Efficient computational algorithms for modeling guided wave dispersion in arterial walls

2018 ◽  
Vol 143 (3) ◽  
pp. 1774-1774
Author(s):  
Ali Vaziri ◽  
Matthew W. Urban ◽  
Wilkins Aquino ◽  
James F. Greenleaf ◽  
Murthy Guddati
Keyword(s):  
Wave Dispersion ◽  
Guided Wave ◽  
Computational Algorithms ◽  
Arterial Walls

Slow Lamb Wave Generation and Reception With a Gold-on-PVDF Interdigitated PVDF Transducer

2004 ◽  
Author(s):  
George M. Lloyd ◽  
Gu Hua ◽  
Ming L. Wang
Keyword(s):  
Lamb Wave ◽  
Single Mode ◽  
Wave Dispersion ◽  
Guided Wave ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Piezoelectric Polymers ◽  
Monitoring Applications ◽  
Signal Processing Algorithms ◽  
Non Destructive

Interdigitated surface and guided-wave transducers have only recently received attention as possible tools for non-destructive testing. This may be due in part to the increasing attention being paid to piezoelectric polymers as practical transduction materials for structural sensing and actuation. However, much remains to be done to produce a rugged, monolithic device oriented toward these sorts of applications, to characterize and optimize its passive and active response, to develop excitation strategies and signal processing algorithms that in tandem can be employed for arrayed structure monitoring applications. In this paper we confine ourselves to the first two topics and report on the development and proof-of-principle testing of a monolithic interdigitated polyvinyldine fluoride (PVDF) transducer. Specifically, we report on the design and response of an interdigitated transducer with relatively large finger spacings. The finger spacing yield measureable responses in the asymptotically slow single-mode region of Lamb wave dispersion behavior for frequency-thickness products which may be useful for nondestructive testing of many mechanical and civil structural systems.

A guided wave dispersion compensation method based on compressed sensing

2018 ◽  
Vol 103 ◽  
pp. 89-104 ◽  
Author(s):  
Cai-bin Xu ◽  
Zhi-bo Yang ◽  
Xue-feng Chen ◽  
Shao-hua Tian ◽  
Yong Xie
Keyword(s):  
Compressed Sensing ◽  
Dispersion Compensation ◽  
Wave Dispersion ◽  
Guided Wave ◽  
Compensation Method

Inversion of guided-wave dispersion data with application to borehole acoustics

2004 ◽  
Vol 115 (1) ◽  
pp. 269-279 ◽  
Author(s):  
Henning Braunisch ◽  
Tarek M. Habashy ◽  
Bikash K. Sinha ◽  
Jahir Pabon ◽  
Jin A. Kong
Keyword(s):  
Wave Dispersion ◽  
Guided Wave ◽  
Dispersion Data

A Simplified Dispersion Compensation Algorithm for the Interpretation of Guided Wave Signals

2019 ◽  
Vol 141 (2) ◽  
Author(s):  
Wenjun Wu ◽  
Yuemin Wang
Keyword(s):  
Guided Waves ◽  
Matching Pursuit ◽  
Dispersion Compensation ◽  
Wave Dispersion ◽  
Guided Wave ◽  
Center Frequency ◽  
Practical Applications ◽  
Compensation Algorithm ◽  
Nonlinear Phase ◽  
Mode Separation

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.

Seismic inversion of shale reservoir properties using microseismic-induced guided waves recorded by distributed acoustic sensing (DAS)

Geophysics ◽  
2021 ◽  
pp. 1-58
Author(s):  
Bin Luo ◽  
Ariel Lellouch ◽  
Ge Jin ◽  
Biondo Biondi ◽  
James Simmons
Keyword(s):  
Hydraulic Fracturing ◽  
Guided Waves ◽  
Wave Dispersion ◽  
Seismic Inversion ◽  
Dispersion Relations ◽  
Guided Wave ◽  
Low Velocity ◽  
Propagator Matrix ◽  
Shale Formation ◽  
Shale Reservoir

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.

scholarly journals Research on ultrasonic guided wave dispersion compensation for steel strand defect detection

2020 ◽  
Vol 740 ◽  
pp. 012101
Author(s):  
Molin Zhao ◽  
Haisheng Wang ◽  
Bin Xue ◽  
Yonggang Yue ◽  
Pengfei Zhang ◽  
...  
Keyword(s):  
Defect Detection ◽  
Dispersion Compensation ◽  
Wave Dispersion ◽  
Guided Wave ◽  
Ultrasonic Guided Wave ◽  
Steel Strand

Spectral analysis of guided wave propagation in discretized domains under local interactions

2019 ◽  
Vol 234 (3) ◽  
pp. 746-769 ◽  
Author(s):  
Pawel Packo ◽  
Piotr Kijanka ◽  
Michael J Leamy
Keyword(s):  
Wave Propagation ◽  
Spectral Analysis ◽  
Wave Dispersion ◽  
Guided Wave ◽  
Numerical Dispersion ◽  
Dispersion Characteristics ◽  
Layered Plates ◽  
Closed Set ◽  
Advantages And Disadvantages ◽  
Transient Simulations

The paper presents a spectral analysis of wave propagation in bounded two-dimensional elastic media discretized under assumptions of two selected local computational strategies. The Local Interaction Simulation Approach and Cellular Automata for Elastodynamics are first overviewed with particular emphasis on their fundamental assumptions, treatment of boundary conditions, and resulting formulations. Each method’s numerical dispersion characteristics for bulk waves are then analyzed using a closed set of iteration equations, after which guided Lamb wave dispersion characteristics are analyzed for homogeneous and layered plates. In all cases, comparisons to finite element dispersion characteristics, re-formulated in the form of local iteration equations, provide insight into the relative advantages and disadvantages of the local formulations and reveal non-physical effects induced by numerical discretization. Finally, verification of the analytical dispersion results is presented using transient simulations with accompanying spectral analysis.

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