Generative design

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Schema of generative design as an iterative process Generative Design Process.png
Schema of generative design as an iterative process
Samba, a piece of furniture created by Guto Requena with generative design Samba Collection.JPG
Samba, a piece of furniture created by Guto Requena with generative design

Generative design is an iterative design process that involves a program that will generate a certain number of outputs that meet certain constraints, and a designer that will fine tune the feasible region by selecting specific output or changing input values, ranges and distribution. The designer does not need to be a human, it can be a test program in a testing environment or an artificial intelligence, for example a generative adversarial network. The designer learns to refine the program (usually involving algorithms) with each iteration as their design goals become better defined over time. [1]

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The output could be images, sounds, architectural models, animation, and much more. It is therefore a fast method of exploring design possibilities that is used in various design fields such as art, architecture, communication design, and product design. [2]

The process combined with the power of digital computers that can explore a very large number of possible permutations of a solution enables designers to generate and test brand new options, beyond what a human alone could accomplish, to arrive at a most effective and optimized design. It mimics nature’s evolutionary approach to design through genetic variation and selection.[ citation needed ]

Generative design has become more important, largely due to new programming environments or scripting capabilities that have made it relatively easy, even for designers with little programming experience, to implement their ideas. [3] Additionally, this process can create solutions to substantially complex problems that would otherwise be resource-exhaustive with an alternative approach making it a more attractive option for problems with a large or unknown solution set. [4] It is also facilitated with tools in commercially available CAD packages. [5] Not only are implementation tools more accessible, but also tools leveraging generative design as a foundation. [6]

Generative design in architecture

Generative design in architecture is an iterative design process that enables architects to explore a wider solution space with more possibility and creativity. [7] Architectural design has long been regarded as a wicked problem. [8] Compared with traditional top-down design approach, generative design can address design problems efficiently, by using a bottom-up paradigm that uses parametric defined rules to generate complex solutions. The solution itself then evolves to a good, if not optimal, solution. [9] The advantage of using generative design as a design tool is that it does not construct fixed geometries, but take a set of design rules that can generate an infinite set of possible design solutions. The generated design solutions can be more sensitive, responsive, and adaptive to the wicked problem.

Generative design involves rule definition and result analysis which are integrated with the design process. [10] By defining parameters and rules, the generative approach is able to provide optimized solution for both structural stability and aesthetics. Possible design algorithms include cellular automata, shape grammar, genetic algorithm, space syntax, and most recently, artificial neural network. Due to the high complexity of the solution generated, rule-based computational tools, such as finite element method and topology optimisation, are more preferable to evaluate and optimise the generated solution. [11] The iterative process provided by computer software enables the trial-and-error approach in design, and involves architects interfering with the optimisation process.

Historical precedent work includes Antoni Gaudí's Sagrada Família, which used rule based geometrical forms for structures, [12] and Buckminster Fuller's Montreal Biosphere where the rules to generate individual components is designed, rather than the final product. [13]

More recent generative design cases includes Foster and Partners' Queen Elizabeth II Great Court, where the tessellated glass roof was designed using a geometric schema to define hierarchical relationships, and then the generated solution was optimized based on geometrical and structural requirement. [14]

See also

Related Research Articles

<span class="mw-page-title-main">Computer-aided design</span> Constructing a product by means of computer

Computer-aided design (CAD) is the use of computers to aid in the creation, modification, analysis, or optimization of a design. This software is used to increase the productivity of the designer, improve the quality of design, improve communications through documentation, and to create a database for manufacturing. Designs made through CAD software help protect products and inventions when used in patent applications. CAD output is often in the form of electronic files for print, machining, or other manufacturing operations. The terms computer-aided drafting (CAD) and computer-aided design and drafting (CADD) are also used.

<span class="mw-page-title-main">Generative art</span> Art created by a set of rules, often using computers

Generative art is art that in whole or in part has been created with the use of an autonomous system. An autonomous system in this context is generally one that is non-human and can independently determine features of an artwork that would otherwise require decisions made directly by the artist. In some cases the human creator may claim that the generative system represents their own artistic idea, and in others that the system takes on the role of the creator.

Creo Parametric, formerly known, together with Creo Elements/Pro, as Pro/Engineer and Wildfire, is a solid modeling or CAD, CAM, CAE, and associative 3D modeling application, running on Microsoft Windows.

<span class="mw-page-title-main">Constructive solid geometry</span> Creating a complex 3D surface or object by combining primitive objects

Constructive solid geometry is a technique used in solid modeling. Constructive solid geometry allows a modeler to create a complex surface or object by using Boolean operators to combine simpler objects, potentially generating visually complex objects by combining a few primitive ones.

