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

2012 ◽  
Vol 163 ◽  
pp. 151-154
Author(s):  
Xiao Ming Zhang ◽  
Yu Qing Wang ◽  
Jun Cai Ding

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.

2021 ◽  
Vol 26 (3) ◽  
pp. 221-230
Author(s):  
Xiaoming Zhang ◽  
Shuangshuang Shao ◽  
Shuijun Shao

Ultrasonic guided waves are widely used in non-destructive testing (NDT), and complete guided wave dispersion, including propagating and evanescent modes in a given waveguide, is essential for NDT. Compared with an infinite plate, the finite lateral width of a rectangular bar introduces a greater density of modes, and the dispersion solutions become more complicated. In this study, a recursive Legendre polynomial analytical integral (RLPAI) method is presented to calculate the dispersion behaviours of guided waves in rectangular bars of orthotropic materials. The existing polynomial method involves a large number of numerical integration steps, and it is often computationally costly to compute these integrals. The presented RLPAI method uses analytical integration instead of numerical integration, thus leading to a significant improvement in the computational speed. The results are compared with those published previously to validate our method, and the computational efficiency is discussed. The full three-dimensional dispersion curves are plotted. The dispersion characteristics of propagating and evanescent waves are investigated in various rectangular bars. The influences of different width-to-thickness ratios on the dispersion curves of four types of low-order modes for a rectangular bar of an orthotropic composite are illustrated.


2018 ◽  
Vol 774 ◽  
pp. 295-302
Author(s):  
Jabid E. Quiroga Mendez ◽  
Octavio Andrés González-Estrada ◽  
Diego F. Villegas

A Semi-Analytical Finite Element (SAFE) formulation is applied to determinethe dispersion curves in homogeneous and isotropic cylindrical waveguides subject touniaxial stress. Bulk waves are required for estimating the guided wave dispersion curvesand acoustoelasticity states a stress dependence of the ultrasound bulk velocities. Therefore,acoustoelasticity influences the wave field of the guided waves. Effective Elastic Constants(EEC) has emerged as a less complex alternative to deal with the acoustoelasticity; allowinga stressed material to be assumed as an unstressed material with EEC which considers thedisturbance linked to the presence of stress. In this approach the isotropic specimen subjectto load is studied by proposing an equivalent stress-free with a modified elasticity matrixwhich terms are the EEC. EEC provides an approximate stress-strain relation facilitating thedetermination of the dispersion curves using the well-studied numerical solution for the stressfreecases reducing the complexity of the numerical implementation. Therefore, a numericalmethod combining the SAFE and EEC is presented as a tool for the dispersion curve generationin stressed cylindrical specimens. The results of this methodology are verified by comparingthem with an approach previously reported in the literature based on SAFE including the fullstrain-displacement relation


1956 ◽  
Vol 23 (1) ◽  
pp. 15-20
Author(s):  
N. J. Huffington

Abstract The analysis of bending and buckling of orthogonally stiffened plates may be simplified by conceptually replacing the plate-stiffener combination by an “equivalent” homogeneous orthotropic plate of constant thickness. This procedure requires the determination of the four elastic rigidity constants which occur in the theory of thin orthotropic plates. Methods are presented whereby these quantities may be determined analytically in terms of the elastic constants and geometrical configuration of the component parts of the structure.


2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Chaojie Hu ◽  
Bin Yang ◽  
Jianjun Yan ◽  
Yanxun Xiang ◽  
Shaoping Zhou ◽  
...  

Abstract This paper investigates the damage localization in a pressure vessel using guided wave-based structural health monitoring (SHM) technology. An online SHM system was developed to automatically select the guided wave propagating path and collect the generated signals during the monitoring process. Deep learning approach was employed to train the convolutional neural network (CNN) model by the guided wave datasets. Two piezo-electric ceramic transducers (PZT) arrays were designed to verify the anti-interference ability and robustness of the CNN model. Results indicate that the CNN model with seven convolution layers, three pooling layers, one fully connected layer, and one Softmax layer could locate the damage with 100% accuracy rate without overfitting. This method has good anti-interference ability in vibration or PZTs failure condition, and the anti-interference ability increases with increasing of PZT numbers. The trained CNN model can locate damage with high accuracy, and it has great potential to be applied in damage localization of pressure vessels.


2019 ◽  
Vol 141 (2) ◽  
Author(s):  
Wenjun Wu ◽  
Yuemin Wang

Due to the multimodal and dispersive characteristics of guided waves, guided wave testing signals are always overlapped and difficult to separate for correct interpretations. To this end, a simplified dispersion compensation algorithm is put forward in this paper. The dispersion elimination is accomplished by compensating the second-order nonlinear phase shift of guided wave signals, which is the cause of the dispersion when narrow band exciting signals are used. This algorithm is easy to implement and has no need of prior knowledge of the guided wave dispersion relationship. Considering that the center frequency, which is a key parameter for this algorithm, is nearly impossible to determine accurately in practical applications, the effect of the center frequency deviation on the algorithm is further studied. Both theoretical analysis and numerical simulation indicate the insensitivity of the algorithm to the deviation of the center frequency, and hence, there is no need to determine the center frequency accurately, facilitating the practical use of the algorithm. Based on this simplified dispersion compensation algorithm and in cooperation with the matching pursuit method, the mode separation is further performed for interpreting of overlapped guided wave signals. Dispersion compensation is first applied to the testing signal with respect to a certain mode which will compress the waveform of the mode while the others still spread. Then, this compressed waveform is separated with the Gabor based matching pursuit method. Both simulation and experiment are designed to demonstrate the effectiveness of the proposed methods.


