posted on 2018-05-14, 10:47authored byJason Hillary, Ed J. Walsh, Amip Shah, Rongliang Zhou, Pat A. Walsh
Building energy simulations have found widespread use as decision-making tools for determining design and retrofitting
actions. Despite their popularity, there exists a well-reported issue regarding the numerical treatment of structural thermalstorage
components in these models. The optimal means of discretising multi-layer structures is complicated by the different
thermo-physical properties, material configurations and boundary conditions encountered within building energy models.
This paper addresses this information gap by proposing a methodology that can be universally applied to all multi-layer
structures, ensuring accurate predictions while avoiding excessive computational cost. Governing dimensionless quantities
of Biot and Fourier numbers are utilised within the discretisation process, making the methodology equally applicable to
all materials. The presented methodology also accounts for the configuration of materials within multi-layer structures
when assigning discretisation levels, leading to nodes being distributed in accordance with expected thermal gradients. The
proposed discretisation methodology has been examined for a number of boundary conditions and wall types with excellent
prediction accuracy achieved throughout. Additionally, the utility of resistance-only layers has been explored as a means of
increasing computational efficiency. This highlighted the importance of considering both layer position and local thermal
properties when simulating multi-layer structures.
Funding
Using the Cloud to Streamline the Development of Mobile Phone Apps
This is the author’s version of a work that was accepted for publication in Energy and Buildngs. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Energy and Buildings, 2018, 170, pp. 122-133, https://doi.org/10.1016/j.enbuild.2018.04.009