مقالات رزومه دکتر مجتبی بابایی

Identifying, detecting, classifying and separating unexploded ordnance (UXO) is one of the essential needs of countries and societies that have been involved in war. Marine mines submerged in seawater or buried in land are a common danger in many areas of the world. The majority of mines are composed of metal and explosive materials. There are many non-destructive schemes for detecting the location, orientation and depth of a metallic mine (modeled as a perfectly conducting sphere and spheroid). These methods of exploration of such materials, which are mainly based on geophysical methods, have a special importance and capability in terms of economy and safety. A major challenge of detecting a metallic object is to discriminate the object, such as an unexploded ordnance, from the noisy environment. It takes time and resources to identify the object, especially due to false signals from other metal objects and cultural features such as metal buildings, pipelines, and oil well casings. By measuring the secondary response of an electrically conductive object placed in a low frequency primary magnetic field, distinct spectral characteristics such as electrical conductivity, magnetic permeability, object geometry, and size can be obtained. Being one of the frequency domain methods, the Electromagnetic Induction method (EMI) is an efficient geophysical method that is used to identify land mines and sea mines. This technique takes into account Eddy-Current Response (ECR) induced on the conducting marine mines as well as Current-Channeling Response (CCR) associated with the perturbation of currents induced in the conductive marine environment. In the processing of the data obtained from geophysical surveys, especially in the EMI, such anomalies are modeled with simple geometric objects such as spheres or spheroids. In the first step of data interpretation and to determine the dimensions of the model that indicates the type of mine or bomb and also to determine its location, it is necessary for the interpreter to have a clear view of how the electromagnetic induction response depends on the geometrical and physical parameters of such materials. For this purpose, in this article, the changes and behavior of the received electromagnetic induction response in the receiver coil are investigated according to the depth, dimension and orientation of the abnormality. The graphs obtained are examined and analyzed using the mentioned variables. While qualitatively determining the state of abnormality to a large extent, the obtained results can be useful in numerical methods of calculation of geometrical and physical quantities of anomalies.

Landmines buried in the sea or land threaten a large number of people around the world, and many people die as a result of these unexploded ordnance. Such ammunition needs to be identified by non-destructive methods. Numerous methods have been used to identify, discriminate and detect them. One of these methods in geophysics is electromagnetism in the time and also frequency domain, by which such anomalies are detected and their physical and geometric parameters are estimated. The electromagnetic induction method (EMI) is one of the frequency domain methods used for this purpose. This technique takes into account Eddy-Current Response (ECR) induced on the conducting marine mines as well as Current-Channeling Response (CCR) associated with the perturbation of currents induced in the conductive marine environment. Sea water is a good conducting medium in low-frequency range. Thus, displacement current can be neglected. The effect of noise due to the background medium can also be neglected. The sphere has often been used as a tractable model of a conducting anomaly in studying the response of electromagnetic induction (EMI) system. A large amount of unexploded ordnance is simulated in the simplest form with a sphere and a spheroid (for more accurate approximation).In this study, using the electromagnetic induction responses which are caused by eddy currents generated on the surface of the object and also the channel current in the host environment, the depth and radius of the buried object are obtained for four different modes of receiver and transmitter coil orientation. The transmitting and receiving coils can be approximated as magnetic dipoles. The incident fields emanating from the transmitting coil are uniform over the extent of the object. The object is considered as a perfect conductor compared to the host environment. To determine the depth and radius, the particle swarm optimization (PSO) algorithm is proposed. This technique is a global optimization method that can be used to solve problems whose answer is a point or surface in a multidimensional space. PSO is adjusted with random particles (models) and searches for targets by updating generations. The algorithm is implemented on the noise-free and noisy data respectively to evaluate the algorithm performance. The simulation results indicate that this method can be an effective way to estimate the depth and radius of the sphere. For noise-free data, the error is almost zero, and when noise is added to detect them, the depth of the anomaly and the radius are calculated with a perfectly acceptable error.

