نشریه فناوری آزمون های غیرمخرب
سال سوم شماره 2 (پیاپی 12، پاییز و زمستان 1401)

The nuclear industry has undergone a significant technological revolution in recent years, with neural networks playing an increasingly important role. These advanced machine learning algorithms are now widely used to analyze nuclear data obtained from various sources, such as calculations, modeling, simulation, and nuclear sensors including gamma ray-based gauges, experimental tests, and non-destructive tests like radiography. Non-destructive measurement methods based on gamma rays passing through materials or processes have gained popularity due to their effectiveness and safety in the nuclear industry. These methods typically use radioactive radioisotope sources like cesium-137 and cobalt-60, along with scintillation detection units, to capture data related to fluid thickness, density, and flow. By applying neural networks, these measurements can be made even more accurate and reliable, ensuring optimal safety and efficiency in the nuclear sector. To investigate this further, a study was conducted to design the geometry of the transmission mode for radioisotope thickness measurement through simulation using the MCNPX Monte Carlo code. The model included three commonly used metals in industries: copper, iron, and aluminum, to determine their thickness. To create the dataset, the thickness of the samples was varied from 0.5 to 50 mm, with a step size of 0.5 mm, and the results of Monte Carlo calculations were recorded as pulse height in the detector. Artificial neural networks were trained based on radial basis functions (RBF) and multilayer perceptron (MLP) techniques using all the results obtained from different energies. After training, the networks were tested to predict the thickness of different metals. The results obtained from the two networks were compared for the output of the model. The study showed that the response of the MLP network was more satisfactory than that of the RBF network in this application. Overall, the study highlights the potential of neural networks in enhancing the accuracy and reliability of non-destructive measurements in the nuclear industry, particularly in predicting the thickness of different materials.

Polyethylene (PE) pipes are widely used in oil and gas industry. Their joints are prone to various flaws e.g., lack of fusion and cold fusion, and are the most problematic part of the pipeline. So, the infrastructure industry requires effective techniques to evaluate the pipes and joints. Butt-fusion (BF) is the most common method of joining PE pipes. Ultrasonic inspections are usually carried out using pulses of finite bandwidth with different frequency components. PE is viscoelastic and its mechanical response at high frequency differs significantly from that of the low frequency. Therefore, when a broadband ultrasound pulse passes through PE pipe, the waveform of the pulse changes as result of attenuation and dispersion of PE. Previously, attenuation was primarily thought of in terms of the reduction of signal amplitude, ultimately limiting the penetration of ultrasound. Actually, one of the major effects of acoustic absorption through PE is wave form distortion. In the present study, with the aim of investigating the possibility of using ultrasonic waves to evaluate HDPE materials and butt fusion of polyethylene pipes, the characteristics and behavior of ultrasonic waves in HDPE materials are studied and researched. For this purpose, the finite element method is used to simulate the propagation of ultrasonic waves in HDPE butt fusion joints. Changes in the wave velocity, and amplitude of the received waves are measured in order to identify the dispersive behavior and attenuation of the waves in HPDE within the effective ultrasonic frequency range of 1-5MHz. Also, by modeling the lack of fusion (LOF) defects embedded in the BF joint with different lengths, the inspection sensitivity, using a 4MHz transducer, for evaluating the LOF defects is evaluated. The numerical results show that the dispersive behavior of longitudinal wave is decreased, as the frequency of transducer increases. Therefore, higher frequency transducers, in the range of 4-5 MHz, can be used for ultrasonic inspection of HDPE butt fusion joints to increase the inspection sensitivity.

