Generative modeling and numerical optimization for energy efficient buildings

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 a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Ullrich, Torsten, Silva, Nelson, Eggeling, Eva, Fellner, Dieter W.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:1553-572X
DOI:10.1109/IECON.2013.6699904