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The purpose of this paper is to employ the acoustic wave propagation method for leakage detection in pipes. The first objective is to use acoustic finite element analysis (AFEA) method to simulate acoustic wave propagation and acoustic wave reflectometry in an intact pipe and in pipes with leaks of various sizes. This is followed by the second objective which is to validate the effectiveness and the practicability of the acoustic wave method via experimental testing. The third objective involves the decomposition and de-noising of the measured acoustic waves using stationary wavelet transform (SWT). It is shown that this approach, which is used for the first time on leakage detection in pipes, can be used to identify, locate and estimate the size of a leakage defect in a pipe.

The research work was designed inline with best practices and acceptable standards. The research methodology focusses on five basic areas: literature review; experimental measurements; simulations; data analysis and writing-up of the study with clear-cut communication of the findings. The approach used was acoustic wave propagation-based method in conjunction with SWT for leakage detection in fluid-filled pipe.

First, the simulation of acoustic wave propagation and acoustic wave reflectometry in fluid-filled pipes with and without leakage have great potential in leakage detection in pipeline systems and can detect very small leaks of 1 mm diameter. Second, the measured noise-contaminated acoustic wave propagation in a fluid-filled pipe can be successfully de-noised using the SWT method in order to clearly identify and locate leakage as little as 5 mm diameter in a pipe. Third, AFEA of a fluid-filled pipe can be achieved with the simulation of only the fluid content of the pipe and without the inclusion of the pipe in the model. This eliminates contact interaction of the solid pipe walls and the fluid, and as a consequence reduces computational time and resources. Fourth, the relationship of the ratio of the leakage diameter to the ratio of the first and second secondary wave amplitudes caused by the leakage can be represented by a second-order polynomial function. Fifth, the identification of leakage in a pipe is intuitive from mere comparison of the acoustic waveforms of an intact pipe with that of a pipe with a leakage.

The research work is a novelty and was developed from the scratch. The AFEA of acoustic wave propagation and acoustic wave reflectometry in a static fluid-filled pipe, and the SWT method have been used for the first time to detect, locate and estimate the size of a leakage in a fluid-filled pipe.

Ion‐acoustic wave propagation in plasma is discussed. Analytical and numerical solutions are given for one‐dimensional plane waves. The similarity of the ion‐acoustic waves to the waves associated with an electrical transmission line is pointed out and the solved examples are compared with experimental observations.

The acousto-ultrasonic approach is used for propagating stress waves through different configurations of CORTEN steel specimens. The propagated waves are recorded and analysed by piezoelectric sensors. The purpose of the study is to study the characteristics of the CORTEN steel by analysing the propagated waves.

To investigate the attenuation in acoustic wave propagation due to the corrosion formation in CORTEN steel specimens and to train a neural network model to classify the attenuated acoustic waves automatically.

Due to the corrosion formation in CORTEN steel specimens, attenuation is observed in amplitude, energy, counts and duration of the propagated waves. When the waves are analysed in their time-frequency characteristics, attenuation is observed in their frequency and spectral energy.

The corrosion formation in CORTEN steel can automatically be analysed by using the acousto-ultrasonic approach and the trained deep learning neural network.

Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.

An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.

With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.

Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.

This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.

The purpose of this paper is to develop a new finite difference method for solving the seismic wave propagation in fluid-solid media, which can be described by the acoustic and viscoelastic wave equations for the fluid and solid parts, respectively.

In this paper, the authors introduced a coordinate transformation method for seismic wave simulation method. In the new method, the irregular fluid–solid interface is transformed into a horizontal interface. Then, a multi-block coordinate transformation method is proposed to mesh every layer to curved grids and transforms every interface to horizontal interface. Meanwhile, a variable grid size is used in different regions according to the shape and the velocity within each region. Finally, a Lebedev-standard staggered coupled grid scheme for curved grids is applied in the multi-block coordinate transformation method to reduce the computational cost.

The instability in the auxiliary coordinate system caused by the standard staggered grid scheme is resolved using a curved grid viscoelastic wave field separation strategy. Several numerical examples are solved using this new method. It has been shown that the new method is stable, efficient and highly accurate in solving the seismic wave equation defined on domain with irregular fluid–solid interface.

First, the irregular fluid–solid interface is transformed into a horizontal interface by using the coordinate transformation method. The conversion between pressures and stresses is easy to implement and adaptive to different irregular fluid–solid interface models, because the normal stress and shear stress vanish when the normal angle is 90° in the interface. Moreover, in the new method, the strong false artificial boundary reflection and instability caused by ladder-shaped grid discretion are resolved as well.

To develop a new method for estimation of damage configuration in composite laminate structure using acoustic wave propagation signal and a reduction‐prediction neural network to deal with high dimensional spectral data.

A reduction‐prediction network, which is a combination of an independent component analysis (ICA) and a multi‐layer perceptron (MLP) neural network, is proposed to quantify the damage state related to transverse matrix cracking in composite laminates using acoustic wave propagation model. Given the Fourier spectral response of the damaged structure under frequency band‐selective excitation, the problem is posed as a parameter estimation problem. The parameters are the stiffness degradation factors, location and approximate size of the stiffness‐degraded zone. A micro‐mechanics model based on damage evolution criteria is incorporated in a spectral finite element model (SFEM) for beam type structure to study the effect of transverse matrix crack density on the acoustic wave response. Spectral data generated by using this model is used in training and testing the network. The ICA network called as the reduction network, reduces the dimensionality of the broad‐band spectral data for training and testing and sends its output as input to the MLP network. The MLP network, in turn, predicts the damage parameters.

Numerical demonstration shows that the developed network can efficiently handle high dimensional spectral data and estimate the damage state, damage location and size accurately.

