Energy load prediction on structures and buildings-Effect of numerical model complexity on simulation of heat fluxes across the structure/environment interface

Abstract

Civil structures, including buildings, constantly exchange heat fluxes with the environment. This includes heat exchange through conduction, convection, radiation and latent heat. A detailed description of the heat fluxes and corresponding transport processes is essential to estimate cooling and heating requirements and inhibit extreme local strains. Moreover, the temperature distribution inside a structure can be predicted by assessing the thermal loads of the environment with respect to the particular material properties of the structure. This is especially substantial for massive structures as thermal stresses can cause cracking. However, in the design of low-energy and passive houses, knowledge about the incoming and outgoing heat fluxes is also of great importance. Considering the numerous meteorological impacts on civil structures, the exact determination of the heat fluxes is quite complex. Most of the studies from literature on heat exchange of civil structures with the environment rely on multiple, not well-founded hypotheses to compensate for the lack of precise data. Therefore, this work aims to improve the understanding and quantification of the heat fluxes between a civil structure and the environment. Various measurement devices have been installed on a gravity dam to capture spatially distributed environmental impacts as well as the temperature distribution inside the structure. This data is used as input to model, quantify and evaluate the governing heat fluxes and thermal transport processes. It can be shown that the temperature fields in civil structures can be modelled even under complex environmental conditions with high accuracy when all essential key processes are incorporated. Furthermore, it is concluded that some simplified models can also yield a good fit even when the modelling parameters are extended beyond their actual definition.