Exploratory Topology Modelling of Form-active Hybrid Structures

Deleuran, Anders Holden; Pauly, Mark; Tamke, Martin; Tinning, Ida Friis; Thomsen, Mette Ramsgaard

doi:10.1016/j.proeng.2016.08.008

Cited by 21 publications

(13 citation statements)

References 6 publications

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“…Design with FAHS -challenge level 1: limits of physical design exploration. Existing design approaches for FAHS structures are based on explorations with small scale physical models, 22,23 which build up an intuition and design repertoire on the side of the designer. The development of the typology, so the very basic elements and connection which constitute form hybrid structures, such as Lace Wall, is done in a manual iterative way.…”

Section: The Challenge In Designing Form-active Hybrid Systemsmentioning

confidence: 99%

“…In here, the designer can build up an intuition about promising design directions and explore them quickly, at least in material systems, which consist of a few hundred interacting elements. 23 Design with FAHS -challenge level 3: bespoke structures and design automation. The before-described digital design method with FAHS, can form the base for a potentially extended use of computational design methods, namely, parametric-and performance-based approaches, such as brute force, evolutionary solvers or other design-related optimisation strategies, to automatically explore the here emerging design spaces and find locally or even globally optimal solutions.…”

Section: The Challenge In Designing Form-active Hybrid Systemsmentioning

confidence: 99%

“…This allows us in Lace Wall to integrate simulation with a sufficient prediction of stress and strains in the form structure into the design environment 28 and most importantly to change the topology of the structure constantly. 23 The ability to work with open topologies and to find physically correct solutions allows a systematic exploration of options through the designer (Figure 3). Bending active and tension elements can be added or removed runningly in an interactive way.…”

Section: Lace Wallmentioning

confidence: 99%

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Machine learning for architectural design: Practices and infrastructure

Tamke

Nicholas

Zwierzycki

2018

International Journal of Architectural Computing

Self Cite

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In this article, we propose that new architectural design practices might be based on machine learning approaches to better leverage data-rich environments and workflows. Through reference to recent architectural research, we describe how the application of machine learning can occur throughout the design and fabrication process, to develop varied relations between design, performance and learning. The impact of machine learning on architectural practices with performance-based design and fabrication is assessed in two cases by the authors. We then summarise what we perceive as current limits to a more widespread application and conclude by providing an outlook and direction for future research for machine learning in architectural design practice.

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Section: The Challenge In Designing Form-active Hybrid Systemsmentioning

confidence: 99%

Section: The Challenge In Designing Form-active Hybrid Systemsmentioning

confidence: 99%

Section: Lace Wallmentioning

confidence: 99%

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Machine learning for architectural design: Practices and infrastructure

Tamke

Nicholas

Zwierzycki

2018

International Journal of Architectural Computing

Self Cite

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“…It can be extended through the definition of new goals in a straightforward way, allowing the use of any function which returns a target position even during the run-time of the solver. This allows us to integrate simulation with a sufficient prediction of stress and strain in the form-found structure into the design environment (Quinn, 2016) and most importantly to change the topology of the structure constantly (Deleuran, 2016). The ability to work with open topologies, to continuously add and remove bendingactive and tension elements and to find physically correct solutions allows a systematic exploration of options through the designer.…”

Section: Approaches Towards Supporting Form-active Hybrid Structure Dmentioning

confidence: 99%

Fabricate 2017

Peters¹,

Trummer²,

Amtsberg³

et al. 2017

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“…In the Complex Modelling project we explore alternative models for intersecting and interfacing different modes of simulation in the design model. [12,13] and the interactive Lace Wall modelling pipeline [14] where designers are free to handshake between the exploratory and structurally accurate modes of modelling at any time.…”

Section: Proposing a New Model: Interfacing Simulations Of Different mentioning

confidence: 99%

Simulation in Complex Modelling

Nicholas¹,

Thomsen²,

Tamke³

et al. 2017

Proceedings of the 2017 Symposium on Simulation for Architecture and Urban Design (SimAUD 2017)

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This paper will discuss the role of simulation in extended architectural design modelling. As a framing paper, the aim is to present and discuss the role of integrated design simulation and feedback between design and simulation in a series of projects under the Complex Modelling framework. Complex Modelling examining how methods from the parallel disciplines engineering and computer science can broaden our practices and transfer central information modelling concepts and tools. With special focus on new hybrid structural morphologies and material fabrication, we ask how to integrate material performance, engage with high degrees of interdependency and allow the emergence of design agency and feedback between the multiple scales of architectural construction. This paper presents examples for integrated design simulation from a series of projects including Lace Wall, A Bridge Too Far and Inflated Restraint developed for the research exhibition Complex Modelling, Meldahls Smedie Gallery, Copenhagen in 2016. Where the direct project aims and outcomes have been reported elsewhere, the aim for this paper is to discuss overarching strategies for working with design integrated simulation.

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Exploratory Topology Modelling of Form-active Hybrid Structures

Cited by 21 publications

References 6 publications

Machine learning for architectural design: Practices and infrastructure

Machine learning for architectural design: Practices and infrastructure

Fabricate 2017

Simulation in Complex Modelling

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