CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id acadia15_095
id acadia15_095
authors Tam, Kam-Ming Mark; Mueller, Caitlin T.
year 2015
title Stress Line Generation for Structurally Performative Architectural Design
doi https://doi.org/10.52842/conf.acadia.2015.095
source ACADIA 2105: Computational Ecologies: Design in the Anthropocene [Proceedings of the 35th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-53726-8] Cincinnati 19-25 October, 2015), pp. 95-109
summary Principal stress lines, which are pairs of orthogonal curves that indicate trajectories of internal forces and therefore idealized paths of material continuity, naturally encode the optimal topology for any structure for a given set of boundary conditions. Although stress line analysis has the potential to offer a direct, and geometrically-provocative approach to optimization that can synthesize both design and structural objectives, its application in design has generally been limited due to the lack of standardization and parameterization of the process for generating and interpreting stress lines. Addressing these barriers that limit the application of the stress line methods, this paper proposes a new implementation framework that will enable designers to take advantage of stress line analysis to inform conceptual structural design. Central to the premise of the research proposal is a new conception of structurally-inspired design exploration that does not impose a singular solution, but instead allows for the exploration of a diverse high-performance design space in order to balance the combination of structural and architectural design objectives.
keywords Topological Optimization, Structural Optimization, Conceptual Structural Design, Principal Stress Lines, Principal Stress Directions, Optimal Structures, Interdisciplinary Design
series ACADIA
type normal paper
email
last changed 2022/06/07 07:56

_id sigradi2015_8.328
id sigradi2015_8.328
authors Mueller, Volker
year 2015
title Learning about Parametric Model Behavior through Multi-Objective Optimization
source SIGRADI 2015 [Proceedings of the 19th Conference of the Iberoamerican Society of Digital Graphics - vol. 1 - ISBN: 978-85-8039-135-0] Florianópolis, SC, Brasil 23-27 November 2015, pp. 405-413.
summary This paper reports about a design process as a case study illustrating different levels of learning that seem required for successful computational design. The learning process occurred during a two-day workshop about parametric design with integrated analysis and multi-objective optimization. First, the design team needs to understand the behavior of the model in order to validate that the model behaves in a way that actually conforms with the project goals; second, the design team needs to learn about potential trade- offs between different project goals, and thus understand the decisions that need to be made, or the additional problems that need to be solved in order to arrive at a better design solution.
keywords Simulation and Modeling, Generative Systems, Parametric Design Multi-objective Optimization, Computational Design Learning
series SIGRADI
email
last changed 2016/03/10 09:55

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