Andreas Nicolai

Stochastic study of hygrothermal performance of a wall assembly—The influence of material properties and boundary coefficients

An accurate description of material properties and boundary conditions is the prerequisite to achieve reliable results of a hygrothermal performance simulation. However, the uncertainties widely exist in those input variables, e.g., due to the inhomogeneous nature of materials and discrepancies in material manufacturing and measurement processes, the material properties are subjected to considerable variation. Therefore, the simulation result may not be only a single value, but in a range of possibilities. In this article, a stochastic approach is developed and implemented by using uncertainty analysis which assesses the uncertainties of a models input variables on that of the output variables, and sensitivity analysis, which identifies the most influential input variables. The hygrothermal performance of one typical wall assembly in North America is studied by applying this approach, considering the uncertainties of material properties of each individual layer and the uncertainties of the interior and exterior boundary coefficients. The influence of wall orientation is also presented. The results show that the effect of a single input variable on an output variable is not constant but varies with time. The key variables that affect the results are also different over time.

CHAMPS-Multizone—A combined heat, air, moisture and pollutant simulation environment for whole-building performance analysis

A computer simulation tool, named “CHAMPS-Multizone,” is introduced in this article for analyzing both energy and indoor air quality (IAQ) performance of buildings. The simulation model accounts for the dynamic effects of outdoor climate conditions (solar radiation, wind speed and direction, and contaminant concentrations), building materials and envelope system design, multi-zone air and contaminant flows in buildings, internal heat and pollutant sources, and operation of the building HVAC systems on the building performance. It enables combined analysis of building energy efficiency and indoor air quality. The model also has the ability to input building geometry data and HVAC system operation related information from software, such as SketchUp and DesignBuilder via IDF file format. A “bridge” to access static and dynamic building data stored in a “Virtual Building” database is also developed, allowing convenient input of initial and boundary conditions for the simulation and for comparisons between the predicted and measured results. This article summarizes the mathematical models, adopted assumptions, methods of implementation, and verification and validation results. The needs and challenges for further development are also discussed.