Drainage conditions of base and sub-base layers are one of the key factors that affect serviceability of asphalt pavement of the roads. The non-destructive testing method of ground penetrating radar (GPR) has been considered as an applicable method in this respect. In this paper, the relationship between obtained data from recorded images by GPR machine and moisture content of asphalt pavement system was investigated. Eighteen cylindrical samples with 80 cm diameter and height were constructed from asphalt, base, sub-base, compacted medium and natural medium in three different moisture percentages, and then were compacted. Then, a GPR machine, with 250 MHz antenna, was conducted over samples for profiling survey and the obtained radar images were analyzed statistically using Labview software. Comparison of the statisticall parameters obtained from the images showed that distribution of kurtosis is similar to a normal distribution and has logical and interpretable variation-trend with moisture percentage. Therefore, by using a linear curve, fitted between kurtosis and moisture content, an equation was extracted which could help to estimate nearly accurate the moisture content of pavement layers, based on the output of GPR test.

Ground-penetrating radar (GPR) is a popular geophysical method for high-resolution imaging of the shallow subsurface structures. Numerical modeling of radar waves plays a significant role in interpretation, processing, and imaging of GPR data. A number of different approaches have been presented for the numerical modeling of GPR data. The most common approach for GPR modeling is the finite-difference method (FDM) because the FDM approach is conceptually simple and easy to program. The difficulties in applying boundary conditions at non-linear boundaries and the lack of sufficient accuracy in complex geometries are the most important drawbacks of FDM. This paper presents a finite-element method, for simulation of ground-penetrating radar (GPR) in two dimensions in the time-domain. FEM is a powerful and versatile numerical technique for handling problems involving complex geometries and inhomogeneous media. The technique is based on a weak formulation of Maxwell’ s equations. In the FEM method, the wavefield is discretized on the elements using Lagrange interpolation, and integration over an element is accomplished based upon the Gaussian-quad integration rule. The major difference between the various numerical methods is in the spatial discretization. In the elementalbased methods, the complex geometry of the problem is divided into several smaller and simpler elements, then the integrals are calculated for each element. These methods have no with any regular or irregular geometry. The responses of the model in the finite-element methods are approximated in nodal points, so nodal polynomials of Lagrange are used for interpolation of the model response. Besides, the systematic generality of the method makes it possible to construct general-purpose computer programs for solving a wide range of problems. In this paper, at first, Maxwell’ s equations are discretized, then the boundary condition is applied to minimize artificial reflections from the edges of the computation domain. Although the governing equations and mechanisms are completely different between radar and seismic waves, most of GPR data processing approaches are derived from seismic data processing. Due to similarities in these two techniques, accordingly, we implement the first-order Clayton and Engquist absorbing boundary conditions (first order CE-ABC) introduced in the numerical finitedifference modeling of seismic wave propagation. This boundary condition is simple to apply. The presented formulations are in matrix notation that simplifies the implementation of the relations in computer programs, especially in MATLAB application. After spatial discretization with FEM, time discretization is done by Finite-Central Difference (FCD). The time discretization is the most massive and time-consuming step in modeling, which spatial discretization has an important role in this process. The stiffness, mass and damping matrices are sparse and symmetrical in FEM; so if we use the optimized numerical algorithms and storages strategies, computational costs and processing-time can be reduced significantly. To investigate the efficiency of FEM, the computer program has been written in MATLAB and has been tested on two models. The results show that the radar wave simulation via FEM is an accurate and effective approach in complex models.

Cleaning of contaminated lands containing unexploded ordnance (UXO) and mine fields demands special consideration in the war-torn countries. Some geophysical methods have been used for detecting these destructive remnants of war. Nowadays, airborne GPR has been considered as a fast and effective tool for UXO detection. In this study, the feasibility of airborne GPR for detection of anti-personal metallic landmines has been investigated by numerical simulation of back scattered GPR waves from two artificial physical models A and B. Model A is a column of a two-layer model comprising of a layer of soil under a layer of air. In model B, an anti-personal metallic landmine has been buried in the center of model A at a depth of 10 cm beneath the soil. By using the numerical finite-difference time-domain (FDTD) method, the radargram and central traces of back scattered GPR waves from both physical models A and B have been simulated in various altitudes (0-10 meters) and operating frequencies of the transmitted GPR wave (100-1500 MHz). To do this, MATLAB and REFLEXW software packages have been employed. Moreover, several signal processing techniques including signal energy analysis, multi resolution wavelet transform, and time-frequency analysis have been performed instead of using the noise removal and trace extraction, which are related to the target. As a result, detection of intended mine becomes possible by applying airborne GPR up to altitude of 10 m and using operation frequency of transmitted GPR wave of 550 MHz to over 1000 MHz.