In this paper, the effects of some field factors in the non-destructive evaluation of the corrosion rate of the floor of oil storage tanks have been investigated using the magnetic flux leakage method at the industrial level. For this purpose, the effect of factors such as the cathodic protection system on the tank, the presence of waste, the presence of metal attachments (spot welding or spatter), distortion of the tank and the coating thickness of plate on the accuracy of the assessment of the size of defects in different situations have been studied. The field inspections were carried out in two oil tanks using the MFL3DiM magnetic flux leakage unit on the detected defects. Two standard steel blocks with thicknesses of 6 and 8 mm and 4 specific defects in different sizes (20, 40, 60 and 80% of the plate thickness) was used for setting and calibrating the device. Ultrasonic thickness measurement was also used to verify the results of MFL measurement.  In addition, the MFL results were clarified by an ultrasonic thickness measuring unit. The results of the evaluations showed that when the cathodic protection system is turn on, it caused a decrease in the measurement accuracy and the corrosion defects with a less than 22 mass loss percent are not identified. Also, the presence of a metal attachments (welding spot) with a height of 5 mm caused defects with a corrosion depth of less than 25% not to be detected. On the other hand, it was observed that the presence of attachments and waste on the bottom of the tank caused the error in detecting the depth of corrosion to be greater than the length and width of the defect. The presence of waste on the bottom of the tank caused defects with a corrosion depth of less than 18% not to be detected. Distortion in the bottom sheet of the tank caused false defects to be detected in the sheet and the dimensions of the real defects were reported completely wrongly. The presence of a coating with a thickness of more than 3000 micrometers made the defects of the calibration plates undetectable. Additional investigations showed that if the difference in the thickness of the non-magnetic coating on the sheet is higher than 500 micrometers, the dimensions of the detected defects are unrealistic and unreliable.

Obstruction of turbine blade in different turbines can lead to dangerous accidents, and it is important to check these blades during construction and operation. Due to blockage of air channels, hot spots can lead to blade damage. In this research, X-ray and neutron radiography are used to examine the blades. Reviews of radiographs show that neutrons produce better images, and internal canals and defects are better seen in these images than X-ray images. It is worth emphasizing that neutron radiography with gadolinium tagging can determine the obstruction of blade and evaluate the density of ceramic materials inside the blade. Regarding neutron radiography with film, it can be emphasized that in addition to determining the obstruction of air ducts, the density of ceramic materials inside the ducts can also be evaluated. Also, by tagging with neutron absorbing materials, the contrast of the remaining materials from the ceramic muscle can be increased. Boron, indium and gadolinium can be named as important neutron absorbers. To improve the quality of neutron radiography images, Gadolinium is mainly used as a high neutron absorber. Although the contrast has increased in the reconstructed images, the reconstructed images from neutron radiography still show their superiority in showing the ducts and channel blockages. Different image processing methods can be implemented for the contrast enhancement. In this research, Gaussian convolution method is used to increase the contrast of the radiographs. Although contrast has increased in the reconstructed images by the Gaussian convolution method, the reconstructed images from neutron radiography show the blade structure and its channel blockages accurately. The opinion of radiography specialists also shows that the neutron radiography method gives 60% more information than the X-ray method, and the reconstructed images increased the contrast of the images between 10 to 20%.

Glass-fiber-polymer-composites are common composite types that can achieve optimum strength or desired mechanical properties for different applications by altering various parameters such as angular alignment of fibers. Fracture in these types of composites involves a combination of different mechanisms such as matrix crack, fiber breakage, delamination, and fiber debonding from the matrix. This paper presents an empirical investigation of the first mode failure mechanisms in glass/epoxy composite beams with different fiber angles by means of nondestructive electromechanical impedance measurements, force-displacement diagrams and observations. For this purpose, after fabricating beam specimens and attaching the piezoelectric sensor on them, the impedance spectra of the beams are compared with the reference beam spectrum during the elongation and crack opening process. Continuous and rapid crack growth was recognized by spatial and temporal synchronization of impedance data, visual observations of calibration indices on the beam specimen during the crack opening, and recorded movies of the tests and force-displacement diagrams. Studying the beam data with different angles arrangement revealed that the sample 0-90 was more stable during crack growth with fewer force variations. Also, the dominant mode of failure in this sample was the matrix fracture. This study showed that the electromechanical impedance measurement can be used as an effective tool for detecting the initiation and propagation of cracks in this type of composite beams due to high sensitivity at different stages of crack growth.

