Abstract
Using guided circumferential wave dispersion characteristics, an inverse method based on artificial neural network (ANN) is presented to determine the material properties of functionally graded materials (FGM) pipes. The group velocities of several lowest modes at several lower frequencies are used as the inputs of the ANN model; the outputs of the ANN are the distribution function of the volume fraction of the FGM pipe. The Legendre polynomials method is used to calculate the dispersion curves for the FGM pipe. The internally recurrent neural network is used to improve the convergence speed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
