TY - GEN
T1 - NLP-based semantic model healing for calculating LCA in early building design stages
AU - Forth, K.
AU - Abualdenien, J.
AU - Borrmann, A.
N1 - Publisher Copyright:
© 2023 the Author(s).
PY - 2023
Y1 - 2023
N2 - To limit the global warming, the environmental impacts of new buildings need to be quantified and optimized already in the early design stages. Semantically rich models, such as Building Information Modeling (BIM), facilitate deriving consistent and automated quantity take-offs of the relevant components for calculating whole building life cycle assessments (LCA). A particular challenge is that early-stage BIM models typically lack stringency in terms of component modeling and material classification. Hence, this paper presents a methodology for enriching knowledge and characteristics from the coarse information available at the early design stages, in a process denoted as semantic model healing. In more detail, the proposed method employs different Natural Language Processing (NLP) strategies to increase the performance of automatically matching materials defined in a BIM model to a knowledge database with environmental indicators of commonly used components, facilitating a seamless LCA in the early stages of design.
AB - To limit the global warming, the environmental impacts of new buildings need to be quantified and optimized already in the early design stages. Semantically rich models, such as Building Information Modeling (BIM), facilitate deriving consistent and automated quantity take-offs of the relevant components for calculating whole building life cycle assessments (LCA). A particular challenge is that early-stage BIM models typically lack stringency in terms of component modeling and material classification. Hence, this paper presents a methodology for enriching knowledge and characteristics from the coarse information available at the early design stages, in a process denoted as semantic model healing. In more detail, the proposed method employs different Natural Language Processing (NLP) strategies to increase the performance of automatically matching materials defined in a BIM model to a knowledge database with environmental indicators of commonly used components, facilitating a seamless LCA in the early stages of design.
UR - http://www.scopus.com/inward/record.url?scp=85160441633&partnerID=8YFLogxK
U2 - 10.1201/9781003354222-10
DO - 10.1201/9781003354222-10
M3 - Conference contribution
AN - SCOPUS:85160441633
SN - 9781032406732
T3 - eWork and eBusiness in Architecture, Engineering and Construction - Proceedings of the 14th European Conference on Product and Process Modelling, ECPPM 2022
SP - 77
EP - 84
BT - eWork and eBusiness in Architecture, Engineering and Construction - Proceedings of the 14th European Conference on Product and Process Modelling, ECPPM 2022
A2 - Hjelseth, Eilif
A2 - Sujan, Sujesh F.
A2 - Scherer, Raimar J.
PB - CRC Press/Balkema
T2 - 14th European Conference on Product and Process Modelling, ECPPM 2022
Y2 - 14 September 2022 through 16 September 2022
ER -
