Asphalt pavements are susceptible to moisture induced-damage, which is caused by moisture interaction with asphalt-aggregate bonds. Although moisture-induced damage in asphalt concrete has been studied for over 70 years, two very fundamental questions remain unanswered: Can the conditions that cause moisture-induced damage be accurately predicted? How can moisture-induced damage be mitigated? The foremost difficulty lies in the fact that the moisture interaction with asphalt-aggregate bonds is a phenomenon that occurs at the atomic or nano-scale level. This Faculty Early Career Development (CAREER) research and education proposal offers a novel approach to understanding and quantifying moisture interactions with asphalt-aggregate bonds at the nano-scale level, and relating these interactions to the moisture-induced damage at the Macro-scale level. The research objectives are to: capture microscopic images of the adhesive and cohesive forces in the asphalt-aggregate system under dry and wet conditions using an atomic force microscope (AFM), determine the microscopic work of adhesion from the AFM data; construct mathematical models and neural networks to determine the bond damage index from the microscopic work of adhesion; and conduct macro-scale testing and develop models to relate the bond damage index to the macro-scale moisture-induced damage in asphalt concrete. The broader impact of this study is that it may result in significant saving of financial and other resources that are currently used to combat pavement distresses originating from moisture-induced damages. The research activities proposed herein will be conducted through the research participation of graduate and undergraduate students. A summer educational event will be established that will focus on the participation of high school students. An advisory board consisting of individuals from academia, industries, government agencies and research institutions will be formed to ensure success of the proposed research, educational and outreach objectives.
Asphalt pavements are susceptible to moisture induced-damage, which is caused by moisture interaction with asphalt-aggregate bonds. Although moisture-induced damage in asphalt concrete has been studied for over 70 years, it still remains an unsolved problem. The foremost difficulty lies in the fact that the moisture interaction with asphalt-aggregate bonds is a phenomenon that occurs at the atomic or nanoscale level. This project brings a fresh perspective to this problem through a fundamental understanding of bond damage at the nanoscale to support characterization and modeling of asphalt concrete for structural integrity at higher scales. In essence, asphalt films were prepared and microscopic images of these samples were captured to determine the adhesion forces between the atoms of a cantilever tip and asphalt molecules of film surface. Different tip length (i.e, long and short) and chemical functional (-COOH, -CH3, -NO, -Si3N4 and –OH) were used to measure the adhesion and bond strength of asphalt under wet and dry conditions. A neural network (NN) model was constructed to quantify adhesion using the data from AFM testing for use in higher scale finite element modeling (FEM). It is shown that adhesion force in wet sample is higher than that in dry sample. As adhesion force represents bond strength, this indicates that bond damage or weakening occurs in asphalt film due to water action. The research confirms the damage of moisture on asphalt binder even with the presence of antistripping agents, though lime showed better performances than other antistripping agents. Adhesion force or bond strength of asphalt sample does not depend on the binder performance grade but adhesion varies with polymer content. This raises a question whether performance grade binders are achieved through polymer modifications. One of the main outcomes of this project is that it has developed a methodology to measure bond energies in terms of adhesion force between asphalt functional groups such as Si3N4, -CH3, -OH, and -COOH. A quantification of bond strength is made using NN programing. The NN model is tested and found to have good predictive capability. Using FEM, it is shown that cohesive damage initiates into matrix materials and then damage progress towards matrix-aggregate interface and initiates adhesive damage. Both cohesive and adhesive damage is higher under wet condition comparing with dry condition. Moisture causes 62.80% more damage in matrix materials considering only the region under the applied deformation. About 17.45% more of the matrix-aggregate interface fails at contact for wet matrix when compared that with the dry matrix. This study has made significant improvements in moisture damage test methods and our understanding of the nano to micro to macro scale behavior of asphalt concrete, which will play vital roles in the design, construction, and maintenance of roadway pavements years to come. This project has resulted in graduating two Ph.D. students, two M.S. students, and five undergraduate students, a majority of them are minority students. Several journals and conference papers were published and presented based on the outcome of this project. This project has made multiple positive impacts on instruction’s laboratory equipment and graduate course materials. This project has organized workshop and seminars that have educated asphalt engineers and professional about nanotechnology based solution to yet unsolved problems such as this. This project is a unique example of a chemo-mechanics problem which solution involves multiple length scale testing and modeling in civil engineering.
