Location

Snowbird, UT, USA

Start Date

1-1-1999 12:00 AM

Description

In this paper, efforts on the inversion of the ultrasonic oblique incidence data to obtain the stiffness constants of orthotropic symmetry material systems such as fiber reinforced composites will be discussed. Artificial Neural Network (ANN) and Hybrid Neural Net/Fuzzy Logic Architectures [1] were used in this effort and the performance will be compared to more traditional methods. This paper seeks to solve these inverse problems in a more general fashion using Artificial Neural Networks (ANN). The acoustical data domains used was the plate wave dispersion curves for unidirectional graphite epoxy composite laminate.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

18B

Chapter

Chapter 5: Engineered Materials

Section

Composites

Pages

1265-1271

DOI

10.1007/978-1-4615-4791-4_162

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

An Artificial Neural Network as a Tool for the Inversion of Ultrasonic Dispersion Data for Material Characterization

Snowbird, UT, USA

In this paper, efforts on the inversion of the ultrasonic oblique incidence data to obtain the stiffness constants of orthotropic symmetry material systems such as fiber reinforced composites will be discussed. Artificial Neural Network (ANN) and Hybrid Neural Net/Fuzzy Logic Architectures [1] were used in this effort and the performance will be compared to more traditional methods. This paper seeks to solve these inverse problems in a more general fashion using Artificial Neural Networks (ANN). The acoustical data domains used was the plate wave dispersion curves for unidirectional graphite epoxy composite laminate.