• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.80-85
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• 2006

The peak demand of electricity in summer season mainly comes from the day time cooling loads. Ice thermal Storage System (ITSS) uses off-peak electricity at night time to make ice for the day time cooling. In order to maximize the use of cold storage in ITSS, the estimation of day time cooling load for the building is necessary. In this study, we present a method of cooling load estimation using 5 years of normalized outdoor temperature, relative humidity, and the building construction data. We applied the hourly-based estimation to a general hospital building with relatively less sudden heat exchange and the results are compared with the measured cooling load of the building. The results show that the cooling loads estimation depends on the indoor cooling design temperature of the building.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.10
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• pp.947-954
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• 2014

Performance of next generation susceptor is affected by temperature uniformity in order to produce reliably large-sized flat panel display. In this paper, we propose a learning estimation model of susceptor to predict and appropriately assess the temperature uniformity. Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) are compared for the suitability of the learning estimation model. It is proved that SVMs provides more suitable verification of uniformity modeling than ANNs during each stage of temperature variations. Practical procedure for uniformity estimation of susceptor temperature was developed using the SVMs prediction algorithm.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.376-385
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• 2018

To estimate the hourly temperature distribution due to solar radiation during the day, on slope in complex terrain, an empirical formula was developed including the hourly deviation in the observed temperature following solar radiation deviation, at weather stations on the east-facing and west-facing slopes. The solar radiation effect was simulated using the empirical formula to estimate hourly temperature at 11 weather observation sites in mountainous agricultural areas, and the result was verified for the period from January 2015 to December 2017. When the estimated temperature was compared with the control, only considering temperature lapse rate, it was found that the tendency to underestimate the temperature from 9 am to 3 pm was reduced with the use of an empirical formula in the form of linear expression; consequently, the estimation error was reduced as well. However, for the time from 5 pm to 6 pm, the estimation error was smaller when a hyperbolic equation drawn from the deviation in solar radiation on the slope, which was calculated based on geometric conditions, was used instead of observed values. The reliability of estimating the daytime temperature at 3 pm was compared with existing estimation model proposed in other studies; the estimation error could be mitigated up to an ME (mean error) of $-0.28^{\circ}C$ and RMSE (root mean square error) of $1.29^{\circ}C$ compared to the estimation error in previous models (ME $-1.20^{\circ}C$, RMSE $2.01^{\circ}C$).

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.5
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• pp.673-679
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• 2001

The objective of this work is to estimate the temperature dependent thermal properties of the APC-2 composite using a inverse parameter estimation technique. The present inverse method features the estimation of the thermal conductivity and the volumetric heat capacity, which are dependent on the temperature inside the composite. Furthermore, the thermal conductivity is directionally dependent because of the aniosotropy of the composite. An on-line temperature measurement system with a suitable method of heating is built. A composite slab is fabricated using thermoplastic prepreg for the investigation. The corresponding computer code for evaluating the thermal properties inversely using the temperature reading transmitted from the measurement system is developed. The parameterized form is used for the rapid and stable estimation. The modified Newtons method is adopted for the solution technique of the inverse analysis. The estimated results are compared with the measured data from a previous study for the verification.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.1
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• pp.7-12
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• 1999

In this paper, the analytical results on the maximum temperature rise estimation, taking account of the magnetizing current, are presented. Magnetizing current effects are considered for the maximum temperature rise estimation during quenches. By introducing the first order model of the infinite solenoids, we calculate the magnetizing and leakage inductances of the coaxial-wound-superconducting transformers. As the permeability of the transformer core increases, so does the magnetizing inductance, while the leakage inductances and the magnetizing current of the transformer go down. These varying permeability effects on maximum temperature rise estimation is applied to the superconducting transformers, of which specifications have already been published. The calculated results showed sufficient margins to the thermal damage.

• Journal of Korean Society of Rural Planning
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• v.27 no.2
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• pp.43-48
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• 2021

In this study, an analysis was performed using the growth data and environment data of Korean melon farmers to confirm the influence of environmental factors variables on fruit weight of Korean melon. The analysis results can be summarized as follows. First, it was confirmed that humidity and temperature were recognized as the most important factors among the core factors of korean melon farm production management. Second, The correlation analysis of fruit weight and environmental factors showed a statistically significant soil temperature, internal humidity. Third, The Pooled OLS model estimation results showed that the estimation coefficient for soil temperature is (-), and the estimation coefficient for soil temperature square is (+), indicating that optimal control temperature exists.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.532-548
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• 2021

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.62-67
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• 2000

The uniformity of temperature on a wafer is one of the most important parameters to control the RTP (Rapid Thermal Process) with proper input signals. Since it is impossible to achieve the uniformity of temperature without exact estimation of temperature at all points on the wafer, the difficulty of understanding internal dynamics and structural complexities of the RTP is a primary obstacle to accurately measure the distributed temperatures on the wafer. Furthermore, it is also hard to accomplish desirable estimation because only few pyrometers have been commonly available in the general equipments. In the paper, a thermal model based on the chamber geometry of the AST SHS200 RTP system is developed to effectively control the thermal uniformity on the wafer. First of all, the estimation method of one-point measurement is developed, which is properly extended to the case of multi-point measurements. This thermal model is validated through certain simulation and experiments. The work can be usefully contributed to building a run-by-run or a real-time controls of the RTP.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.26-34
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• 2016

Military devices and systems powered by batteries need to operate at extreme temperature and estimate the available capacity of the battery at different temperature conditions. However, accurate estimation of battery capacity is challenging due to the temperature-sensitive nature of electrochemical energy storage. In this paper, Peukert's equation with temperature factor is derived, and methods for estimating the absolute capacity of lithium-polymer battery and the state-of-charge(SOC) with respect to varying currents and temperatures are presented. The proposed estimation method is experimentally verified under three different discharge currents(0.5 A, 1 A, 3 A) and six different temperatures ranging from -30 to 45 deg. C. The results show the proposed method reduces the Peukert's estimation error by up to 30 % under or at extreme condition.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.63-73
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• 2013

Dynamic strain history curve measured in the field is influenced by various factors such as vehicle type, speed, noise, temperature and running location etc.. Because such curve is used for vehicle weight estimation methodology suggested by Moses, exact strain history curve is the most important thing for exact estimation of vehicle weight. In this paper, effect of such factors mentioned above is investigated on the measured strain history curves, and results of weight estimation of vehicles are discussed quantitatively. From this study, it was known that temperature effect contained in the strain history curve measured for long time in-site gives the biggest effect on result of weight estimation and it can be removed by using the mode value. Furthermore, gross vehicle weight can be estimated within 5% error corresponding to A class of the European classification if effects of temperature and noise are removed and vehicle properties such as speed, axle arrangement and running location are considered properly.