Kristen S. Cetin

Thermal comfort evaluation for mechanically conditioned buildings using response surfaces in an uncertainty analysis framework

An uncertainty analysis methodology is proposed to aid in quantifying the risks of thermal comfort under-performance posed by changes to variations in physical and operational characteristics of a building and its environment. This includes those implemented for building energy savings, peak electricity load reductions, or those due to climatic changes. Using building performance data as input, a response surface methodology is used to develop a model to predict building thermal performance for ranges of user-defined design variables. This model is verified for accuracy using in- and out-of-sample data. Uncertainly analysis is then used to estimate the probability of achieving an acceptable threshold of thermal comfort performance. A case study is presented to demonstrate the implementation and interpretation of the results of this methodology, which evaluates the effects of a 1-h demand response event on thermal comfort of a residential mechanically-conditioned building. The case study finds that a second-order response surface provides a reasonably accurate model of thermal comfort. For the studied single family home, compared to varying the air exchange rate, the indoor set-point temperature has a greater influence on achieving an acceptable level of thermal comfort.

Characterizing large residential appliance peak load reduction potential utilizing a probabilistic approach

This research investigates the demand response potential of four electric grid-connected large residential appliances, including refrigerators, clothes washers, clothes dryers, and dishwashers. Field-collected energy use data from these applinaces in 326 residential buildings is collected for a 1-year period and analyzed. Uncertainty analysis is based on the Monte Carlo simulation method, showing the different possible ranges of demand response for each appliance. Clothes dryers are found to have the strongest demand response potential, due in part to their high power demand when on. However this high peak reduction occurs in the afternoon and evening only, as dryers are found to be used very little in the night and morning. Refrigerators provide the second strongest demand response potential, in part due to the nearly 100% of residential buildings that have one or more of them, and the higher predictability of their electricity demand behavior. In addition, unlike dryers, refrigerators have a similar demnad response potential at all times of the day. Clothes washers and dishwasher were found to have the least demand response potential. Results of this work are intended to provide updated information on power demand and time of use of appliances and a methodology for assessment of demand response and peak load reduction of smart applinaces on a house-by-house or community scale.

Design and Construction of the World’s First Full-Scale Electrically Conductive Concrete Heated Airport Pavement System at a U.S. Airport

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).

Construction Techniques for Electrically Conductive Heated Pavement Systems

Ice and snow accumulation on airport paved surfaces has the potential to cause fatal accidents and monetary loss due to flight delays and cancellations. Traditional de-icing methods involving the application of chemicals or salt and employing large machines can create negative environmental and structural impact on airport infrastructure systems. These methods are also considered to be labor intensive and a safety hazard, especially in congested areas such as aprons. Heated pavement systems using electrically conductive concrete (ECON) have been proposed as a promising alternative technology for preventing ice accumulation and mitigating the adverse effects of using traditional snow removal methods. The objective of this study is to present information and experience about the design, construction procedures, and performance of heated pavement systems using jointed plain concrete pavements for the construction of large-scale heated airport pavements. It is based on detailed field demonstration of the electrically conductive concrete (ECON) heated pavement system (HPS) at the north general aviation (GA) apron of the Des Moines International Airport (DSM) in Iowa, in collaboration with contractors, and airport staff representatives. The expected outcome of this study will help the construction industry to better understand optimal ECON construction methods.