Non-destructive methods are used as accurate tools to evaluate and monitor asphalt mixtures. Among these methods, ultrasonic waves have been proposed as a widely used technique to evaluate the properties of asphalt mixtures. The use of ultrasonic waves has several significant advantages in the asphalt pavement evaluation process, including measuring voids and density, determining mechanical properties, and examining durability. By increasing the amount of air voids in asphalt mixtures, the speed of ultrasonic waves will decrease. In addition, ultrasonic waves make it possible to determine different mechanical properties of asphalt mixtures. To better understand the mechanical behavior of asphalt mixtures, researchers have proposed various mathematical relationships. These relationships establish connections between different moduli, including dynamic and Young's moduli, which act as basic mechanical properties of asphalt mixtures, and variables related to ultrasonic waves. Also, the speed of ultrasonic waves decreases when the asphalt mixtures are exposed to moisture damage. Therefore, with the increase in durability, the speed of ultrasound waves increases. In addition, changes in the amount of bitumen in the asphalt mixture have a significant effect on the speed of ultrasonic waves. Changes in the amount of bitumen affect the stiffness and density of the asphalt mixture and subsequently change the characteristics of the propagation of ultrasonic waves. By studying these effects, engineers can deepen their understanding of the relationship between bitumen content and mixture properties and develop relationships governing these phenomena and the optimal asphalt mixture. This research focuses on the application of ultrasonic methods to evaluate the properties of asphalt mixtures. The aim of this research is to investigate the relationships between these properties and variables related to ultrasonic waves, such as wave speed and propagation time, and to contribute to the advancement of the understanding of asphalt mixture behavior and the development of more effective and sustainable road construction.

During the past decades, imaging and spectroscopic techniques with wide applications have rapidly developed for determining the quality of agricultural products in a non-destructive manner. As a synergy between spectroscopy and imaging technologies, spectral imaging methods have emerged to deal with quality assessment problems along with ideas with effective and practical applications to food and agriculture industries. Agricultural commercialization has prompted the need to determine the quality of agricultural inputs, especially seeds, in order to optimize production and increase economic returns. Seed viability is a critical consideration to ensure high yields. Most of the time, farmers suffer losses after a significant percentage of seeds fail to germinate after planting. Seed viability is very important in the quality characteristics of seeds that reflect the potential of seed germination, and it is necessary to have a quick and effective method to determine the quality and state of germination and seed viability prior to cultivation and sale and during planting. Some research based on spectrum and/or image processing and analysis have been investigated to verify the external and internal quality of seed types. Spectroscopy is used to examine and measure the spectra produced by the interaction of matter with electromagnetic radiation or the radiation emitted from it, and the near-infrared (NIR) technique is one of these techniques for non-destructive tests of samples. Hyperspectral and multispectral imaging is another non-destructive technique that is used to obtain spectral and spatial information about materials, including seeds. The use of Raman spectroscopy is an alternative non-destructive method that is used to check seed viability with non-destructive laser radiation. Thermal imaging is a technique for converting the invisible radiation pattern of an object into visible images and extracting and analyzing the properties of the material without any contact. And finally, the use of electromagnetic waves with different wavelengths from 1 to 100 nm and energy of approximately 0.12 to 12-kilo electron volts. The low power penetration of these waves and their ability to detect internal changes in density makes soft X-rays suitable for use in evaluating agricultural products. This article refers to the comparative introduction and application of emerging techniques in the study of seed viability, including the near-infrared spectroscopy, hyperspectral and multispectral imaging, Raman spectroscopy, infrared thermography, and soft X-ray imaging.

Various destructive and nondestructive methods are used for in line inspection of pipelines. A pipe may fail because of different causes such as corrosion, pitting, stress corrosion cracking (SCC), weld cracks and mechanical impacts and damages. Corrosion failures in a pipe can take place in different ways, some of them are easy to detect and others require special facilities and methods. The best selection of the inspection tools depends on the type of application, mechanism of corrosion, chemical environment and the material. This paper investigates and compares different types of in-line inspection tools for pipelines and compare their advantages and disadvantages. Today, the most common method for In Line Inspection of pipelines is Magnetic Flux Leakage (MFL), which is used for detection of wall thickness reduction of pipelines, various cracks, corrosion and pitting in pipes. Therefore, it can’t be applied for nonmagnetic materials. The Eddy Current (EC) test is a non-contact test with relatively low velocity which is sensitive to the stand off from the material surface during the test and it is used only for conductive materials. Ultrasonic testing is a common method with high accuracy. It is widely used for detection of different defects and is based on sending short wavelength high frequency ultrasonic waves into the material and receiving their reflections. By interpreting the results, various defects and reduction in the wall thickness of the pipes can be detected. Acoustic Emission (AE) testing, which is based on interpretation of elastic deformations, elastic strain energy changes and stress distribution, is not considered as a common test for inspection of pipelines, yet. Electromagnetic Acoustic Transducers (EMAT) are a new type of ultrasonic testing method which do not require liquid coupling but should be used at a definite distance from the pipe wall during the test. It is concluded that the fastest and most reliable method for In-Line Inspection (ILI) of pipelines is currently the Magnetic Flux Leakage (MFL) method.