IDENTIFICATION OF SUBSURFACE DRAIN LOCATIONS WITH GROUND-PENETRATING RADAR

1989 ◽  
Vol 69 (2) ◽  
pp. 223-234 ◽  
Author(s):  
T. L. CHOW ◽  
H. W. REES
Keyword(s):  
Dielectric Constant ◽  
New Brunswick ◽  
Ground Penetrating Radar ◽  
Electromagnetic Wave Propagation ◽  
Soil Types ◽  
Propagation Time ◽  
Wave Propagation Velocity ◽  
Apparent Dielectric Constant ◽  
Ground Penetrating ◽  
Moisture Conditions

Ground-penetrating radar (GPR) is a geophysical tool designed for subsurface probing of materials with contrasting dielectric properties. The applicability of this technique to locate agricultural drain tiles or tubes under some soil types and moisture conditions found in New Brunswick and Nova Scotia was evaluated. A method using GPR graphical outputs from adjacent, paired parallel traverses was developed to verify tile drain signatures. Over 50 drains, installed from 1 to 50 years ago, in soils developed in morainal till, glaciofluvial, and glaciomarine deposits were detected with the GPR system and confirmed by excavation. These included both clay and plastic drains. With experience, reliability was found to be close to 100%. The possibility of using the system for determining depth to the drain is also discussed briefly. Key words: Ground-penetrating radar, tube drain location, apparent dielectric constant, propagation time, electromagnetic wave, propagation velocity

Imaging the internal structure of trunks via multiscale phase inversion of ground-penetrating radar data

2021 ◽  
pp. 1-53
Author(s):  
Lei Fu ◽  
Lanbo Liu
Keyword(s):  
Dielectric Constant ◽  
Internal Structure ◽  
Ground Penetrating Radar ◽  
Phase Inversion ◽  
Multiscale Approach ◽  
White Oak ◽  
Near Surface ◽  
Oak Tree ◽  
Ground Penetrating ◽  
Constant Distribution

Ground-penetrating radar (GPR) is a geophysical technique widely used in near-surface non-invasive detecting. It has the ability to obtaining a high-resolution internal structure of living trunks. Full wave inversion (FWI) has been widely used to reconstruct the dielectric constant and conductivity distribution for cross-well application. However, in some cases, the amplitude information is not reliable due to the antenna coupling, radiation pattern and other effects. We present a multiscale phase inversion (MPI) method, which largely matches the phase information by normalizing the magnitude spectrum; in addition, a natural multiscale approach by integrating the input data with different times is implemented to partly mitigate the local minimal problem. Two synthetic GPR datasets generated from a healthy oak tree trunk and from a decayed trunk are tested by MPI and FWI. Field GPR dataset consisting of 30 common shot GPR data are acquired on a standing white oak tree (Quercus alba); the MPI and FWI methods are used to reconstruct the dielectric constant distribution of the tree cross-section. Results indicate that MPI has more tolerance to the starting model, noise level and source wavelet. It can provide a more accurate image of the dielectric constant distribution compared to the conventional FWI.

Kinetic Study of Portland Cement Hydration with Ground Penetrating Radar

2013 ◽  
Vol 539 ◽  
pp. 25-29
Author(s):  
Wei Chen ◽  
Pei Liang Shen ◽  
Jian Xin Lu ◽  
Wan Ru Zhang
Keyword(s):  
Dielectric Constant ◽  
Dielectric Properties ◽  
Ground Penetrating Radar ◽  
Cement Hydration ◽  
Relative Dielectric Constant ◽  
Gradual Decline ◽  
Hardening Process ◽  
Ground Penetrating ◽  
Kinetics Of ◽  
Portland Cement Hydration

The variations of dielectric constant and the amplitude of reflected EM wave of concrete during the first 3 days are measured with Ground Penetrating Radar (GPR) at 20 oC. The amplitude decreases sharply after mixing with water, and then increases till a stabilized stage, followed by a gradual decline. The relative dielectric constant decreases with increasing hydrating time. The results show that the dielectric properties of concrete can be used as an effective way of studying the kinetics of concrete setting and hardening process at early ages.

