Airtightness of buildings - Calculation of combined standard uncertainty

The paper presents a calculation method for the combined standard uncertainty associated with the buildings airtightness measurement done in accordance with the ISO standard 9972:2006 (or EN 13829).

The method consists in an application of the law of propagation of uncertainty (JCGM 100:2008) combined with a linear regression (y = a x + b). It goes from the measured values to the air leakage rate and the air change rate.

Numerical evaluation of airtightness measurement protocols

In France, starting January 1st, 2013, the energy performance regulation will impose an airtightness treatment for every new residential building. This translates into several tens if not hundreds of thousands of envelope airtightness measurements a year that will have to be performed. They will have to be performed by a certified operator and according to the NF EN 13829 standard. This ISO standard is being revised under the Vienna agreement to become an EN ISO standard.

Interlaboratory tests for the determination of repeatability and reproducibility of buildings airtightness measurements

The issue of the uncertainty of building airtightness measurements has built up a greater importance since this topic was introduced in many regulations regarding the energy performance of buildings. Different studies have contributed to the evaluation of the uncertainty but the question is still incompletely solved in practice.
To contribute to the determination of the repeatability and reproducibility of these measurements in practice, the Belgian Building Research Institute organized interlaboratory tests with 10 other laboratories.

Quantification of uncertainty in thermal building simulation - Part 1: Stochastic building model.

In order to quantify uncertainty in thermal building simulation stochastic modelling is applied on a building model. An application of stochastic differential equations is presented in Part I comprising a general heat balance for an arbitrary number of loads and zones in a building to determine the thermal behaviour under random conditions. Randomness in the input as well as the model coefficients is considered. Two different approaches are presented namely equations for first and second order time varying statistical moments and Monte Carlo Simulation.