• Proceedings of the Korean Vacuum Society Conference
• /
• 2012.02a
• /
• pp.524-524
• /
• 2012

Thermal Barrier Coating (TBC)은 미사일, 로켓발사체와 같이 고온에 노출되는 장비를 열로부터 보호하기 위한 코팅이다. 일반적인 Thermal Barrier Coating (TBC)은 모재와 코팅층간의 낮은 접합력과 높은 열충격으로 인한 박리가 많이 나타난다. 그래서 접합력을 높이고, 열충격을 줄이기 위해 모재와 코팅층 사이에 본드코팅층을 만든 Duplex - Thermal Barrier Coating (Duplex-TBC)이 개발되었다. 그러나 Duplex - Thermal Barrier Coating (Duplex-TBC)은 금속재료인 본드코팅층과 세라믹재료인 탑코팅층 사이에서 박리가 많이 발생한다. 이러한 문제점을 해결하기 위해 두 가지 분말을 동시에 코팅하여 본드코팅과 탑코팅의 경계가 없는 Functional Gradient Material - Thermal Barrier Coating (FGM-TBC)의 연구가 필요하다. 본 연구에서는 Functional Gradient Material - Thermal Barrier Coating (FGM-TBC)의 열충격 특성에 미치는 진공 플라즈마 용사 조건의 영향을 조사하였다. Functional Gradient Material - Thermal Barrier Coating (FGM-TBC)는 진공 플라즈마 용사장치를 사용하여 Cu-Cr 합금위에 코팅하였다. 거리, Carrier gas flow, 그리고 챔버 내부의 압력을 달리하여 제조하였다. 사용한 분말은 본드코팅용으로 Amdry 962와 내열 세라믹코팅을 위해 204NS를 사용하였고, 각각 분말 공급조건을 조절하여 두 분말의 비율을 달리하였다. 제조한 Functional Gradient Material - Thermal Barrier Coating (FGM-TBC) 코팅은 전기로에서 50분간 가열한 후, 수조에서 10분간 냉각하는 열충격 실험을 통해 열차폐 성능을 평가 하였다. 이러한 과정에서 진공 플라즈마 용사 조건 및 FGM 조성과 비율이 내열충격 특성에 미치는 영향을 미세조직학적 관점에서 고찰하였다.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.11 no.5
• /
• pp.78-84
• /
• 2007

In the regeneratively cooled combustion chambers of liquid rocket engine using hydrocarbon fuels, coking occurs as the wall temperature increases which results in compounds deposition on the wall of cooling channels. This phenomenon reduces cooling capability of the coolant which finally causes damage to the combustor by overheating of the chamber wall. In this paper, experiment results using an electrical heating equipment to simulate the regeneratively cooled channel are introduced and based on the results the compatibility of copper alloy with hydrocarbon fuel Jet A-1 is investigated.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.5 no.2
• /
• pp.155-169
• /
• 2007

A transport container for a 500 kCi tritium storage vessel was developed, which could be used for the transport of metal tritide from Wolsong TRF facility to a disposal site. The structural, thermal, shielding, and confinement analyses were performed for the container in a view of Type B. As a result of structural analysis, the developed container sustained its integrity under normal and accidental conditions. The maximum temperature increase of the inner storage vessel by radiation was evaluated at $134.8^{\circ}C at room temperature. In $800^{\circ}C$ fire test, The thermal barrier of container sustained the inner vessel at $405^{\circ}C after 30 min, which temperature was allowable for the container integrity since maximum design temperature of inner vessel was $550^{\circ}C. In the evaluation of the shielding, the activity of radiation was nearly zero on the outer surface of inner vessel. Consequently the transport container for a 500 kCi tritium was evaluated to pass all the safety tests including accidental condition, so it was concluded that the designed transport container is proper to be used.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.329-352
• /
• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.