ASU Scholarship Showcase

During much of 2009 and 2010, the alternative energy marketplace has been in a state of unpredictable change. The financial landscape is uncertain and profits are slim. Many companies are wondering if the journey to find alternative means for energy production is worth the investment. Wind, hydro and solar projects are all struggling to make ends meet in an economic landscape that predicts success but presents challenges. Strong, lean and agile companies seem to be able to maintain a slim competitive advantage afloat, while larger, slower companies are drowning in a myriad of intricate supply chains and non-existent credit. This paper evaluates innovation opportunities for alternative energy companies, with a focus on large scale, highly integrated solar providers.

In-process laser heating technique delivers a cost-efficient way to improve mechanical and geometrical properties to nearly isotropic and extremely smooth, respectively. The technique involves the incorperation of a solid-state laser into a commercial off-the-shelf 3D printer, mechanical system to allow controllable laser allumination on desired surfaces, and a gcode postprocesser to proper control of the mechanical system. This process uses laser for local heating, to enhance mass transfer between boundaries or to enhance surface reflow to smooth surface irregularity, to improve mechanical and geometrical properties. Only less than 3 W of laser power (CO2 laser) was used for high temperature material like PEEK and Ultem; less than 1 W (808nm laser) was found to be sufficient for achieving optimal properties for PLA. This technique has the potential for after-market integration into most commercial FFF 3D printers to achieved nearly isotropic and smooth 3D printed objects with various thermoplastic polymers.

The central objective of this paper is to demonstrate that the validity of the Hughes and Coakley (H&C) model of deviance in sport is context specific and depends on the time, place, social groups involved, and the relative power of the audience and deviant(s). H&C argued that performance enhancing substance (PES) use constituted a single type of deviant behavior among athletes (i.e., positive deviance). The Heckert and Heckert (H&H) deviance framework made it possible to theorize performance-enhancing substances and methods (PESM) use as four ideal types of deviant behavior among athletes and in sports collectives. Given the variability in the historical and social contexts where PESM use has occurred in sport, a comprehensive explanatory framework is needed to understand a full range of PESM behaviors. This paper demonstrates that the H&H framework has a clear explanatory advantage over the H&C model.

The impact of undergraduate research experiences (UREs) is supported by evidence from physical and life science fields, especially when student-apprentices work in traditional laboratories. Within social sciences specifically, some excellent student outcomes associated with UREs adhere to non–lab-based modalities like course-based research experiences (CUREs). Here, the authors evaluate the laboratory-based undergraduate research experiences (LUREs) as a potentially valuable approach for incorporating social science undergraduates in research. Using comparative analysis of survey data from students completing three types of social science-based UREs (n = 235), individual research experiences (IREs), CUREs, or LUREs, students perceived gains overall regardless of the type of experience, with some indication that LUREs are the most effective.

Major urban centers are warming due to a combination of global and local phenomena. City governments are increasingly adopting strategies to mitigate the causes and impacts of extreme heat on their populations. Among these strategies are high solar-reflectance (cool) surfaces installed on building roofs and walls. Use of cool surfaces is a cost-effective and simple strategy that replaces conventional darker surfaces with surfaces that have a high reflectance to shortwave (solar) energy.

This report reviews the recent history of cool-surface deployment efforts. This includes peer-reviewed literature, conference proceedings, and grey literature to identify challenges and barriers to wide-scale deployment of cool surfaces. We have also researched heat action plans and programs from cities and different codes and standards, as well as available incentive and rebate programs.

The review identifies challenges, barriers, and opportunities associated with large-scale deployment of cool surfaces and categorizes them broadly as being related to product development & performance or policies & mandates. It provides a foundation upon which we intend to build a roadmap for rapidly accelerating future deployments of cool surfaces. This roadmap will address identified challenges and incorporate lessons learned from historical efforts to generate a practical and actionable plan.

Recently the domestic aviation industry has been influenced by rapidly growing ultra low-cost carriers (ULCCs). The pattern of airport markets served by ULCCs is incongruous with legacy carriers and low-cost airlines alike. Existing literature, however, is limited for North American ULCCs: research has only recently begun to identify them separately from mainstream low-cost carriers. This study sought to understand the market factors that influence ULCC service decisions. The relationship between ULCC operations and airport market factors was analyzed using three methods: mapping 2019 flight data for four ULCCs combined, two regression analyses to evaluate variables, and three case studies examining distinct scenarios through interviews with airport managers. Enplanement data were assembled for every domestic airport offering scheduled service in 2019. Independent variables were collected for each Part 139 airport. The first model estimated an ordinary least squares regression model to analyze ULCC enplanements. The second model estimated a binary logistic equation for presence of ULCC service. Case studies for Bellingham, Waco, and Lincoln were selected using compelling airport factors and relevant ULCC experience. Maps of ULCC enplanements revealed concentrations of operations on the East Coast. Both regression analyses showed strong relationships between population and non-ULCC enplanements (two measures of airport market size) and ULCC operations. A significant relationship also existed between tourism and enplanements. In the logit model, distance and competition variables were associated with ULCC presence. Case studies emphasized the importance of airport fees and competition in ULCC preferences, although aeronautical costs were generally not significant in the regressions.

Urea is an added value chemical with wide applications in the industry and agriculture. The release of urea waste to the environment affects ecosystem health despite its low toxicity. Online monitoring of urea for industrial applications and environmental health is an unaddressed challenge. Electroanalytical techniques can be a smart integrated solution for online monitoring if sensors can overcome the major barrier associated with long-term stability. Mixed metal oxides have shown excellent stability in environmental conditions with long lasting operational lives. However, these materials have been barely explored for sensing applications. This work presents a proof of concept that demonstrates the applicability of an indirect electroanalytical quantification method of urea. The use of Ti/RuO2-TiO2-SnO2 dimensional stable anode (DSA®) can provide accurate and sensitive quantification of urea in aqueous samples exploiting the excellent catalytic properties of DSA® on the electrogeneration of active chlorine species. The cathodic reduction of accumulated HClO/ClO− from anodic electrogeneration presented a direct relationship with urea concentration. This novel method can allow urea quantification with a competitive LOD of 1.83 × 10−6 mol L−1 within a linear range of 6.66 × 10−6 to 3.33 × 10−4 mol L−1 of urea concentration.

Human team members show a remarkable ability to infer the state of their partners and anticipate their needs and actions. Prior research demonstrates that an artificial system can make some predictions accurately concerning artificial agents. This study investigated whether an artificial system could generate a robust Theory of Mind of human teammates. An urban search and rescue (USAR) task environment was developed to elicit human teamwork and evaluate inference and prediction about team members by software agents and humans. The task varied team members’ roles and skills, types of task synchronization and interdependence, task risk and reward, completeness of mission planning, and information asymmetry. The task was implemented in MinecraftTM and applied in a study of 64 teams, each with three remotely distributed members. An evaluation of six Artificial Social Intelligences (ASI) and several human observers addressed the accuracy with which each predicted team performance, inferred experimentally manipulated knowledge of team members, and predicted member actions. All agents performed above chance; humans slightly outperformed ASI agents on some tasks and significantly outperformed ASI agents on others; no one ASI agent reliably outperformed the others; and the accuracy of ASI agents and human observers improved rapidly though modestly during the brief trials.