Research Papers

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

[+] Author and Article Information
Chi-Lun Lin

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

Dane Coffey

Walt Disney Imagineering,
1401 Flower Street,
Glendale, CA 91201
e-mail: dcoffey86@gmail.com

Daniel Keefe

Department of Computer Science and
University of Minnesota,
200 Union St SE,
Minneapolis, MN 55455
e-mail: keefe@cs.umn.edu

Arthur Erdman

Department of Mechanical Engineering,
University of Minnesota,
111 Church St SE,
Minneapolis, MN 55455
e-mail: agerdman@umn.edu

Manuscript received January 14, 2018; final manuscript received March 26, 2018; published online May 4, 2018. Assoc. Editor: Rita M. Patterson.

J. Med. Devices 12(2), 021007 (May 04, 2018) (7 pages) Paper No: MED-18-1008; doi: 10.1115/1.4040043 History: Received January 14, 2018; Revised March 26, 2018

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.

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Grahic Jump Location
Fig. 1

Examples of designing a biopsy needle using direct manipulation via data visualizations. In forward design, the user drags an edge of the opening window to the right (a). This operation is interpreted as decreasing the window length (b). In inverse design, the user attempts to move a high-stress region (the cursor location) away from the corner of the opening window. The user right-clicks on the region (c), then, the system suggests design alternatives that have the closest distances (determined by calculating the differences between the parameter values and the weighting) from the current one, shown as preview bubbles (enlarged view in circular windows). Each of the preview bubbles shows a magnified view of local stress distribution, which informs where the high-stress region can possibly move to. The user finally moves into the most-right preview bubble to switch to a new design alternative. This design alternative shows the high-stress region has moved away from the window corner (d).

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Fig. 2

An illustration of the VAB tissue cutting mechanism

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Fig. 3

Flowchart for populating a VAB tool design space of in dbd

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Fig. 4

Geometrical assembly of the abaqus Explicit model

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Fig. 10

Shrinking a high-stress area occurred near the cutters tip: (a) step 1, (b) step 2, and (c) step 3

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Fig. 9

(a) The dry tap was identified in both the deformed mesh view (top) and the sectional view of the stress contour (bottom); (b) five preview bubbles were trigger; (c) a design solution reached by moving into the preview bubble in red: (a) step 1 (deformed mesh shown on the top and stress distribution shown on the bottom), (b) step 2, and (c) step 3

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Fig. 8

Directly manipulating on the visualization to reduce the axial tissue displacement: (a) step 1, (b) step 2, and (c) step 3

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Fig. 7

Reduction of axial cutting force caused by increasing the slice-push ratio (bottom: r = 0.1, top: r = 10), which results in a smaller axial tissue displacement. It is also observed for the case on the top, the tissue fracture occurs mostly surrounding the cutting1 edge. This causes more tissue volume to be captured inside the inner cutter.

Grahic Jump Location
Fig. 6

Weighting conditions set in the radar chart widget

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Fig. 5

Design space loaded in dbd. Ignore the gray sphere in the enlarged local visualization, which was created for the development purposes and will be removed in the future versions.



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