William G. Buttlar

The phase-field method has emerged as a robust computational approach for simulating complex crack initiation and propagation in solids. Building on this framework, we previously recast the Park-PaulinoRoesler (PPR) cohesive zone model within a phase-field formulation through appropriate geometric and degradation functions, resulting in the regularized PPR model, which enables the modeling of fracture across materials exhibiting convex, linear, or concave traction-separation relationships across fracture surfaces. While the original formulation was developed for rate- and temperature-independent materials, several engineering materials such as polymers and asphaltic mixtures exhibit strong viscoelastic and thermal sensitivity. In this work, we extend the regularized PPR model to thermo-viscoelastic media through a weakly coupled formulation for isotropic linear viscoelasticity. In this new formulation, the bulk response is described using a generalized Maxwell model, while fracture evolution is governed by a crack-driving force that accounts for both elastic energy storage and viscous dissipation associated with time-dependent deformation. We use an incremental recursive scheme to efficiently update stresses without explicit evaluation of hereditary convolution integrals. The formulation is first verified against analytical solutions for a one-dimensional bar and subsequently validated against fracture experiments on asphaltic materials. Additional thermo-mechanical examples demonstrate the ability of the model to capture thermally induced fracture under both steady-state temperature gradients and transient cooling. The results show that the proposed framework reproduces the experimentally observed load-displacement responses while naturally capturing rate- and temperature-dependent fracture behavior.

Rutting in asphalt pavements, characterized by longitudinal surface depressions in wheel paths, poses significant safety concerns. Accurate identification and measurement of rutting are crucial for maintaining road safety, ensuring ride quality, and reducing fuel consumption. Traditional methods, such as manual assessments, are labor-intensive, time-consuming, and prone to human error. High-frequency laser systems, while precise for pavement monitoring, are expensive, require specialized training for operation, and involve substantial maintenance costs, making them less accessible and convenient for many highway agencies and municipalities, underscoring the need for more affordable and practical solutions. This article introduces an accurate, efficient, and cost-effective alternative for rut depth measurement using inexpensive, commercial solid-state lidar (SSL) technology. The study is an investigation of the feasibility and reliability of SSL technology for measuring rutting distress in asphalt pavement. Measurements obtained using SSL technology were compared with measurements obtained using a laser rut bar system, as well as manual measurements. Specifically, for a specified road test section, the SSL system achieved a coefficient of determination ( R ² ) of 0.81, a mean absolute error of 0.07 in., and a root mean square error of 0.08 in. Additionally, comparing SSL performance with manual measurements, the error in rut depth measurement was less than 20%. A network-level survey in Columbia, Missouri, demonstrated the SSL system’s capability for extensive pavement condition monitoring at highway speeds.

With an increasing focus on improving the sustainability of asphalt mixtures, the use of recycled materials in asphalt mixtures has received significantly more attention recently. In Missouri, the incorporation of recycled materials including reclaimed asphalt pavement (RAP) and ground tire rubber (GTR) is limited to dense graded mixtures only. Missouri routinely uses stone mastic asphalt (SMA) mixtures on its interstates with high traffic for enhanced performance, and several studies have found that these recycled materials can be incorporated in SMAs without compromising their performance. This study aimed at investigating the effects of incorporating RAP and GTR in Missouri SMA mixtures. A total of 10 mixtures with varying dosages of recycled materials were designed using balanced mix design (BMD) methodology. The mechanical performance was determined by the mixture’s resistance to rutting using the Hamburg Wheel-Tracking test and cracking using the IDEAL-CT test. In addition, a disc-shaped compact tension (DC[T]) test was performed to determine thermal cracking resistance of the asphalt mixtures. Since sustainability is a key aspect of using recycled materials in asphalt mixtures, life cycle assessment (LCA) was conducted to quantify the global warming potential (GWP) of each mixture. This research showed that SMA mixture modification by 15% asphalt binder replacement with RAP proved to be the most desirable in mechanical and environmental performance. The addition of GTR did not have an adverse effect on the GWP, while the mixtures exhibited improved performance. Overall, the use of RAP and GTR in conjunction can be recommended for their implementation in SMA mixtures in Missouri.

This study employs a microstructure-based finite element modeling approach to understand the mechanical behavior of asphalt mixtures across different length scales. Specifically, this work aims to develop a multi-scale modeling approach employing representative volume elements (RVEs) of optimal size; this is a key issue in asphalt modeling for high-fidelity fracture modeling of heterogeneous asphalt mixtures. To determine the optimal RVE size, a convergence analysis of homogenized elastic properties is conducted using two types of RVEs, one made with polydisperse spherical inclusions, and another made with polydisperse truncated cylindrical inclusions, each aligned with the American Association of State Highway and Transportation Official’s maximum density gradation curve for a 12.5 mm Nominal Maximum Aggregate Size (NMAS). The minimum RVE lengths for this NMAS were found to be in the range of 32–34 mm. After the optimal RVE size for each inclusion shape is obtained, computational models of heterogeneous Indirect Tensile Asphalt Cracking Test samples are then generated. These models include the components of viscoelastic mastic, linear elastic aggregates, and cohesive zone modeling to simulate the rate-dependent failure evolution from micro- to macro-cracking. Examination of load-displacement responses at multiple loading rates shows that both heterogeneous models replicate experimentally measured data satisfactorily. Through micro- and macro-level analyses, this study enhances our understanding of the composition-performance relationships in asphalt pavement materials. The procedure proposed in this study allows us to identify the optimal RVE sizes that preserve computational efficiency without significantly compromising their ability to capture the asphalt material behavior under specific operational conditions.

