Uncertainty and sensitivity analysis using building information modeling
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2019 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong. Building design decision-making is associated with uncertainties due to variations over time and unpredictable parameters. There is a growing demand for probabilistic methods, i.e., uncertainty and sensitivity analyses to handle the uncertainties in building design. This research intends to encourage the application of Building Information Modeling (BIM) for addressing design uncertainties affecting building energy performance. The mapping between BIM (Revit and Dynamo) and a customized model-based energy analysis tool in Excel is investigated to translate architectural models to energy models and conduct the probabilistic analyses. The application of this method is demonstrated with a test case of a hypothetical residential unit in College Station, Texas, USA. Input variables in this example are the thermal properties of building elements, and the two simulation outputs are annual heating and cooling energy consumption, and deviation from comfort temperature. The results indicate the probability distribution of simulation outputs and the importance factor of each design input. This method deals with uncertainties and provides a more reliable and robust basis for design decision-making.
