A novel inverse data driven modelling approach to performance-based building design during early stages. (August 2019)
- Record Type:
- Journal Article
- Title:
- A novel inverse data driven modelling approach to performance-based building design during early stages. (August 2019)
- Main Title:
- A novel inverse data driven modelling approach to performance-based building design during early stages
- Authors:
- Rezaee, Roya
Brown, Jason
Haymaker, John
Augenbroe, Godfried - Abstract:
- Highlights: Energy-based design consists of iterative process of divergent & convergent phases. Designers make decision under high level of uncertainties at earlier stages. Current building industry lacks an effective approach to energy-based design. An inverse data-driven method is proposed combining divergent & convergent phases. Input to inverse method is energy target & output is probabilities of design parameters. Abstract: Energy analysis at the early stage of building design is a critical, yet difficult task in performance-based design. The difficulty arises from the complex, iterative, and uncertain nature of building design and the challenges of integration with well-posed energy assessment tools. The purpose of this article is to first review characteristics of performance-based design and establish requirements for a methodology that includes generating promising design alternatives, assessing the energy performance in tandem with the generation of alternatives, and choosing an alternative design solution with confidence. The study then proposes a novel systematic data-driven method, based on linear inverse modeling that generates plausible ranges for design parameters given a preferred energy target. The energy performance in this method is described as a linear function of the design parameters for a particular scenario of design. The application of the proposed method in a case study shows that it is capable of helping designers make informed decisionsHighlights: Energy-based design consists of iterative process of divergent & convergent phases. Designers make decision under high level of uncertainties at earlier stages. Current building industry lacks an effective approach to energy-based design. An inverse data-driven method is proposed combining divergent & convergent phases. Input to inverse method is energy target & output is probabilities of design parameters. Abstract: Energy analysis at the early stage of building design is a critical, yet difficult task in performance-based design. The difficulty arises from the complex, iterative, and uncertain nature of building design and the challenges of integration with well-posed energy assessment tools. The purpose of this article is to first review characteristics of performance-based design and establish requirements for a methodology that includes generating promising design alternatives, assessing the energy performance in tandem with the generation of alternatives, and choosing an alternative design solution with confidence. The study then proposes a novel systematic data-driven method, based on linear inverse modeling that generates plausible ranges for design parameters given a preferred energy target. The energy performance in this method is described as a linear function of the design parameters for a particular scenario of design. The application of the proposed method in a case study shows that it is capable of helping designers make informed decisions regarding energy performance iteratively and confidently at the early stages of building design. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 41(2019)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 41(2019)
- Issue Display:
- Volume 41, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 41
- Issue:
- 2019
- Issue Sort Value:
- 2019-0041-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-08
- Subjects:
- Early stage of architectural design -- Data driven model -- Inverse modeling -- Divergent and convergent phases of design -- Energy analysis
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2019.100925 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 14138.xml