• Resources Recycling
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• v.31 no.2
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• pp.33-39
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• 2022

In this study, analytical thermochemical modeling factors that contribute to maintaining a specific temperature range during vanadium roasting as a pretreatment using a rotary kiln are investigated. The model-related mechanisms include thermochemical reaction rates, heat balance, and heat transfer, through which the resultant temperature can be estimated intuitively. Ultimately, by optimizing these parameters, the ideal roasting temperature in the kiln is ≈1000 ℃ (or ≈1273 K) for long-term operation. Therefore, the heat generated from hydrocarbon (natural gas) fuel combustion and ore oxidation reactions, as well as the radiant heat transferred to ores, are assessed. In addition, thermochemical methods for relieving the temperature gradient in order to maintain the optimum temperature range of the rotary kiln are suggested.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.71-78
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• 2024

During the initial thermal design process, determining the thermal effect of various design variables in a complex orbital thermal environment is time-consuming. To save time in the initial design phase, it is necessary to quickly derive optimal design parameters and predict the temperature. To address these challenges, Veritrek, a software specialized in optimal design using a reduced-order model (ROM), was released in 2018. In this paper, we utilized the Veritrek software to build a reduced-order model, conduct sensitivity analysis, and perform optimal design analysis for a graphite sheet-based cryogenic cooler thermal control system. The goal was to determine the optimal design values for the number of graphite sheet layers, radiator area, and thickness that would meet the allowable temperature of the cryogenic cooler.

• Food Science and Preservation
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• v.9 no.3
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• pp.261-266
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• 2002

A transpiration model was selected and tested experimentally to predict transpiration into of Fuji apple stored in a normal air and controlled atmospheres (l∼3% O$_2$+ l∼3% CO$_2$) at 0$\^{C}$ and 98% RH for 6weeks. CA storage decreased the respiration rate of Fuji apple by 50% when compared with normal air storage. The transpiration rates of apple showed 50∼70% higher in normal air storage than those in CA storage and were decreased by increasing CO$_2$concentration under same concentration of O$_2$. The transpiration rates estimated by the selected model were in good agreement with experimental data for Fuji apples under controlled atmosphere conditions and normal air. When the respiratory heat generation rate u of Fuji apple increased with storage conditions, the evaporating surface temperature and transpiration rate also increased. But since some portion of respiratory heat was used as latent heat in the evaporating surface, the change of u value had a little effect on the determination of the evaporation temperature and the transpiration rate.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.476-481
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• 1998

본 연구에서는 PWR 핵연료집합체를 금속 전환시켜 형성된 금속저장체에 대한 온도분포를 계산하였다. 해석모델은 PWR 핵연료집합체 2개 및 4개를 1개의 금속저장체로 전환한 경우로 하였다. PWR 핵연료를 금속 전환할 경우 금속전환 과정에서 Sr과 Cs를 선택적으로 제거함으로서 냉각부하를 약 1/2로 줄일 수 있고 체적을 약 1/4로 줄일 수 있는 잇점이 있다. 열해석 결과 2 PWR 핵연료 금속저장체에서 저장시스템 주변 공기의 온도가 50 $^{\circ}C$ 인 경우, 금속 연료봉의 최고온도는 164 $^{\circ}C$로 나타났다. 또한, 4 PWR 핵연료 금속저장체의 경우 금속 연료봉의 최고온도는 사각형 저장체에서 193 $^{\circ}C$, 육각형 저장체에서 183 $^{\circ}C$ 로 나타났다. 따라서 건식 저장에서 연료봉의 온도를 낮게 하기 위해서는 저장 밀도를 높일 수 있는 연료봉 밀집화 (rod consolidation) 방식이 경제성 측면뿐만 아니라 열안전성 측면에서도 유리한 것으로 나타났다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.39-47
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• 1999

