Introducing microclimate into simulation models for buildings
Doctoral thesis
Permanent lenke
https://hdl.handle.net/11250/2824181Utgivelsesdato
2019Metadata
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Sammendrag
The contemporary sustainability imperativeness requires high performance
buildings. Smart solutions during the design or retrofitting phase can
significantly contribute towards decreasing the energy consumption and gas
emissions, as well as increasing the durability and life cycle of building
materials. An invaluable tool that can facilitate both the design and retrofitting
process is the building performance simulation. The optimization of building
simulation models can lead towards better decision-making, and subsequently
towards sustainability.
Climatic loads are one of the key variables in the building performance
simulation. However, the climatic loads acting on buildings are determined by
the micro scale climate. Buildings with the exact same geometry and
construction can be subjected to different climatic loads depending on the local
district morphology they belong to, even within the borders of the same city.
Increasing the accuracy of climatic loads by taking into consideration the
microclimate, will automatically increase the prediction accuracy of the
building performance simulation.
This PhD research project aims on improving aspects of the building
performance simulation by accounting for the microclimate. The climatedriven loads of wind, wind-driven rain and solar radiation acting on buildings
are defined with respect to the microclimate, and some methods to introduce
them in simulation models for buildings are investigated.
A simple hygrothermal model that can predict how the surface temperature
and moisture content vary spatially along building façades is developed. The
model is developed upon the basic principles of heat and moisture transport
within the context of building physics. The developed model takes into
consideration the microclimatic loads of wind-driven rain and solar radiation,
which are determined by the surroundings and the building’s geometry. In
addition, the building’s spatial architectural details are considered, thus
revealing areas of high-exposure or shelter from rain and solar radiation. As a
result, the climate-driven loads acting on the building façade investigated are
more accurately defined. In contrast to most of the contemporary simulation
models that treat façades uniformly, the developed model is able to predict the
spatial variations of surface temperature and moisture content along the
building façades. On-site surface temperature and moisture measurements in
two different façades verify the spatial accuracy of the model presented.
Furthermore, the micro-scale wind effects on buildings are researched. The
wind-induced pressurization of the building envelope is one of the driving
mechanisms of air infiltration, and air infiltration is crucial to the building
energy consumption. As a result, predicting with high accuracy the windinduced pressures acting on buildings can significantly improve the calculation
of air infiltration and consequently of building energy demands.
Full-scale measurements on two reference buildings reveal high spatial
pressure variations along the building façades. The measurements reveal that
the wind-induced pressure variations are essentially determined by the
building’s surroundings and geometry. A common method to express the windinduced pressure acting on a body is by means of wind pressure coefficients
(Cp). Therefore, the use of building-specific wind pressure coefficients as
appropriate boundary conditions that can introduce the microclimate into
building energy simulation is researched.
Building-specific wind pressure coefficients are calculated through full-scale
measurements and computational fluid dynamics (CFD) simulations. The
results show that building-specific wind pressure coefficients are able to
capture the microclimatic effect. The use of building-specific Cp values on
building energy simulations for the calculation of air infiltration is validated
against tracer gas measurements for a reference building. In contrast to the
conventional methods used for the air infiltration calculation, building-specific
wind pressure coefficients manage to account for the microclimate. The results
indicate that the prediction accuracy of calculated air infiltration rates using
building-specific Cp values is significantly higher than the rest of the methods.
Furthermore, the use of fluctuating building-specific Cp values is evaluated. The
Monte Carlo method is employed, and the probability distribution function
(pdf) of building-specific Cp values is combined with the wind speed pdf. Cross
validation with on-site measurements suggests that the statistical method can
improve even further the accuracy of the air infiltration calculation. Bærekraftig utvikling krever høyytelsesbygninger. Smarte løsninger i prosjektering av nye bygg og rehabilitering av eldre bygg kan bidra til å redusere energiforbruk og klimagassutslipp, samt å øke holdbarhet og levetid for bygningsmaterialer. Bygningssimulering (Building Performace Simulation, BPS) er et viktig verktøy for å tilrettelegge for både god prosjektering av nye bygg og rehabilitering av eldre bygg. Optimalisering av simuleringsmodeller for bygninger kan effektivisere beslutningsprosessene og bidra til bærekraftig utvikling.
Klimabelastninger er viktige variabler i BPS. Opptredende klimabelastning på en bygning påvirkes av omkringliggende mikroklima. Bygninger med lik oppbygning og identisk geometrisk utforming kan være utsatt for ulike klimabelastninger innenfor samme bygrense, på grunn av ulik omkringliggende topologi. Ved å ta hensyn til mikroklima kan man oppnå mer nøyaktige data på klimabelastninger, som resulterer i mer nøyaktige bygningssimuleringer.
Dette PhD forskningsprosjektet sikter på å forbedre aspekter ved bygningssimuleringer ved å ta hensyn til mikroklima. Klimabelastningene fra vind, slagregn og solstråling som opptrer på bygninger defineres med hensyn til mikroklima, og det er undersøkt hvordan man kan inkludere dem i bygningssimuleringsmodeller.