Evidence-Based Parametric Design: Computationally Generated Spatial Morphologies Satisfying Behavioural-Based Design Constraints

Authors Vasiliki Kondyli, Carl Schultz, Mehul Bhatt



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Vasiliki Kondyli
Carl Schultz
Mehul Bhatt

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Vasiliki Kondyli, Carl Schultz, and Mehul Bhatt. Evidence-Based Parametric Design: Computationally Generated Spatial Morphologies Satisfying Behavioural-Based Design Constraints. In 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 86, pp. 11:1-11:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
https://doi.org/10.4230/LIPIcs.COSIT.2017.11

Abstract

Parametric design is an established method in engineering and architecture facilitating the rapid generation and evaluation of a large number of configurations and shapes of complex physical structures according to constraints specified by the designer. However, the emphasis of parametric design systems, particularly in the context of architectural design of large-scale spaces, is on numerical aspects (e.g., maximising areas, specifying dimensions of walls) and does not address human-centred design criteria, for example, as developed from behavioural evidence-based studies. This paper aims at providing an evidence-based human-centred approach for defining design constraints for parametric modelling systems. We determine design rules that address wayfinding issues through behavioural multi-modal data analysis of a wayfinding case study in two healthcare environments of the Parkland hospital (Dallas). Our rules are related to the environmental factors of visibility and positioning of manifest cues along the navigation route. We implement our rules in FreeCAD, an open-source parametric system.
Keywords
  • parametric modelling
  • behavioural studies
  • Evidence-Based Design
  • design computing
  • wayfinding
  • spatial cognition

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