Ground Penetrating Radar (GPR) method has been extensively employed to map shallow subsurface targets. This method has been widely used to image faults, deformations and discontinuity in network inside rock in engineering and geological studies. The first aim of this study is to show applicability of GPR method in geotechnical study of conductive area (similar to the area around a dam) and the second goal of the study is to verify the capability of a new generation of GPR system (Loza) in imaging of deep targets. In addition, the main features of this system are described in this paper. GPR signal propagation is strongly controlled by water content. It has limited performance in fine grain soils such as clays, marl and silts, or in saline groundwater, all of which strongly attenuate signals. The main restriction of the method is the limited penetration especially in the areas with conductive materials. Unlike the common GPR systems, the Loza system can penetrate deep into the ground even in the conductive areas (up to 250 m). The GPR Loza is a portable, enhanced-power ground penetrating mono-pulse radar developed by VNIISMI Ltd. A distinctive feature of this instrument as compared to other commercial GPR systems is an increase in the transmitter peak power by a factor of 10000 to work in environments with high conductivity. The 10 KW high-power transmitter with 25 MHz unshielded antenna and 6 m length was applied for subsurface study to the depth of 10 m. The average velocity of subsurface was chosen 0.11 m (ns) −1according to the subsurface materials. With the Loza GPR system, the high power transmission of radar waves in asynchronous mode are recorded with resistive loaded dipole receivers. Geophysical study by GPR method was carried out to find the geophysical properties around Khansar dam. Khansar dam is an earth dam with clay core and 5 million cubic meters reservoir capacity. The dam is of 770 m length, 38 m height, and 10 m crest width. It is located south of Khansar city in the east of Zagrous Chain Mountains. The main geological layers in the study area are limestone, schist and young alluvium. The objective of the study was to investigate contacts of the clay core of the dam with the bedrock and alluvium, groundwater level and the channel and cavities in the bedrock, alluvium and dam. A total of 9916 m parallel and perpendicular profiles was designed for achieving these purposes. The profiles over the dam consist of two groups of profiles. First, profiles that were carried out along the dam, over the rip rap and berms and second, the profiles that were carried out over the dam along the river. Three profiles have been selected for interpretation. Despite the conductive area of the dam, suitable data was received from the depth of 100 m. For each profile, the geological model is designed based on the interpretation and analysis of GPR data. Furthermore, the Krot software was applied for processing and data interpretation. Several anomalies have been detected based on the GPR processed data and geological information. Moreover, Geological layers and the bedrock (which is crashed along some profile) have been detected in the radar grams. In addition, a buried channel is distinguished in the profiles which is located over a crashed zone. The buried channel, weak and heterogeneous zones are interpreted in the GPR radar grams and plotted in the map of the dam. Separation of the geological structure to the depth of 100 m verifies the applicability of this system. Subsequent drilling results in the dam area approve the results of the GPR data.

Accurate prediction of river daily discharge is a suitable tool for water resources planning and management. In this paper, cross station discharge of the Arkansas River in U. S. A, were examined using Gaussian Process Regression (GPR), Extreme Learning Machine (ELM) and complete ensemble empirical mode decomposition combined models. For this Purpose, in the first step, the daily and monthly discharge was predicted via GPR and ELM models. Then, the discharge time series were broken up by CEEMD method into cages, and these subclasses were introduced into the Gaussian process regression end ELM modeling to simulate discharge. Furthermore, direct correlation (DC), Root Mean Square Error (RMSE), correlation coefficient (R) and Mean Absolute Percentage Error (MAPE) were used to evaluate the efficiency of the models. The results showed that the CEEMD approach improved the performance of the above mentioned models dramatically. For instance, the values of MAPE correspond to GPR hybrid model in forecasting discharge in the first, second and third station with CEEMD pre-processing were reduced by 34, 27and 32 percent, respectively, as compared to those in the GPR model without pre-processing. Also, the effect of each of the sub-series of ensemble empirical mode decomposition model (Residual and IMFs) was studied to improve predictive outcomes. It was observed that the most inefficient subseries in the complete ensemble empirical mode decomposition model is the residual subseries. The CEEMD-ELM model can be used in watershed management and flood control in Iran.

