• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2263_2264
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• 2009

원자력은 나라의 기저전력을 책임지는 대표적인 발전소다. 시간이 지남에 따라 에너지 수요는 증가하지만 원자력 에너지의 연료인 우라늄은 고갈이 되어가고 있다. 그 해결책으로 고속로 기술에는 소듐 냉각 고속로, 건식처리 방법으로는 파이로프로세싱이 있다. 이 기술로 사용 후 원전연료를 재처리하여 불가 수 십년에 불가한 원전문제를 수 천년으로 늘릴 수 있다. 하지만 우리나라는 사용 후 원전연료에 대해 정책방향이 결정되지 않았으며, 지역단체, 환경단체 등의 단체에서의 반대도 만만치 않을 것이다. 원전연료 관리 정책이 결정되어 국가 에너지안보의 기틀을 마련해야 할 것이다.

• Journal of Internet of Things and Convergence
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• v.6 no.1
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• pp.1-8
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• 2020

Following the advanced fuel cycle initiative (AFCI) promotions in the United States, the analytic proposition for global fuel cycle initiative (GFCI) has been investigated using dynamical simulations. The political and economic aspects are considered simultaneously due to the particular characteristics of the nuclear materials. The spent nuclear fuels (SNFs) are treated as the reprocessing by the nuclear non-proliferation treaty (NPT) exemption nations and the NPT excluded nations. Otherwise, the pyroprocessing and repository can be done without NPT restriction. In addition, the international trade is considered as the economic aspect where the energy production is a key issue of the GFCI. The dynamical simulations have been done until 2050. The result of the International Trade shows the gradually increasing shape. Additionally, the Nuclear Power Plant Operation shows the increasing by stepwise shape.

• Journal of Hydrogen and New Energy
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• v.28 no.2
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• pp.129-136
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• 2017

Characteristics of $ZrO_2$ felt supported Cu/Zn catalysts have been investigated for the production of hydrogen via methanol steam reforming. Cu and Zn in different weight percent were loaded using wet impregnation over $ZrO_2$ felt support. The catalysts were characterized with BET and FE-SEM. The performance of these synthesized catalysts were investigated at SCR=1.5, $GHSV=2000h^{-1}$, temperature=$300{\sim}400^{\circ}C$, and pressure=2.5~19.5 barA. The results showed that the $Cu^{32.5}Zn^{7.5}ZrO_2$ catalyst was most active in terms of methanol conversion and hydrogen production. The methanol conversion in steam reforming of methanol was 84.6% at 19.5 barA and furnace $400^{\circ}C$ over $Cu^{32.5}Zn^{7.5}ZrO_2$ catalyst. The catalysts prepared using $ZrO_2$ felt show higher reactor temperature than the pellet type catalyst at same furnace temperature.

• Cement Symposium
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• no.29
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• pp.245-252
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• 2002

소성 영역(Sintering zone)에서 클링커(Clinker)의 형상 형성은 시멘트 생산 공정에서 가장 중요한 생산 공정중의 하나이다. 소성공정의 진단 및 최적 제어의 핵심은 써모그래프(Thermo graph), 즉 적외선 카메라를 이용한 온도 분포의 측정이다. 여기에서 다룰 ''PIT Indicator'' 시스템은 분진이 많은 열악한 산업 현장의 연소 시스템에 적용할 수 있도록 특별히 설계한 공냉식의 2개 채널을 가진 광학 장비에 기초하고 있다. 비디오 영상과 써모그래프 이미지 그리고 다양한 연소 특성이 카메라를 통하여 얻어지고 자기 학습 기능을 가진 소프트웨어에서 기록되고 분석된다. 이때 얻은 데이터는 수학적 모델에서 온라인으로 Free Lime 함유율을 예측하는데 이용된다. 열분포의 써모그래프 표시와 공정상의 다양한 운전 특성을 분석하여 주는 ''PIT Indicator'' 소프트웨어를 통하여 다른 공정 제어 시스템과 연결이 가능하다. 이와 같은 하드웨어와 소프트웨어를 이용하여 최적화가 필요한 여러요소들의 최적화를 동시에 그리고 온라인으로 수행할 수가 있다. Free Lime 함유율의 연속적인 온라인 연산을 통해 생산 설비 및 공정에 맞는 최소한의 에너지를 Kiln 에 공급함으로써 근본적으로 1차 연료의 절감이 가능하고 NOx와 같은 유해 가스의 배출량도 제어할 수 있다. 또한 별도로 NOx에 대한 모델을 개발하여 NOx를 정확하게 예측하는 것도 가능하다.

