Technical Briefs

Visual Steering Commands for Trade Space Exploration: User-Guided Sampling With Example

[+] Author and Article Information
Gary Stump

Applied Research Laboratory, Pennsylvania State University, State College, PA 16804gms158@psu.edu

Sara Lego

Applied Research Laboratory, Pennsylvania State University, State College, PA 16804ses244@psu.edu

Mike Yukish

Applied Research Laboratory, Pennsylvania State University, State College, PA 16804may106@psu.edu

Timothy W. Simpson1

Department of Mechanical and Nuclear Engineering, Pennsylvania State University, University Park, PA 16802tws8@psu.edu

Joseph A. Donndelinger

Vehicle Development Research Laboratory, General Motors Research and Development Center, Warren, MI 48090joe.donndelinger@gm.com


Corresponding author.

J. Comput. Inf. Sci. Eng 9(4), 044501 (Nov 02, 2009) (10 pages) doi:10.1115/1.3243633 History: Received July 28, 2007; Revised July 26, 2009; Published November 02, 2009; Online November 02, 2009

Recent advancements in computing power and speed provide opportunities to revolutionize trade space exploration, particularly for the design of complex systems such as automobiles, aircraft, and spacecraft. In this paper, we introduce three visual steering commands to support trade space exploration and demonstrate their use within a powerful data visualization tool that allows designers to explore multidimensional trade spaces using glyph, 1D and 2D histograms, 2D scatter, scatter matrix, and parallel coordinate plots, linked views, brushing, preference shading, and Pareto frontier display. In particular, we define three user-guided samplers that enable designers to explore (1) the entire design space, (2) near a point of interest, or (3) within a region of high preference. We illustrate these three samplers with a vehicle configuration model that evaluates the technical feasibility of new vehicle concepts. Future research is also discussed.

Copyright © 2009 by American Society of Mechanical Engineers
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Figure 5

Preference-based sampler example: (a) original 100 sample points with preference shading; (b) samples increase in direction of preference; (c) brush settings indicating preference structure

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Figure 6

Exploration engine—system architecture

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Figure 7

Use of design space sampler to achieve more uniform sample distributions: (a) histogram of 78 initial vehicle configurations; (b) histograms updated with 22 new samples

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Figure 8

2D scatter plot of Obj1 versus Obj2: (a) placement of —⌾|Attractor_1 in 2–D scatter plot; (b) updated scatter plot after using point sampler

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Figure 9

Parallel coordinates plot showing Obj1–Obj5 and ConVio (with ConVio=color)

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Figure 10

Plot of Obj1–Obj3 with Obj4=size, ConVio=transparency, and Preference shading=color: (a) glyph plot of current designs; (b) glyph plot after preference-based sampling

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Figure 1

Typical approach to trade space exploration

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Figure 2

Examples of data analysis tools in ATSV: (a) linked views that display the same brush settings; (b) Pareto frontier display (+) and preference shading; (c) using brushing to zoom in within the trade space

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Figure 3

Design space sampler examples: (a) 100 samples in A, B∊[0,1]; (b) 100 new samples in A, B∊[0,0.5]

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Figure 4

Generating new samples near a point of interest with the attractor: (a) original 100 sample points; (b) sample points move toward attractor

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Figure 11

Selection of final vehicle design point: (a) brush/preference controls for making final selection; (b) resulting glyph plot including mass contours



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