Modelling ground‐penetrating radar wave propagation using graphics processor unit parallel implementation of the symplectic Euler method

Abstract

Inversion of ground‐penetrating radar signals requires accurate and efficient forward modelling. The symplectic Euler method promises good results when simulating ground‐penetrating radar wave propagation in substructures, but its computational efficiency is limited by the same Courant–Friedrichs–Lewy stability condition as the finite‐difference time‐domain method. A two‐dimensional graphics processor unit–accelerated parallel symplectic Euler algorithm is used to simulate ground‐penetrating radar wave propagation. We compared the reflection waveforms as well as the simulation time of the complex underground structure models simulated by the parallel symplectic Euler method with traditional finite‐difference time‐domain method. Results show that the parallel symplectic Euler algorithm achieves the same level of accuracy as the standard finite‐difference time‐domain method. Moreover, it significantly improves the computational efficiency, as the calculation speed is improved by more than 21 times. We verify the performance of the proposed algorithm through a map of the single‐track radar data for a three‐layered pavement model and a simulation wiggle map for a structural damage pavement model. This provides a theoretical basis for accurately interpreting ground‐penetrating radar detection data and efficient forward modelling for the next step of inversion imaging.

Exploring a near‐surface subsidence over a rehabilitated underground mine through ambient seismic noise tomography in combination with other geophysical methods

“…However, the tilt angle operator uses zero values to delimit the edges, and in cases with multiple sources, this can result in the interpretation of additional edges (Cooper and Cowan, 2006; Li et al ., 2014). Although tilt angle maps can be easily interpreted following the contrasts produced by declinations, the images must be confronted with the solutions produced by an algorithm that takes into account the geometry and depth of the source, for example, Euler's deconvolution technique (Oruç, 2011; Fang et al ., 2019). Further, the simulated annealing algorithm proposed by Nava‐Flores et al .…”

Forward Analysis of GPR for Underground Pipes Using CUDA-Implemented Conformal Symplectic Euler Algorithm

“…In order to accurately interpret the measured GPR images of underground pipes, it is necessary to study the GPR data numerical simulation of underground pipes, and evaluate what useful information can be reasonably extracted from the field data under various conditions [17]- [21]. In the previous study, we established an accurate and efficient forward model based on the symplectic Euler algorithm, surface conformal technology and GPU acceleration technology to simulate the circular cavity disease in pavement structure [22], [23]. However, the CPML boundary was not used in the previous simulation, and the absorption at the boundary was poor.…”