• Composites Research
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• v.18 no.3
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• pp.38-46
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• 2005

In order to characterize the outstanding performance of three-dimensional (3D) composites, the low velocity impact test has been carried out. 3D fiber structures have been achieved by using the automated tape placement (ATP) process and a stitching method. Materials for the ATP and the stitching process were carbon/epoxy prepreg tapes and Kevlar fibers, respectively. Two-dimensional composites with the same stacking sequence as 3D counterparts have also been fabricated for the comparison of damage tolerance. For the assessment of damage after the impact loading, specimens were subjected to C-Scan nondestructive inspection. Compression after impact (CAI) tests were conducted to evaluate residual compressive strength. The damage area of 3D composites was greatly reduced $(30-40\%)$ compared with that of 2D composites. Although the CAI strength did not show drastic improvement for 3D composites, the ratio of retained strength was $5-10\%$ higher than 2D samples. The effect of stitching on the impact performance was negligible above the energy level of 35 Joules.

• Journal of Radiation Protection and Research
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• v.42 no.4
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• pp.197-204
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• 2017

Background: X-ray imaging detectors for the nondestructive cargo container inspection using MeV-energy X-rays should accurately portray the internal structure of the irradiated container. Internal and external factors can cause noise, affecting image quality, and scattered radiation is the greatest source of noise. To obtain a high-performance transmission image, the influence of scattered radiation must be minimized, and this can be accomplished through several methods. The scatter rejection method using an anti-scatter grid is the preferred method to reduce the impact of scattered radiation. In this paper, we present an evaluation the characteristics of the signal and noise according to physical and material changes in the anti-scatter grid of the imaging detector used in cargo container scanners. Materials and Methods: We evaluated the characteristics of the signal and noise according to changes in the grid ratio and the material of the anti-scatter grid in an X-ray image detector using MCNP6. The grid was composed of iron, lead, or tungsten, and the grid ratio was set to 2.5, 12.5, 25, or 37.5. X-ray spectrum sources for simulation were generated by 6- and 9-MeV electron impacts on the tungsten target using MCNP6. The object in the simulation was designed using metallic material of various thicknesses inside the steel container. Using the results of the computational simulation, we calculated the change in the scatter-to-primary ratio and the signal-to-noise ratio improvement factor according to the grid ratio and the grid material, respectively. Results and Discussion: Changing the grid ratios of the anti-scatter grid and the grid material decreased the scatter linearly, affecting the signal-to-noise ratio. Conclusion: The grid ratio and material of the anti-scatter grid affected the response characteristics of a container scanner using high-energy X-rays, but to a minimal extent; thus, it may not be practically effective to incorporate anti-scatter grids into container scanners.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.1044-1062
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• 2017

The construction project of the Kijang research reactor (KJRR), which is the second research reactor in Korea, has been launched. The KJRR was designed to use, for the first time, U-Mo fuel. Plate-type U-7 wt.% Mo/Al-5 wt.% Si, referred to as U-7Mo/Ale5Si, dispersion fuel with a uranium loading of $8.0gU/cm^3$, was selected to achieve higher fuel efficiency and performance than are possible when using $U_3Si_2/Al$ dispersion fuel. To qualify the U-Mo fuel in terms of plate geometry, the first miniplates [HANARO Miniplate (HAMP-1)], containing U-7Mo/Al-5Si dispersion fuel ($8gU/cm^3$), were fabricated at the Korea Atomic Energy Research Institute and recently irradiated at HANARO. The PIE (Post-irradiation Examination) results of the HAMP-1 irradiation test were analyzed in depth in order to verify the safe in-pile performance of the U-7Mo/Al-5Si dispersion fuel under the KJRR irradiation conditions. Nondestructive analyses included visual inspection, gamma spectrometric mapping, and two-dimensional measurements of the plate thickness and oxide thickness. Destructive PIE work was also carried out, focusing on characterization of the microstructural behavior using optical microscopy and scanning electron microscopy. Electron probe microanalysis was also used to measure the elemental concentrations in the interaction layer formed between the U-Mo kernels and the matrix. A blistering threshold test and a bending test were performed on the irradiated HAMP-1 miniplates that were saved from the destructive tests. Swelling evaluation of the U-Mo fuel was also conducted using two methods: plate thickness measurement and meat thickness measurement.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6A
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• pp.597-605
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• 2009

The safety of expressway bridges was estimated by checking the external condition rank based on the nondestructive inspection and material test and by measuring load carrying capacity based on the result of load test. Although the load carrying capacity of the bridges was clearly low compared to the design standard, it was examined that many of the bridges have good external condition rank relatively. Also, it can be assured that load carrying capacity shows a considerable difference according to various condition even though the bridges have similar construction year and a structural type. Therefore, this study showed various problems of the current safety measurement of expressway bridges by considering the status of the expressway bridges, external condition rank, and method of safety diagnosis and repair, rehabilitation for maintenance. Based on the existing data of over 400 expressway bridges, the load carrying capacity was analyzed quantitatively considering bridge type, serviced life, design live load, external condition rank and traffic count as variables. The result of this study will be expected to provide the basic information for a reasonable safety assessment of expressway bridge.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.