This study focused on the improvement or redesign of dense-graded mixtures in Missouri by applying various strategies typified by a balanced mix design (BMD) approach. Briefly, the BMD approach involves designing mixtures using appropriate thresholds of mixture performance tests to control major distresses. In this study, two existing dense-graded mixtures from Missouri were adopted with 33% binder replacement by recycled asphalt pavement (RAP). Appropriate thresholds from three commonly used cracking tests, namely the disk-shaped compact tension test, or DC(T), the Illinois Flexibility Index Test (I-FIT), and the indirect tensile asphalt cracking test (IDEAL-CT), were paired with the Hamburg wheel track test (HWTT) toward the improvement or rebalancing of mixes designed before the availability or specified use of these tests. Preliminary test results showed that the existing mix designs did not satisfy the cracking thresholds adopted in this study, and thus the following modifications were made to the mixtures: (a) replacing the base binder with a softer grade binder, (b) adding a rejuvenator, and (c) adding ground tire rubber (either 10% or 20% by weight of base binder). According to the results, modification with rubber and softer binder was the most efficient strategy for improving and balancing DC(T) fracture energy and HWTT performance. On the other hand, the use of a softer binder or rejuvenator led to the best success in meeting semicircular bend (SCB) (I-FIT) and IDEAL-CT test requirements in balance with HWTT requirements.

Research has demonstrated that asphalt pavements can be a strategic destination for some of the major streams of waste materials around the globe, such as scrap tires and plastics. Ground tire rubber (GTR) from scrap tires has been used in asphalt pavements since the 1960s but has yet to approach its full potential in relation to market adoption. The heightened restrictions imposed by China in relation to waste stream contamination in 2018 have catalyzed research on incorporating post-consumer recycled (PCR) plastics into asphalt pavements. A field demonstration project was carried out in Columbia, MO to evaluate modern recycled plastic and GTR additives in an asphalt pavement overlay. The demonstration focused on dry-process modification, which requires minimal alterations to an existing asphalt plant and allows a higher amount of recyclates to be utilized. The project was also designed to assist in the Missouri Department of Transportation’s early roll-out of balanced mix design asphalt design and quality assurance specifications. The results of the study indicated the viability of dry-process GTR and PCR plastic additives used with neat (unmodified) asphalt binder as an alternative to binders modified with virgin polymers, chemical treatments, or both, in a wet process. The results of the study also suggest the viability of hybrid wet polymer-modified binder with dry-process PCR plastic as a greener alternative to binders modified with virgin polymers, chemical treatments, or both. Future studies will be needed to examine additional PCR plastic streams, especially mixed polymer streams.

The purpose of this paper is to quantify the economic impacts associated with an investment in transportation systems. Here, we apply the methodology to projected comprehensive economic impacts of an Hyperloop route. The methodology is a low-frequency economic growth model that includes cumulative gains in real GDP, cost savings and the greenhouse gas savings of the proposed Hyperloop technology. To calibrate the model, we consider a route spanning from Texas to Chicago and covering 1,575 miles across the proposed hyperloop system. The infrastructure investment is obtained from construction cost estimates presented in previous feasibility studies. Our contribution is to present a simple general equilibrium approach to quantifying transportation economic impacts. To our knowledge, our is the first quantitative assessment of the Hyperloop technology. We include an analysis of the public finance aspects of the route, thus adding an answer to the question regarding the national merits of such an investment project. Our findings suggest that for returns comparable to the interstate highway system, the project could be paid for out of the stream of future tax revenues. There are additional gains through lower fares and travel times. Lastly, the environmental gains, especially from reduced air travel, are quantitatively significant.

The Hamburg wheel tracking test (HWTT) is a widely used testing procedure designed to accelerate and simulate the rutting phenomena in the laboratory. Rut depth, as one of the outputs of the HWTT, is dependent on a number of parameters related to mix design and testing conditions. This study introduces a new model for predicting the rutting depth of asphalt mixtures using a deep learning technique - the convolution neural network (CNN). A database containing 10,000 data points from a comprehensive collection of HWTT results was used to develop a CNN-based machine learning prediction model. The model has been formulated in terms of known influencing mixture variables such as asphalt binder high-temperature performance grade, mixture type, aggregate size, aggregate gradation, asphalt content, total asphalt binder recycling content, and testing parameters, including testing temperature and number of wheel passes. The model can be used as a tool to estimate the rut depth in asphalt mixtures when laboratory testing is not feasible or for cost-saving, and pre-design trials.