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문성진(Sungjin Moon),전상태(Sangtae Jeon),장범준(Beomjun Jang),김용모(Yongmo Kim) 대한기계학회 2011 대한기계학회 춘추학술대회 Vol.2011 No.6
The present study has numerically investigated the combustion processes of the pulverized coal. The pulverized coal combustion involves the complex physical processes such as devolatilization, char oxidation, turbulence-chemistry interaction, and radiative heat transfer. These physical processes are implemented in the framework of Eulerian-Lagrangian and Eulerian-Eulerian formulations. The pulverized coal combustion models developed in this study are validated against the experimental data of the pulverized coal jet flames. Numerical results indicate that the present approaches have the capability to realistically predict the essential features of pulverized coal combustion processes.
차량실내소음저감차량실내소음저감을 위한 제진재 위치 최적화 기법 개발
문성진(Sungjin Moon),김수곤(Sugon kim),박우선(Woosun Park) 한국자동차공학회 2010 한국자동차공학회 부문종합 학술대회 Vol.2010 No.5
In this study, an optimization method of damping sheet treatment was developed to reduce the structure-borne noise below 500 [Hz]. As a method to optimize the damping sheet treatment, both the velocity distribution and the sum of strain energy distribution on panels are investigated and used to determine where the damping sheet is patched. The optimization procedure was proposed to find the optimum damping treatment developed in this paper consists of panel contribution analysis, the velocity distribution and the sum of strain energy distribution on panels. As a result of this study, either not only both the design weight and the cost of damping material have reduced, but also the structure-borne noise has improved.
Eulerian과 Lagrangian 모델을 이용한 미분탄연소 해석
이정원(Jeongwon Lee),문성진(Sungjin Moon),장범준(Beomjun Jang),김용모(Yongmo Kim) 한국연소학회 2010 KOSCOSYMPOSIUM논문집 Vol.- No.41
The numerical models dealing with pulverized coal combustion can be categorized by both Eulerian-Lagrangian and Eulerian-Eulerian approach. In this study, both pulverized coal combustion approaches are implemented and validated against the experimental data of the pulverized coal jet flame in the horizontal chamber. Based on numerical results, the detailed discussions are made for the comparative performance, accuracy, and computational efficiency, and limitation of both combustion models.
휴대 단말기 그라운드 방사 안테나(GradiANT: Ground Radiation Antenna) 기술 소개
김지훈(Jihoon Kim),문성진(Sungjin Moon),김형동(Hyeongdong Kim) 한국전자파학회 2015 한국전자파학회논문지 Vol.26 No.11
최근 휴대 단말기 안테나의 소형화와 고성능화에 대한 요구가 증대되고 있다. 단말기의 그라운드는 좋은 방사체로, 이를 활용한 휴대 단말기 그라운드 방사 안테나는 안테나의 소형화 및 고성능화를 동시에 만족시킬 수 있기 때문에, 많은 관심을 받고 있다. 그라운드 방사 안테나는 단말기 그라운드의 특성 모드를 제어하고, 이를 안테나와 결합하여 그라운드를 방사체로 활용하기 때문에 그 방사 성능이 우수하다. 본 논문에서는 그라운드의 특성 모드 이론에 대해 설명하고, 이를 활용한 그라운드 방사 안테나의 다양한 적용 예시를 단일 대역, 광대역 및 이중 대역 그라운드 방사 안테나로 나누어 소개하고자 한다. Ground radiation antenna in mobile devices is becoming an issue for satisfying both miniaturization and high performance. Ground radiation antenna controls the characteristic mode of the ground plane and couples this mode with the ground radiation antenna, thereby having good radiation performance. In this paper, the characteristic mode theory and applications of ground radiation antenna will be introduced. The operating mechanism of single band, wideband and dual-band ground radiation antennas are studied.
목동현(Dong Hyeon Mok),이우석(WooSeok Lee),김종승(JongSeung Kim),정현동(Hyun Dong Jung),장호연(Ho Yeon Jang),문성진(SungJin Moon),이채연(ChaeHyeon Lee),백서인(Seoin Back) 한국세라믹학회 2022 세라미스트 Vol.25 No.2
Towards a sustainable energy future, it is essential to develop new catalysts with improved properties for key catalytic systems such as Haber-Bosch process, water electrolysis and fuel cell. Unfortunately, the current state-of-the-art catalysts still suffer from high cost of noble metals, insufficient catalytic activity and long-term stability. Furthermore, the current strategy to develop new catalysts relies on “trial-and-error” method, which could be time-consuming and inefficient. To tackle this challenge, atomic-level simulations have demonstrated the potential to facilitate catalyst discovery. For the past decades, the simulations have become reasonably accurate so that they can provide useful insights toward the origin of experimentally observed improvements in catalytic properties. In addition, with the exponential increase in computing power, high-throughput catalyst screening has become feasible. More excitingly, recent advances in machine learning have opened the possibility to further accelerate catalyst discovery. Herein, we introduce recent applications and challenges of computation and machine learning for catalyst discovery.