Advertisement

Parametric Design: Theoretical Development and Algorithmic Foundation for Design Generation in Architecture

  • Ning GuEmail author
  • Rongrong Yu
  • Peiman Amini Behbahani
Living reference work entry

Abstract

This chapter presents the theoretical foundation of parametric design for design generation in architecture. Parametric design has been increasingly applied to architectural design in recent years. It is essentially a digital design method, which can be characterized by rule-algorithmic design and multiple-solution generation. Parametric design originates from generative design, which is a typical computational design approach based on rules or algorithms (e.g., in generative grammars or evolutionary systems). This chapter starts with a critical review of generative design, followed by the background, history, and theory of parametric design, including various fundamental concepts and applications that underpin parametric design, and concludes with a discussion of the impact of parametric design on architecture.

Keywords

Parametric design Architectural design Generative design Mathematics Algorithm 

References

  1. Abdelsalam M (2009) The use of the smart geometry through various design processes: using the programming platform (parametric features) and generative components. Proceedings of the Arab Society for Computer Aided Architectural Design (ASCAAD 2009), Manama, Kingdom of Bahrain, pp 297–304Google Scholar
  2. Akın Ö (2001) Variants in design cognition. In: Eastman C, Newstetter W, McCracken M (eds) Design knowing and learning: cognition in design education. Elsevier Science, Oxford, pp 105–124CrossRefGoogle Scholar
  3. Almusharaf AM, Elnimeiri M (2010) A performance-based design approach for early tall building form development. Proceedings of the Arab Society for Computer Aided Architectural Design (ASCAAD 2010), Fez, Morocco, pp 39–50Google Scholar
  4. Baerlecken D, Martin M, Judith R, Arne K (2010) Integrative parametric form-finding processes. Proceedings of the 15th international conference on computer aided architectural design research in Asia (CAADRIA), Hong Kong, pp 303–312Google Scholar
  5. Barrios C (2005) Transformations on parametric design models. Proceedings of the 11th international conference on computer aided architectural design futures (CAAD Future), Vienna, Austria, pp 393–400Google Scholar
  6. Batty M (1997a) Cellular automata and urban form: a primer. J Am Plan Assoc 63(2):266–274CrossRefGoogle Scholar
  7. Batty M (1997b) Urban systems as cellular automata. Environ Planning B Plan Des 24:159–164CrossRefGoogle Scholar
  8. Bernal M (2011) Analysis model for incremental precision along design stages. Proceedings of the 16th international conference on computer aided architectural design research in Asia(CAADRIA), Newcastle, Australia, pp 19–18Google Scholar
  9. Blum C, Li X (2008) Swarm intelligence in optimization. In: Blum C, Merkle D (eds) Swarm Intelligence. Springer, Berlin, pp 43–85CrossRefGoogle Scholar
  10. Boden M, Edmonds E (2007) What is generative art. Digit Creat 20(1):21–46Google Scholar
  11. Burry M (2003) Between intuition and process: parametric design and rapid prototyping. In: Kolarevic B (ed) Architecture in the digital age – design and manufacturing. Spon Press, New York/London, pp 149–162Google Scholar
  12. Burry J, Holzer D (2009) Sharing design space: remote concurrent shared parametric modeling. Proceedings of 27th eCAADe conference, Istanbul, Turkey, pp 333–340Google Scholar
  13. Cárdenas CA (2007) Modeling strategies: parametric design for fabrication in architectural practice. Dissertation, Harvard UniversityGoogle Scholar
  14. Chakrabarti A, Shea K, Stone R, Cagan J, Campbell M, Hernandez NV, Wood KL (2011) Computer-based design synthesis research: an overview. J Comput Inf Sci Eng 11:021003–021012CrossRefGoogle Scholar
  15. Chien SF (1998) Supporting information navigation in generative design systems. Dissertation, Carnegie Melon UniversityGoogle Scholar
  16. Dorst K (2011) The core of ‘design thinking’ and its application. Des Stud 32(6):521–532CrossRefGoogle Scholar
  17. Eastman CM (ed) (2008) BIM handbook: a guide to building information modeling for owners, managers, designers, engineers and contractors. Wiley, HobokenGoogle Scholar
  18. Eckert C, Kelly I, Stacey M (1999) Interactive generative systems for conceptual design: an empirical perspective. Artif Intell Eng Des Anal Manuf 13:303–329CrossRefGoogle Scholar
