Neural Network Material Models Determined From Structural Tests
Zhang, Mingfu Michael
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https://hdl.handle.net/2142/83429
Description
Title
Neural Network Material Models Determined From Structural Tests
Author(s)
Zhang, Mingfu Michael
Issue Date
1997
Doctoral Committee Chair(s)
Ghaboussi, J.
D. Pecknold
Department of Study
Civil Engineering
Discipline
Civil Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Artificial Intelligence
Language
eng
Abstract
A nested modular neural network structure is introduced in this study and applied to model uniaxial concrete behavior under cyclic loading and biaxial concrete behavior under monotonic loading and unloading. The results show that the nested modular neural network structure is more flexible and efficient to model path-dependent material behavior than the fully-connected internal neural network structure.
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