Geophysics ◽  
2021 ◽  
pp. 1-58
Author(s):  
Bin Luo ◽  
Ariel Lellouch ◽  
Ge Jin ◽  
Biondo Biondi ◽  
James Simmons

Shale formation properties are crucial for the hydrocarbon production performance of unconventional reservoirs. Microseismic-induced guided waves, which propagate within the low-velocity shale formation, are an ideal candidate for accurate estimation of the shale thickness, velocity, and anisotropy. A DAS fiber deployed along the horizontal section of a monitor well can provide a high-resolution recording of guided waves excited by microseismic events during hydraulic fracturing operations. These guided waves manifest a highly dispersive behavior that allows for seismic inversion of the shale formation properties. An adaptation of the propagator matrix method is presented to estimate guided wave dispersion curves and its accuracy is validated by comparison to 3-D elastic wavefield simulations. The propagator matrix formulation holds for cases of vertical transverse isotropy (VTI) as well. A sensitivity analysis of the theoretical dispersion relations of the guided waves shows that they are mostly influenced by the thickness and S-wave velocity of the low-velocity shale reservoir. The VTI parameters of the formation are also shown to have an impact on the dispersion relations. These physical insights provide the foundation for a dispersion-based model inversion for a 1-D depth-dependent structure of the reservoir and its surroundings. The inversion procedure is validated in a synthetic case and applied to the field records collected in an Eagle Ford hydraulic fracturing project. The inverted structure agrees well with a sonic log acquired several hundred meters away from the monitor well. Seismic inversion using guided wave dispersion therefore shows promise to become a novel and cost-effective strategy for in-situ estimation of reservoir structure and properties, which complements microseismic-based interpretation and production-related information.


Author(s):  
Younho Cho ◽  
Joseph L. Rose ◽  
Chong Myoung Lee ◽  
Gregory N. Bogan

An efficient technique for the calculation of guided wave dispersion curves in composite pipes is presented. The technique uses a forward-calculating variational calculus approach rather than the guess and iterate process required when using the more traditional partial wave superposition technique. The formulation of each method is outlined and compared. The forward-calculating formulation is used to develop finite element software for dispersion curve calculation. Finally, the technique is used to calculate dispersion curves for several structures, including an isotropic bar, two multi-layer composite bars, and a composite pipe.


Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. V303-V315 ◽  
Author(s):  
Jiannan Wang ◽  
Robert R. Stewart ◽  
Nikolay I. Dyaur ◽  
M. Lee Bell

Marine guided waves are strongly dispersive and commonly observed in seismic surveys worldwide in areas of shallow water with a hard seafloor. They are energetic and can obscure deeper reflection signals. We have conducted several ultrasonic physical modeling experiments to observe marine guided waves. The guided-wave dispersion curves from these surveys fit theoretical calculations very well. We next developed a new method to extract the subbottom S-wave velocity and density from water column guided waves using least-squares inversion. We have also developed a dispersion-curve filter, in the velocity-frequency domain, to attenuate the guided waves. We then applied these techniques to the physical modeling data, which have different water depths and different subbottom materials. The extracted results (S-wave velocity, density, and water depth) match the actual values well. The dispersion-domain filter clarifies reflections by attenuating the guided waves, which benefits further processing and interpretation.


2021 ◽  
pp. 147592172110239
Author(s):  
Ranting Cui ◽  
Guillermo Azuara ◽  
Francesco Lanza di Scalea ◽  
Eduardo Barrera

The detection and localization of structural damage in a stiffened skin-to-stringer composite panel typical of modern aircraft construction can be addressed by ultrasonic-guided wave transducer arrays. However, the geometrical and material complexities of this part make it quite difficult to utilize physics-based concepts of wave scattering. A data-driven deep learning (DL) approach based on the convolutional neural network (CNN) is used instead for this application. The DL technique automatically selects the most sensitive wave features based on the learned training data. In addition, the generalization abilities of the network allow for detection of damage that can be different from the training scenarios. This article describes a specific 1D-CNN algorithm that has been designed for this application, and it demonstrates its ability to image damage in key regions of the stiffened composite test panel, particularly the skin region, the stringer’s flange region, and the stringer’s cap region. Covering the stringer’s regions from guided wave transducers located solely on the skin is a particularly attractive feature of the proposed SHM approach for this kind of complex structure.


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