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A platform for research: civil engineering, architecture and urbanism
Parametric Stock Flow Modelling of Historical Building Typologies
While the construction sector is a major consumer of new raw materials, it also contributes largely to waste generation. Therefore, improved estimates of demolition waste and the identification of components and materials for reuse or recycling are an important prerequisite for better waste management in the construction sector. The aim of this study is to investigate the differences and possibilities between static bottom-up models and parametric BIM-integrated bottom-up models for material flow analyses to predict the building material composition of historical building typologies. Findings are, when comparing the predictive capabilities of the pre-audit model with a novel implementation of a generative parametric model, that we see a drastic improvement in the error-reduction. The test models and test cases are based on limited data but given the significance of the magnitude of variance between the two models, there is a strong indication that the most precise modelling approach is obtained when utilizing a parametric model based on historical building traditions. In contrast, the use of normal static prediction-based modelling is hard to justify since data on demolition waste is of poor quality. Combining the two modelling approaches might present a new alternative to reduce factor errors in predictions of demolition waste and create a foundation for better pre-demolition audits and BIM models for material passports.
Parametric Stock Flow Modelling of Historical Building Typologies
While the construction sector is a major consumer of new raw materials, it also contributes largely to waste generation. Therefore, improved estimates of demolition waste and the identification of components and materials for reuse or recycling are an important prerequisite for better waste management in the construction sector. The aim of this study is to investigate the differences and possibilities between static bottom-up models and parametric BIM-integrated bottom-up models for material flow analyses to predict the building material composition of historical building typologies. Findings are, when comparing the predictive capabilities of the pre-audit model with a novel implementation of a generative parametric model, that we see a drastic improvement in the error-reduction. The test models and test cases are based on limited data but given the significance of the magnitude of variance between the two models, there is a strong indication that the most precise modelling approach is obtained when utilizing a parametric model based on historical building traditions. In contrast, the use of normal static prediction-based modelling is hard to justify since data on demolition waste is of poor quality. Combining the two modelling approaches might present a new alternative to reduce factor errors in predictions of demolition waste and create a foundation for better pre-demolition audits and BIM models for material passports.
Parametric Stock Flow Modelling of Historical Building Typologies
Kristoffer Negendahl (author) / Alexander Barholm-Hansen (author) / Rune Andersen (author)
2022
Article (Journal)
Electronic Resource
Unknown
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