<span class="mw-page-title-main">Solid modeling</span> Set of principles for modeling solid geometry

Solid modeling is a consistent set of principles for mathematical and computer modeling of three-dimensional shapes (solids). Solid modeling is distinguished within the broader related areas of geometric modeling and computer graphics, such as 3D modeling, by its emphasis on physical fidelity. Together, the principles of geometric and solid modeling form the foundation of 3D-computer-aided design and in general support the creation, exchange, visualization, animation, interrogation, and annotation of digital models of physical objects.

<span class="mw-page-title-main">Computer-aided architectural design</span>

Computer-aided architectural design (CAAD) software programs are the repository of accurate and comprehensive records of buildings and are used by architects and architectural companies for architectural design and architectural engineering. As the latter often involve floor plan designs CAAD software greatly simplifies this task.

CAD data exchange is a method of drawing data exchange used to translate between different computer-aided design (CAD) authoring systems or between CAD and other downstream CAx systems.

Geometric modeling is a branch of applied mathematics and computational geometry that studies methods and algorithms for the mathematical description of shapes. The shapes studied in geometric modeling are mostly two- or three-dimensional, although many of its tools and principles can be applied to sets of any finite dimension. Today most geometric modeling is done with computers and for computer-based applications. Two-dimensional models are important in computer typography and technical drawing. Three-dimensional models are central to computer-aided design and manufacturing (CAD/CAM), and widely used in many applied technical fields such as civil and mechanical engineering, architecture, geology and medical image processing.

Virtual engineering (VE) is defined as integrating geometric models and related engineering tools such as analysis, simulation, optimization, and decision making tools, etc., within a computer-generated environment that facilitates multidisciplinary collaborative product development. Virtual engineering shares many characteristics with software engineering, such as the ability to obtain many different results through different implementations.

Architectural design optimization (ADO) is a subfield of engineering that uses optimization methods to study, aid, and solve architectural design problems, such as optimal floorplan layout design, optimal circulation paths between rooms, sustainability and the like. ADO can be achieved through retrofitting, or it can be incorporated within the initial construction a building. Methods of ADO might include the use of metaheuristic, direct search or model-based optimisation. It could also be a more rudimentary process involving identification of a perceived or existing problem with a buildings design in the concept design phase.

<span class="mw-page-title-main">Geometric design</span> Branch of computational geometry

Geometrical design (GD) is a branch of computational geometry. It deals with the construction and representation of free-form curves, surfaces, or volumes and is closely related to geometric modeling. Core problems are curve and surface modelling and representation. GD studies especially the construction and manipulation of curves and surfaces given by a set of points using polynomial, rational, piecewise polynomial, or piecewise rational methods. The most important instruments here are parametric curves and parametric surfaces, such as Bézier curves, spline curves and surfaces. An important non-parametric approach is the level-set method.

Design Automation usually refers to electronic design automation, or Design Automation which is a Product Configurator. Extending Computer-Aided Design (CAD), automated design and Computer-Automated Design (CAutoD) are more concerned with a broader range of applications, such as automotive engineering, civil engineering, composite material design, control engineering, dynamic system identification and optimization, financial systems, industrial equipment, mechatronic systems, steel construction, structural optimisation, and the invention of novel systems.

<span class="mw-page-title-main">Grasshopper 3D</span> Programming language

Grasshopper is a visual programming language and environment that runs within the Rhinoceros 3D computer-aided design (CAD) application. The program was created by David Rutten at Robert McNeel & Associates. Programs are created by dragging components onto a canvas. The outputs of these components are then connected to the inputs of subsequent components.

<span class="mw-page-title-main">Parametric design</span> Engineering design method

Parametric design is a design method in which features, such as building elements and engineering components, are shaped based on algorithmic processes rather than direct manipulation. In this approach, parameters and rules establish the relationship between design intent and design response. The term parametric refers to the input parameters that are fed into the algorithms.

Janice Richmond "Jan" Lourie is an American computer scientist and graphic artist. In the late 1960s she was a pioneer in CAD/CAM for the textile industry. She is best known for inventing a set of software tools that facilitate the textile production stream from artist to manufacturer. For the Graphical Design Of Textiles process she was granted IBM's first software patent. Other projects, in differing disciplines, share the focus on graphic representation. She returns throughout an ongoing career to the stacked two-dimensional tabular arrays of textiles and computer graphics, and the topological structures of interrelated data.

<span class="mw-page-title-main">Freeform surface machining</span> Machining techniques for complex surfaces

In manufacturing, freeform surface machining refers to the machining of complex surfaces that are not uniformly planar. The industries which most often manufactures free-form surfaces are basically aerospace, automotive, die mold industries, biomedical and power sector for turbine blades manufacturing. Generally 3- or 5-axis CNC milling machines are used for this purpose. The manufacturing process of freeform surfaces is not an easy job, as the tool path generation in present CAM technology is generally based on geometric computation so tool path are not optimum. The geometry can also be not described explicitly so errors and discontinuities occurrence in the solid structure cannot be avoided. Free-form surfaces are machined with the help of different tool path generation method like adaptive iso-planar tool path generation, constant scallop tool path generation, adaptive iso-parametric method, iso-curvature, isophote and by other methods. The different methods are chosen based on the parameters which is needed to be optimized.

