Use of Parametric Approach for User-Oriented Development in Building Design: Preliminary Investigations

Giuseppe Canestrino (1)
(1) Department of Civil Engineering, University of Calabria, Italy, Italy

Abstract

Building design is a highly interdisciplinary research field integrating technological, architectural, structural, social and other aspects. Participatory design, or co-design, already used in other disciplines, is now facilitated by the diffusion of Building Information Modelling which offers greater control of the interdisciplinary aspects in building design. But unlike other disciplines, architecture is characterized by a high number of requirements, partly formalizable, quantifiable and optimizable and partly only intuitive. Furthermore is difficulty to employ a collaborative design framework because designer and end user work on different knowledge levels: one works on satisfying classes of requirements, and the other is unable to abstract his needs and therefore properly formalize requirements or desires. The use of simple parametric models in the pre-design phase, based on algorithms capable of generating geometries dependent on multiple modifiable variables, could overcome this problem.
This paper offers a preliminary investigation on the possibility of integrating bottom-up design aspects by giving parametric models to possible end users and allowing them to explore the design space, identifying preferential outputs and overcoming some of their technical gaps. Working in parametric environments in the pre-design phase opens to the integration of tools such as evolutionary multiobjective optimization algorithms (EMOA). New fitness functions can be defined to bring design closer to the end users’ proposed outputs without neglecting performance optimization, which is typical in parametric design. The framework proposed differs from existing “product configurator”, used in industrial design, which allows the personalization of aesthetic characteristics. This paper aims at a greater understanding of the end user’s will for satisfying them better in the subsequent design phases.
The technological tools currently available to make this framework possible will be analysed, identifying shortcomings and problems, along with methodological implications.

Full text article

Generated from XML file

References

Alexander C. Notes on the synthesis of form. Harvard: Harvard University Press; 1972.

Alexander C, Schmidt R, Moore Alexander M, Hanson B, Mehaffy M.. Generative Codes. The path to building welcoming, beautiful, sustainable neighbourhoods; 2005. Retrieved April 4, 2020, from https://www.livingneighborhoods.org/library/generativecodesv10.pdf

Alexander C, Silverstein M, Angel S, Ishikawa S, Abrams D. The Oregon Experiment. New York: Oxford University Press; 1975.

De Carlo G, Bunčuga F. Conversazioni su architettura e libertà [trad. Conversations on architecture and freedom. Milano: Elèuthera; 2000.

Garbad MJ. Understanding K-means Clustering in Machine Learning; 2018, September. Retrieved April 4, 2020, from Towards Data Science: https://towardsdatascience.com/understanding-k-means-clustering-in-machine-learning-6a6e67336aa1

Ghery Technologies. Museo Soumaya. Facade design to fabrication; 2013.

Giffinger R, Fertner C, Kramar H, Kalasek R, Milanovic NP, Meijers E. Smart cities. Ranking of European medium-sized cities. Vienna: Centre of Regional Science; 2007.

Habermas J. A reply to my critics. In: Thompson JB, Held D, editors. Habermas: critical debates. London: Macmillan press LTD; 1982.

Hergul S. Understanding Simple Heat Maps for Smarter UI Design; 2020. Retrieved April 28, 2020, from uxpin.com: https://www.uxpin.com/studio/blog/understanding-simple-heat-maps-smarter-ui-design/

McLuhan M. Understanding Media: the extensions of man. New York: McGraw-Hill; 1964

Mitra M. K-Means clustering in machine learning - a review. The Peer Research Nest 2019;1(4):1-14.

Negroponte N. Soft Architecture Machines. Cambridge: MIT Press; 1975.

Nuijsink C. "Less money, More creativity", interview with Alejandro Aravena. Mark Magazine 2008;15:175-183.

Pask G. The architectural relevance of cybernetics. Architectural Design 1966:494-496.

Purini F. (2018). Il BIM. Un parere in evoluzione. [trad. The BIM. An evolving opinion.]. Op.cit. Selezione della critica d'arte contemporanea 2018;162;5-16.

Ratti C. Architettura open source. Torino: Giulio Einaudi Editore; 2014.

Ratti C, Antonelli P, Bly A, Dietrich L, Grima J, Hill D, Habraken J, Haw A, Maeda J, Negroponte N, Obrist HU, Reas C, Santambrogio M, Shepard M, Somajni C, Sterlin B. Open Source Architecture (OsArc). Domus 2011;948:I-IV.

Sacchi, L. La fine del disegno? [trad. The end of Drawing?]. Op. cit. Selezione della critica d'arte contemporanea 2015:153;5-16.

Shape Diver. Shape Diver | Online Parametric Technology Overview. Retrieved April 4, 2020, from https://www.shapediver.com/overview/

Tedeschi A. AAD_Algorithms-Aided Design. Brienza: Le Penseur; 2014.

The Musem of Modern Art. Epilogue - Cedric Price. In Riley T, Deyong S, De Michelis M, Apraxine P, Antonelli P, di Carlo T, Cline B, The changing of the avant-garde: visionary architectural drawings from the Howard Gilman Collection. New York: Distributed Art Publishers; 2002. p.156

United Nations General Assembly. Transforming our world: the 2030 Agenda for Sustainable Development; 2015.

Whitehead H. (2010). Foreword. In Woodbury R. Elements of parametric design. New York: Routledge; 2010. p.1

Wilkinson L, Friendly M. The History of Cluster Heat Map. The American Statistician 2009;63-2;179-184

Authors

Giuseppe Canestrino
[email protected] (Primary Contact)
Canestrino, G. (2021). Use of Parametric Approach for User-Oriented Development in Building Design: Preliminary Investigations. ARCHive-SR, 5(1), 74–80. https://doi.org/10.21625/archive.v5i1.826

Article Details