Development and verification of the open source platform, HAM-Tools, for hygrothermal performance simulation of buildings using a stochastic approach
envelope, simulation, moisture, degradation
Building envelope design and analysis through simulation tools are areas of research and professional practice within the architecture, engineering, and construction (AEC) industries that can have substantial economic outcomes. Approximately 20% of whole building capital costs are associated with building envelopes. High moisture content within building envelopes is known to promote mold and corrosion while also reducing thermal resistance. Thus, simulating envelope moisture behavior is useful in evaluating designs. To allow for future stochastic and degradation modeling this project has augmented the open source platform, HAM-Tools and verified its results by using WUFI Pro 6.1 software. HAM-Tools is a robust one-dimensional H.A.M. analysis software using MATLAB and Simulink computational environments which allows for further development and research. In this work, wind-driven rain, rain penetration, as well as heat & moisture sources in air layers have been added to HAM-Tools. The paper compares the results from HAM-Tools and WUFI for a set of common ventilated cladding scenarios. Insulation degradation (which cannot be analyzed in WUFI) is also integrated into HAM-Tools and moisture content is simulated over a 10-year period to demonstrate how the platform can be used to examine long term moisture impact. The results of the study show that HAM-Tools and WUFI can produce relatively close results for moisture content within the envelope given the same ventilated scenarios. The 10-year studies with and without insulation degradation show that there are times where there are significant differences in the moisture content predicted with and without insulation degradation.
Tsinghua University Press
Daniel Chung, Jin Wen, L. James Lo. Development and verification of the open source platform, HAM-Tools, for hygrothermal performance simulation of buildings using a stochastic approach. Build Simul, 2020, 13(3): 497–514.