• Nuclear Engineering and Technology
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• 제55권11호
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• pp.4213-4227
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• 2023

Computer Automated Radioactive Particle Tracking (CARPT) technique has been successfully utilized to measure the velocity profiles and mixing parameters in different multiphase flow systems where a single radioactive tracer is used to track the tagged phase. However, many industrial processes use a wide range of particles with different physical properties where solid particles could vary in size, shape and density. For application in such systems, the capability of current single tracer CARPT can be advanced to track more than one particle simultaneously. Tracking multiple particles will thus enable to track the motion of particles of different size shape and density, determine segregation of particles and probing particle interactions. In this work, a newly developed Multiple Radioactive Particle Tracking technique (M-RPT) used to track two different radioactive tracers is demonstrated. The M-RPT electronics was developed that can differentiate between gamma counts obtained from the different radioactive tracers on the basis of their gamma energy peak. The M-RPT technique was validated by tracking two stationary and moving particles (Sc-46 and Co-60) simultaneously. Finally, M-RPT was successfully implemented to track two phases, solid and liquid, simultaneously in three phase slurry bubble column reactors.

• 원자력산업
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• 제4권2호통권18호
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• pp.12-19
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• 1984

• 원자력산업
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• 제5권3호통권25호
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• pp.28-33
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• 1985

• Corrosion Science and Technology
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• 제18권1호
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• pp.1-7
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• 2019

To find proper lathe machining parameters for SA182 Grade 304 stainless steel (SS), six kinds of samples with different machining surface states were prepared using a lathe. Surface morphologies and microstructures of near surface deformed layers on different samples were analysed. Surface morphologies and chemical composition of oxide films formed on different samples in simulated primary water with $100{\mu}g/L\;O_2$ at $310^{\circ}C$ were characterized. Results showed that surface roughness was mainly affected by lathe feed. Surface machining caused grain refinement at the top layer. A severely deformed layer with different thicknesses formed on all samples. In addition to high defect density caused by surface deformation, phase transformation, residual stress, and strain also affected the oxidation behaviour of SA182 Grade 304 SS in the test solution. Machining parameters used for # 4 (feed, 0.15 mm/r; back engagement, 2 mm; cutting speed, 114.86 m/min) and # 6 (feed,0.20 mm/r; back engagement, 1 mm; cutting speed, 73.01 m/min) samples were found to be proper for lathe machining of SA182 Grade 304 SS.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 추계학술발표회 발표논문집
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• pp.1343-1344
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• 2004

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2018년도 추계학술논문요약집
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• pp.83-84
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• 2018

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1167-1174
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• 2022

Cast austenitic stainless steels (CASSs) are widely used as structural materials in the nuclear industry. The main drawback of CASSs is the reduction in fracture toughness due to long-term exposure to operating environment. Even though ultrasonic non-destructive testing has been conducted in major nuclear components and pipes, the detection of cracks is difficult due to the scattering and attenuation of ultrasonic waves by the coarse grains and the inhomogeneity of CASS materials. In this study, the ultrasonic signals measured in thermally aged CASS were discriminated for the first time with the simple ultrasonic technique (UT) and machine learning (ML) models. Several different ML models, specifically the K-nearest neighbors (KNN), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP) models, were used to classify the ultrasonic signals as thermal aging condition of CASS specimens. We identified that the ML models can predict the category of ultrasonic signals effectively according to the aging condition.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1672-1678
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• 2024

We introduce a creative approach combining machine learning with optimization techniques to enhance the optimization of the loading pattern (LP). Finding the optimal LP is a critical decision that impacts both the reload safety and the economic feasibility of the nuclear fuel cycle. While simulated annealing (SA) is a widely accepted technique to solve the LP optimization problem, it suffers from the drawback of high computational cost since LP optimization requires three-dimensional depletion calculations. In this note, we introduce a technique to tackle this issue by leveraging neural networks to filter out inappropriate patterns, thereby reducing the number of SA evaluations. We demonstrate the efficacy of our novel approach by constructing a machine learning-based optimization model for the LP data of the Korea Standard Nuclear Power Plant (OPR-1000).

• 한국자기공명학회논문지
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• 제24권2호
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• pp.59-65
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• 2020

Nitrogen-Vacancy (NV) center in diamond has been an emerging versatile tool for quantum sensing applications. Amongst various applications, nano-scale nuclear magnetic resonance (NMR) using a single or ensemble NV centers has demonstrated promising results, opening possibility of a single molecule NMR for its chemical structural studies or multi-nuclear spin spectroscopy for quantum information science. However, there is a key challenge, which limited the spectral resolution of NMR detection using NV centers; the interrogation duration for NV-NMR detection technique has been limited by the NV sensor spin lifetime (T₁ ~ 3ms), which is orders of magnitude shorter than the coherence times of nuclear spins in bulk liquid samples (T₂ ~ 1s) or intrinsic ¹³C nuclear spins in diamond. Recent studies have shown that quantum memory technique or synchronized readout detection technique can further narrow down the spectral linewidth of NMR signal. In this short review paper, we overview basic concepts of nanoscale NMR using NV centers, and introduce further developments in high spectral resolution NV NMR studies.

• Asian-Australasian Journal of Animal Sciences
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• 제24권1호
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• pp.1-8
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• 2011

Large quantities of high-quality recipient oocytes with uniform cytoplasm are needed for research in the promising field of somatic cell nuclear transfer (SCNT) and embryonic stem cell research. In canines, however, it is difficult to obtain large quantities of oocytes because each donor produces a limited number of mature oocytes in vivo. Although in vitro maturation (IVM) is considered an alternative approach to oocyte production, this technique is still too rudimentary to be used for the production of highquality, uniform oocytes in large quantities. One technique for overcoming this difficulty is to use oocytes obtained from different species. This technique is known as interspecies SCNT (iSCNT). This review provides an overview of recent advances in canine - porcine interspecies SCNT.