Dispersion Characteristics Of Guided Waves Research Articles

Theoretical and experimental investigation of circumferential guided waves in orthotropic annuli

The fiber composite materials fabricated by stacking the lamina structure obtain increasing attention in the industry, and at the same time, damage analysis is essential for safe operation. A proposed way to detect defects such as debonding and delamination is to induce circumferential guided waves. Accurate determination of the dispersion characteristics and wave fields is a prerequisite for using acoustic guided waves. The aim of this work is to provide such an accurate dispersion results in an arbitrarily thick cylindrically orthotropic homogeneous cylindrical shell of uniform thickness. Compared with the traditional SAFE method, the proposed method, which combines the two numerical methods, namely Floquet Boundary Condition (Floquet BC) Method and Sweeping Frequency Finite Element Modeling (SFFEM) method has obvious advantages. Through Floquet BC method, a theoretical result can be easily obtained without tedious code writing. Then SFFEM helps to verify the theoretical result in an experimental way. Besides, the slight gap between the theoretical and experimental results works as a basis for calibrating the elastic constants of composite materials provided in the manual. Simulations in COMSOL Multiphysics FE software supported by both methods and experiments by the latter have been carried out in this work. The calculated phase velocity dispersion curves demonstrated the efficiency of those two methods. The developed method can be adapted to other complex pipeline structures to extract circumferential guided wave dispersion characteristics by both simulation and experimental measurements.

A unified description of surface waves and guided waves with relative amplitude dispersion maps

SUMMARYCompared with surface waves, guided waves are rarely applied in near-surface investigation. The main reason may lie in the complexity of their dispersion curves. Besides, the study and understanding of guided wave dispersion characteristics are now also inadequate and not deep enough. In this paper, we derived the complete theoretical dispersion curves of P–SV-wave and pure P-wave systems in layered media based on the transmission matrix method and obtained the relative displacement amplitude coefficients at the free surface as a function of frequency and phase velocity for both surface and guided waves. By assigning the value of relative displacement amplitude coefficient to the corresponding point (f,v) on dispersion curve, we got a multi-information diagram called relative amplitude dispersion map (RADM). As a unified description of surface and guided waves, RADM not only shows the velocity–frequency relationship but also represents the polarized energy ratio at the free surface by display colours. The accuracy of RADM was proved by synthetic seismic records, in which RADMs fit well with the corresponding dispersion energy of surface and guided waves. In addition, we designed six models with different Poisson's ratio (PR) and different layer numbers for comparison. It shows that the dispersive vertical-to-horizontal amplitude ratio of guided waves is complex and discontinuous in RADM, which brings great difficulty for mode identification and even affects the subsequent inversion. Tests also show that for high PR layers, the trends of guided P–SV-wave dispersion curves are basically consistent with those of pure P wave. With the decrease of PR, dispersion curves of guided P–SV wave gradually deviate from those of pure P wave. However, RADMs can be greatly consistent with the dispersion energy in either case. This is of great significance for the inversion of near-surface P and S velocities by using dispersion relationships of multimode surface and guided waves.

Direct Calculation of the Group Velocity for Two-Dimensional Complex, Composite and Periodic Structures Using a Wave and Finite Element Scheme

Guided waves have immense potential for structural health monitoring applications in numerous industries including aerospace. It is necessary to evaluate guided wave dispersion characteristics, i.e., group velocity and phase velocity profiles, for using them effectively. For complex structures, the profiles can have highly irregular shapes. In this work, a direct method for calculating the group velocity profiles for complex, composite, and periodic structures using a wave and finite element scheme is presented. The group velocity calculation technique is easy to implement, highly computationally efficient, and works with the standard finite element formulation. The major contribution is summarised in the form of a comprehensive algorithm for calculating the group velocity profiles. The method is compared with the existing analytical and numerical methods for calculation of dispersion curves. Finally, an experimental study in a multilayered composite plate is conducted and the results are found to be in good agreement. The technique is suitable to be used in all guided wave application areas such as material characterisation, non-destructive testing, and structural health monitoring.

Electromagnetic-pulse-induced acoustic testing for nondestructive testing of plastic composite/metal adhesive bonding

For the hydrogen tanks of type 2 and 3, the metal lining and composite wrapping are bonded together by adhesive. To ensure the safety of these tanks for long-term use, nondestructive testing (NDT) and nondestructive evaluation (NDE) of their plastic composite/metal adhesive bonds are required. However, up to now, there is no effective NDT method for the debonding detection of hydrogen tanks of type 2 and 3. In this study, we propose the use of electromagnetic-pulse-induced acoustic testing (EPAT) to generate guided waves in plastic composite/metal adhesive bonding to detect debonding in adhesive parts. The EPAT method can excite the electromagnetic force from outside of the plastic composite material without contact, thereby directly exciting sound waves on the metal contacting the plastic composite. Through reasonable design, the intensity of the pulsed magnetic field can pass through a very thick plastic composite material and directly induces guided waves in the inner side metal. Therefore, EPAT method has the potential to detect the debonding of plastic composite/metal adhesive bonding in hydrogen tanks of type 2 and type 3 at the site of use. EPAT testing of acrylic/aluminum, glass-fiber-reinforced plastic/aluminum, and carbon-fiber-reinforced plastic/aluminum specimens was performed. The testing signals were analyzed in the time domain and frequency domain. The results indicate that the time-domain signals exhibited guided wave dispersion characteristics. In addition, the guided wave signals showed significant differences between the specimen with debonding and that without debonding, which could be used for the detection of debonding. In addition, different frequency guided waves had different sensitivities to debonding defects.