Only numerical validation based on a damage model is reported in absence of experimental data. Uncertainties during actual online health monitoring may produce errors in the network output. Fault‐tolerance issues are not attempted. The method needs to be tested using measured spectral data using multiple sensors and wide variety of damages.

The developed network and estimation methodology can be employed in practical structural monitoring system, such as for monitoring critical composite structure components in aircrafts, spacecrafts and marine vehicles.

A new method is reported in the paper, which employs the previous works of the authors on SFEM and neural network. The paper addresses the important problem of high data dimensionality, which is of significant importance from practical engineering application viewpoint.

The objective of this study is to model the influence of free gas, in the form of size‐distributed fine bubbles, on sound attenuation and dispersion in a thin‐walled elastic cylindrical tube filled with viscoelastic polymeric liquid.

Sound wave propagation in the system is described within a three‐phase interaction scheme, based on a quasi‐homogeneous approach to liquid‐gas mixture dynamics in the wave. Coupled equations of tube wall deformations and viscoelastic liquid dynamics in the tube are solved using a long‐wave approximation. The dissipative losses, stemming from flow gradients in the wave, as well as from non‐equilibrium bubble‐liquid interaction, are accounted for. The dispersion equation for the waveguide is obtained and studied numerically.

The results of the study indicate that bubble‐size distribution in viscoelastic liquid has an essential impact on sound propagation in the tube at sufficiently high frequencies. The frequency range in which the mixture heterogeneity influences the acoustic properties of the system is sensitive to both the distribution parameters and the rheological properties of the liquid. As distinct to polydispersity features, the viscoelastic properties of liquid are also relevant in the low‐frequency range, where they lead to an increase of the wave speed and a decrease of its attenuation.

A model of sound wave propagation in a tube filled with a heterogeneous viscoelastic liquid‐bubble mixture is formulated. The study provides a basis for modeling transient processes in tubes filled with polymeric liquids containing free gas, and for acoustic control of certain processes in polymer technologies.

In this work, an SFEM is proposed for solving acoustic problems by redistributing the entries in the mass matrix to “tune” the balance between “stiffness” and “mass” of discrete equation systems, aiming to minimize the dispersion error. The paper aims to discuss this issue.

This is done by simply shifting the four integration points’ locations when computing the entries of the mass matrix in the scheme of SFEM, while ensuring the mass conservation. The proposed method is devised for bilinear quadratic elements.

The balance between “stiffness” and “mass” of discrete equation systems is critically important in simulating wave propagation problems such as acoustics. A formula is also derived for possibly the best mass redistribution in terms of minimizing dispersion error reduction. Both theoretical and numerical examples demonstrate that the present method possesses distinct advantages compared with the conventional SFEM using the same quadrilateral mesh.

After introducing the mass-redistribution technique, the magnitude of the leading relative dispersion error (the quadratic term) of MR-SFEM is bounded by (5/8), which is much smaller than that of original SFEM models with traditional mass matrix (13/4) and consistence mass matrix (2). Owing to properly turning the balancing between stiffness and mass, the MR-SFEM achieves higher accuracy and much better natural eigenfrequencies prediction than the original SFEM does.

This paper aims to show results of numerical simulations of transonic flow around a supercritical airfoil at chord Reynolds number Re_c = 3 × 10⁶, with the aim of elucidating the mechanisms responsible for large-scale shock oscillations, namely, transonic buffet.

Unsteady Reynolds-averaged Navier–Stokes simulations and detached-eddy simulations provide a preliminary buffet map, while a high fidelity implicit large-eddy simulation with an upstream laminar boundary layer is used to ascertain the physical feasibility of the various buffet mechanisms. Numerical experiments with unsteady RANS highlight the role of waves travelling on pressure side in the buffet mechanism. Estimates of the propagation velocities of coherent disturbances and of acoustic waves are obtained, to check the validity of popular mechanisms based on acoustic feedback from the trailing edge.

Unsteady RANS numerical experiments demonstrate that the pressure side of the airfoil plays a marginal role in the buffet mechanism. Implicit LES data show that the only plausible self-sustaining mechanism involves waves scattered from the trailing edge and penetrating the sonic region from above the suction side shock. An interesting side result of this study is that buffet appears to be more intense in the case that the boundary layer state upstream of the shock is turbulent, rather than laminar.

The results of the study will be of interest to any researcher involved with transonic buffet.

The reliable transcranial imaging of brain inner structures for diagnostic purposes is deemed crucial owing to the decisive importance and contribution of the brain in human life. The purpose of this paper is to investigate the potential application of medical ultrasounds to transcranial imaging using advanced techniques, such as the total focussing method.

Initially, the fundamental details of the total focussing method are presented, while the skull properties, such as the increased acoustic velocity and scattering, are thoroughly examined. Although, these skull characteristics constitute the main drawback of typical transcranial ultrasonic propagation algorithms, they are exploited to focus the acoustic waves towards the brain. To this goal, a virtual source is designed, considering the wave refraction, to efficiently correct the reconstructed brain image. Finally, the verification of the novel method is conducted through numerical simulations of various realistic setups.

The theoretically designed virtual source resembles a focussed sensor; therefore, the directivity increment, owing to the propagation through the skull, is confirmed. Moreover, numerical simulations of real-world scenarios indicate that the typical artifacts of the conventional total focussing method are fully overcome because of the increased directivity of the proposed technique, while the reconstructed image is efficiently corrected when the proposed virtual source is used.

A new systematic methodology along with the design of a flexible virtual source is developed in this paper for the reliable and precise transcranial ultrasonic image reconstruction of the brain. Despite the slight degradation owing to the skull scattering, the combined application of the total focussing method and the featured virtual source can successfully detect arbitrary anomalies in the brain that cannot be spotted by conventional techniques.