Evaluation of discretized transport properties for numerical modelling of heat and moisture transfer in building structures

Graham H. Galbraith, Jintang Li, Jiansong Guo, David Kelly, R. Craig McLean, John Grunewald

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Over the past decade, a large number of numerical models have been developed to predict heat and moisture transfer within building envelopes. In these models, the moisture transfer mechanism has been described and correlated by reference to the various transport phenomena and corresponding theories, viz. heat transfer and fluid flow. However, predicting the coupled heat and moisture performance of a building construction has never been a straightforward task, since a steady state situation hardly ever occurs and the transport properties (heat and moisture) of a material vary with moisture content and temperature. This paper discusses the transport phenomenon and the various numerical algorithms used in the discretization equations and how different algorithms affect the modelled results. Computer simulations have been conducted for different building materials and material combinations and comparisons have been made to evaluate the selection of discretized transport properties. Discrepancies in results are demonstrated between different mathematical interpolations, namely the Resistance (R ) type formula and Linear ( L ) interpolation. Recommendations are given as guidance towards applying the most appropriate formulations for a given modelling scenario.
Original languageEnglish
Pages (from-to)240-260
Number of pages20
JournalJournal of Thermal Envelope and Building Science
Volume34
Issue number3
Publication statusPublished - 2001

Fingerprint

Transport properties
Moisture
Interpolation
Flow of fluids
Numerical models
Hot Temperature
Heat transfer
Computer simulation
Temperature

Keywords

  • moisture
  • numerical modelling
  • transport
  • building materials
  • heat
  • chemical engineering

Cite this

Galbraith, Graham H. ; Li, Jintang ; Guo, Jiansong ; Kelly, David ; McLean, R. Craig ; Grunewald, John. / Evaluation of discretized transport properties for numerical modelling of heat and moisture transfer in building structures. In: Journal of Thermal Envelope and Building Science. 2001 ; Vol. 34, No. 3. pp. 240-260.
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Evaluation of discretized transport properties for numerical modelling of heat and moisture transfer in building structures. / Galbraith, Graham H.; Li, Jintang; Guo, Jiansong; Kelly, David; McLean, R. Craig; Grunewald, John.

In: Journal of Thermal Envelope and Building Science, Vol. 34, No. 3, 2001, p. 240-260.

Research output: Contribution to journalArticle

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AU - Galbraith, Graham H.

AU - Li, Jintang

AU - Guo, Jiansong

AU - Kelly, David

AU - McLean, R. Craig

AU - Grunewald, John

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AB - Over the past decade, a large number of numerical models have been developed to predict heat and moisture transfer within building envelopes. In these models, the moisture transfer mechanism has been described and correlated by reference to the various transport phenomena and corresponding theories, viz. heat transfer and fluid flow. However, predicting the coupled heat and moisture performance of a building construction has never been a straightforward task, since a steady state situation hardly ever occurs and the transport properties (heat and moisture) of a material vary with moisture content and temperature. This paper discusses the transport phenomenon and the various numerical algorithms used in the discretization equations and how different algorithms affect the modelled results. Computer simulations have been conducted for different building materials and material combinations and comparisons have been made to evaluate the selection of discretized transport properties. Discrepancies in results are demonstrated between different mathematical interpolations, namely the Resistance (R ) type formula and Linear ( L ) interpolation. Recommendations are given as guidance towards applying the most appropriate formulations for a given modelling scenario.

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