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Research Papers

Modeling Phase Change Materials With Conduction Transfer Functions for Passive Solar Applications

[+] Author and Article Information
Jason P. Barbour

 University of Virginia, Department of Civil Engineering, P.O. Box 400742, Charlottesville, VA 22904-4742jpb3h@virginia.edu

Douglas C. Hittle

 Colorado State University, Department of Mechanical Engineering, Solar Energy House 2, Fort Collins, CO 80523hittle@engr.colostate.edu

J. Sol. Energy Eng 128(1), 58-68 (Mar 16, 2005) (11 pages) doi:10.1115/1.2000977 History: Received May 13, 2003; Revised March 16, 2005

The use of passive solar design in our homes and buildings is one way to offset the ever-increasing dependence on fossil fuels and the resulting pollution to our air, our land, and our waters. A well-designed sunroom has the potential to reduce the annual heating loads by one-third or more. By integrating phase change materials (PCMs) into building elements, such as floor tile and wallboard, the benefits of the sunroom can be further enhanced by providing enhanced energy storage. To maximize benefits from PCMs, an engineering analysis tool is needed to provide insight into the most efficient use of this developing technology. Thus far, modeling of the PCMs has been restricted to finite difference and finite element methods, which are not well suited to inclusion in a comprehensive annual building simulation program such as BLAST or EnergyPlus . Conduction transfer functions (CTFs) have long been used to predict transient heat conduction in such programs. Phase changes often do not occur at a single temperature, but do so over a range of temperatures. The phase change energy can be represented by an elevated heat capacity over the temperature range during which the phase change occurs. By calculating an extra set(s) of CTFs for the phase change properties, the CTF method can be extended to include the energy of phase transitions by switching between the two (or more) sets of CTFs. This method can be used to accurately predict the internal and external temperatures of PCM-containing building elements during transient heat conduction. The amount of energy storage and release during a phase transition can also be modeled with this method, although there may be some degree of inaccuracy due to switching between two or more sets of CTFs. CTFs have the potential to provide an efficient method of modeling PCMs in annual building simulation programs, but more work is needed to reduce errors associated with their use.

Copyright © 2006 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

ORNL heat capacity relationship

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Figure 2

ORNL results, temperature profiles compared to model—Fig. 1 from Kedl (17), used with permission

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Figure 3

Simplified heat capacity relationship of Approaches 1 and 2

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Figure 4

Example: Possible arrangement of two sublayers

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Figure 5

Example: Heat capacity relationship of Approach 3

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Figure 6

Simplified heat capacity relationship of Approach 3a

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Figure 7

Experimental setup used by ORNL

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Figure 8

Temperature profile in standard wallboard

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Figure 9

1 sublayer, 2 zones (Approach 1)

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Figure 10

3 sublayers, 2 zones (Approach 2)

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Figure 11

1 sublayer, 4 zones (Approach 3a)

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Figure 12

3 sublayers, 4 zones (Approaches 2 and 3a combined)

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Figure 13

Predicted heat storage using 2 zone, 1 sublayer model

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Figure 14

Predicted storage using 2 zone, 1 sublayer model, normalized

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Figure 15

Predicted storage using 2 zone, 4 sublayer model, normalized

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Figure 16

Predicted storage using 4 zone, 1 sublayer model, normalized

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Figure 17

Predicted storage using 10 zone, 1 sublayer model, normalized

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Figure 18

Predicted storage using 4 zone, 3 sublayer model, normalized

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Figure 19

Predicted storage using 10 zone, 1 sublayer model, normalized

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Figure 20

Predicted storage using 10 zone, 1 sublayer model-correlated

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