0000000000053490
AUTHOR
Merethe Solvang Tingstveit
Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II
Detailed parametric analysis and measurements are required to reduce building energy usage while maintaining acceptable thermal conditions. This research suggested a system that combines Building Information Modeling (BIM), machine learning, and the non-dominated sorting genetic algorithm-II (NSGA II) to investigate the impact of building factors on energy usage and find the optimal design. A plugin is developed to receive sensor data and export all necessary information from BIM to MSSQL and Excel. The BIM model was imported to IDA Indoor Climate and Energy (IDA ICE) to execute an energy consumption simulation and then a pairwise test to produce the sample data set. To study the data set a…
Hygrothermal conditions in Cross Laminated Timber (CLT) dwellings
The use of CLT has been increasing the last decade, and a subsequently focus on documentation of the accompanying indoor climate and exposed wooden surfaces on human well-being. This study presents the results of a measurement campaign conducted over one year of a CLT apartment building in Grimstad, Norway. The apartment building consists of three floors with 35 apartments and comply with the Norwegian passive house standard and energy grade A. Measurements of the relative humidity (RH), indoor air temperature and wood moisture content (MC) were performed in the exposed CLT spruce panels in three apartments in two different floors. The results from the three apartments show a relatively sma…