Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements.

Scholarship of Application. Background: Capstone courses constitute the culminating experience in engineering curricula. A core characteristic is the student team and project-based nature, with many team deliverables. The ensuing difficulty is to fairly assess the individual team member's contribution toward the team effort. Contribution: The method presented here is based on weekly peer evaluation of the individual team member's contribution, which subsequently yields a participation factor (PF), in turn scaling the team grade in accordance with the individual student performance. Intended Outcome: This method allows the timely adjustment of the individual student effort to match the group expectations and rewards high-performing students by making higher individual grades than the team average possible, while penalizing underperforming free riders by not benefiting from other student's performance. Application Design: The method allows students to continuously calibrate their own and their teammate's expectations and improve their peer score by adjusting their individual efforts. This feedback also requires students to practice professional communication, and in particular giving and receiving critical feedback, and thus is highly aligned with industry needs. Findings: Results evaluated over three iterations of the assessment process indicate a weak positive correlation (0.26) of the peer evaluation with the individual instructor-graded deliverables as well as the individual student grade point average (GPA, 0.23). Further, survey-based data indicate student agreement that the PF is a fair reflection of the individual performance, and a neutral perceived overall assessment system effectiveness, with reported primary barriers being the difficulty in assigning fair peer grades and of open, critical discussion.

The University of Maine Stormwater Management and Research Team (SMART) program began in 2014 with the goal of creating a diverse science-technology-engineering-math (STEM) pathway with community water research. The program engages female and underrepresented minority high school students in locally relevant STEM research. It focuses on creating educational experiences that are active and relevant to students that build confidence, connect knowledge and skills directly to solving problems in local communities, and support student cultural identities. The core tools of the SMART program are resources and relationships: university-designed or commercial water data collection equipment, data loggers and chemistry supplies, on-campus science and engineering training for teacher-mentors and students, and a community mentor network. The program supports an annual summer institute that trains both students and teacher-mentors and academic-year student research projects. SMART groups are formed at local schools or community centers. Activities revolve around engaging students in citizen-science to expand their understanding of the environment, developing community strategies to address the complex problem of stormwater pollution, and using the tools of science, engineering, and technology effectively. In addition, the program supports teachers and students in reaching out to local science and engineering professionals to form a mentor network for student research. Over 3 years, 220 students and 25 teachers have been trained in the science and engineering of stormwater, having taken and recorded over 4000 local water measurements (i.e., temperature, conductivity, pH). In all cohorts to date, over 75% of student participants have self-identified as either female or a racial minority. Of approximately 125 currently college-eligible former and current SMART students, more than 41% have been accepted or are enrolled in a secondary STEM degree program. In pre- and post-program surveys, female and underrepresented minority students reported that SMART activities and their relationship with mentors have increased their awareness of how stormwater affects the community and increased their interest in pursuing a STEM career. With its focus on problem-solving at the community level, SMART supports students in active, local, and culturally relevant science and engineering experiences that contribute to building their confidence and affirming their decision to pursue post-secondary STEM careers.

The study of unsteady aerodynamic phenomena in wind tunnels is supported by gust-generating devices capable of generating adjustable magnitude and periodicity velocity fluctuations in a flowfield. Gusts are typically generated actively by introducing moving vanes to direct the flow, or passively by tailoring the boundary layer growth and shape in the tunnel. The flow facility used here is a student-built closed-return low-speed wind tunnel, with a test section size of 750 mm × 750 mm and a maximum speed of 25 m/s. A two-vane gust generator utilizing NACA0018 airfoil sections of 150 mm chord length was designed and installed upstream of the test section. The flowfield was mapped with the installed vanes with and without gust actuation, utilizing a hot wire system. The tunnel with gust vanes exhibits a spatially uniform baseline turbulence intensity of 5%, with a steady state velocity deficit of 1 m/s in the vane–wake region. Upon introducing the gusting conditions at vane deflection angles of up to ±45°, velocity differences of up to 4 m/s were attained at 18 m/s freestream velocity at oscillation frequencies ranging between 1 Hz and 2 Hz.