FAULT IDENTIFICATION USING FINITE ELEMENT MODELS AND NEURAL NETWORKS

1999 ◽  
Vol 13 (3) ◽  
pp. 475-490 ◽  
Author(s):  
T. MARWALA ◽  
H.E.M. HUNT
Author(s):  
Yaser Ismail ◽  
Lei Wan ◽  
Jiayun Chen ◽  
Jianqiao Ye ◽  
Dongmin Yang

AbstractThis paper presents a robust ABAQUS® plug-in called Virtual Data Generator (VDGen) for generating virtual data for identifying the uncertain material properties in unidirectional lamina through artificial neural networks (ANNs). The plug-in supports the 3D finite element models of unit cells with square and hexagonal fibre arrays, uses Latin-Hypercube sampling methods and robustly imposes periodic boundary conditions. Using the data generated from the plug-in, ANN is demonstrated to explicitly and accurately parameterise the relationship between fibre mechanical properties and fibre/matrix interphase parameters at microscale and the mechanical properties of a UD lamina at macroscale. The plug-in tool is applicable to general unidirectional lamina and enables easy establishment of high-fidelity micromechanical finite element models with identified material properties.


2005 ◽  
Vol 280 (3-5) ◽  
pp. 555-578 ◽  
Author(s):  
Jong Jae Lee ◽  
Jong Won Lee ◽  
Jin Hak Yi ◽  
Chung Bang Yun ◽  
Hie Young Jung

1988 ◽  
Vol 16 (1) ◽  
pp. 18-43 ◽  
Author(s):  
J. T. Oden ◽  
T. L. Lin ◽  
J. M. Bass

Abstract Mathematical models of finite deformation of a rolling viscoelastic cylinder in contact with a rough foundation are developed in preparation for a general model for rolling tires. Variational principles and finite element models are derived. Numerical results are obtained for a variety of cases, including that of a pure elastic rubber cylinder, a viscoelastic cylinder, the development of standing waves, and frictional effects.


1997 ◽  
Author(s):  
Francois Hemez ◽  
Emmanuel Pagnacco ◽  
Francois Hemez ◽  
Emmanuel Pagnacco

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