EARLY CAREER AWARDS SELECTED VIRTUALLY

August 4, 2020

During its virtual Council meeting July 17-24, ELECTRI International heard five faculty members offer outstanding proposals for ELECTRI’s consideration. During a live Q & A, each researcher had the opportunity to explain and expand upon the projects being offered to the EC industry.

Hala Nassereddine, University of Kentucky, was selected for the Russell J Alessi Early Career Award for her proposal: Allocating and Leveraging BIM Efforts for Electrical Contractors. She addressed the increased complexity of construction projects coupled with the increase in customer expectations as a factor fueling electrical contractor interest in innovation as a source of competitive advantage.

To unlock the full potential of VR/AR, it is important to develop reliable BIM models that are frequently updated, but it is not practical to provide a one-size-fits-all strategy to allocate modeling efforts. The main objective of this research will be to investigate the level of effort needed to develop/update BIM models. The report will provide electrical contractors with a set of tools to leverage their BIM resources before and during construction.

Sogand Hasanzadeh, Purdue University, was named the Thomas Glavinich Early Career Award winner for her proposal: Examining a Latent Side-Effect of Electrical Safety Interventions among T&D Line Workers.  On-the-job injuries in the T&D sector still occur even after implementing safety interventions. The high rate of injuries and fatalities suggests the possibility of a latent side effect of safety interventions, known as risk compensation. The project’s overall objective will be to examine empirically the risk-taking behavior of T&D line workers as a function of the number and type of fall and electrical safety interventions in place for their protection.

The investigator will use immersive mixed-reality (Vitual+Augmented+Physical Reality) combined with wearable sensors to track workers’ motions, localize their positions, obtain real time musculoskeletal data, monitor their psychophysiological responses, and create the perceptions necessary to capture the naturalistic behavior of line installers and repairers.  She will identify at-risk T&D line workers who are more likely to be involved in risk-compensatory behavior; examine whether safety interventions might become counterproductive because of the risk-compensation, productivity demand, and time pressure for early completion of jobs; and propose strategies to improve T&D training programs.