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Back propagation neural networks for predicting ultimate strengths of unidirectional graphite/epoxy tensile specimens
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Hill, Eric v. K. Walker, James L. |
| Copyright Year | 1993 |
| Description | The research presented herein demonstrates the feasibility of predicting ultimate strengths in simple composite structures through a neural network analysis of their acoustic emission (AE) amplitude distribution data. A series of eleven ASTM D-3039 unidirectional graphite/epoxy tensile samples were loaded to failure to generate the amplitude distributions for this analysis. A back propagation neural network was trained to correlate the AE amplitude distribution signatures generated during the first 25% of loading with the ultimate strengths of the samples. The network was trained using two sets of inputs: (1) the statistical parameters obtained from a Weibull distribution fit of the amplitude distribution data, and (2) the event frequency (amplitude) distribution itself. The neural networks were able to predict ultimate strengths with a worst case error of -8.99% for the Weibull modeled amplitude distribution data and 3.74% when the amplitude distribution itself was used to train the network. The principal reason for the improved prediction capability of the latter technique lies in the ability of the neural network to extract subtle features from within the amplitude distribution. |
| File Size | 230448 |
| Page Count | 3 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19980019498 |
| Archival Resource Key | ark:/13960/t05x77p43 |
| Language | English |
| Publisher Date | 1993-01-01 |
| Access Restriction | Open |
| Subject Keyword | Structural Mechanics Specimen Geometry Network Analysis Predictions Acoustic Emission Graphite-epoxy Composites Frequency Distribution Composite Structures Tensile Strength Weibull Density Functions Failure Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