Parametric thinking is the influence of engaging in a thinking process that links, relates and outputs calculated actions to generate solutions to problems, rather than simply seeking them. It has its origins in the design fields of urban design, architectural design, interior design, industrial and furniture design. The process is associated with parametricism, a style within contemporary avant-garde architecture, promoted as a successor to post-modern architecture and modern architecture.

Design for additive manufacturing is design for manufacturability as applied to additive manufacturing (AM). It is a general type of design methods or tools whereby functional performance and/or other key product life-cycle considerations such as manufacturability, reliability, and cost can be optimized subjected to the capabilities of additive manufacturing technologies.

Geometric constraint solving is constraint satisfaction in a computational geometry setting, which has primary applications in computer aided design. A problem to be solved consists of a given set of geometric elements and a description of geometric constraints between the elements, which could be non-parametric or parametric. The goal is to find the positions of geometric elements in 2D or 3D space that satisfy the given constraints, which is done by dedicated software components called geometric constraint solvers.

References

  1. Meintjes, Keith. ""Generative Design" – What's That? - CIMdata" . Retrieved 2018-06-15.
  2. ENGINEERING.com. "Generative Design: The Road to Production". www.engineering.com. Retrieved 2019-12-05.
  3. Schwab, Katharine (16 April 2019). "This is the first commercial chair made using generative design". Fast Company. Retrieved 13 August 2019.
  4. Prasanta, Rajamoney, Shankar A. Rosenbloom, Paul S.; Wagner, Chris Bose (2014-09-04). Compositional model-based design: A generative approach to the conceptual design of physical systems. University of Southern California. OCLC   1003551283.{{cite book}}: CS1 maint: multiple names: authors list (link)
  5. Barbieri, Loris; Muzzupappa, Maurizio (2022). "Performance-Driven Engineering Design Approaches Based on Generative Design and Topology Optimization Tools: A Comparative Study". Applied Sciences. 12 (4): 2106. doi: 10.3390/app12042106 .
  6. Anderson, Fraser; Grossman, Tovi; Fitzmaurice, George (2017-10-20). Trigger-Action-Circuits: Leveraging Generative Design to Enable Novices to Design and Build Circuitry. ACM. pp. 331–342. doi:10.1145/3126594.3126637. ISBN   9781450349819. S2CID   10091635.
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  8. Rittel, Horst W. J.; Webber, Melvin M. (1973). "Dilemmas in a General Theory of Planning" (PDF). Policy Sciences. 4 (2): 155–169. doi:10.1007/bf01405730. S2CID   18634229. Archived from the original (PDF) on 30 September 2007.
  9. Mitchell, Melanie; Taylor, Charles E (1999). "Evolutionary computation: an overview". Annual Review of Ecology and Systematics. 30 (1): 593–616. doi:10.1146/annurev.ecolsys.30.1.593.
  10. Shea, Kristina; Aish, Robert; Gourtovaia, Marina (2005). "Towards integrated performance-driven generative design tools". Automation in Construction. 14 (2): 253–264. doi:10.1016/j.autcon.2004.07.002.
  11. Dapogny, Charles; Faure, Alexis; Michailidis, Georgios; Allaire, Grégoire; Couvelas, Agnes; Estevez, Rafael (2017). "Geometric constraints for shape and topology optimization in architectural design" (PDF). Computational Mechanics. 59 (6): 933–965. Bibcode:2017CompM..59..933D. doi:10.1007/s00466-017-1383-6. S2CID   41570887.
  12. Hernandez, Carlos Roberto Barrios (2006). "Thinking parametric design: introducing parametric Gaudi". Design Studies. 27 (3): 309–324. doi:10.1016/j.destud.2005.11.006.
  13. Edmondson, Amy C (2012). "Structure and pattern integrity". A Fuller explanation: The synergetic geometry of R. Buckminster Fuller (PDF). Springer Science & Business Media. pp. 54–60. doi:10.1007/978-1-4684-7485-5. ISBN   978-0-8176-3338-7.
  14. Williams, Chris JK (2001). Burry, Mark; Datta, Sambit; Dawson, Anthony; Rollo, John (eds.). The analytic and numerical definition of the geometry of the British Museum Great Court Roof (PDF). Proceedings of mathematics & design 2001: the third international conference. Vol. 200. Geelong Vic Australia: Deakin University. pp. 434–440. ISBN   0-7300-2526-8.

Further reading