Airport agencies spend millions of dollars to remove ice and snow from airport pavement surfaces to achieve accessible, safe, and sustainable operations during the winter. Electrically conductive concrete (ECON) based heated pavement system (HPS) has gained attention as a promising alternative technology for preventing snow and ice accumulation by maintaining pavement surface temperatures above the freezing point. The objective of this study was to demonstrate the world’s first full-scale ECON-based HPS at a U.S. airport. Two ECON slabs were designed and constructed in the General Aviation (GA) apron at the Des Moines International Airport (DSM), Iowa in 2016. Systematic design components were identified, and construction procedures were developed and implemented for ECON-based HPS. Using collected sensor data, the performance of the constructed and remotely-operated ECON slabs was evaluated under real weather conditions at DSM in the 2016–2017 winter season. The results demonstrate that ECON-based HPS have promising deicing and anti-icing capacities, promising to provide uniform heat distribution and prevent snow and ice accumulations on the entire area of application under various winter weather conditions, including extreme cold weather (i.e., arctic blasts).
Abstract:In recent years, the use of UAS (Unmanned Aerial Systems) has moved beyond the realm of military operations and has made its way into the hands of consumers and commercial industries. Although the applications of UAS in commercial industries are virtually endless, there are many issues regarding their operations that need to be considered before these valuable pieces of equipment are allowed for widespread civil use. Currently, UAS operations in the public domain are guided and controlled by the FAA Part 107 rules after overwhelming public pressure caused by the earlier 333 exemption. In order to approach such larger issues, this paper will exploit the use of value models, which will help to quantify how the different environmental and operational scenarios play a role in UAS operations based on the task being performed. The primary aim of this research is to use the attributes from key factors of the UAS such as the autonomy levels (AL) and technology readiness levels (TRL) along with their operating scenario factors, such as the environmental complexity and task complexity, based on the operating environment in which a UAS performs its task. To analyze the performance of autonomous UAS in different operational scenarios, the physical characteristics and class of a UAS may be linked to its AL and TRL. Using these parameters, the risks faced by the UAS in a particular mission are quantified and a value is assigned to the abstract entities involved. Although there are many critical questions with respect to good practices to be followed by UAS operators in order to obtain valuable data and information on the structures being scanned and monitored, there are many other challenges with regards to large scale operations of UAS such as the ethical, legal and societal implications that have to be addressed.
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