A new approach to performance-based building design exploration using linear inverse modeling. Issue 3 (4th May 2019)

• Record Type: Journal Article
• Authors: Rezaee, Roya; Brown, Jason; Haymaker, John; Augenbroe, Godfried
• Is Part Of: Journal of building performance simulation. Volume 12:Issue 3(2019)
• Page Start: 246
• Page End: 271
• Publication Date: 2019-05-04
• Subjects: inverse modelling -- uncertainty analysis -- energy assessment -- early stage of design -- design exploration; 690.0113
• DOI: 10.1080/19401493.2018.1507046
• Languages: English
• ISSNs: 1940-1493

Abstract

Abstract : Despite the development of a large number of building performance simulation tools, designers still need a systematic framework appropriate for energy-oriented decision-making in the early stages of design. While the current workflow follows a "forward" modelling procedure in which simulation tools predict the performance of a design, this study proposes an "inverse" procedure that entails a performance objective that estimates design parameters. Using linear inverse modelling, this approach generates plausible ranges for design parameters given a preferred thermal performance. The paper begins by demonstrating that thermal demand in a particular building operation-and-climate condition can be expressed as a linear regression model and then, in two case-studies, uses the regression model to develop an inverse algorithm. After defining energy performance targets as input, users obtain a probabilistic estimate of design parameters as output that represents a large "menu" of feasible design solutions, provides confidence, and embodies the iterative nature of design.