Application of Symplectic Partitioned Runge-Kutta Method and Total-Field Scattered-Field Formulation to Simulation of GPR Data

2014 ◽  
Vol 926-930 ◽  
pp. 2777-2780
Author(s):  
Hong Yuan Fang ◽  
Jian Li ◽  
Jia Li
Keyword(s):  
Scattered Field ◽  
Measured Signal ◽  
Total Field ◽  
Time Step ◽  
Absorbing Boundary ◽  
Runge Kutta Method ◽  
Actual Field ◽  
Ground Penetrating ◽  
Radar Wave ◽  
Difference Time

The second-order Lobatto IIIA-IIIB symplectic partitioned RungeKutta (SPRK) method, combining with the first-order Mur absorbing boundary condition, is developed for the simulation of ground penetrating radar wave propagation in layered pavement structure. For 2-dimetional case, a significant advantage of this method is that only two functions need to be calculated at each time step. The total-field/scattered-field technique is used for plane wave excitation. Numerical examples are presented to verify the accuracy and efficiency of the proposed algorithm. The results illustrate that the reflected signal calculated by the SPRK method is in good agreement with that obtained using the finite difference time domain (FDTD) scheme, but the CPU time consumed by proposed algorithm is reduce about 20% of the FDTD scheme. In addition, an actual field test is conducted to evaluate the further performance of the SPRK method. It is found that the simulated waveform fits well with the measured signal in many aspects, especially in the peak amplitude and time delay.

Simulation of ground‐penetrating radar waves in a 2-D soil model

Geophysics ◽  
1996 ◽  
Vol 61 (4) ◽  
pp. 1034-1049 ◽  
Author(s):  
David A. Casper ◽  
K ‐J. Samuel Kung
Keyword(s):  
Ground Penetrating Radar ◽  
Flow Simulation ◽  
Absorbing Boundary Conditions ◽  
Absorbing Boundary ◽  
Background Medium ◽  
Soil Model ◽  
Soil Structures ◽  
Homogeneous Background ◽  
Ground Penetrating ◽  
Radar Wave

We have developed a pseudospectral forward modeling algorithm for ground‐penetrating radar (GPR) based on an explicit solution of the 2-D lossy electromagnetic wave equation. Complex soil structures can be accommodated with heterogeneous spatial distributions of both wave velocity and electrical conductivity. This algorithm uses a Gaussian line source with uniform directivity, and there are conductive buffer regions surrounding the soil model to approximate absorbing boundary conditions. Three soil models are used to illustrate different aspects of radar wave propagation. The first model is lossless with homogeneous layers imbedded in a homogeneous background medium, the second model has the same lossless layers in a lossy background medium, and the third model is lossless and uses a nonsaturated water flow simulation to create a complex spatial velocity distribution. Two separate simulations with different source frequencies are presented for each soil model. Results indicate that higher frequency GPR will produce a sharper wavelet and can map soil layering structures with high resolution. In a conductive soil, however, higher frequencies attenuate more rapidly and the radar may not detect deeper layers.

Numerical Simulation Modeling of GPR on Road Disease

2012 ◽  
Vol 178-181 ◽  
pp. 1463-1468
Author(s):  
Bo Zhai ◽  
Zhi Min Gong
Keyword(s):  
Numerical Simulation ◽  
Wave Propagation ◽  
Simulation Modeling ◽  
Electromagnetic Wave Propagation ◽  
Fdtd Method ◽  
Road Maintenance ◽  
Ground Penetrating ◽  
Radar Wave ◽  
Difference Time ◽  
Propagation Rules

Numerical simulation of ground penetrating radar is an effective way of analyzing and studying high frequency electromagnetic wave propagation rules in the underground media. In this paper, Finite-Difference Time-Domain (FDTD) method is used for numerical simulation to form radar records reflection profile about road disease such as loose disease. The purpose is to study and sum up the radar wave propagation rules and reflection signal characters in this diseases media, in order to provide reliable theory support for road maintenance and evaluation.

Application of the piecewise constant method in nonlinear dynamics of drill string

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jialin Tian ◽  
Jie Wang ◽  
Yi Zhou ◽  
Lin Yang ◽  
Changyue Fan ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Dynamic Model ◽  
Dynamic Characteristics ◽  
Drill String ◽  
Vibration Velocity ◽  
Kutta Method ◽  
Time Step ◽  
Piecewise Constant ◽  
Runge Kutta Method ◽  
Runge Kutta

Abstract Aiming at the current development of drilling technology and the deepening of oil and gas exploration, we focus on better studying the nonlinear dynamic characteristics of the drill string under complex working conditions and knowing the real movement of the drill string during drilling. This paper firstly combines the actual situation of the well to establish the dynamic model of the horizontal drill string, and analyzes the dynamic characteristics, giving the expression of the force of each part of the model. Secondly, it introduces the piecewise constant method (simply known as PT method), and gives the solution equation. Then according to the basic parameters, the axial vibration displacement and vibration velocity at the test points are solved by the PT method and the Runge–Kutta method, respectively, and the phase diagram, the Poincare map, and the spectrogram are obtained. The results obtained by the two methods are compared and analyzed. Finally, the relevant experimental tests are carried out. It shows that the results of the dynamic model of the horizontal drill string are basically consistent with the results obtained by the actual test, which verifies the validity of the dynamic model and the correctness of the calculated results. When solving the drill string nonlinear dynamics, the results of the PT method is closer to the theoretical solution than that of the Runge–Kutta method with the same order and time step. And the PT method is better than the Runge–Kutta method with the same order in smoothness and continuity in solving the drill string nonlinear dynamics.

Memory-Efficient 3-D LWD Solver With the Flipped Total Field/Scattered Field-Based DGFD Method

2020 ◽  
Vol 17 (9) ◽  
pp. 1498-1502 ◽  
Author(s):  
Runren Zhang ◽  
Zhenguan Wu ◽  
Qingtao Sun ◽  
Mingwei Zhuang ◽  
Qiang-Ming Cai ◽  
...  
Keyword(s):  
Scattered Field ◽  
Total Field ◽  
Memory Efficient
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