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Integrating the Multi-Functional Space and Long-Span Structure for Sports Arena Design : A design exploration process based on design optimization and self-organizing map. / Pan, Wang; Sun, Yimin; Turrin, Michela; Louter, Christian; Sariyildiz, Sevil.

Proceedings of the IASS Symposium 2018: Creativity in Structural Design. ed. / Caitlin Mueller; Sigrid Adriaenssens. IASS, 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Pan, W, Sun, Y, Turrin, M, Louter, C & Sariyildiz, S 2018, Integrating the Multi-Functional Space and Long-Span Structure for Sports Arena Design: A design exploration process based on design optimization and self-organizing map. in C Mueller & S Adriaenssens (eds), Proceedings of the IASS Symposium 2018: Creativity in Structural Design. IASS, IASS 2018: Annual Symposium of the International Association for Shell and Spatial Structures , Boston, United States, 16/07/18.

APA

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BibTeX

@inproceedings{1deee01af377443aaa7ad1eea632fe8a,
title = "Integrating the Multi-Functional Space and Long-Span Structure for Sports Arena Design: A design exploration process based on design optimization and self-organizing map",
abstract = "The multi-functional space of sports arena is highly related to the long-span structure. To support the integration of these two aspects, design optimization combining parametric modeling, performance simulations, and searching algorithm can be used. However, optimization is powerful in dealing with quantitative performance, but for some soft requirements on buildings, design exploration of geometries based on the judgments of architects is still necessary. Self-organizing map (SOM), as a model-based clustering algorithm, can be used to support this kind of explorations on geometric typology. Nevertheless, it is difficult to ensure the accuracy of clustering, especially for complex parametric models. To support the design exploration on geometry (besides the exploration on quantitative performance supported by optimization) during the conceptual design of sports arenas, this paper proposed a process based on a versatile and flexible parametric model for sports arenas and self-organizing map (SOM). Within this process, to increase the accuracy of SOM clustering, a pre-processing step for the parameters of design alternatives is also proposed. A design of a hypothetic sports arena is used as a case to demonstrate and verify the process.",
keywords = "design exploration, self-organizing map (SOM), clustering, parametric modeling, multi-objective optimization (MOO), multi-functional space of sports arenas, long-span structure",
author = "Wang Pan and Yimin Sun and Michela Turrin and Christian Louter and Sevil Sariyildiz",
year = "2018",
language = "English",
editor = "Caitlin Mueller and Sigrid Adriaenssens",
booktitle = "Proceedings of the IASS Symposium 2018",
publisher = "IASS",

}

RIS

TY - GEN

T1 - Integrating the Multi-Functional Space and Long-Span Structure for Sports Arena Design

T2 - A design exploration process based on design optimization and self-organizing map

AU - Pan, Wang

AU - Sun, Yimin

AU - Turrin, Michela

AU - Louter, Christian

AU - Sariyildiz, Sevil

PY - 2018

Y1 - 2018

N2 - The multi-functional space of sports arena is highly related to the long-span structure. To support the integration of these two aspects, design optimization combining parametric modeling, performance simulations, and searching algorithm can be used. However, optimization is powerful in dealing with quantitative performance, but for some soft requirements on buildings, design exploration of geometries based on the judgments of architects is still necessary. Self-organizing map (SOM), as a model-based clustering algorithm, can be used to support this kind of explorations on geometric typology. Nevertheless, it is difficult to ensure the accuracy of clustering, especially for complex parametric models. To support the design exploration on geometry (besides the exploration on quantitative performance supported by optimization) during the conceptual design of sports arenas, this paper proposed a process based on a versatile and flexible parametric model for sports arenas and self-organizing map (SOM). Within this process, to increase the accuracy of SOM clustering, a pre-processing step for the parameters of design alternatives is also proposed. A design of a hypothetic sports arena is used as a case to demonstrate and verify the process.

AB - The multi-functional space of sports arena is highly related to the long-span structure. To support the integration of these two aspects, design optimization combining parametric modeling, performance simulations, and searching algorithm can be used. However, optimization is powerful in dealing with quantitative performance, but for some soft requirements on buildings, design exploration of geometries based on the judgments of architects is still necessary. Self-organizing map (SOM), as a model-based clustering algorithm, can be used to support this kind of explorations on geometric typology. Nevertheless, it is difficult to ensure the accuracy of clustering, especially for complex parametric models. To support the design exploration on geometry (besides the exploration on quantitative performance supported by optimization) during the conceptual design of sports arenas, this paper proposed a process based on a versatile and flexible parametric model for sports arenas and self-organizing map (SOM). Within this process, to increase the accuracy of SOM clustering, a pre-processing step for the parameters of design alternatives is also proposed. A design of a hypothetic sports arena is used as a case to demonstrate and verify the process.

KW - design exploration

KW - self-organizing map (SOM)

KW - clustering

KW - parametric modeling

KW - multi-objective optimization (MOO)

KW - multi-functional space of sports arenas

KW - long-span structure

M3 - Conference contribution

BT - Proceedings of the IASS Symposium 2018

A2 - Mueller, Caitlin

A2 - Adriaenssens, Sigrid

PB - IASS

ER -

ID: 51432376