Assessment of uncertainty and confidence in building design exploration. Issue 4 (7th October 2015)

• Record Type: Journal Article
• Authors: Stouffs, Rudi; Rafiq, Yaqub; Rezaee, Roya; Brown, Jason; Augenbroe, Godfried; Kim, Jinsol
• Is Part Of: AI EDAM. Volume 29:Issue 4(2015)
• Page Start: 429
• Page End: 441
• Publication Date: 2015-10-07
• Subjects: Engineering design -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; 620.00420285
• DOI: 10.1017/S0890060415000426
• Languages: English
• ISSNs: 0890-0604

Abstract

<abstract abstract-type="normal"> <title>Abstract</title> <p>Performance assessment at early stages of buildings design is complicated by an inherent lack of information on the design and the uncertainty in how a building design may evolve to a final design. This pilot study reports on an initial quantification of such uncertainty associated with building energy performance and develops a method for informing decision makers of the risks in early design decisions under this uncertainty. Two case studies of building design decision situations under this uncertainty are explored along with using two different energy modeling tools: a reduced-order model and a high-order model. The intended contribution is to identify if a decision can be made with confidence in early design given a high level of uncertainty in the evolution of a design and what models can support decisions of this sort. Integration of the proposed decision support approach with a computer-aided design model is shown as well.</p> </abstract>