CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id ecaade2018_170
authors Shahsavari, Fatemeh, Koosha, Rasool, Vahid, Milad R., Yan, Wei and Clayton, Mark
year 2018
title Towards the Application of Uncertainty Analysis in Architectural Design Decision-Making - A Probabilistic Model and Applications
source Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 295-304
summary To this day, proper handling of uncertainties -including unknown variables in primary stages of a design, an actual climate data, occupants' behavior, and degradation of material properties over the time- remains as a primary challenge in an architectural design decision-making process. For many years, conventional methods based on the architects' intuition have been used as a standard approach dealing with uncertainties and estimating the resulting errors. However, with buildings reaching great complexity in both their design and material selections, conventional approaches come short to account for ever-existing but unpredictable uncertainties and prove incapable of meeting the growing demand for precise and reliable predictions. This study aims to develop a probability-based framework and associated prototypes to employ uncertainty analysis and sensitivity analysis in architectural design decision-making. The current research explores an advanced physical model for thermal energy exchange characteristics of a hypothetical building and uses it as a test case to demonstrate the proposed probability-based analysis framework. The proposed framework provides a means to employ uncertainty and sensitivity analysis to improve reliability and effectiveness in a buildings design decision-making process.
keywords Probability-based design decision; uncertainty analysis; sensitivity analysis; building energy consumption model
series eCAADe
full text file.pdf (1,389,202 bytes)
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