• 센서학회지
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• 제31권5호
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• pp.348-352
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• 2022

Hydrogen gas (H₂) which is odorless, colorless is attracting attention as a renewable energy source in varions applications but its leakage can lead to disastrous disasters, such as inflammable, explosive, and narcotic disasters at high concentrations. Therefore, it is necessary to develop H₂ gas sensor with high performance. In this paper, we confirmed that H₂ gas detection ability of SnO₂ based H₂ gas sensor along with thermal treatment effect of SnO₂. Proposed SnO₂ based H₂ gas sensor is fabricated by MEMS technologies such as photolithgraphy, sputtering and lift-off process, etc. Deposited SnO₂ thin films are thermally treated in various thermal treatement temperature in range of 500-900 ℃ and their H₂ gas detection ability is estimatied by measuring output current of H₂ gas sensor. Based on experimental results, fabricated H₂ gas sensor with SnO₂ thin film which is thermally treated at 700 ℃ has a superior H₂ gas detection ability, and it can be expected to utilize at the practical applications.

• Korean Chemical Engineering Research
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• 제61권2호
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• pp.278-286
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• 2023

The present work evaluated the production of biohydrogen under mesophilic and thermophilic conditions through dark fermentation of palm oil mill effluent (POME) in batch mode using the design of experiment methodology. Response surface methodology (RSM) was applied to investigate the influence of the two significant parameters, POME concentration as substrate (5, 12.5, and 20 g/l), and volumetric substrate to inoculum ratio (1:1, 1:1.5, and 1:2, v/v.%), with inoculum concentration of 14.3 g VSS/l. All the experiments were analyzed at 37 ℃ and 55 ℃ at an incubation time of 24 h. The highest chemical oxygen demand (COD) removal, hydrogen content (H₂%), and hydrogen yield (HY) at a substrate concentration of 12.5 g COD/l and S:I ratio of 1:1.5 in mesophilic and thermophilic conditions were obtained (27.3, 24.2%), (57.92, 66.24%), and (6.43, 12.27 ml H₂/g COD_rem), respectively. The results show that thermophilic temperature in terms of COD removal was more effective for higher COD concentrations than for lower concentrations. Optimum parameters projected by RSM with S:I ratio of 1:1.6 and POME concentration of 14.3 g COD/l showed higher results in both temperatures. It is recognized how RSM and optimization processes can predict and affect the process performance under different operational conditions.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4134-4145
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• 2022

The collimator is one of the high-heat-flux components used to avoid a series of vacuum and thermal problems. In this paper, the heat load distribution throughout the collimator is first calculated through experimental data, and a transient thermodynamic simulation analysis of the original model is carried out. The error of the pipe outlet temperature between the simulated and experimental values is 1.632%, indicating that the simulation result is reliable. Second, the model is optimized to improve the heat transfer performance of the collimator, including the contact mode between the pipe and the flange, the pipe material and the addition of a twisted tape in the pipe. It is concluded that the convective heat transfer coefficient of the optimized model is increased by 15.381% and the maximum wall temperature is reduced by 16.415%; thus, the heat transfer capacity of the optimized model is effectively improved. Third, to adapt the long-pulse steady-state operation of the experimental advanced superconducting Tokamak (EAST) in the future, steady-state simulations of the original and optimized collimators are carried out. The results show that the maximum temperature of the optimized model is reduced by 37.864% compared with that of the original model. The optimized model was changed as little as possible to obtain a better heat exchange structure on the premise of ensuring the consumption of the same mass flow rate of water so that the collimator can adapt to operational environments with higher heat fluxes and long pulses in the future. These research methods also provide a reference for the future design of components under high-energy and long-pulse operational conditions.

