Project Details

Description

This grant provides funding to examine the impact of high speed, distributed graphical design environments on the efficiency, effectiveness, and satisfaction of the decision-making process during design optimization. These graphical design environments will be implemented using metamodels (simplified models of more complex models) to enhance the speed of the visual design interfaces. The effect of response delay and the availability of a graphical representation of a design and its performance on design time, design quality, and the design process will be examined using metamodel-driven graphical design environments. Students in both graduate and undergraduate courses will help assess various aspects of the graphical design environments within the context of three examples: the design of a bimorph actuator for minimally invasive surgical tools, the design of a desk lamp, and structural design using topology optimization. The desk lamp example will also involve collaboration with researchers from Ecole Centrale Paris in France to examine the effectiveness of graphical design environments for distributed design optimization.

If successful, the results of this research will help guide the development of future graphical design environments to improve design optimization. The proposed research will provide objective and substantive evidence of the impact, both positive and negative, of various components of current graphical user interfaces, leading to improved graphical design environments. The rapid feedback on design performance combined with graphical representations of a design and its performance will help designers improve their understanding of the relationship between a design and its performance, making designers more knowledgeable and, therefore, better decision-makers. Furthermore, by integrating the proposed research within several graduate and undergraduate courses, students will be better educated to work in a distributed design environment.

StatusFinished
Effective start/end date8/15/007/31/04

Funding

  • National Science Foundation: $322,703.00

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