• 한국의류학회지
• /
• 제27권5호
• /
• pp.582-587
• /
• 2003

To examine the effect of heat treatment temperature in finishing process on PET/PBT Fabric, PET/PBT Fabrics were treated at different relaxing temp., pre-set temp., and final-set temp.. The dimensions such as thickness and density were measured, and the handles were evaluated by Kawabata system. In relaxing which was wet heat treatment, thickness and bulkiness were increased, and NUMERI, FUKURAMI, SOFUTOSA, and THV also were increased but KOSHI was decreased with elevating temperature. With elevating pre-set temp., thickness and bulkiness were decreased, but KOSHI was increased. NUMERI, FUKURAMI, SOFUTOSA, and THV were the best at 180$^{\circ}C$ pre-set treatment. In final-set which was dry heat treatment like pre-set, thickness, bulkiness, NUMERI, HUKURAMI, SOFUTOSA, and THV were decreased, but KOSHI value was increased with elevating temperature. Therefore the best heat treatment condition was 130$^{\circ}C$ relaxing, 180$^{\circ}C$ pre-set, and 160$^{\circ}C$ final-set. And the handle of PET/PBT Fabric was affected much more by relaxing temp. than pre-set temp. and final-set temp.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2013년도 추계학술대회
• /
• pp.722-725
• /
• 2013

본 연구에서는 열처리를 하지 않은 소자와 열처리 소자의 기본 특성을 비교, 분석하고 온도에 따른 특성 변화를 확인하였다. 사용된 소자는 상부전극이 Pt/Ti(150nm), 하부전극은 Pt(150nm), 산화층은 $HfO_2$(70nm)이고, 열처리 온도는 $500^{\circ}C$, $850^{\circ}C$ 이다. 측정 소자 성능은 Set/Reset 전압, sensing window(저항상태 차이)다. 측정결과 세 종류의 소자의 기본 특성은 열처리별 온도가 높을수록 Set/Reset전압과 sensing window가 증가하였다. 온도에 따른 기본특성 분석 실험 결과 온도가 증가함에 따라 Set/Reset전압과 sensing window가 감소하였다. Set/Reset 전압의 온도에 따른 변화율은 $850^{\circ}C$ 열처리한 소자가 제일 작았고, sensing window의 변화율은 $500^{\circ}C$ 열처리 소자에서 가장 작은 변화율을 보였다. Set/Reset 전압의 변화율 과 sensing window를 고려했을 때 $500^{\circ}C$ 열처리 소자가 좋은 메모리 특성을 보였다.

• 한국멀티미디어학회논문지
• /
• 제23권2호
• /
• pp.155-165
• /
• 2020

In this paper, we propose a smart thermostat temperature set-point control method based on machine learning and rule engine, which controls thermostat's temperature set-point so that it can achieve energy savings as much as possible without sacrifice of occupants' comfort while users' preference usage pattern is respected. First, the proposed method periodically mines data about how user likes for heating (winter)/cooling (summer) his or her home by learning his or her usage pattern of setting temperature set-point of the thermostat during the past several weeks. Then, from this learning, the proposed method establishes a weekly schedule about temperature setting. Next, by referring to thermal comfort chart by ASHRAE, it makes rules about how to adjust temperature set-points as much as low (winter) or high (summer) while the newly adjusted temperature set-point satisfies thermal comfort zone for predicted humidity. In order to make rules work on time or events, we adopt rule engine so that it can achieve energy savings properly without sacrifice of occupants' comfort. Through experiments, it is shown that the proposed smart thermostat temperature set-point control method can achieve better energy savings while keeping human comfort compared to other conventional thermostat.

