4.7 Article

Lumped parameter models for building thermal modelling: An analytic approach to simplifying complex multi-layered constructions

Journal

ENERGY AND BUILDINGS
Volume 60, Issue -, Pages 174-184

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2013.01.014

Keywords

Lumped Parameter Model; Building; Thermal simulation; Construction; Dominant layer model; DLM

Funding

  1. Wates Family Enterprise Trust
  2. EPSRC [EP/J002380/1]
  3. EPSRC [EP/J002380/1] Funding Source: UKRI
  4. Engineering and Physical Sciences Research Council [EP/J002380/1] Funding Source: researchfish

Ask authors/readers for more resources

There are many sophisticated building simulators capable of accurately modelling the thermal performance of buildings. Lumped Parameter Models (LPMs) are an alternative which, due to their shorter computational time, can be used where many runs are needed, for example when completing computer-based optimisation. In this paper, a new, more accurate, analytic method is presented for creating the parameters of a second order LPM, consisting of three resistors and two capacitors, that can be used to represent multi-layered constructions. The method to create this LPM is more intuitive than the alternatives in the literature and has been named the Dominant Layer Model. This new method does not require complex numerical operations, but is obtained using a simple analysis of the relative influence of the different layers within a construction on its overall dynamic behaviour. The method has been used to compare the dynamic response of four different typical constructions of varying thickness and materials as well as two more complex constructions as a proof of concept. When compared with a model that truthfully represents all layers in the construction, the new method is largely accurate and outperforms the only other model in the literature obtained with an analytical method. (C) 2013 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available