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- Member of: ASU Electronic Theses and Dissertations
- Member of: ASU Retirees Association (ASURA) Video History Project Interviews
- Member of: Metis Center for Infrastructure and Sustainable Engineering
Bob Francis grew up in Yuma, Arizona and graduated from ASU. After spending a year teaching high school in Yuma, he returned to ASU in 1970, starting in the Alumni Association. After a few years, he moved to the Office of Undergraduate Admissions where he spent most of his career. He retired in 2002.
Important / interesting parts of the interview include:
• The beginning of the Office of Undergraduate Admissions in Part 2
• The changing attitude about the role of the University in marketing itself to students and parents in Part 3
• The role of the Devils’ Advocates played in selling the University in Part 4
• The role Don Dotts and Christine Kajikawa Wilkinson played in Bob’s career in Part 6


To address the dearth of knowledge about person-based and trip-level exposure, we developed the Icarus model. Icarus uses mesoscale traffic model—activity-based model—to analyze the heat exposure of regions of interest at an individual level. The goal with Icarus was to design accurate, granular models of population and temperature behavior for a target region, which could be transformed into a heat exposure model by means of simulation and spatial-temporal joining. By combining and implementing the most robust software and data available, Icarus was able to capture person-based exposure with unparalleled detail. Here we describe the model methodology. We use the metropolitan region of Phoenix, Arizona, USA to carry out a case study using Icarus.




This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.

Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.
