Multivariate Interactive Visualization of Data in Generative Design

Andre Chaszar, P von Buelow, Michela Turrin

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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We describe our work on providing support for design decision making in generative design systems producing large quantities of data, motivated by the continuing challenge of making sense of large design and simulation result datasets. Our approach provides methods and tools for multivariate interactive data visualization of the generated designs and simulation results, enabling designers to focus not only on high-performing results but also examine suboptimal designs’ attributes and outcomes, thus discovering relationships giving greater insight to design performance and facilitating guidance of further design generation. We illustrate this by an example exploring building massing and envelope design (fenestration arrangement and external shading) with simulations of daylighting and heat gain. We conclude that the visualization techniques investigated can help designers better comprehend inter-relationships between variable parameters, constraints and outcomes, with consequent benefits of: finding good design outcomes; verifying that simulation results are reliable and; understanding characteristics of the fitness landscape.
Original languageEnglish
Title of host publicationProceedings of the Symposium on Simulation for Architecture and Urban Design (simAUD 2016)
EditorsRamtin Attar, Angelos Chronis, Sean Hanna, Michela Turrin
ISBN (Print)978-1-365-05872-1
Publication statusPublished - 2016
EventSimAUD EU 2016: 7th annual Symposium on Simulation for Architecture and Urban Design - London, United Kingdom
Duration: 16 May 201618 May 2016


ConferenceSimAUD EU 2016: 7th annual Symposium on Simulation for Architecture and Urban Design
Country/TerritoryUnited Kingdom


  • parametric
  • performance design
  • optimization
  • exploration
  • visualization
  • multi-objective
  • multivariate
  • evolutionary computing


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