Towards a pre-design method for low carbon architectural strategies

To face climate change, Switzerland proposes the 2050 energy strategy by fixing greenhouse gas (GHG) emission targets for the built environment. Designers will then have to increase operating performances while inimizing embodied impacts. This represents an issue for the building design process. In addition, there is a relationship between the design efficiency and the early integration of the knowledge about design. The purpose of this paper is to highlight the potential of a pre-design method to identify the building design parameters that reach the 2050 climate change objectives. To that end, four major steps are developed in this project. First, design parameters (e.g. wall thermal transmittance) which influence the building GHG emissions the most, are identified thanks to a literature review. Morris method (Saltelli et al, 2004) is used to create combinations of design parameters changing their values one by one. Secondly, these combinations are attributed to architectural feasibility studies (Sinclair, 2013) developed in the brief design phase to perform lifecycle analysis. Thirdly, KBOB database (KBOB et al., 2014) and lifetime of components proposed by PI-BAT were used for assessing GHG emissions. Lesosai software was used for primary energy assessment. Lastly, the combinations of design parameters and their relative GHG emissions are interpreted with data mining and visualization techniques. The smart living lab building has been chosen as a case study: this building aims at achieving the 2050 goals of the 2000-watt society vision and will be built by 2020 in Fribourg, Switzerland. Thanks to the preliminary results it is possible to rank the design parameters according to their GHG contribution, in order to highlight them during the early building design stage. The method offers combinations of design parameters allowing to reach the 2050 climate change objectives. Data mining and visualization enable designers to easily find the values of these parameters to fit into the architectural strategy. In order to offer a wider range of design parameter values, techniques to enhance the database should be further investigated.

Published in:
Proceedings of PLEA 2016, 32th international Conference on Passive and Low Energy Architecture
Presented at:
PLEA2016, Los Angeles, USA, July 11-13, 2016

 Record created 2016-01-07, last modified 2018-03-18

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