Dynamic modeling and simulation of frost and defrost conditions for refrigeration systems
type: CreativeWork
description: Heating and cooling systems are widely used throughout the world in an array of applications as a means of providing thermal energy transfer. Recent decades have seen economic and environmental awareness come to a forefront and innovation resultingly being pushed toward a standard of greater performance and efficiency. With their nearly universal presence, it therefore comes as no surprise that heating and cooling systems have also been subject to such guidelines. One of the biggest contributors to performance degradation and inefficiency in air conditioning and refrigeration applications today is the accumulation of frost on heat exchanger surfaces. The presence of frost often incurs a decrease in the amount of cooling capacity achievable, resulting in the need for defrost cycles. Much work has been done to date to establish strategies aimed at improving defrost decision making and allow for improved operational efficiency. Nonetheless, some of the most common methods still permit defrost to run when unnecessary. Modeling has therefore been used to provide greater insight and prediction capability of these processes. However, current methods lack the qualities necessary to allow for the implementation of a model-based defrost strategy aimed at further improving upon existing defrost techniques. This thesis makes contributions toward improving refrigeration operational efficiency through the development of a model for dynamically simulating refrigeration systems operating under both frost and defrost conditions. Modeling provides the tools necessary to form more accurate defrost decisions through a greater understanding of frosting behavior and its effect on system performance. Such insight is achieved by means of developed frost growth and melt models discussed in the first part of this thesis. Validation results demonstrate good prediction capability of both frost thickness as a function of time and estimated time to defrost. The second portion of this thesis addr…
abstract: Heating and cooling systems are widely used throughout the world in an array of applications as a means of providing thermal energy transfer. Recent decades have seen economic and environmental awareness come to a forefront and innovation resultingly being pushed toward a standard of greater performance and efficiency. With their nearly universal presence, it therefore comes as no surprise that heating and cooling systems have also been subject to such guidelines. One of the biggest contributors to performance degradation and inefficiency in air conditioning and refrigeration applications today is the accumulation of frost on heat exchanger surfaces. The presence of frost often incurs a decrease in the amount of cooling capacity achievable, resulting in the need for defrost cycles. Much work has been done to date to establish strategies aimed at improving defrost decision making and allow for improved operational efficiency. Nonetheless, some of the most common methods still permit defrost to run when unnecessary. Modeling has therefore been used to provide greater insight and prediction capability of these processes. However, current methods lack the qualities necessary to allow for the implementation of a model-based defrost strategy aimed at further improving upon existing defrost techniques. This thesis makes contributions toward improving refrigeration operational efficiency through the development of a model for dynamically simulating refrigeration systems operating under both frost and defrost conditions. Modeling provides the tools necessary to form more accurate defrost decisions through a greater understanding of frosting behavior and its effect on system performance. Such insight is achieved by means of developed frost growth and melt models discussed in the first part of this thesis. Validation results demonstrate good prediction capability of both frost thickness as a function of time and estimated time to defrost. The second portion of this thesis addr…
author: Gonzales, Lindsey M
language: en
keywords: frost, defrost, refrigeration, modeling, simulation, dynamic, coupled
date published: 2015-07-22T22:17:31Z
date modified: 2026-07-22T22:26:11Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/78475