• Fire Science and Engineering
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• v.32 no.6
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• pp.22-27
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• 2018

The flame length in coaxial diffusion flame configurations was investigated when the kerosene fuel flow rate, temperature of the oxidizer stream, and inert gas concentrations in the oxidizer stream were varied. The diffusion flame was photographed using a Schlieren camera under each of the experimental conditions and the obtained images were then digitized to measure the flame length. The measured flame lengths were proportional to the kerosene fuel flow rate and increased with increasing temperature of the oxidizer stream. In addition, increases in the inert gas concentration in the oxidizer stream resulted in stretching of the flame. In particular, the flame was further elongated in the oxidizer steam diluted with helium gas. Inert substitutions in the oxidizer stream that can adjust the viscous drag are believed to be one of the important mechanisms that affect the length of the coaxial diffusion flames.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.5
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• pp.645-652
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• 2010

The aim of this investigation was study on the non-evaporation diesel spray characteristics injected through a common-rail diesel injector under various ambient pressure. The diesel spray was investigated with observation of macroscopic characteristics such as spray tip penetration and spray cone angle by the shadowgraph and the image processing method. The numerical study was conducted using a computational fluid dynamics code, AVL-FIRE. The breakup models used were WAVE model and standard $k-{\varepsilon}$ turbulence model was applied. The numerical study used input data which spray cone angle and fuel injection rate was achieved by Zeuch's method. Comparison with experimental result such as spray tip penetration was good agreement. Distribution of droplet diameter were conducted on four planes where the axial distances were 5, 15, 39 and 49mm respectively downstream from the orifice exit.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.5
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• pp.451-457
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• 2011

The main objective of this study is to investigate the variation in the ignition characteristics of coals as a function of moisture content in a laminar flow reactor (LFR) equipped with a fuel moisture micro-supplier designed by the Pusan Clean Coal Center. The volatile ignition position and time were observed experimentally when a pulverized coal with moisture was fed into the LFR under burning conditions similar to those at the exit of the pulverizer and real boiler. The reaction-zone temperature along the centerline of the reactor was measured with a $70-{\mu}m$, R-type thermocouple. For different moisture contents, the volatile ignition position was determined based on an average of 15 to 20 images captured by a CCD camera using a proprietary image-processing technique. The reaction zone decreased proportionally as a function of the moisture content. As the moisture content increased, the volatile ignition positions were 2.92, 3.36, 3.96, and 4.65 mm corresponding to ignition times of 1.46, 1.68, 2.00, and 2.33 ms, respectively. These results indicate that the ignition position and time increased exponentially. We also calculated the ignition-delay time derived from the adiabatic thermal explosion. It showed a trend that was similar to that of the experimental data.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Clean Technology
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• v.27 no.4
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• pp.341-349
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• 2021

In combustion facilities, the nitrogen and sulfur in fossil fuels react with oxygen to generate air pollutants such as nitrogen oxides (NO_X) and sulfur oxides (SO_X), which are harmful to the human body and cause environmental pollution. There are regulations worldwide to reduce NO_X and SO_X, and various technologies are being applied to meet these regulations. There are commercialized methods to reduce NO_X and SO_X emissions such as selective catalytic reduction (SCR), selective non-catalytic reduction (SNCR) and wet flue gas desulfurization (WFGD), but due to the disadvantages of these methods, many studies have been conducted to simultaneously remove NO_X and SO_X. However, even in the NO_X and SO_X simultaneous removal methods, there are problems with wastewater generation due to oxidants and absorbents, costs incurred due to the use of catalysts and electrolysis to activate specific oxidants, and the harmfulness of gas oxidants themselves. Therefore, in this research, microbubbles generated in a high-pressure disperser and reducing agents were used to reduce costs and facilitate wastewater treatment in order to compensate for the shortcomings of the NO_X, SO_X simultaneous treatment method. It was confirmed through image processing and ESR (electron spin resonance) analysis that the disperser generates real microbubbles. NO_X and SO_X removal tests according to temperature were also conducted using only microbubbles. In addition, the removal efficiencies of NO_X and SO_X are about 75% and 99% using a reducing agent and microbubbles to reduce wastewater. When a small amount of oxidizing agent was added to this microbubble system, both NO_X and SO_X removal rates achieved 99% or more. Based on these findings, it is expected that this suggested method will contribute to solving the cost and environmental problems associated with the wet oxidation removal method.