The Proceedings of Conference of Kanto Branch
Online ISSN : 2424-2691
ISSN-L : 2424-2691
2002.8
Conference information
Estimating Design Parameters of Jointed Part using Neural Network : Jointed part composed of 2 beams
Hiroyuki OTSUKAAkifumi OKABENoboru TOMIOKA
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CONFERENCE PROCEEDINGS FREE ACCESS

Pages 293-294

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Abstract
In this paper, the method, which estimates the design parameters (thickness, shape of cross section, length of partition, position of flange etc.) using neural network, is described. We deal with simple joined part models composed of 2 beams as an antomobile body structure. At first, some learning data are prepared by changing the design parameters. Next, the relation between joint stiffness and design parameter is constructed by using neural network. Once the trained neural network is given, the design parameter can be estimated by only inputting the some values of joint stiffness into the trained neural network. It was shown that the design parameters were obtained from the values of joint stiffness by using the trained neural network.
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© 2002 The Japan Society of Mechanical Engineers
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