TY - GEN
T1 - CONNECTED DESIGN DECISION NETWORKS
T2 - 6th International Conference Central Europe towards Sustainable Building, CESB 2022
AU - Forth, Kasimir
AU - Schneider-Marin, Patricia
AU - Theißen, Sebastian
AU - Höper, Jannick
AU - Svane, Nanna Dyrup
AU - Borrmann, André
N1 - Publisher Copyright:
© 2022 The Author(s). Licensed under a CC-BY 4.0 licence.
PY - 2022/12/21
Y1 - 2022/12/21
N2 - Life Cycle Assessment (LCA) has become the standard method to evaluate environmental impact throughout the life cycle of buildings. However, detailed data about the future building as well as knowledge about the mutual influence of decisions concerning the various disciplines involved are often missing in early design phases, otherwise known to bear the highest potential for emissions savings. Hence, a meaningful basis for decision making is lacking. This study suggests a method to digitally represent decisions and their interdependencies in early design phases and visualize their possible consequences for the life cycle of the future building. The method is based on identification of relevant processes and tasks concerning architecture and Heating Ventilation and Air Conditioning (HVAC). Decisions trees of these tasks are used as a point of departure. Connecting the decision trees to a multidimensional, Connected Design Decision Network (CDDN) enables an interdisciplinary design team to pinpoint strategic decision nodes with comparatively more interdependencies with other subsets and high influence on LCA results. We believe that a transparent decision making in early design stages can be valuable to both the design team as well as clients and contractors and bear potential for an increased mutual awareness minimizing late and expensive redesigns.
AB - Life Cycle Assessment (LCA) has become the standard method to evaluate environmental impact throughout the life cycle of buildings. However, detailed data about the future building as well as knowledge about the mutual influence of decisions concerning the various disciplines involved are often missing in early design phases, otherwise known to bear the highest potential for emissions savings. Hence, a meaningful basis for decision making is lacking. This study suggests a method to digitally represent decisions and their interdependencies in early design phases and visualize their possible consequences for the life cycle of the future building. The method is based on identification of relevant processes and tasks concerning architecture and Heating Ventilation and Air Conditioning (HVAC). Decisions trees of these tasks are used as a point of departure. Connecting the decision trees to a multidimensional, Connected Design Decision Network (CDDN) enables an interdisciplinary design team to pinpoint strategic decision nodes with comparatively more interdependencies with other subsets and high influence on LCA results. We believe that a transparent decision making in early design stages can be valuable to both the design team as well as clients and contractors and bear potential for an increased mutual awareness minimizing late and expensive redesigns.
KW - LCA
KW - Multi-Criteria Decision Making (MCDM)
KW - early design phase
KW - integrated design process
KW - interdisciplinary decision network
UR - http://www.scopus.com/inward/record.url?scp=85159951207&partnerID=8YFLogxK
U2 - 10.14311/APP.2022.38.0124
DO - 10.14311/APP.2022.38.0124
M3 - Conference contribution
AN - SCOPUS:85159951207
T3 - Acta Polytechnica CTU Proceedings
SP - 124
EP - 130
BT - Central Europe towards Sustainable Building 2022, CESB 2022
A2 - Sojkova, Katerina
A2 - Hajek, Petr
A2 - Tywoniak, Jan
A2 - Horicka, Jana
A2 - Lupisek, Antonin
PB - Czech Technical University in Prague
Y2 - 4 July 2022 through 6 July 2022
ER -