• 한국분말재료학회지
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• 제30권2호
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• pp.146-155
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• 2023

The Ti-6Al-4V lattice structure is widely used in the aerospace industry owing to its high specific strength, specific stiffness, and energy absorption. The quality, performance, and surface roughness of the additively manufactured parts are significantly dependent on various process parameters. Therefore, it is important to study process parameter optimization for relative density and surface roughness control. Here, the part density and surface roughness are examined according to the hatching space, laser power, and scan rotation during laser-powder bed fusion (LPBF), and the optimal process parameters for LPBF are investigated. It has high density and low surface roughness in the specific process parameter ranges of hatching space (0.06-0.12 mm), laser power (225-325 W), and scan rotation (15°). In addition, to investigate the compressive behavior of the lattice structure, a finite element analysis is performed based on the homogenization method. Finite element analysis using the homogenization method indicates that the number of elements decreases from 437,710 to 27 and the analysis time decreases from 3,360 to 9 s. In addition, to verify the reliability of this method, stress-strain data from the compression test and analysis are compared.

• Journal of Astronomy and Space Sciences
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• 제39권1호
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• pp.1-10
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• 2022

The universe is thought to be filled with not only Standard Model (SM) matters but also dark matters. Dark matter is thought to play a major role in its construction. However, the identity of dark matter is as yet unknown, with various search methods from astrophysical observartion to particle collider experiments. Because of the cross-section that is a thousand times smaller than SM particles, dark matter research requires a large amount of data processing. Therefore, optimization and parallelization in High Performance Computing is required. Dark matter in hypothetical hidden sector is though to be connected to dark photons which carries forces similar to photons in electromagnetism. In the recent analysis, it was studied using the decays of a dark photon at collider experiments. Based on this, we studies double dark photon decays at lepton colliders. The signal channels are e⁺e^- → A'A' and e⁺e^- → A'A'γ where dark photon A' decays dimuon. These signal channels are based on the theory that dark photons only decay into heavily charged leptons, which can explain the muon magnetic momentum anomaly. We scanned the cross-section according to the dark photon mass in experiments. MadGraph5 was used to generate events based on a simplified model. Additionally, to get the maximum expected number of events for the double dark photon channel, the detector efficiency for several center of mass (CM) energy were studied using Delphes and MadAnalysis5 for performance comparison. The results of this study will contribute to the search for double dark photon channels at lepton colliders.

• 한국재료학회지
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• 제33권5호
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• pp.175-188
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• 2023

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

• Nuclear Engineering and Technology
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• 제55권7호
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• pp.2628-2641
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• 2023

Nuclear safety is the lifeline for the development and application of nuclear energy. In severe accidents of pressurized water reactor (PWR), aerosols, as the main carrier of fission products, are suspended in the containment vessel, posing a potential threat of radioactive contamination caused by leakage into the environment. The gas-phase aerosols suspended in the containment will settle onto the wall or sump water through the natural deposition mechanism, thereby reducing atmospheric radioactivity. Aiming at the low accuracy of the aerosol model in the ISAA code, this paper improves the natural deposition model of aerosol in the containment. The aerosol dynamic shape factor was introduced to correct the natural deposition rate of non-spherical aerosols. Moreover, the gravity, Brownian diffusion, thermophoresis and diffusiophoresis deposition models were improved. In addition, ABCOVE, AHMED and LACE experiments were selected to validate and evaluate the improved ISAA code. According to the calculation results, the improved model can more accurately simulate the peak aerosol mass and respond to the influence of the containment pressure and temperature on the natural deposition rate of aerosols. At the same time, it can significantly improve the calculation accuracy of the residual mass of aerosols in the containment. The performance of improved ISAA can meet the requirements for analyzing the natural deposition behavior of aerosol in containment of advanced PWRs in severe accident. In the future, further optimization will be made to address the problems found in the current aerosol model.

