Indoor Climate Simulation

At the IOER, the overheating risk in buildings and the effectiveness of adaptation measures to reduce this risk are analysed primarily by means of thermal, dynamic building simulations. For the building simulations, the building under investigation is transferred into a three-dimensional simulation model that, in addition to the physical properties of the walls and ceilings, also takes into account schedules for the use of the rooms and the heat loads released as a result (appliances, lighting, presence of people) as well as the effect of window ventilation. In addition to these parameters, the meteorological weather or climate data set (in hourly resolution) is decisive in determining how strong the overheating intensity is in the building.


The quality of the simulation models and their results are checked by means of indoor climate measurements (LINK IN). This involves checking whether the measured indoor temperature curve corresponds to the simulated one (see Schünemann et al. 2021). Within the joint projects HeatResilientCity and Klimakonform, three apartment buildings, a school, a kindergarten and administrative buildings (see figures) were examined in this way for their indoor overheating risk.


The approach of building typology (e.g. Schinke et al. 2012) is used here to obtain transferable statements regarding the heat load of buildings of the same typology (e.g. Gründerzeit buildings, prefabricated buildings, high-rise buildings) from individual simulated reference buildings.

Significant studies by the IOER on overheating risk in buildings are based on building simulations:

  • The influence of building design and climate was shown in a comparison of two apartment buildings in Germany and South Korea (Schünemann et al. 2022).
  • The dependence of indoor overheating risk on the location of the flat within the apartment building showed that the top floors and rooms with windows facing east and west are particularly prone to high heat load (Schünemann et al. 2020, Schiela et al. 2020).
  • The comparison of the effectiveness of different adaptation measures on the heat load in apartment buildings (Schünemann et al. 2020).
  • For the climate in Germany, it was also shown how significant the influence of night-time ventilation behaviour is on the indoor overheating intensity in the dwelling and how important it is that this can be realistically represented by taking into account wind- and temperature-induced air exchange in thermal building simulation (Schünemann et al. 2021b)
  • And finally, the analysis of the effect of open space in the city on the heat load in the building using the model chain microscale urban climate simulation, is recognised as the - thermal building simulation in cooperation with the Technical University of Dresden (Chair of Meteorology) (Schuenemann et al., submitted 2022)

Further German Language Literature:

Schiela, David; Schünemann, Christoph: Strategien gegen die Überhitzung, In: Gebäude-Energieberater (2020) 5, S. 20-23 www.geb-info.de/schwerpunkt/strategien-gegen-die-ueberhitzung

Westermann, Janneke R.; Bolsius, Jens; Kunze, Stefanie et al.: Hitzeanpassung von Stadtquartieren. Akteursperspektiven und Umsetzungsansätze, In: GAIA - Ecological Perspectives for Science and Society 30 (2021) 4, S.257-267 doi.org/10.14512/gaia.30.4.9

 

Prefabricated b., Dresden

High-rise b., Seoul, Korea

"Gründerzeit" b., Erfurt

Administrative b., Naumburg

Kindergarten, Erfurt

School building, Plauen