Optimising GPR modelling: A practical, multi-threaded approach to 3D FDTD numerical modelling

Millington, T. M.; Cassidy, Nigel J.

doi:10.1016/j.cageo.2009.12.006

Cited by 29 publications

(10 citation statements)

References 15 publications

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“…At present, the forward modeling methods of GPR mainly include the finite element method (FEM) [16,17], ray tracing method [18,19], the pseudo-spectral time domain method (PSTD) [20], the fast multipole method [21], the finite difference time domain method (FDTD) [22][23][24], the alternating direction-implicit FDTD (ADI-FDTD) [25], and the symplectic Euler algorithm [26,27]. Although these methods can accurately simulate the propagation of a GPR electromagnetic wave in underground structures, these algorithms have some shortcomings with respect to efficiency and precision.…”

Section: Introductionmentioning

confidence: 99%

Analysis of GPR Wave Propagation Using CUDA‐Implemented Conformal Symplectic Partitioned Runge‐Kutta Method

2019

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Accurate forward modeling is of great significance for improving the accuracy and speed of inversion. For forward modeling of large sizes and fine structures, numerical accuracy and computational efficiency are not high, due to the stability conditions and the dense grid number. In this paper, the symplectic partitioned Runge-Kutta (SPRK) method, surface conformal technique, and graphics processor unit (GPU) acceleration technique are combined to establish a precise and efficient numerical model of electromagnetic wave propagation in complex geoelectric structures, with the goal of realizing a refined and efficient calculation of the electromagnetic response of an arbitrarily shaped underground target. The results show that the accuracy and efficiency of ground-penetrating radar (GPR) forward modeling are greatly improved when using our algorithm. This provides a theoretical basis for accurately interpreting GPR detection data and accurate and efficient forward modeling for the next step of inversion imaging.

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Section: Introductionmentioning

confidence: 99%

Analysis of GPR Wave Propagation Using CUDA‐Implemented Conformal Symplectic Partitioned Runge‐Kutta Method

2019

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“…GPU computing has developed in various fields, such as acoustics [22], biomedical applications [23], plasmonics [24], dispersive media [25], and computational electromagnetism [26][27][28][29][30][31][32][33][34]. FDTD based on the GPU acceleration technique has been applied in the GPR simulation model [35,36], but the pseudo-waves that are generated by the ladder approximation in FDTD modeling method are not considered. This study combines FDTD method and surface conformal technique and GPU acceleration technique proposing a precise and efficient forward modeling algorithm of GPR which can greatly reduce computation time and the pseudo-waves that are generated by the ladder approximation.…”

Section: Introductionmentioning

confidence: 99%

Analysis of GPR Wave Propagation in Complex Underground Structures Using CUDA-Implemented Conformal FDTD Method

Lei

Wang²,

Fang

et al. 2019

International Journal of Antennas and Propagation

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Ground penetrating radar (GPR), as a kind of fast, effective, and nondestructive tool, has been widely applied to nondestructive testing of road quality. The finite-difference time-domain method (FDTD) is the common numerical method studying the GPR wave propagation law in layered structure. However, the numerical accuracy and computational efficiency are not high because of the Courant-Friedrichs-Lewy (CFL) stability condition. In order to improve the accuracy and efficiency of FDTD simulation model, a parallel conformal FDTD algorithm based on graphics processor unit (GPU) acceleration technology and surface conformal technique was developed. The numerical simulation results showed that CUDA-implemented conformal FDTD method could greatly reduce computational time and the pseudo-waves generated by the ladder approximation. And the efficiency and accuracy of the proposed method are higher than the traditional FDTD method in simulating GPR wave propagation in two-dimensional (2D) complex underground structures.

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“…4). The GPR data have been obtained using the 3D FDTD method developed in [20,21], which incorporates air-soil interface and realistic antenna configurations, accurate source wavelets, truthful material property descriptions to provide reliable numerical simulations of GPR surveys. The simulations consist of a shielded dipole antenna, having a central frequency of 900 MHz, which radiates over a 0.12 m diameter, circular, water-filled metal pipe buried to a depth of 0.5 m in a dry, lowto-medium loss, uniform sandy soil of relative permittivity ε b ≈ 3.0 and a static conductivity of σ b = 10 mS/m.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…While in [11] the regularization parameter needed in the inversion was determined only by taking into account the expected noise level, here we also constrain it to the features of the scenario. The reconstruction performances of the tomographic algorithm are assessed against synthetic data generated by a finitedifference time-domain (FDTD) forward modeling scheme that is able to simulate realistic GPR experiments [20,21].…”

Section: Introductionmentioning

confidence: 99%

Bistatic Tomographic GPR Imaging for Incipient Pipeline Leakage Evaluation

Crocco¹,

Soldovieri²,

Millington³

et al. 2010

PIER

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Abstract-In this work, we present an inverse scattering approach to address the timely detection of damage and leakage from pipelines via multi-bistatic ground penetrating radar (GPR) surveys. The approach belongs to the class of linearized distorted wave models and explicitly accounts for the available knowledge on the investigated scenario in terms of pipe position and size. The inversion is regularized by studying the properties of the relevant linear operator in such a way to guarantee an early warning capability. The approach has been tested by means of synthetic data generated via a finite-difference timedomain forward solver capable of accurately and realistically modeling GPR experiments. The achieved results show that it is possible to detect the presence of leakage even in its first stages of development.

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Optimising GPR modelling: A practical, multi-threaded approach to 3D FDTD numerical modelling

Cited by 29 publications

References 15 publications

Analysis of GPR Wave Propagation Using CUDA‐Implemented Conformal Symplectic Partitioned Runge‐Kutta Method

Analysis of GPR Wave Propagation Using CUDA‐Implemented Conformal Symplectic Partitioned Runge‐Kutta Method

Analysis of GPR Wave Propagation in Complex Underground Structures Using CUDA-Implemented Conformal FDTD Method

Bistatic Tomographic GPR Imaging for Incipient Pipeline Leakage Evaluation

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