Abstract
Enhanced fabric performance is fundamental to reduce the energy consumption in buildings. Research has shown that the thermal mass of the fabric can be used as a passive design strategy to reduce energy use for space conditioning. Concrete is a high density material, therefore said to have high thermal mass. Insulating concrete formwork (ICF) consists of cast in-situ concrete poured between two layers of insulation. ICF is generally perceived as a thermally lightweight construction, although previous field studies indicated that ICF shows evidence of heat storage effects.There is a need for accurate performance prediction when designing new buildings. This is challenging in particular when using advanced or new methods (such as ICF), that are not yet well researched. Building Performance Simulation (BPS) is often used to predict the thermal performance of buildings. Large discrepancies can occur in the simulation predictions provided by different BPS tools. In many cases assumptions embedded within the tools are outside of the modeller's control. At other times, users are required to make decisions on whether to rely on the default settings or to specify the input values and algorithms to be used in the simulation. This paper investigates the “modelling gap”, the impact of default settings and the implications of the various calculation algorithms on the results divergence in thermal mass simulation using different tools. ICF is compared with low and high thermal mass constructions. The results indicated that the modelling uncertainties accounted for up to 26% of the variation in the simulation predictions.
Highlights
In an attempt to combat the impact of climate change, governments have set targets to reduce energy consumption and CO2 emissions
Annual and hourly simulation results obtained by the two Building Performance Simulation (BPS) tools when the user relies on the default setting are presented first
To be able to support the commercial proposition of new materials and innovative building technologies it is important to predict and communicate their thermal behaviour and energy performance accurately
Summary
In an attempt to combat the impact of climate change, governments have set targets to reduce energy consumption and CO2 emissions. In Europe, 40% of the total energy consumption and 36% of the total CO2 emissions derive directly from the built environment [1]. Energy efficient buildings steer a new era of development, including new materials, innovative envelope technologies and advanced design ideas [2,3,4]. Improvements in building energy efficiency are mainly focused on reduction of fabric heat losses (reduced infiltration, better insulation etc.) and the optimal use of solar gains [5]. To quantify the potential of new materials and technologies in energy consumption savings and CO2 emission reductions, the use of reliable dynamic Building Performance Simulation (BPS) is essential. Simulation-based support for innovative building envelope technologies
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