Andreas Holm and Hartwig M. Kuenzel
Year:
2001
Bibliographic info:
Building Simulation, 7, 2001, Rio de Janeiro, Brazil, p. 949-956

In civil engineering there is an increasing demand for calculation methods to assess the moisture behaviour of building components. Current tasks, such as preserving historical buildings or restoring and insulating existing buildings are closely related to the moisture conditions in a building structure. In this context, questions regarding moisture behaviour and the related transport processes occurring under natural climatic conditions as well as the risks thus involved always occur. These questions can either be answered with the help of experiments or by numerical simulations. In view of the fact that experiments are often time-consuming and, in some cases, meteorologically both  problematic  and expensive, intensive work has  been  done  over  the past few years on the development of mathematical approaches and procedures to evaluate real thermal and moisture transfer processes. Until now the uncertainty of input data was explicitly left out of hygrothermal modeling. This was done because the understanding of the individual  physical  processes and their impact on the component assembly was the first priority. But the hygrothermal conditions within a construction and the building depends on a large number of factors such as outdoor and indoor climate and material properties. This may introduce significant uncertainities in the results. Today, an increasing demand exists to define more realistically processes which also include kind and dimension of the element of uncertainty. These influence on the results considered in this paper. The necessary input data for hygrothermal calculations are described with a specific uncertainty. This work is focused on uncertainty approaches for hygrothermal building simulations; With the help of the sensitivity analysis, one can study how  sensitive  the  solution  of  a problem based on the data confidence input and its reaction to a single parameter of uncertainty.