WISDOM Antenna Pattern in the presence of Rover and Soil

2021 ◽  
Author(s):  
Wolf-Stefan Benedix ◽  
Dirk Plettemeier ◽  
Christoph Statz ◽  
Yun Lu ◽  
Ronny Hahnel ◽  
...  
Keyword(s):  
Pattern Matching ◽  
Ground Penetrating Radar ◽  
Electromagnetic Waves ◽  
Complete System ◽  
Near Field ◽  
System Model ◽  
Soil Types ◽  
Broadband Antenna ◽  
Shallow Subsurface ◽  
Ground Penetrating

<p>The WISDOM ground-penetrating radar aboard the 2022 ESA-Roscosmos Rosalind-Franklin ExoMars Rover will probe the shallow subsurface of Oxia Planum using electromagnetic waves. A dual-polarized broadband antenna assembly transmits the WISDOM signal into the Martian subsurface and receives the return signal. This antenna assembly has been extensively tested and characterized w.r.t. the most significant antenna parameters (gain, pattern, matching). However, during the design phase, these parameters were simulated or measured without the environment, i.e., in the absence of other objects like brackets, rover vehicle, or soil. Some measurements of the rover's influence on the WISDOM data were performed during the instrument's integration.</p><p>It was shown that the rover structure and close surroundings in the near-field region of the WISDOM antenna assembly have a significant impact on the WISDOM signal and sounding performance. Hence, it is essential to include the simulations' environment, especially with varying surface and underground.</p><p>With this contribution, we outline the influences of rover and ground on the antenna's pattern and particularly on the footprint. We employ a 3D field solver with a complete system model above different soil types, i.e., subsurface materials with various combinations of permittivity and conductivity.</p>

scholarly journals Soil water content estimation using ground penetrating radar data via group intelligence optimization algorithms: An application in the Northern Shaanxi Coal Mining Area

2020 ◽  
pp. 014459872097336
Author(s):  
Fan Cui ◽  
Jianyu Ni ◽  
Yunfei Du ◽  
Yuxuan Zhao ◽  
Yingqing Zhou
Keyword(s):  
Dielectric Constant ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Error Rate ◽  
Ground Penetrating Radar ◽  
Volumetric Water Content ◽  
Average Error ◽  
Average Error Rate ◽  
Ground Penetrating

The determination of quantitative relationship between soil dielectric constant and water content is an important basis for measuring soil water content based on ground penetrating radar (GPR) technology. The calculation of soil volumetric water content using GPR technology is usually based on the classic Topp formula. However, there are large errors between measured values and calculated values when using the formula, and it cannot be flexibly applied to different media. To solve these problems, first, a combination of GPR and shallow drilling is used to calibrate the wave velocity to obtain an accurate dielectric constant. Then, combined with experimental moisture content, the intelligent group algorithm is applied to accurately build mathematical models of the relative dielectric constant and volumetric water content, and the Topp formula is revised for sand and clay media. Compared with the classic Topp formula, the average error rate of sand is decreased by nearly 15.8%, the average error rate of clay is decreased by 31.75%. The calculation accuracy of the formula has been greatly improved. It proves that the revised model is accurate, and at the same time, it proves the rationality of the method of using GPR wave velocity calibration method to accurately calculate the volumetric water content.

Ü-Net: Deep-Learning Schemes for Ground Penetrating Radar Data Inversion

2020 ◽  
Vol 25 (2) ◽  
pp. 287-292
Author(s):  
Longhao Xie ◽  
Qing Zhao ◽  
Chunguang Ma ◽  
Binbin Liao ◽  
Jianjian Huo
Keyword(s):  
Neural Network ◽  
Dielectric Constant ◽  
Data Compression ◽  
Ground Penetrating Radar ◽  
Quantitative Imaging ◽  
Inversion Method ◽  
Output Unit ◽  
Data Inversion ◽  
Ground Penetrating ◽  
Constant Distribution

Electromagnetic (EM) inversion is a quantitative imaging technique that can describe the dielectric constant distribution of a target based on the EM signals scattered from it. In this paper, a novel deep neural network (DNN) based methodology for ground penetrating radar (GPR) data inversion, known as the Ü-net is introduced. The proposed Ü-net consists of three parts: a data compression unit, U-net, and an output unit. The novel inversion approach, based on supervised learning, uses a neural network to generate the dielectric constant distribution from GPR data. The GPR data can be compressed and reshaped the size using data compression unit. The U-net maps the object features to the dielectric constant distribution. The output unit meshes the dielectric constant distribution more finely. A novel feature of the proposed methodology is the application of instance normalization (IN) to the DNN EM inversion method and a comparison of its performance to batch normalization (BN). The validity of this technique is confirmed by numerical simulations. The Mean-Square Error of the test data sets is 0.087. These simulations prove that the instance normalization is suitable for GPR data inversion. The proposed approach is promising for achieving quality dielectric constant images in real-time.

