id |
cf2011_p098 |
authors |
Bernal, Marcelo; Eastman Charles |
year |
2011 |
title |
Top-down Approach for Interaction of Knowledge-Based Parametric Objects and Preliminary Massing Studies for Decision Making in Early Design Stages |
source |
Computer Aided Architectural Design Futures 2011 [Proceedings of the 14th International Conference on Computer Aided Architectural Design Futures / ISBN 9782874561429] Liege (Belgium) 4-8 July 2011, pp. 149-164. |
summary |
Design activities vary from high-degree of freedom in early concept design stages to highly constrained solution spaces in late ones. Such late developments entail large amount of expertise from technical domains. Multiple parallel models handle different aspects of a project, from geometric master models to specific building components. This variety of models must keep consistency with the design intent while they are dealing with specific domains of knowledge such as architectural design, structure, HVAC, MEP, or plumbing systems. Most of the expertise embedded within the above domains can be translated into parametric objects by capturing design and engineering knowledge through parameters, constraints, or conditionals. The aim of this research is capturing such expertise into knowledge-based parametric objects (KPO) for re-usability along the design process. The proposed case study ‚Äì provided by SOM New York‚ is the interaction between a massing study of a high-rise and its building service core, which at the same time handles elevators, restrooms, emergency stairs, and space for technical systems. This project is focused on capturing design expertise, involved in the definition of a building service core, from a high-rise senior designer, and re-using this object for interaction in real-time with a preliminary massing study model of a building, which will drive the adaption process of the service core. This interaction attempts to provide an integrated design environment for feedback from technical domains to early design stages for decision-making, and generate a well-defined first building draft. The challenges addressed to drive the instantiation of the service core according to the shifting characteristics of the high-rise are automatic instantiation and adaptation of objects based on decision rules, and updating in real-time shared parameters and information derived from the high-rise massing study. The interaction between both models facilitates the process from the designer‚Äôs perspective of reusing previous design solutions in new projects. The massing study model is the component that handles information from the perspective of the outer shape design intent. Variations at this massing study model level drive the behavior of the service core model, which must adapt its configuration to the shifting geometry of the building during design exploration in early concept design stages. These variations depend on a list of inputs derived from multiple sources such as variable lot sizes, building type, variable square footage of the building, considerations about modularity, number of stories, floor-to-floor height, total building height, or total building square footage. The shifting combination of this set of parameters determines the final aspect of the building and, consequently, the final configuration of the service core. The service core is the second component involved in the automatic generation of a building draft. In the context of BIM, it is an assembly of objects, which contains other objects representing elevators, restrooms, emergency stairs, and space for several technical systems. This assembly is driven by different layouts depending on the building type, a drop-off sequence, which is the process of continuous reduction of elevators along the building, and how this reduction affects the re-arrangement of the service core layout. Results from this research involves a methodology for capturing design knowledge, a methodology for defining the architecture of smart parametric objects, and a method for real-time-feedback for decision making in early design stages. The project also wants to demonstrate the feasibility of continuous growth on top of existing parametric objects allowing the creation of libraries of smart re-usable objects for automation in design. |
keywords |
design automation, parametric modeling, design rules, knowledge-based design |
series |
CAAD Futures |
email |
|
full text |
file.pdf (5,884,901 bytes) |
references |
Content-type: text/plain
|
Amor, R. & Faraj, I. (2001)
Misconceptions about integrated project databases
, ITcon, 6, 57-68
|
|
|
|
Bloom, B., Englehart, M., Furst, E., Hill, W., & Krathwohl, D. (1956)
Taxonomy of educational objectives: The classification of educational goals
, Handbook I : Cognitive domain. New York : Addison Wesley
|
|
|
|
Eastman, C., Tiecholz, P., Sacks, R. & Liston, K. (2008)
BIM for architects and engineers
, BIM Handbook : A guide to building information modeling for owners, managers, designers, engineers and contractors, Hoboken, New Jersey : John Wiley & Sons Inc, 149-204
|
|
|
|
Frazer, J.H., Tang, M.X. & Jian, S. (1999)
Towards a generative system for intelligent design support
, Proceedings of the 4th Conference on Computer Aided Architectural Design Research in Asia, Shanghai, China, 285-294
|
|
|
|
Goodrich, M. & Tamassia, R. (2006)
Data Structures and algorithms
, Java, Hoboken, New Jersey : John Wiley & Sons Inc
|
|
|
|
Lee, G., Sacks, R., & Eastman, C. (2005)
Specifying parametric building object behavior (BOB) for building information modeling system
, Automation in Construction, 15, 6, 758-776
|
|
|
|
Nassar, K., Thabet, W., & Beliveau, Y. (2003)
Building assembly detailing using constraint-based modeling
, Automation in Construction, 12, 365-379
|
|
|
|
Pahl, G., Beitz, W., Feldhusen, J. & Grote, K.H. (2007)
Engineering design, a systematic approach (3rd edition)
, London : Springer-Verlag London Limited
|
|
|
|
Shea, K., Aish, R. & Gourtovaia, M. (2003)
Towards integrated performance-based generative design tools
, Proceedings of the 21st Conference of Education and Research in Computer Aided Architectural Design in Europe, eCAADe, Graz, Austria. 553-560
|
|
|
|
last changed |
2012/02/11 19:21 |
|