This paper describes on-line retrainable RBF network in order to control the coiling temperature for a hot coil strip at Pohang Iron & Steel Company(POSCO). The proposed neural network can be used for improving conventional rule-based lookup table, which generates a heat transmission coefficient. To cope with time-varying characteristics of hot coil process, additional synaptic weights for on-line retraining purposes are introduced to hidden-to-output weights of conventional RBF network. Those weights are locally adjusted to newly incoming test data while preserving old information trained with off-line past data. Hence the effect of catastrophic interference can be greatly alleviated with the proposed network. In addition, rejection scheme is introduced for reliability concerns. From the experimental results applied to the actual process, it is noticed that overall control performance represents about 2.2% increase compared to the conventional one.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.2
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• pp.240-249
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• 1985

여러 가지 조건하에서 한쪽면만 이온질화 처리된 SCM4 의 평판을 모델로 하여 질화층의 기계적 성질과 잔류응력을 연구하였다. 질화층에서의 재료의 성질은 질소함량분포에 비례하여 변할 것이 라는 가정하에 외팔보의 굽힘과 온도-곡률의 관계를 구하는 이론적 모델을 정립하고 이에 따른 간접적 실험방법을 제시하였다. 질화층 표면에서의 선팽창 계수는 질화되지 않은 코어의 값에 비 해 2내지 12% 증가를 보였고 탄성계수는 50내지 700%증가를 보였다. 질화로 인한 축방향 팽창은 변형도로 약 0.002를 얻었다. 상온에서의 코어의 최대인장 잔류응력은 2내지 25Kg/mm$^{2}$이 며, 질화층표면에서 일어나는 최대압축잔류응력은 질화조건에 따라 50내지 300Kg/mm$^{2}$을 얻었다.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.121-129
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• 2001

This paper demonstrates the development of optical temperature sensor based on the etched planar waveguide Bragg grating. Topics include design and fabrication of the etched planar waveguide Bragg grating, investigation of the grating reflection characteristics, and temperature measurement capabilities. The typical bandwidth and reflectivity of the surface etched grating has been ~0.2nm and ~7%, respectively, at a wavelength of ～1552nm. The temperature-induced wavelength change of the optical sensor is found to be slightly non-linear over ～20$0^{\circ}C$ temperature range. Theoretical models for the grating response of the sensor based on waveguide and plate deformation theories agree with experiments to within acceptable tolerance.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.121-141
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• 2017

The thermal analysis of an underground power conduit for electrical cables is essential to determine their current capacity with an increasing number of demands for high-voltage underground cables. The temperature rises around a buried cable, caused by excessive heat dissipation, may increase considerably the thermal resistance of the cables, leading to the danger of "thermal runaway" or damaging to insulators. It is a key design factor to develop the mechanism on thermal behavior of backfilling materials for underground power conduits. With a full-scale field test, a numerical model was developed to estimate the temperature change as well as the thermal resistance existing between an underground power conduit and backfill materials. In comparison with the field test, the numerical model for analyzing thermal behavior depending on density, moisture content and soil constituents is verified by the one-year-long field measurement.

• Korean Journal of Food Science and Technology
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• v.53 no.5
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• pp.657-668
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• 2021

We prepared the growth and survival models of enterohemorrhagic Escherichia coli (EHEC) and Campylobacter jejuni in milk as a function of temperature and assessed the microbiological risks associated with the consumption of whole milk. EHEC and C. jejuni were not detected in whole milk (n=195) in the retail market. The minimum growth temperature of EHEC in milk was 7℃. The lag time of EHEC in whole milk was longer than that in skim milk. The survival ability of C. jejuni in milk was better at 4℃ than at 10℃. Lower delta values were observed in whole milk than in skim milk, indicating that C. jejuni survived better in skim milk. The probability of foodborne illness from whole milk consumption was 5.70×10^-5 for EHEC and 9.86×10^-9 for C. jejuni. Sensitivity analysis results show that the market temperature of EHEC and the dose-response model of C. jejuni are correlated with the probability of foodborne illness.