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Generative modeling and numerical optimization for energy efficient buildings

 
: Ullrich, Torsten; Silva, Nelson; Eggeling, Eva; Fellner, Dieter W.

:

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Industrial Electronics Society -IES-:
IECON 2013, 39th Annual Conference of the IEEE Industrial Electronics Society. Proceedings : Vienna, Austria, 10 - 14 November 2013
Piscataway, NJ: IEEE, 2013
ISBN: 978-1-4799-0223-1
ISBN: 978-1-4799-0224-8 (Print)
pp.4756-4761
IEEE Industrial Electronics Society (IECON Annual Conference) <39, 2013, Vienna>
English
Conference Paper
Fraunhofer Austria ()
3D graphics; generative modeling; numerical simulations; optimization; General Energy Simulation; Forschungsgruppe Semantic Models, Immersive Systems (SMIS)

Abstract
A procedural model is a script, which generates a geometric object. The script's input parameters offer a simple way to specify and modify the scripting output. Due to its algorithmic character, a procedural model is perfectly suited to describe geometric shapes with well-organized structures and repetitive forms.
In this paper, we interpret a generative script as a function, which is nested into an objective function. Thus, the script's parameters can be optimized according to an objective. We demonstrate this approach using architectural examples: each generative script creates a building with several free parameters. The objective function is an energy-efficiency-simulation that approximates a building's annual energy consumption. Consequently, the nested objective function reads a set of building parameters and returns the energy needs for the corresponding building. This nested function is passed to a minimization and optimization process. Outcome is the best building (within the family of buildings described by its script) concerning energy-efficiency. Our contribution is a new way of modeling. The generative approach separates design and engineering: the complete design is encoded in a script and the script ensures that all parameter combinations (within a fixed range) generate a valid design. Then the design can be optimized numerically.

: http://publica.fraunhofer.de/documents/N-285617.html