RETRACTED ARTICLE: Investigation of guided wave dispersion characteristics for fundamental modes in an axisymmetric cylindrical waveguide using rooting strategy approach

We, the Editor & Publisher of Mechanics of Advanced Materials and Structures, have retracted the following article: T. Jothi Saravana (2020) Investigation of guided wave dispersion characteristics for fundamental modes in an axisymmetric cylindrical waveguide using rooting strategy approach. DOI: 10.1080/15376494.2020.1777601 After publication, the author, T.J. Saravana, requested the retraction of this article due to his use of third-party data without the required permissions. Further investigations revealed that the article contained data from an unpublished thesis titled "Analyses on Acoustic Emission Wave Propagation in a Stay Cable using Semi-Analytical FEM" authored by Yang Yaohua in 2018, that was used without permission. As the reuse of data from a third party without acquiring the required permissions is a serious breach of publishing ethics, we are retracting the article from the journal. The author agrees to this retraction. We have received guidance from our policy on publishing ethics and integrity and the COPE guidelines on retractions, which have informed our decision-making process. To maintain the scholarly record, the retracted article will remain available online. We will ensure that it is identified as "Retracted" by adding a digital watermark on each page.

Bayesian dynamic modification of corrosion in a cylindrical rod quantified by guided waves technique

ABSTRACT In this study, both estimation and modification strategies of measurement uncertainty were investigated when using a guided waves (GWs) technique to quantify the corrosion level of a cylindrical rod induced by an accelerated setup, thus providing essential and reliable information for making decisions regarding necessary remedial work. First, the remnant diameters under corrosion were quantified based on the dispersion characteristics of GWs, and the measurement uncertainty derived from time-frequency analysis was specifically considered. After demonstrating the equivalence with the self-adaptive Monte Carlo method, the method in guide to the expression of uncertainty in measurement (GUM) was used as a more efficient approach for carrying out interval estimation of the corrosion level. Furthermore, a designed Bayesian dynamic linear model (BDLM) with a model monitoring mechanism was introduced to modify the measurement sequence. Thus, not only were more credible estimations achieved but discrepant sequences of measurement data could also be identified to avoid a misled judgement.

Sparse recovery of multiple dispersive guided-wave modes for defect localization using a Bayesian approach

Guided wave (GW) testing has become one of the most important nondestructive tools for evaluation of structural in-service degradation. Although GW testing was widely used to inspect and screen many engineering structures, there are still challenges associated with its applications, which mostly originate from the dispersive and multi-mode nature of GW signals as well as noise contamination. To deal with these challenges, an effective GW signal processing technique is introduced that enables one to accurately recover multiple modes from noisy dispersive GW signals for defect localization. To characterize the dispersion phenomenon, the chirp model is introduced first, which is derived from GW dispersion characteristics. Based on this model, an over-complete dictionary is designed by considering all possible defect locations (by discretization) and the propagation paths of GW modes caused by these defects. Then the prior knowledge that structural defects or damage typically occur in localized areas and correspondingly only a small number of modes are included in the GW signals is exploited by a robust sparse Bayesian learning (SBL) framework to reduce the ill-conditioning in the inverse problem. During the implementation of the robust SBL algorithm, irrelevant basis vectors in the dictionary are pruned out and the posterior probabilities of the small number nonzero basis coefficients corresponding to those “active” GW modes are established. After sparse representation of the GW signal, the information of propagation paths and group delays of GW modes are used to identify each GW mode and then localize defects. Illustrative results from numerical simulations and experiment studies on plate structures are presented to demonstrate the capability of the proposed method.

Calculation of Guided Wave Dispersion Characteristics Using a Three-Transducer Measurement System

Guided ultrasonic waves are of significant interest in the health monitoring of thin structures, and dispersion curves are important tools in the deployment of any guided wave application. Most methods of determining dispersion curves require accurate knowledge of the material properties and thickness of the structure to be inspected, or extensive experimental tests. This paper presents an experimental technique that allows rapid generation of dispersion curves for guided wave applications when knowledge of the material properties and thickness of the structure to be inspected are unknown. The technique uses a single source and measurements at two points, making it experimentally simple. A formulation is presented that allows calculation of phase and group velocities if the wavepacket propagation time and relative phase shift can be measured. The methodology for determining the wavepacket propagation time and relative phase shift from the acquired signals is described. The technique is validated using synthesized signals, finite element model-generated signals and experimental signals from a 3 mm-thick aluminium plate. Accuracies to within 1% are achieved in the experimental measurements.

Inverse Identification of Elastic Constants of Orthotropic Plates Using the Dispersion of Guided Waves and Artical Neural Network

Using guided wave dispersion characteristics, a procedure based on articial neural network (ANN) is presented to inversely determine the elastic constants of orthotropic plate. The Legendre polynomial method is employed as the forward solver to calculate the dispersion curves of SH wave for orthotropic plates. The group velocities of lowest modes at five lower frequencies are used as the inputs for the ANN model. The outputs of the ANN are the elastic constants of orthotropic plates. This procedure is examined for an actual orthotropic plate. The results indicate that the identified elastic constants are sufficiently close to the original one. The developed inverse procedure is concluded to be robust and efficient.

Determination of Material Properties of Functionally Graded Plate Using the Dispersion of Guided Waves and an Artificial Neural Network

Abstract Using guided wave dispersion characteristics, an inverse method based on artificial neural network (ANN) is presented to determine the material properties of functionally graded materials (FGM) plates. 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 plate. The Legendre polynomials method is used to calculate the dispersion curves for the FGM plate. Levenberg-Marquardt algorithm is used as numerical optimization to speed up the training process of the ANN model.