Ground water, cavities, and isolate buried structures embedded at shallow depths are well detectable by resistivity and GPR methods because of distinct contrast in their electric and electromagnetic properties in comparison with their surrounding media. In this research work, 3 different profiles on such targets have been chosen, and their responses have been investigated. Using both resistivity and GPR methods together, it has also been possible to investigate capabilities and limitations of the methods in practice. The results obtained from this research work indicate that the GPR method, in addition to its speed and simplicity in data acquisition, is very successful in detection of interfaces or boundaries between different media in which electromagnetic properties at the boundaries change rapidly. The resistivity surveys, which have been carried out using Wenner array in this study, indicate low resistivity of the media under investigation. The low resistivity of the subsurface media caused the depth of penetration of the GPR method to be low, and as a result, made it impossible to investigate the targets buried at depths greater than 2 meters. Unlike the GPR method, the resistivity method has not been very successful in detection of multiple targets with high resistivity contrasts. Lower resolution of the resistivity method in comparison with GPR method has caused this problem. In this study, considerable information has been obtained by selecting two different processing algorithms and applying them on a series of raw GPR dataset.The obtained information from the resistivities of the subsurface structures as a result of the resistivity surveys has made it possible to choose and apply these processing algorithms. This research work well indicates that high conductive areas in resistivity sections coincide with the areas in the GPR sections having intensive attenuation. This characteristic can be used well in the interpretation of the GPR sections. Finally the resistivity method can be introduced as a suitable supplementary geophysical method to the GPR method.

Ground penetrating radar (GPR) is a non-destructive evaluation geophysical method that is able to detect and imaging the all kinds of human handmade structures, subsurface heterogeneities caused by buried objects, identifying empty spaces and cavities in environments and shallow buried targets. GPR has many applications in diverse fields of engineering and science. In the present research, the ability of employing GPR method to detect and determine the location of unmarked graves and buried corps, for archaeological purposes and similar cases has been investigated. In Iran country, the GPR method has not been widely used in archeology, especially for discovery of unmarked graves and detection of buried corps...

Radar method (GPR) is one of the electromagnetic methods to detect shallow depth of underground layers. Sarab E Ghanbar region which is situated at south of Kermanshah city is at thrusted Zagros region. At this region limestone with different ages are adjacent to radiolarites sediments. Due to fractured Limestone and low permeability of radiolarites, study of radiolarites is important as the latter acts as a dam to water flow from limestone. 100MHZ unshielded antenna has been used to a small part of radiolarites to detect fractured and deformed layers. Depth of penetration of radar waves is lm and their velocity is 0.069m/ns. Radargrams show the main fracture at 8m from the first point of the measurements. Deformed layers are located at different horizontal distances at maximum depth of 1.5m. Some radargrams show an anticline at 22m which is in agreement with field observation.

Ground penetrating radar (GPR) is a strong tool for non-destructive detection of buried targets. This radar can determine the location and shape of targets based on the received signals from the electromagnetic waves transmitted to the ground. In this paper, we intend to determine the depth and diameter of buried cylindrical conductor targets in an unknown background environment using the ground penetrating radar. Examples include the detection of water, oil or gas pipes buried under the ground. For this purpose, the SAR algorithm is used and a new method for estimating the depth and diameter of the scatterer is proposed, assuming that relative permittivity of the host environment is not known. The geometry of the problem is two-dimensional and the configuration of the antennas is similar to that of the commercial ones, which is multi-monostatic. For assessment, the proposed method is implemented on the raw data related to buried targets at the depth of 1m. The GPRMAX_2Dsoftware is used to provide raw data to reconstruct the shape of scatterer. Results show that the scatterer depth and diameter are estimated with acceptable accuracy.