Quantitative characterization of microstructure of asphalt mixtures to evaluate fatigue crack growth

textStudies show that the microstructure of the fine aggregate matrix has a significant influence on the mechanical properties and evolution of damage in an asphalt mixture. However, very little work has been done to quantitatively characterize the microstructure of the asphalt binder within the fine aggregate matrix of asphalt mixtures. The first objective of this study was to quantitatively characterize the three dimensional microstructure of the asphalt binder within the fine aggregate matrix (FAM) of an asphalt mixture and compare the influence of binder content, coarse aggregate gradation, and fine aggregate gradation on this microstructure. Studies indicate that gradation of the fine aggregate has the most influence of the degree of anisotropy whereas gradation of the coarse aggregate has the most influence on the direction anisotropy of the asphalt mastic within the fine aggregate matrix. Addition of asphalt binder or adjustments to the fine aggregate gradation also resulted in a more uniform distribution of the asphalt mastic within the fine aggregate matrix. The second objective of this study was to compare the internal microstructure of the mortar within a full-scale asphalt mixture to the internal microstructure of the FAM specimen and also conduct a limited evaluation of the influence of mixture properties and methods of compaction on the engineering properties of the FAM specimens. Fatigue cracking is a significant form of pavement distress in flexible pavements. The properties of the sand-asphalt mortars or FAM can be used to characterize the evolution of fatigue crack growth and self-healing in full-scale asphalt mixtures. The results from this study, although limited in number, indicate that in most cases the SGC (Superpave Gyratory Compactor) compacted FAM specimen had a microstructure that most closely resembled the microstructure of the mortar within a full-scale asphalt mixture. Another finding from this study was that, at a given level of damage, the healing characteristic of the three different types of FAM mixes evaluated was not significantly different. This indicates that the healing rate is mostly dictated by the type of binder and not significantly influenced by the gradation or binder content, as long as the volumetric distribution of the mastic was the same.Civil, Architectural, and Environmental Engineerin

Capturing the Essence of Being Human: Two Marketing Tools That Rely on Anthropomorphization to Work

Technology has facilitated production processes that are mechanized and impersonal. With the increasing mechanization and automation of the value chain, marketers may find it valuable to remind consumers that there is a human source behind marketing activities. My dissertation comprises of two essays that focus on subtle, but impactful, marketing cues that make the human source salient. Specifically, I identify handwritten fonts (essay 1) and round-numbers (essay 2) as means by which the essence of being human can be captured and examine when, and why, these cues lead to positive (essay 1) versus negative (essay 2) consumer response. Essay 1 (chapter 2) investigates how product packaging using handwritten (vs. typewritten) fonts can increase product evaluation. It argues that the favorable evaluation stems from a response to handwritten fonts as subtle anthropomorphic cue. The extant literature has relied largely on overt anthropomorphic cues (e.g. human form and features) that evoke the tendency to anthropomorphize. In the current work, I propose that from a visual standpoint, anthropomorphism may occur also from activating the salience of a human source and introduce handwritten fonts as one such cue. Essay 2 (chapter 3) examines the role of numerical precision in surge pricing and its impact on consumer’s price fairness perception. I show that the surge price in the form of round (vs. precise) numbers will decrease consumer’s fairness perception in circumstances where ease of justification is low and thus the motivation to anthropomorphize (attribute to a human source) is high. I argue that the effect stems from the human tendency to round-off numbers, and such inference is particularly magnified in occasions where there is need to justify and make sense of one’s choice by attributing the surge to a human (versus non-human) source.Marketing and Entrepreneurship, Department o

Research report (Southwest Region University Transportation Center (U.S.))

"The main objective of this study was to quantitatively characterize the three dimensional micro-structure of the asphalt binder withing the fine aggregate matrix of an asphalt mixture and compare the influence of binder content, coarse aggregate gradation, and fine aggregate gradation on this micro-structure.

Research report (Southwest Region University Transportation Center (U.S.))

Report on a study comparing the internal microstructure of mortar within full asphalt mix to the internal microstructure of fine aggregate matrix to reduce fatigue cracking in flexible pavements

Insights into the accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models

Insights into accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. Following provision of historical trend data on the domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N=86 teams/359 forecasts), with an opportunity to update forecasts based on new data six months later (Tournament 2; N=120 teams/546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than simple statistical models (historical means, random walk, or linear regressions) or the aggregate forecasts of a sample from the general public (N=802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models, and based predictions on prior data