  19. Fasoulaki E (2007) Genetic algorithms in architecture: a necessity or a trend? Proceedings of 10th generative art international conference. Milan, ItalyGoogle Scholar
  20. Fischer T, Herr C (2001) Teaching generative design. Proceedings of 4th generative art international conferene. Milan, ItalyGoogle Scholar
  21. Fischer T, Burry M, Frazer J (2003) Triangulation of generative form for parametric design and rapid prototyping. Proceedings of 21th eCAADe conference, Graz, Austria, pp 441–448Google Scholar
  22. Fischer T, Burry M, Frazer J (2005) Triangulation of generative form for parametric design and rapid prototyping. Autom Constr 14(2):233–240CrossRefGoogle Scholar
  23. Frazer J (2016) Parametric computation: history and future. Archit Des 86(2):18–23Google Scholar
  24. Gane V, Haymaker J (2009) Design scenarios: methodology for requirements driven parametric modeling of high-rises. Proceedings of the 9th international conference (CONVR 2009), Sydney, Australia, pp 79–90Google Scholar
  25. Garnier S, Gautrais J, Theraulaz G (2007) The biological principles of swarm intelligence. Swarm Intell 1:3–31CrossRefGoogle Scholar
  26. Gero JS (1996) Creativity, emergence and evolution in design. Knowl-Based Syst 9(7):435–448CrossRefGoogle Scholar
  27. Gero JS, Kazakov V (1996) An exploration-based evolutionary model of generative design process. Comput Aided Civ Infrastruct Eng 11(3):211–218CrossRefGoogle Scholar
  28. Grasl T, Economou A (2013) From topologies to shapes: parametric shape grammars implemented by graphs. Environ Plan B: Plan Des 40:905–922CrossRefGoogle Scholar
  29. Hernandez CRB (2006) Thinking parametric design: introducing parametric Gaudi. Des Stud 27(3):309–324CrossRefGoogle Scholar
  30. Herr C, Kvan T (2007) Adapting cellular automata to support the architectural design process. Autom Constr 16(2007):61–69CrossRefGoogle Scholar
  31. Hillyard RC, Braid IC (1978) Analysis of dimensions and tolerances in computer-aided mechanical design. Comput Aided Des 10(3):161–166CrossRefGoogle Scholar
  32. Hnizda M (2009) Systems-thinking: formalization of parametric process. Proceedings of the Arab Society for Computer Aided Architectural Design (ASCAAD 2009), Manama, Kingdom of Bahrain, pp 215–223Google Scholar
  33. Holland J (1968) Hierarchical descriptions, universal spaces and adaptive systems: technical report. University of Michigan, Ann ArborGoogle Scholar
  34. Holland J (ed) (1975) Adaptation in natural and artificial systems. An introductory analysis with application to biology, control, and artificial intelligence. University of Michigan Press, Ann ArborzbMATHGoogle Scholar
  35. Holland N (2011) Inform form perform. Proceedings of ACADIA regional 2011 conference, pp 131–140Google Scholar
  36. Holzer D, Hough R, Burry M (2007) Parametric design and structural optimisation for early design exploration. Int J Archit Comput 5(4):625–643CrossRefGoogle Scholar
  37. Hornby GS, Pollack J (2001) The advantages of generative grammatical encodings for physical design, 2001 IE congress on evolutionary computation. IEEE, SeoulCrossRefGoogle Scholar
  38. Jo J, Gero JS (1998) Space layout planning using an evolutionary approach. Artif Intell Eng 12(3):149–162CrossRefGoogle Scholar
  39. Karle D, Kelly B (2011) Parametric thinking. In: Proceedings of ACADIA regional 2011 conference, pp 109–113Google Scholar
  40. Knight T (2003) Computing with emergence. Environ Plan B Plan Des 30:125–156CrossRefGoogle Scholar
  41. Kolarevic B (ed) (2003) Architecture in the digital age: design and manufacturing. Spon Press, New YorkGoogle Scholar
  42. Krish S (2011) A practical generative design method. Comput Aided Des 43:88–100CrossRefGoogle Scholar
  43. Leach N (ed) (2008) (Im)material processes – new digital techniques for architecture. China Architecture & Building Press, BeijingGoogle Scholar
  44. Lee JH, Ostwald M, Gu N (2016) A justified plan graph (JPG) grammar approach to identifying spatial design patterns in an architectural style. Environ Plann B: Urban Analytics City Sci 45(1):67–89Google Scholar
  45. Light R, Gossard D (1982) Modification of geometric models through variational geometry. Comput Aided Des 14(4):209–214CrossRefGoogle Scholar
  46. Maher ML (1990) Process models for design synthesis. AI Mag 11:49–58Google Scholar
  47. Maher A, Burry M (2003) The parametric bridge: connecting digital design techniques in architecture and engineering. Proceedings of the 2003 annual conference of the association for computer aided design in architecture, Indianapolis, Indiana, pp 39–47Google Scholar
