Research on Non-Manifold Polyhedron from Function-to-Form Mapping

2013 ◽  
Vol 709 ◽  
pp. 499-502
Author(s):  
Zhi Gang Xu ◽  
Jin Wang ◽  
Zi Xang Li ◽  
Chun Po Sun ◽  
Tao Tao Liu
Keyword(s):  
Computational Design ◽  
Design Tools ◽  
Mapping Model ◽  
Shape Decomposition ◽  
Design Computing ◽  
Mapping Process

In this paper, a class of non-manifold polyhedron is introduced and researched from a decomposition and mapping model (D-M for short). Design computing from function-to-form mapping and shape decomposition etc is reported. Modelling of non-manifold polyhedron is the key issue to develop function to form mapping process; and research on function to form mapping could help to develop the creative computational design tools.

An Interactive Morphological Matrix Computational Design Tool: A Hybrid of Two Methods

2007 ◽  
Author(s):  
Cari R. Bryant ◽  
Matt Bohm ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Computational Design ◽  
Design Tool ◽  
Design Tools ◽  
Concept Generation ◽  
University Of Missouri ◽  
Generation Algorithm ◽  
Design Theories ◽  
The University ◽  
Matrix Generator

This paper builds on previous concept generation techniques explored at the University of Missouri - Rolla and presents an interactive concept generation tool aimed specifically at the early concept generation phase of the design process. Research into automated concept generation design theories led to the creation of two distinct design tools: an automated morphological search that presents a designer with a static matrix of solutions that solve the desired input functionality and a computational concept generation algorithm that presents a designer with a static list of compatible component chains that solve the desired input functionality. The merger of both the automated morphological matrix and concept generation algorithm yields an interactive concept generator that allows the user to select specific solution components while receiving instantaneous feedback on component compatibility. The research presented evaluates the conceptual results from the hybrid morphological matrix approach and compares interactively constructed solutions to those returned by the non-interactive automated morphological matrix generator using a dog food sample packet counter as a case study.

scholarly journals Virtual Parts Repository 2: Model-driven design of genetic regulatory circuits

2021 ◽  
Author(s):  
Göksel Mısırlı ◽  
Bill Yang ◽  
Katherine James ◽  
Anil Wipat
Keyword(s):  
Design Patterns ◽  
Computational Models ◽  
Environmental Changes ◽  
Computational Design ◽  
Language Models ◽  
Design Tools ◽  
Hierarchical Systems ◽  
Genetic Circuits ◽  
Model Driven ◽  
Regulatory Circuits

Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits where manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater for the modular composition of models of synthetic systems that do not yet exist in nature. Here, we present the Virtual Parts Repository 2, a resource to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular and composable models. The repository is service-oriented and can be utilized by design tools in computational workflows. Designs provided in Synthetic Biology Open Language documents are used to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a rule-based modeling abstraction based on reaction networks to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction incorporates design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids and cellular resource dependency. The computational resources and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications.

scholarly journals Special Issue: Design computing and cognition

2005 ◽  
Vol 19 (4) ◽  
pp. 227-228
Author(s):  
ANDY DONG
Keyword(s):  
Cognitive Processes ◽  
Computational Models ◽  
Design Science ◽  
Computational Design ◽  
Human Cognition ◽  
Design Cognition ◽  
Special Issue ◽  
Models Of Computation ◽  
Design Computing ◽  
Design Systems

The field of research in design computing and cognition focuses on computational theories and systems that enact design. Design computing and cognition produces a unifying framework to model and explain design beyond the description of “design computing and cognition,” as in “design computing” and “design cognition” as two cognate disciplines. Research in design computing and cognition recognizes not only the essential relationship between human cognitive processes as models of computation but also how models of computation inspire conceptual realizations of human cognition in design. The articles in this Special Issue address the concomitant key areas of research in design computing and cognition: computational models of design, computational representations in design, computational design systems, and design cognition. The computationally inspired perspectives, metaphors, models, and theories that the papers deliver create a base for computing and cognition to (re)shape design practice and its role in design science and inquiry.

A Testing Method and Cognitive Model of Human Diagram Understanding for Automating Design Sketch Recognition

2009 ◽  
Author(s):  
Mark D. Fuge ◽  
Levent Burak Kara
Keyword(s):  
Cognitive Processes ◽  
Visual Recognition ◽  
Peripheral Vision ◽  
Cognitive Model ◽  
Computational Design ◽  
Design Tools ◽  
Testing Method ◽  
Human Attention ◽  
Automated Tools ◽  
Insight Into

Sketches, whether hand-drawn or computer generated, are a natural and integral part of the design process. Despite this fact, modern day computational design tools are ill-equipped to take full advantage of sketching input. The computational challenges of recognizing sketches are easily overcome by human visual recognition and much insight stands to be gained by emulating human cognitive processes. Creating robust, automated tools that overcome the ambiguity of sketching input would allow for advances not only in the practice of engineering design, but in the education of design itself. One first step toward the development of a robust sketching tool is to determine how humans interpret mechanical engineering diagrams. This paper presents two contributions toward the goal of an automated diagram understanding system. First, a method is presented to gain insight into human diagram recognition using techniques analogous to peripheral vision and human attention. Following this, a cognitive model of human diagram understanding is presented from which to further develop computational design tools. With this work, researchers should be able to (1) improve understanding of human diagram recognition and (2) use our model to emulate human diagram recognition in future computational design tools.

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