Elsevier

Computer-Aided Design

Volume 43, Issue 6, June 2011, Pages 664-676
Computer-Aided Design

Computational algorithms to evaluate design solutions using Space Syntax

https://doi.org/10.1016/j.cad.2011.02.011Get rights and content

Abstract

In the past, conventional computer-aided architectural design (CAAD) systems could not manage semantic information on building components and spaces but only graphical and geometric information. However, since the advent of Building Information Modeling (BIM), which has been used for managing semantic building information, determining spatial relationships as well as quantities and properties of building components in CAAD systems has become easier. It is necessary to make current CAAD systems capable of performing spatial analysis functions using BIM because they can easily recognize building components and spaces. Accordingly, this study aims to develop the computational algorithms to evaluate design solutions using Space Syntax during the process of computer-aided architectural designing. To extract topological information from design solutions, this study proposes algorithms to recognize building information produced in the form of Industry Foundation Classes (IFC), deduce the necessary topological information, and store the information in the form of matrices. The Space Syntax theory is employed to evaluate the solutions based on social properties of spaces in a building and examine the potential for adding a spatial analysis function into CAAD applications. The developed algorithms calculate the integration value for each space from spatial connectivity based on J-graphs. To validate the proposed algorithms, a program named J-Studio for Architectural Planning (J-SAP) was developed to evaluate design solutions easily and quickly. The validation results are as follows: (1) the topological information extracted from building information was decoded into a dimensionless representation and legible J-graph, (2) mathematical analyses for choosing a better design solution during computer-aided architectural designing were presented, and (3) the examination of the privacy level of each space in a building through Space Syntax analysis was discussed. Thus, this study demonstrates the possibility of determining the social properties and accessibility of spaces during the process of computer-aided architectural designing to meet client requirements by extracting topological information from building information model and performing Space Syntax analysis for evaluating alternatives using the information.

Highlights

► This study has intended to develop the computational algorithms to evaluate design solutions. ► Space Syntax was employed to examine the social properties and accessibility of spaces in a building. ► We examined the potential for adding a spatial analysis function into CAD systems. ► Analyses for choosing a better design during the process of CAD were presented. ► The examination of the privacy level of each space in a building was discussed.

Introduction

Rapid development of digital technology has influenced conventional computer-aided architectural design (CAAD) systems to be equipped with excellent capacity to manage graphical and geometric information. However, the CAAD systems that focused only on drafting and modeling capabilities could not manage semantic building information, including the entities of building components and spaces. To overcome these shortcomings, novel approaches such as building information modeling (BIM), product modeling and object-based data modeling have been employed to improve or replace conventional techniques in CAAD. These techniques allow CAAD applications to manage semantic information generated and maintained throughout the life cycle of a building, in addition to geometric and graphical information. They cover elements such as geometry, spatial relationships, geographic information, and quantities and properties of building components [1]. Traditional CAAD systems could manage only symbols, geometric and text information; they could not include semantic information pertaining to building components and spaces. Therefore, if only this information is available, it is difficult to construct algorithms that evaluate design solutions through spatial analysis. However, since the advent of BIM, finding the quantities and properties of building components and spatial relationships in CAAD systems has become easier. This improves the possibility of constructing algorithms for design evaluation through spatial analysis, as well as building design by drawing and rendering. Current CAAD systems with BIM capability can recognize building components and spaces, but cannot yet perform spatial analysis that measures the topological properties of the building entities using Space Syntax technique. Currently, BIM is used mainly for the purposes of costing, scheduling, performance simulation, code checking, and visualization. Few studies have focused on analyzing spatial relations using BIM because it is currently in the early stages of development. The Space Syntax method introduced by Hillier and Hanson [2], [3] has mainly been used for the quantitative analysis of spatial relations. Therefore, the aim of this study is to develop computational algorithms that can evaluate design solutions using Space Syntax during computer-aided architectural designing.

Section snippets

Backgrounds and literature review

In this section, we introduce the theories and techniques employed in this study and review related works on evaluating design solutions in architectural design.

Research methods

The algorithms developed in this study are those used to evaluate design solutions during the process of computer-aided architectural designing. We employed the concept of Space Syntax to evaluate the solutions by calculating the integration value for each space from spatial connectivity in a building (Fig. 5).

Development of algorithms

In this section, the processes for developing algorithms to evaluate design solutions are presented. For convenience, the algorithms are represented as pseudocodes. Pseudocode is a compact and informal high-level description of a computer programming algorithm that uses the structural conventions of a programming language, but typically omits details.

Topological aspects of building information need to be discussed in both vector space and raster space. The vector space is a continuous space and

Application and discussion

This section presents case studies to demonstrate the application of J-SAP and discusses the potentials and limitations of our proposals.

Conclusion

This study attempts to develop computational algorithms for evaluating design solutions using Space Syntax. Such algorithms can also present the results of Space Syntax analysis such as J-graphs and mathematical analyses. As necessary preconditions for developing algorithms to evaluate design, the topological information extracted from the IFC formatted building information can be reordered and stored in matrices. Through application of algorithms for the evaluation, design solutions can be

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant number: 20100024189).

References (36)

  • B. Lawson

    How designers think: the design process demystified

    (1997)
  • Y.E. Kalay

    Architecture’s new media

    (2003)
  • Autodesk, Inc. Building information modeling. 2010. Available at:...
  • G.V.R. Holness

    Building information modeling gaining momentum

    ASHRAE Journal

    (2008)
  • C.M. Eastman

    Building product models: computer environments supporting design and construction

    (1999)
  • S.K. Jeong et al.

    The generation of plans with the shape grammar and numerical analysis of space

    Journal of the Architectural Institute of Korea

    (1999)
  • J.E. Hwang et al.

    Managing and retrieving spatial information in architectural floor plan database

    Journal of Asian Architecture and Building Engineering

    (2003)
  • Khemlani L. The IFC building model: a look under the hood. AECbytes. 2004. Available at:...
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