• Journal of Radiation Protection and Research
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• 제47권4호
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• pp.181-194
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• 2022

Internal dosimetry is a discipline which brings together a set of knowledge, tools and procedures for calculating the dose received after incorporation of radionuclides into the body. Several steps are necessary to calculate the committed effective dose (CED) for workers or members of the public. Each step uses the best available knowledge in the field of radionuclide biokinetics, energy deposition in organs and tissues, the efficiency of radiation to cause a stochastic effect, or in the contributions of individual organs and tissues to overall detriment from radiation. In all these fields, knowledge is abundant and supported by many works initiated several decades ago. That makes the CED a very robust quantity, representing exposure for reference persons in reference situation of exposure and to be used for optimization and assessment of compliance with dose limits. However, the CED suffers from certain limitations, accepted by the International Commission on Radiological Protection (ICRP) for reasons of simplification. Some of its limitations deserve to be overcome and the ICRP is continuously working on this. Beyond the efforts to make the CED an even more reliable and precise tool, there is an increasing demand for personalized dosimetry, particularly in the medical field. To respond to this demand, currently available tools in dosimetry can be adjusted. However, this would require coupling these efforts with a better assessment of the individual risk, which would then have to consider the physiology of the persons concerned but also their lifestyle and medical history. Dosimetry and risk assessment are closely linked and can only be developed in parallel. This paper presents the state of the art of internal dosimetry knowledge and the limitations to be overcome both to make the CED more precise and to develop other dosimetric quantities, which would make it possible to better approximate the individual dose.

• 한국컴퓨터정보학회논문지
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• 제28권4호
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• pp.113-120
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• 2023

스마트 팜은 IoT 기술과 인공지능 기술이 접목되면서 농작물에 투입되는 노동력·에너지·양분 등을 최소화는 연구가 꾸준히 증가하고 있는 상황이다. 그러나, 스마트 팜에서 농작물의 생육 정보를 효율적으로 관리하는 연구는 현재까지 미진한 상태이다. 본 논문에서는 스마트 팜에 자율 센서를 적용하여 농작물의 생육 정보를 효율적으로 모니터링할 수 있는 관리 기법을 제안한다. 제안 기법은 농작물의 생육 정보를 자율 센서를 통해 수집한 후 생육 정보를 농작물 재배에 재활용하는데 초점을 갖는다. 특히, 제안 기법은 농작물의 생육 정보를 한 슬롯으로 할당한 후 로드밸런싱을 수행하도록 농작물별로 가중치를 부여하며, 농작물의 생육 정보 간의 간섭을 서로 최소화한다. 또한, 제안 기법은 농작물의 생육 정보를 4단계 (센싱 탐지 단계, 센싱 전송 단계, 애플리케이션 처리 단계, 데이터 관리 단계 등)로 처리할 때, 농작물의 중요 관리점을 실시간으로 전산화하기 때문에 관리 기준 이외의 경우에는 즉각적인 경고 시스템이 동작한다. 성능평가 결과, 자율 센서의 정확도는 기존 기법보다 평균 22.9%의 향상된 결과를 얻었으며, 효율성은 기존 기법보다 평균 16.4% 향상된 결과를 얻었다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2022년도 춘계학술대회
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• pp.317-318
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• 2022

전(全)세계적인 탈탄소화에 따라 그린에너지로의 전환 가속화를 위한 디지털트윈을 활용한 최적화 및 생산성 향상 모색하고 있으며, 주요국은 미래 핵심기술로 디지털트윈을 선정하여 선박 및 해양에너지 운용 최적화를 위한 SW 개발 등 경쟁이 가속화 되고 있음. 국제적으로 탄소 배출량에 대한 규제 강화로 선박의 운영비용 절감 및 조선 산업의 경쟁력 강화를 위해서는 선박의 탄소배출량 사전 예측 및 탄소저감 운항 솔루션을 위한 선제적 대응이 필요함. 이를 위해 선박해양시스템의 탄소 투명성 확보를 지원하는 개방형 디지털 플랫폼 기술 개발 및 환경 구축에 대한 기획을 수행하였음