Evaluation of moisture susceptibility tests for warm mix asphalts

Buss, Ashley; Williams, R. Christopher; Schram, Scott

doi:10.1016/j.conbuildmat.2015.11.010

Cited by 31 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, application of the additives generally improved the ITSR values, which reflects an important reduction in water sensitivity for the WMA manufactured at 145 • C when using the additives analysed. These findings are also in agreement with other studies that employed chemical additives to act as anti-stripping agents [29,30]. However, when the reduction in manufacturing temperature is higher (near 45 • C), it is important to note that a significant decrease in tensile strength could occur, despite the fact that the ITSR are quite similar to those presented by the HMA (with the exception of the additive A3, which showed an important increase in water sensitivity for the mixture manufactured at 120 • C), and therefore, the durability of the material could also be reduced.…”

Section: Effect Of Different Additives On Wma Behavioursupporting

confidence: 93%

Study of Surfactant Additives for the Manufacture of Warm Mix Asphalt: From Laboratory Design to Asphalt Plant Manufacture

2017

View full text Add to dashboard Cite

Warm Mix Asphalt (WMA), manufactured at a lower temperature than the traditional Hot Mix Asphalt (HMA), allows for important economic and environmental benefits when considered for application in roads. Nonetheless, despite the benefits, its application in pavement for roads is not as widespread as desired from an environmental point of view; more in-depth studies to investigate its development and wider applicability are required. Thus, the present paper aims to contribute to the implementation of this cleaner technology to produce WMA (based on chemical additives) for its application in pavement for roads, including from the stage of the design of the material in the laboratory (by selecting the most appropriate manufacturing temperature and additive type and dosage) to its production in a conventional industrial plant for its use in a trial section. Results demonstrate that it is possible to reduce the manufacturing temperature of asphalt mixtures by using chemical additives, recording similar mechanical behaviour (or even superior) to conventional hot mixtures when specific studies are developed for the optimal design of the WMA. It was also shown that these mixtures could be produced in a conventional asphalt plant without implementing important changes in equipment, which implies a cost-effective solution that can readily be incorporated into traditional plant procedures.

show abstract

Section: Effect Of Different Additives On Wma Behavioursupporting

confidence: 93%

Study of Surfactant Additives for the Manufacture of Warm Mix Asphalt: From Laboratory Design to Asphalt Plant Manufacture

2017

View full text Add to dashboard Cite

show abstract

“…To evaluate water susceptibility, some specimens of each mixture were conditioned in air (dry) at the specific test temperature, while others were conditioned in water (wet) at 40°C for 72 h before dry conditioning, as suggested by EN 12697-12 (Method A). The detrimental effect of water is one of the major concerns about WMA mixtures, especially when porous asphalt is involved (19,20).…”

Section: Test Proceduresmentioning

confidence: 99%

Performance Assessment of Plant-Produced Warm Recycled Mixtures for Open-Graded Wearing Courses

Frigio

Stimilli

Virgili

et al. 2017

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Sustainable solutions, such as the combination of reclaimed asphalt pavement (RAP) as a partial substitution of virgin materials and warm-mix asphalt (WMA) additives to decrease production temperatures, represent the new research frontier in the asphalt industry. Specific investigations must evaluate the consequences of recycled WMA performance, especially in the case of open-graded (OG) mixtures, given that lower production temperatures can affect the adhesion properties and durability of those materials. This paper describes an experimental effort that involved OG mixtures produced in plant at warm temperatures (130°C) with two WMA chemical additives characterized by different compositions. In addition, an equivalent mixture (used as a control for comparison purposes) was produced at standard temperatures. Each material was prepared with a polymer-modified binder and 15% RAP. The main objective of the study was to characterize volumetric and mechanical properties of the investigated mixtures with particular attention paid to compactability aptitude and durability. To this end, gyratory-compacted specimens were subjected to several laboratory tests after dry and wet conditioning (i.e., indirect tensile strength, Cantabro test, semicircular bending, and repeated indirect tensile loading). Moreover, plant production of the investigated mixtures made it possible to evaluate the feasibility of large-scale processes. The WMA mixtures showed significant water susceptibility, although they guaranteed good compactability and satisfied mechanical acceptance requirements and international recommendations for raveling resistance in dry conditions. The chemical composition of the WMA additives was found essential to reduce the water damage. Surfactants and adhesion enhancers included within one of the investigated WMA additives ensured better water resistance than the other additive classified as a viscous regulator.

show abstract

“…Buss et al [24] compared laboratory compacted samples to the field cores in terms of Hamburg rut depth. To this end, the asphalt materials used to pave four sections were sampled, and laboratory specimens were fabricated.…”

Section: Introductionmentioning

confidence: 99%

“…This study proposes a new deep learning approach to predict the rutting depth versus wheel pass curve obtained from the HWTT as a function of asphalt mixture properties. Considering the increasing use of the HWTT in the balanced mix design movement across the United States [11], [14], [24], [28], such models can provide both time and cost savings for the purposes of initial design and material screening. A subset of deep learning entitled the convolution neural network (CNN) method is used herein to create an analytical model that can be easily programmed into a spreadsheet or into cloud-based services.…”

Section: Introductionmentioning

confidence: 99%

A deep learning approach to predict Hamburg rutting curve

Majidifard

Jahangiri

Rath

et al. 2021

Road Materials and Pavement Design

View full text Add to dashboard Cite

Rutting continues to be one of the principal distresses in asphalt pavements worldwide. This type of distress is caused by permanent deformation and shear failure of the asphalt mix under the repetition of heavy loads. The Hamburg wheel tracking test (HWTT) is a widely used testing procedure designed to accelerate, and to 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 a comprehensive collection of HWTT results was used to develop a CNNbased machine learning prediction model. The database includes 10,000 rutting depth data points measured across a large variety of asphalt mixtures. 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. A rigorous validation process was used to assess the accuracy of the model to predict total rut depth and the HWTT rutting curve. A sensitivity analysis is presented, which evaluates the effect of the investigated variables on rutting depth predictions by the CNN model. 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, pre-design trials.

show abstract

Evaluation of moisture susceptibility tests for warm mix asphalts

Cited by 31 publications

References 6 publications

Study of Surfactant Additives for the Manufacture of Warm Mix Asphalt: From Laboratory Design to Asphalt Plant Manufacture

Study of Surfactant Additives for the Manufacture of Warm Mix Asphalt: From Laboratory Design to Asphalt Plant Manufacture

Performance Assessment of Plant-Produced Warm Recycled Mixtures for Open-Graded Wearing Courses

A deep learning approach to predict Hamburg rutting curve

Contact Info

Product

Resources

About