CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id caadria2023_403
authors Kim, Jong Bum, Kim, Seongchan and Aman, Jayedi
year 2023
title An Urban Building Energy Simulation Method Integrating Parametric BIM and Machine Learning
doi https://doi.org/10.52842/conf.caadria.2023.1.665
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 665–674
summary This research investigates a method of urban building energy simulation (UBES) by integrating Building Information Modeling (BIM), building simulation, and algorithm-based prediction to forecast the impact of surrounding conditions. In the urban context, building energy performances are determined not only by the individual building design but also by the building's surrounding context. Many energy performances are sensitive to outdoor and surrounding building conditions, such as neighbouring building volumes, heights, and spaces between buildings. However, such surrounding conditions were overlooked because they can exponentially increase the complexity of urban modeling and simulation. In that regard, the research sought to investigate a novel framework to take advantage of accurate performance simulations and algorithm-based fast predictions. This paper presents our UBES method implemented from three research phases: (i) building a parametric urban model in BIM to provide simulation inputs, (ii) creating a parametric simulation interface to produce training and validation data, and (iii) creating a prediction interface using a Support Vector Machine (SVR) algorithm. Lastly, the paper elaborates on the findings from the prediction results.
keywords Urban Energy Simulation, Solar Accessibility, Surrounding Conditions, Parametric BIM, Machine Learning, Support Vector Machine, Sustainable Cities and Communities
series CAADRIA
email
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