期刊
AUTOMATION IN CONSTRUCTION
卷 70, 期 -, 页码 1-13出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.autcon.2016.06.011
关键词
Building integrated design; Building energy optimization; Construction cost optimization; Genetic algorithms; Single house design; Multiobjective optimization; Building information model; Interoperability; Semantic BIM
资金
- PROGEMI development company
- French National Research and Technology Association [ANRT 2012/0361]
- French Research National Agency (ANR)
- French Agency for Environment and Energy Management (ADEME)
- scope of the research projects Multi-PHysical and Interactive CO-SIMulation [COSIMPHI ANR-13-VBDU-0002]
- Refurbishment of collective housing with ENergy Optimization and IntegRated approach [RENOIR 1504C0118]
The single family home market is facing increasing challenges in managing environmental issues. The required objective of building energy performance can be achieved by limiting extra cost, integrating building design, and using the most appropriate and readily available materials. However, standard computations, such as the French building energy code used here, require vocational expertise that involves managing separate processes and numerous design variables. The design is therefore restricted to well-known techniques, especially for small constructions. In this paper, the usual stakeholder constraints and possible developments in design practice are considered through the use of real product databases and vocational tools to calculate construction costs. In the first stage, which takes into account cost and energy demand, an integrated approach to building envelope design is detailed, including a semantic system to automate the process. Then an optimization method (a genetic algorithm) is proposed to assess energy performance and the cost of the building envelope. This process is illustrated as a case study for a single family house. The results highlight various optimal solution domains specific to the case study, which can be further managed through a decision support system. (C) 2016 Elsevier B.V. All rights reserved.
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