastic Analysis of Falling Weight Deflectometer Deflections for Rigid and Flexible Pavements

This paper investigates the ability of a generalized Westergaard model consisting of a viscoelastic plate on a viscoelastic Winkler foundation to describe deflections of both rigid and flexible pavements under dynamic loading. The pavement response to falling weight deflectometer (FWD) loading was simulated, and a semianalytical solution involving the use of a Hankel transform in space and a finite difference method in time was developed. The obtained solution was used to interpret FWD data collected at the Minnesota Road Research Facility. It was shown that a good match between the simulated and measured response data could be obtained for both rigid and flexible pavements if inertia and viscoelastic effects were accounted for. The proposed model is thus an attractive tool for analysis of pavement–vehicle interaction.

Responses and Performance of Stabilized Full-Depth Reclaimed Pavements at the Minnesota Road Research Facility

This paper details the construction and analysis of three stabilized full-depth reclamation (SFDR) sections (Cells 2, 3, and 4) constructed at the Minnesota Road Research Facility on I-94 in 2008. Three test sections with different ratios of pulverized asphalt concrete to granular base were constructed, and the performance of full-depth reclaimed pavements stabilized with engineered emulsion was studied. Emulsion content and base structure varied between test sections. Each test section was designed for 3.5 million equivalent single-axle loads for a period of 5 years. As of June 30, 2012, the sections had been subjected to approximately 2.2 million such loads. Responses were measured with strain gauges embedded at the bottom of the hot-mix asphalt and SFDR layers in each test section. The strain gauges indicated that the bottom of both the hot-mix asphalt and the SFDR layers was subject to horizontal tensile strain from falling weight deflectometer testing and heavy vehicle loading. Pavement performance for rutting, cracking, and international roughness index was measured periodically. The results indicated that all three cells were performing well. The only crack in the three cells was in Cell 3; the roughness index values were well within the acceptable range and rutting, although progressing, was still acceptable. The paper concludes with modeled responses and performance predictions from DARWinME and BISAR. Model predictions indicate that an SFDR layer will provide greater structural benefits and increased performance than will similar structures with unstabilized full-depth reclaimed or granular base layers.

Detection of Subsurface Joint Deterioration

Results of a blind test evaluation of various nondestructive testing techniques, including well-established methods such as chain dragging, rod sounding, and ground-penetrating radar, compared with an emerging ultrasonic array technology for determining the extent of concrete joint deterioration, are presented. Nondestructive testing at two concrete pavement joints at the Minnesota Road Research Facility was performed, and the results were independently evaluated and submitted to the Minnesota Department of Transportation. Significant discrepancies in subsurface deterioration assessments were observed between these techniques. Forensic evaluation (trenching and coring) was used to resolve the discrepancies in test results. It was concluded that the ultrasound array analysis was the only method that could accurately determine the horizontal extent of the deterioration otherwise undetected by the other available nondestructive evaluation methods. Additionally, ultrasonic tomography analysis was able to determine the depth of the deterioration. These results make this emerging technology an attractive alternative to traditional nondestructive testing methods for assessment of concrete pavement joints.

Use of the Mechanistic–Empirical Pavement Design Guide and CalME to Mitigate Rutting in Asphalt Overlays of Concrete Pavements

This paper describes the development of an approach for the prediction of rutting of newly constructed composite pavements and asphalt overlays of existing concrete pavements [asphalt concrete over portland cement concrete (AC–PCC)]. The rutting model of the Mechanistic–Empirical Pavement Design Guide (MEPDG) and the CalME procedure being developed by the California Department of Transportation and the University of California Pavement Research Center are investigated, and a procedure for incorporating the CalME rutting model into the MEPDG framework is introduced. The goal is to provide pavement engineers with a procedure for rutting in AC–PCC design and analysis that does not require uncommon inputs and does not force the user outside the MEPDG framework. The paper describes the procedure's validation with experimental data from the Pavement Research Center and from the Minnesota Road Research Facility. A brief sensitivity analysis of the procedure for rutting in AC–PCC is presented.

Leaching of Alkaline Substances and Heavy Metals from Recycled Concrete Aggregate Used as Unbound Base Course

