Optimizing Design With Extensive Simulation Data: A Case Study of Designing a Vacuum-Assisted Biopsy Tool

Author:

Lin Chi-Lun1,Coffey Dane2,Keefe Daniel3,Erdman Arthur4

Affiliation:

1. Department of Mechanical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City 701, Taiwan e-mail:

2. Walt Disney Imagineering, 1401 Flower Street, Glendale, CA 91201 e-mail:

3. Department of Computer Science and Engineering, University of Minnesota, 200 Union St SE, Minneapolis, MN 55455 e-mail:

4. Mem. ASME Department of Mechanical Engineering, University of Minnesota, 111 Church St SE, Minneapolis, MN 55455 e-mail:

Abstract

Design by Dragging (DBD) [1] is a virtual design tool, which displays three-dimensional (3D) visualizations of many simulation results obtained by sampling a large design space and ties this visual display together with a new user interface. The design space is explored through mouse-based interactions performed directly on top of the 3D data visualizations. Our previous study [1] introduced the realization of DBD with a simplistic example of biopsy needle design under a static bending force. This paper considers a realistic problem of designing a vacuum-assisted biopsy (VAB) needle that brings in more technical challenges to include dynamic tissue reaction forces, nonlinear tissue deformation, and progressive tissue damage in an integrated visualization with design suggestions. The emphasis is placed on the inverse design strategy in DBD, which involves clicking directly on a stress (or other output field parameter) contour and dragging it to a new (usually preferable) position on the contour. Subsequently, the software computes the best fit for the design variables for generating a new output stress field based on the user input. Three cases demonstrated how the inverse design can assist users in intuitively and interactively approaching desired design solutions. This paper illustrates how virtual prototyping may be used to replace (or reduce reliance on) purely experimental trial-and-error methods for achieving optimal designs.

Funder

National Science Foundation

National Institutes of Health

Publisher

ASME International

Subject

Biomedical Engineering,Medicine (miscellaneous)

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