Enhancement on the edges of the causative source is a tool in the interpretation of potential field data. There are many methods for recognizing the edges, most of which involve high pass filters based on derivatives of potential field data. In this paper, a new edge detection method is introduce, called the enhanced mathematical morphology (EMM) filter for interpretation of field data. The EMM filter uses the ratio of the erosion of the total horizontal derivative to the dilation of the total horizontal derivative to recognize the edges of the sources, and can display the edges of the bodies simultaneously. Edge detection of the potential field data has been widely used as a significant tool for geophysical exploration technologies, which can delineate the horizontal locations of causative sources. Normally, various high-pass filters are used to recognize the edges of the potential field data (Evjen 1936; Fedi and Florio 2001; Verduzco et al. 2004; Cooper and Cowan 2006; Cooper and Cowan 2011; Ma and Li 2012; Ma 2013).
The EMM filter uses the ratio of the erosion of THD to the dilation of THD to recognize the edges of the source. Mathematical morphology was developed by Matheron and Serra in 1964 (SERRA, 1983); which is an image analysis and recognition tool. The structuring element (SE) is a basic operator in mathematical morphology, used to interact with an image and to draw conclusions about how a shape fits or misses the shapes in the image. SE consists of a matrix of 0s and 1s that can have any arbitrary shape and size. The basic operations of mathematical morphology are dilation and erosion. Dilation is defined as the maximum value in the window ascertained by the SE. Erosion is defined as the minimum value in the window ascertained by the SE. The EMM filter is expressed as (Lili et al., 2013):
where imerode (F,SE) and imdilate (F,SE) represent the erosion and dilation of the THD, respectively.
In this paper, a new relationship is presented for EMM filter that is tested on synthetic data with and without noise as well as the real potential field data in Qom salt dome. The EMM method successfully delineates the edges of the causative sources, which gives better resolution of the deeper source than other filters, and can display the edges of the bodies in a more centralized way. In this article, a new relationship is defined for the EMM filter as:
The EMM filter was used to recognize the edges of the sources. It can display the edges of the shallow and deep bodies simultaneously. The EMM filter does not require the computation of vertical derivatives, which makes this method computationally stable. The EMM filter is tested on synthetic, and real potential field data in Qom salt dome and the edge detection was done with reasonable results.

The gravity method is one of the geophysical tools used for geological, engineering and environmental investigations where the detection of geological boundaries, cavities, subsurface karstic features, subsoil irregularities, or landfills are essential. In higher accuracy measurements, the microgravity method has been widely and successfully used for locating and monitoring subsurface materials.
Since microgravity methods measure gravity variations at the surface, they are directly influenced by the density distribution in the subsurface and particularly by the presence of formation material, which may create a mass deficit relative to the density of the surrounding terrain. In many cases, deep or small-scale heterogeneities generating low-amplitude anomalies can be detected and the reliability of further interpretation requires highly accurate measurements which are carefully corrected for any quantifiable disturbing effects. The main purpose of the research, that was conducted in small part of a dam site, is to determine the quality and type of subsurface structures in location of tunnel construction. Study area for collecting microgravity data was located at a small part, considered for construction of Siah Bisheh dam, road Tehran to Chalous. Position of microgravity stations were over a tunnel path which in some parts encountered with collapsing structures. The study area was part of Alborz Mountains. Geology formation(Shemshak formation), consisting of lime beds together with igneous rocks which are severely affected by fractures. Data were collected along 13 profiles with separating distance of 15 m. The stations distance and number of data were 15 m and 148 respectively. Bouguer gravity anomaly was calculated after making corrections such as earth tide, free air, Bouguer, topography and terrain effects. The regional effect obtained using a program that is written in FORTRAN to fit orthogonal and orthonormal polynomials on the observed data and then residuals were estimated. Three negative anomalies were distinguishable in residual gravity map. Data of these anomalies are modeled with a 3-D inversion approach using GROWTH 2.0 software. The GROWTH 2.0 is an inversion tool which enables the user to obtain, in a nearly automatic and non-subjective mode, a 3D model of the subsurface density anomalies based on the observed gravity anomaly data. The current version of the tool has been developed from an earlier code (Camacho et al., 2002). In a nearly automatic approach, the software provides a 3-D model informing on the location and shape of the main structural building blocks of the subsurface structures. Then densities contrast of these anomalies was estimated. Result of the inversion was a 3-D distribution of densities contrast. To show this distribution of the densities contrast, the horizontal and vertical sections at different depth and different horizontal positions were selected and interpreted. From these sections it is indicated that the effective depth of the data, for identifying martial of subsurface structures from the inversion, is about 50 m. In the sections, areas with low densitig contrasts are related to the fractured limestone and those with high contrast ones are related to the compact limestone or igneous rocks. Existence of igneous and lime rocks that have more density and compactness, increase the quality of the structures in the path of the tunnel construction. Areas including fractured limestone, with lower density, decrease the quality of the structure and increase the risk of water permeability and collapsing in the path of the tunnel construction. Thus by interpreting of the results of the microgravity data inversion, areas with high and low compactness and good and bad quality rocks for tunnel construction are recognized, those are related to the fractured or karstic limestone and limestone and igneous rocks. Also boundaries of these formations where densitig contrasts vary suddenly, are related to the existence of faults.

In this paper, a novel scheme for depth estimation of a buried conductive sphere as a metallic mine using electromagnetic induction (EMI) data is presented. In electromagnetic induction method, the transmitter coil produces the incident magnetic and electric fields that obey the Maxwell’s equations. In the receiver coil, the received response is created in two modes. Eddy-current mode ( ec V ) is derived from the perfect conductor placed in the shallow depth and another mode called current-channeling response ( cc V ) which depends on the conductivity of the medium. As expected, these responses differ depending on the direction of the incident field related to the receiver coil’s axis. There is a case that the transmitter coil’s axis is parallel to the ground surface and only the eddy current response is measured in the receiver coil. By defining the maximum value of , ecV ,the problem with depth determination transformed into the problem with finding a solution for a nonlinear equation of the form   0 zf .The method is applied to synthetic data with and without random errors. In all of the cases examined, the maximum error in depth is less than 6%.