There is an increasing trend toward using recycled concrete aggregate (RCA) in construction. However, concerns have been expressed in laboratory studies about the highly alkaline leachate, high-pH leaching patterns, and release of heavy metals from RCA (e.g., chromium, lead, and arsenic). In this study, RCA materials from a wide geographical area were investigated. Physical, chemical, and mineralogical properties were characterized and laboratory column leaching tests were conducted. Two field test sites were installed and instrumented, one at the Minnesota Road Research (MnROAD) facility in Minnesota and a second at a surface parking facility at the University of Wisconsin–Madison. The MnROAD site showed a neutral leachate pH (between 6.5 and 8.0) after 7 months of service life [1.2 pore volumes of flow (PVFs)]; however, the pH from column leaching tests ranged between 11.0 and 12.5 and showed no decline over 100 PVFs. Because of the large difference between the field and laboratory results, two samples of RCA in Wisconsin, one from a recent demolition of concrete pavement (WR-F) and the other from an RCA stockpile with an age of 5 to 10 years (WR-SP), were used in the Wisconsin field site to verify the Minnesota data and investigate the long-term leaching of alkaline compounds and heavy metals. WR-F RCA started with a high leachate pH (12.6) and remained constant for the first 5 PVFs; however, WR-SP RCA started at a lower pH (7.3) but showed a gradually increasing trend, up to pH = 11.9 for the first 2 PVFs. The pHs from both RCAs were higher than the U.S. Environmental Protection Agency drinking water standard. Arsenic, chromium, lead, and selenium in the RCA field leachate were observed to be higher than the maximum contaminant level for the U.S. drinking water standard.

Integration and road tests of a self-sensing CNT concrete pavement system for traffic detection

In this paper, a self-sensing carbon nanotube (CNT) concrete pavement system for traffic detection is proposed and tested in a roadway. Pre-cast and cast-in-place self-sensing CNT concrete sensors were simultaneously integrated into a controlled pavement test section at the Minnesota Road Research Facility (MnROAD), USA. Road tests of the system were conducted by using an MnROAD five-axle semi-trailer tractor truck and a van, respectively, both in the winter and summer. Test results show that the proposed self-sensing pavement system can accurately detect the passing of different vehicles under different vehicular speeds and test environments. These findings indicate that the developed self-sensing CNT concrete pavement system can achieve real-time vehicle flow detection with a high detection rate and a low false-alarm rate.

Concrete Pavement Joint Diagnostics with Ultrasonic Tomography

An important issue in extending the life of jointed plain concrete pavement is the proper construction and maintenance of transverse joints. The capabilities of an ultrasonic tomography device in providing information essential to joint rehabilitation decisions as well as the quality control of rehabilitation construction are presented. Testing was conducted at various partial-depth repair locations of a recently repaired in-service highway to determine the presence and extent of debonding between the partial-depth repair and the existing concrete. Testing also was conducted at the Minnesota Road Research Facility to evaluate the subsurface condition along various transverse joints. Real-time diagnosis with the intensity-based signals of the synthetic aperture focusing technique was successful in pinpointing the location of debonded concrete interfaces within partial-depth repairs. Ultrasonic tomography testing also showed the capability of identifying that a joint is in need of repair and subsequently diagnosing the extent of subsurface deterioration throughout the joint.

Development of a Global Positioning System–Based Vehicle Tracking System for the Minnesota Road Research Facility

One of the more important tasks in operating a pavement research test track is tracking the location of individual vehicles during load response testing. The location of a vehicle's tires profoundly affects values obtained from embedded pavement load response sensors. To improve the efficiency of load response testing both in the field and during analysis, a Global Positioning System-based vehicle tracking system (VTS) was developed and tested at the Minnesota Road Research Facility (MnROAD). The VTS demonstrated its capability of tracking vehicle motion with an accuracy of ± 1 in. (2.5 cm) at speeds up to 45 mph (70 km/h). These results matched or exceeded the accuracy obtained with a high-definition video camera previously used for tracking vehicle position at MnROAD. Additional field trials were conducted in greater Minnesota to determine the operational area of the VTS. Overall, the VTS received real-time kinematic signal correction in nearly 80% of the tested areas. The capabilities of the VTS spawned the development of the wireless triggering system. Through wireless triggering of data acquisition, the load test process can be greatly simplified. Although preliminary testing confirmed it as proof of concept, hardware issues dictate that additional development is necessary.

Adaptation of Mechanistic-Empirical Pavement Design Guide for Design of Minnesota Low-Volume Portland Cement Concrete Pavements

A new Mechanistic-Empirical Pavement Design Guide (MEPDG) was recently proposed in the United States. The performance prediction models in the MEPDG were calibrated using nationwide pavement performance data. This study examined the feasibility of adapting a recent version of the MEPDG for the design of low-volume concrete pavements in Minnesota. To achieve this, a comprehensive evaluation of the MEPDG Version 0.910 performance prediction models was conducted. It was found that the faulting model produced acceptable predictions, whereas the cracking model had to be adjusted. Although performance data from the Minnesota Road Research facility were actively used in calibration of the MEPDG, it is necessary to perform calibrations against a wider range of local variables to achieve a practical design procedure for Minnesota. The cracking model was recalibrated using the design and performance data for 65 pavement sections located in Minnesota, Iowa, Wisconsin, and Illinois. A prototype catalog of recommended design features for low-volume portland cement concrete pavements in Minnesota was developed using MEPDG Version 0.910. The catalog offers a variety of feasible design alternatives for a given combination of site conditions. It is recognized, however, that Version 0.910 is not the final version of the MEPDG. Therefore, the catalog should be updated after the MEPDG software is finalized.