Ground Penetrating Radar for Water Content and Compaction Evaluation: A Laboratory Test on Construction Material

2020 ◽  
Vol 25 (2) ◽  
pp. 169-179
Author(s):  
Hashem Ranjy Roodposhti ◽  
Mohammad Kazem Hafizi ◽  
Mohammad Reza Soleymani Kermani
Keyword(s):  
Dielectric Constant ◽  
Water Content ◽  
Ground Penetrating Radar ◽  
Large Scale ◽  
Construction Material ◽  
Construction Materials ◽  
Dielectric Constants ◽  
Base Layer ◽  
Subsurface Water ◽  
Ground Penetrating

With the aid of ground penetrating radar (GPR), it is possible to evaluate physical properties of a constructed base layer in engineered structures (pavement, land consolidation projects, etc.) non-destructively, quickly, and accurately. High spatial variations of subsurface water content and deficient compaction can lead to unexpected damage and structural instability. In this research, we established a relationship between the dielectric constant, water content, and compaction, whereby, an interactive relationship between these parameters is presented. To achieve this, large-scale laboratory experiments were carried out on construction materials to simulate field conditions. According to USCS, the tested soil type was GW-GM (type E base layer according to Iran's highway specifications code). Furthermore, water content and compaction were changed between 4% -12.9% and 84.7% -94.9%, respectively. The travel-times in each test, including three profiles with more than 210 traces, are measured automatically. Additionally, the calculated dielectric constants were compared with the Topp and Roth equations. R-square and RMS error of the final interactive equation between dielectric constant and water content-compaction were 0.95 and 0.41, respectively. Moreover, the sensitivity analysis of the proposed interactive equation shows that changes in water content of soil have greater impact on dielectric constant than soil compaction changes. The data also indicate the importance of considering the compaction changes of soil to reduce the error in dielectric constant estimation.

Experimental Research on Dielectric Constant Model for Asphalt Concrete Material

2011 ◽  
Vol 250-253 ◽  
pp. 2760-2764
Author(s):  
Bei Zhang ◽  
Yan Hui Zhong ◽  
Hua Xue Liu ◽  
Fu Ming Wang
Keyword(s):  
Dielectric Constant ◽  
Experimental Research ◽  
Ground Penetrating Radar ◽  
Asphalt Concrete ◽  
Concrete Material ◽  
The Real ◽  
Applied Technology ◽  
New Models ◽  
Pavement Structures ◽  
Ground Penetrating

Aiming at the problems of the applied technology of ground penetrating radar(GPR), the rationality and applicability of some common existed dielectric constant models to asphalt concrete material are verified and modified based on experiment, and then the new dielectric constant model models suitable for asphalt concrete material are established. The new models are applied to the real project, the results show that the new models can explain the characteristics of asphalt concrete material more accurately, and the calculated error of the compaction of pavement structures based on the modified models is significantly reduced compared to that based on the existed models.

scholarly journals Laboratory Measurements of Subsurface Spatial Moisture Content by Ground-Penetrating Radar (GPR) Diffraction and Reflection Imaging of Agricultural Soils

2018 ◽  
Vol 10 (10) ◽  
pp. 1667 ◽  
Author(s):  
Omer Shamir ◽  
Naftaly Goldshleger ◽  
Uri Basson ◽  
Moshe Reshef
Keyword(s):  
Dielectric Constant ◽  
Soil Moisture ◽  
Moisture Content ◽  
Ground Penetrating Radar ◽  
Soil Type ◽  
Soil Moisture Content ◽  
Root Zone ◽  
Effective Dielectric Constant ◽  
Agricultural Practice ◽  
Ground Penetrating

Soil moisture content (SMC) down to the root zone is a major factor for the efficient cultivation of agricultural crops, especially in arid and semi-arid regions. Precise SMC can maximize crop yields (both quality and quantity), prevent crop damage, and decrease irrigation expenses and water waste, among other benefits. This study focuses on the subsurface spatial electromagnetic mapping of physical properties, mainly moisture content, using a ground-penetrating radar (GPR). In the laboratory, GPR measurements were carried out using an 800 MHz central-frequency antenna and conducted in soil boxes with loess soil type (calcic haploxeralf) from the northern Negev, hamra soil type (typic rhodoxeralf) from the Sharon coastal plain, and grumusol soil type (typic chromoxerets) from the Jezreel valley, Israel. These measurements enabled highly accurate, close-to-real-time evaluations of physical soil qualities (i.e., wave velocity and dielectric constant) connected to SMC. A mixture model based mainly on soil texture, porosity, and effective dielectric constant (permittivity) was developed to measure the subsurface spatial volumetric soil moisture content (VSMC) for a wide range of moisture contents. The analysis of the travel times for GPR reflection and diffraction waves enabled calculating electromagnetic velocities, effective dielectric constants, and spatial SMC under laboratory conditions, where the required penetration depth is low (root zone). The average VSMC was determined with an average accuracy of ±1.5% and was correlated to a standard oven-drying method, making this spatial method useful for agricultural practice and for the design of irrigation plans for different interfaces.

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