  48. Monedero J (2000) Parametric design: a review and some experiences. Autom Constr 9(4):369–377CrossRefGoogle Scholar
  49. Ostwald M (2012) Systems and enablers: modeling the impact of contemporary computational methods and technologies on the design process. In: Gu N, Wang X (eds) Computational design methods and technologies: applications in CAD, CAM and CAE education. IGI Global, Pennsylvania, pp 1–17Google Scholar
  50. Oxman R (1990) Design shells: a formalism for prototype refinement in knowledge-based design systems. Artif Intell Eng 5(1):2–8MathSciNetCrossRefGoogle Scholar
  51. Oxman R (2006) Theory and design in the first digital age. Des Stud 27(3):229–265CrossRefGoogle Scholar
  52. Parish Y, Müller P (2001) Procedural modeling of cities. Proceedings of the 28th annual conference on computer graphics and interactive techniques. ACM, New York, pp 301–308Google Scholar
  53. Peña W, Parshall S (eds) (2001) Problem seeking: an architectural programming primer. Wiley, New YorkGoogle Scholar
  54. Rajus V S, Woodbury R, Erhan H, Riecke B E, Mueller V (2010) Collaboration in parametric design: analyzing user interaction during information sharing. Proceedings of the 30th annual conference of the Association for Computer Aided Design in Architecture (ACADIA), New York, pp 320–326Google Scholar
  55. Roberto C, Hernandez B (2004) Parametric Gaudi. Proceedings of the 8th Iberoamerican congress of digital graphics (SIGraDi 2004), Porte Alegre, Brasil, pp 213–215Google Scholar
  56. Salim F, Burry J (2010) Software openness: evaluating parameters of parametric modeling tools to support creativity and multidisciplinary design integration. Proceedings of computational science and its applications (ICCSA 2010), Berlin and Heidelberg, Germany, pp 483–497CrossRefGoogle Scholar
  57. Sarkar P (2000) A brief history of cellular automata. ACM Comput Surv 32(1):80–107CrossRefGoogle Scholar
  58. Schlueter A, Thesseling F (2008) Balancing design and performance in building retrofitting: a case study based on parametric modeling. Proceedings of the 28th annual conference of the Association for Computer Aided Design in Architecture (ACADIA) pp 214–221Google Scholar
  59. Schumacher P (2009) Parametricism – a new global style for architecture and urban design. AD Archit Des – Digi Cities 79(4):14–23MathSciNetGoogle Scholar
  60. Singh V, Gu N (2011) Towards an integrated generative design framework. Des Stud 33:185–207CrossRefGoogle Scholar
  61. Stiny G, Gips J (1972) Shape grammars and the generative specification of painting and sculpture. Inf Process 71:1460–1465Google Scholar
  62. Stiny G, Mitchell WJ (1978) The Palladian grammar. Environ Plan B 5:5–18CrossRefGoogle Scholar
  63. Tching J, Reis J, Paio A (2016) A cognitive walkthrough towards an interface model for shape grammar implementations. Comput Sci Inf Technol 4:92–119Google Scholar
  64. Von Neumann J (1951) The general and logical theory of automata. In: Taub AH (ed) John von Neumann, collected works. Pergammon Press, New York, pp 280–326Google Scholar
  65. Wolfram S (1986) Random sequence generation by cellular automata. Adv Appl Math 7:123–169MathSciNetCrossRefGoogle Scholar
  66. Woodbury R (ed) (2010) Elements of parametric design. Routledge, New YorkGoogle Scholar
  67. Woodbury RF, Burrow AL (2006) Whither design space? Artificial intelligence for engineering design. Anal Manuf 20(2):63–82Google Scholar
  68. Woodbury R, Aish R, Kilian A (2007) Some patterns for parametric modeling. Proceedings of the 27th annual conference of the association for computer aided design in architecture Halifax, Nova Scotia, pp 222–229Google Scholar
  69. Yu R, Gero JS, Gu N (2013) Impact of using rule algorithms on designers’ behavior in a parametric design environment: preliminary results from a pilot study. Proceedings of the 15th International conference on computer aided architectural design futures (CAAD FUTURES 2013), Shanghai, China, pp 13–22Google Scholar
  70. Yu R, Gu N, Ostwald M, Gero J (2015a) Empirical support for problem-solution co-evolution in a parametric design environment. Artif Intell Eng Des Anal Manuf (AIEDAM) 29(01):33–44CrossRefGoogle Scholar
  71. Yu R, Ostwald M, Gu N (2015b) Parametrically generating new instances of traditional chinese private gardens that replicate selected socio-spatial and aesthetic properties. Nexus Netw J 17(3):807–829CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Art, Architecture and DesignUniversity of South AustraliaAdelaideAustralia
  2. 2.School of Engineering and Built EnvironmentGriffith UniversitySouthportAustralia

Personalised recommendations