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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/21274
Title: Numerical Investigation of One-Dimensional Storage Tank Models and the Development of Analytical Modelling Techniques
Authors: Unrau, Cody
Advisor: Lightstone, Marilyn
Department: Mechanical Engineering
Keywords: Thermal Storage;One-Dimensional Model;Solar Thermal;TRNSYS
Publication Date: Jun-2017
Abstract: To assess the long-term performance of a solar thermal system, mathematical models that accurately capture the effects of heat transfer within and interactions between individual components are required. For solar domestic hot water systems, the components can include the solar collectors, storage tanks, heat exchangers, pumps, and associated piping. In addition, weather data and demand profiles are also required. Simplified models for each component are needed to reduce the computational time required to run long-term simulations. The simplified models, however, must also be sufficiently accurate in order to provide meaningful system-level results. Accurate prediction of the temperature profiles in the storage tanks of these systems is important since the temperature within the tank has a large impact on the efficiency of the entire system. TRNSYS, which is a commercial code commonly used for such simulations, contains a variety of different one-dimensional storage tank models. Previous research has indicated that these models have deficiencies in predicting experimental data. Therefore, this thesis is focussed on the analysis of the tank modelling used in TRNSYS. Results of this thesis show that the poor predictions are a result of numerical diffusion due to insufficient grid resolution. The correct theoretical profiles could be obtained by using a large number of nodes. However, this would lead to a significant increase in computational time. Alternative modelling strategies were also developed using analytical techniques to more accurately predict the temperature profiles within a storage tank while keeping a relatively low computational cost. Different models were created which considered the different mixing mechanisms present in a storage tank, such as increasing inlet temperatures with time, heat losses to the surroundings, tank wall heat conduction, and inlet jet mixing.
URI: http://hdl.handle.net/11375/21274
Appears in Collections:Open Access Dissertations and Theses

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