Research Papers: Design Theory and Methodology

Bond Graph Based Automated Modeling for Computer-Aided Design of Dynamic Systems

[+] Author and Article Information
Zhaohong Wu

Technology Development Department, Marine Acquisition Product Line, CGGVeritas Inc., Houston, TX 77072zhaohong.wu@cggveritas.com

Matthew I. Campbell

Department of Mechanical Engineering, University of Texas at Austin, Austin, TX 78712mc1@mail.utexas.edu

Benito R. Fernández

Department of Mechanical Engineering, University of Texas at Austin, Austin, TX 78712benito@mail.utexas.edu

J. Mech. Des 130(4), 041102 (Mar 19, 2008) (11 pages) doi:10.1115/1.2885180 History: Received November 19, 2006; Revised October 03, 2007; Published March 19, 2008

This paper introduces research leading to a computer-aided design tool in which engineering designers can test various design concepts (topologies) in an environment equipped to automatically model the dynamics and conveniently optimize the specified components (given the evaluation criteria defined by human designers). A component repository is developed to store not only the component dynamics models, but also other information such as typical component design constraints and physical constitutive laws. In this paper, automated modeling of design configurations is introduced through a design representation called a conceptual dynamics graph (CD graph) and generic models of various components. CD graphs contain the information on how physical components as well as their generic models are topologically connected. A generic component model can accommodate various types of coupling between this component and its environment. This paper also discusses a systematic approach to automatically prepare a mechatronic design problem for the use of optimization to tune the parameters for optimum dynamics. Since genetic algorithms are used for this optimization, this preparation decodes and encodes proper design variables into design genotypes while taking into consideration the design constraints and physical constitutive laws.

Copyright © 2008 by American Society of Mechanical Engineers
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Figure 1

Graph depicting the assistive design tool introduced in this paper

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Figure 2

A VC specifies how the interactions between components occur. It provides multidomain information (D1–D8) with certain coupling types (C0–C2) at each domain between the connected components.

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Figure 4

A spring with port a and port b

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Figure 5

Generic model of a two-port spring

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Figure 6

Generic model of a 2D three-port bar

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Figure 7

A 2D generic model of a wheel (gear) with two ports

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Figure 8

3D generic model of a wheel (gear) with two ports

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Figure 9

The system model generation of a 2D crank-and-slider system can be done by connecting the ports in a domain-to-domain manner. The schematic geometric expression of the simplified crank-slider conceptual design is shown in (a) and its CD graph in (b). (c)–(e) represent the BG models for VCs.

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Figure 10

Optimization for a weighing machine design. Samples of design constraints and constitutive laws are listed at different levels.

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Figure 11

The system BG model generated from the CD graph

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Figure 12

CD graph of a weighing machine design

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Figure 13

Automatic construction of genotype representation (c) based on the hierarchical representation of component design rules (a) and (b)

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Figure 14

Equations generated from the CD graph of the weighing machine by automated modeling based on modularized BG models. There are two outputs defined at the beginning of the design process, y1 (the footpad displacement) and y2 (the angle of the dial rotation).

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Figure 15

Response of the best design obtained by GA optimization for weighing machine design. The green dot line and the blue solid line are the footpad and dial responses, respectively.



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