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Abstract:	Im SFB Advanced Computational Design werden Entwurfswerkzeuge und -prozesse durch multi- und interdisziplinäre Grundlagenforschung entwickelt. Das Ziel ist, durch eine neue Generation von Computational-Design-Methoden höhere Entwurfsqualität und effizientere Prozesse in Architektur und Bauwesen zu ermöglichen. Die Forschung wird in drei Bereichen durchgeführt: Entwurfsmethodik (A1), visuelle und haptische Entwurfsinteraktion (A2) und Formfindung (A3). Der Bereich A1 umfasst die konzeptionelle Grundlage für neuartige digitale Entwurfsmethoden basierend auf Lernmethoden. Zudem werden die in den Bereichen A2 und A3 entwickelten Computational-Design-Werkzeuge und -Methoden in einer Plattform verknüpft. Der Bereich A2 eröffnet Designern neuartige Feedback-Kanäle in digitalen Werkzeugen durch Lichtsimulation und haptisches Feedback. Im Bereich A3 werden die Randbedingungen im Formfindungsprozess hinsichtlich Geometrie, Material, Mechanik und Statik untersucht. Die Schwerpunkte liegen in der Unterteilung von komplexen Flächen in Paneele, der Analyse von formaktiven Strukturen sowie der Modellierung und experimentellen Analyse von neuartigen Kompositmaterialien. Die Exploration von Entwürfen in Interaktion mit intelligenten Materialmodellen und Algorithmen zur Bewertung der Tragstruktur dient einerseits der Entwicklung eines methodischen Ansatzes für die Entdeckung von neuen Möglichkeiten in der Formfindung und ermöglicht andererseits die experimentelle Validierung. Advanced Computational Design The SFB Advanced Computational Design addresses the research question of how to advance design tools and processes through multi- and interdisciplinary basic research. We will develop advanced computational design tools in order to improve design quality and efficiency of processes in architecture and construction. The proposed research is structured in three areas: design methodology (A1), visual and haptic design interaction (A2) and form finding (A3). A1 focuses on the conceptual basis for new digital methods of design based on machine learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form finding will be explored through physical experiments, which will allow for reconsidering model assumptions and constraints, validating the developed algorithmic approaches, and finding new ones.
Source:	Bautechnik 99 (2022), No. 10
Page/s:	720-730
Language of Publication:	German

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