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Hygrothermal simulation is applied to compute the performance of materials, assemblies, systems and whole buildings. Commercially available simulation models require deterministic input for, among others, material properties, climatic boundary conditions, building use and ventilation conditions. The simulations result in a deterministic output, e.g. the time dependent moisture content of a material layer or humidity of interior air. Uncertainties in the input parameters are often not considered or assessed with limited parametric studies. One way to gain comprehensive insight into sensitivities of input parameters and their impact on uncertainties in the results are large-scale parametric simulations. This paper will outline a methodology to run large-scale parametric simulations via high-performance cloud computing (HPC Cloud) based on a use case of a twin tower, 283-unit residential condominium where extensive expert investigation established, among other issues, exterior plaster failure and high interior humidity levels with apparent biological growth. Competing opinions and the inability to field test the experts’ hypotheses resulted in HPC modelling to determine causes for failure of plaster coated exterior walls and high humidity in the condominium living environment. This study outlines a method for cloud-computing-based hygrothermal simulation and demonstrates that, in general, multi-physics building simulation using HPC Cloud computing is accessible, affordable, and beneficial for private clients. It can be applied to initial design and repair to reduce downstream risk. HPC cloud computing enables the prediction of future performance of buildings by simulation for a broad range of input parameters in a reasonable time due to the performance benefits with HPC cloud computing. Invasive / destructive building forensics can be reduced. Together with the ability to separate design, material, and workmanship deficiencies, the design process, potential forensic investigations, or litigation can draw huge benefits from utilizing HPC cloud computing with hygrothermal building simulation.
Citation: Thermal Buildings XIV 2019
Product Details
- Published:
- 2019
- Number of Pages:
- 10
- Units of Measure:
- Dual
- File Size:
- 1 file , 2.4 MB
- Product Code(s):
- D-Bldgs19-092