• 한국지열·수열에너지학회논문집
• /
• 제10권2호
• /
• pp.7-12
• /
• 2014

Government has recently restricted heating and cooling set temperatures for the commercial and public buildings due to increasing national energy consumption. The goal of this paper is to visualize a future two way indoor set temperature control impact on building energy consumption by using TRNSYS simulation modeling. The building was modelled based on the twin test cell with the same dimension. Air source ground coupled heat pump performance data has been used for modeling by TRNSYS 17. Daejeon weather data has been used from Korea Solar Energy Society. The heating set temperature in the reference room is $24^{\circ}C$ as well as the target room set temperature are $23^{\circ}C$, $22^{\circ}C$, $21^{\circ}C$ and $20^{\circ}C$. The cooling set temperature of the reference room is also $24^{\circ}C$ as well as the target room set temperature of $25^{\circ}C$, $26^{\circ}C$, $27^{\circ}C$ and $28^{\circ}C$. For the air source heat pump system, heating season energy consumption is $35.52kWh/m^2y$ in the reference room. But the heating energy consumption in the target room is reduced to 7.5% whenever the set temperature decreased every $1^{\circ}C$. The cooling energy consumption in the reference room is $4.57kWh/m^2y$. On the other hand, the energy consumption in the target room is reduced to 22% whenever the set temperature increased every $1^{\circ}C$ by two way controller. For the geothermal heat pump system, heating energy consumption in the reference room is reduced to 20.7%. The target room heating energy consumption is reduced to 32.6% when the set temperature is $22^{\circ}C$. The energy consumption in the target room is reduced to 59.5% when the set temperature is $26^{\circ}C$.

• 설비공학논문집
• /
• 제23권6호
• /
• pp.441-448
• /
• 2011

The energy consumption of a condensing gas boiler may be greatly reduced by the effective operation of the unit. In this study, the supply water algorithm for a condensing gas boiler control was developed by using the fuzzy logic. This includes the supply water set temperature algorithm, and the control algorithms of a gas valve, a blower and a pump. For the set temperature algorithm, the outside air temperature and the return water temperature were used as input variables. The supply water temperature difference and its slope were used as input variables of the gas valve and blower control algorithm. And the supply water temperature and the return water temperature were used as input variables of the pump control algorithm. In order to analyse performances of these algorithms, the dynamic model of a condensing gas boiler was used. The initial start-up test, the supply water set temperature change test, the outside air temperature change test, and the return water temperature change test were performed. Simulation results showed that algorithms developed in this study may be practically applied for the effective control of a condensing gas boiler.

• 설비공학논문집
• /
• 제12권4호
• /
• pp.354-362
• /
• 2000

Optimal supervisory control strategy for the set points of controlled variables in the central cooling system has been studied by computer simulation. A quadratic linear regression equation for predicting the total cooling system power in terms of the controlled and uncontrolled variables was developed using simulated data collected under different values of controlled and uncontrolled variables. The optimal set temperatures such as supply air temperature, chilled water temperature, and condenser water temperature, are determined such that energy consumption is minimized as uncontrolled variables, load, ambient wet bulb temperature, and sensible heat ratio, are changed. The chilled water loop pump and cooling tower fan speeds are controlled by the PID controller such that the supply air and condenser water set temperatures reach the set points designated by the optimal supervisory controller. The influences of the controlled variables on the total system and component power consumption was determined. It is possible to minimize total energy consumption by selecting the optimal set temperatures through the trade-off among the component powers. The total system power is minimized at lower supply, higher chilled water, and lower condenser water set temperature conditions.

• 한국압력기기공학회 논문집
• /
• 제12권1호
• /
• pp.49-55
• /
• 2016

This paper analyzed a root cause of abnormality in the temperature and vibration at generator-side bearing of motor generator set (MG Set), which is a power supply system to control element drive mechanism (CEDM) of nuclear power plants (NPPs), and modified the design of roller-type and sealing method to improve the abnormalities. From the inspection of MG Set and analysis of temperature variation during service, it was found that the abnormal temperature transition was basically associated with original design of generator-side bearing, whose roller was axially restrained by inner race, and that the abnormal vibration level was caused by inserting small chips of cage and V-ring, which were generated due to the abnormal temperature transition at roller bearing. Type of bearing and sealing method were modified based on these analyses. The temperature and vibration level measured at roller bearing showed that the modifications clearly improved the operational stability of MG Set.

• 한국응용과학기술학회지
• /
• 제35권2호
• /
• pp.357-366
• /
• 2018

본 연구는 가정용 냉장고를 대상으로 냉동실과 냉장실의 설정온도를 각기 달리할 경우 냉동실과 냉장실 고내의 온도를 실측하여 냉장고 식품 보관 온도분포를 추정하고자 한다. 또한, 각 실의 설정온도를 중심으로 상하로 온도차가 얼마나 큰가를 파악하고, 설정온도로 회복하는데 소요되는 시간을 파악하고자 한다. 그리고 설정된 온도로 회복하기 위해 소비하는 전력량을 측정함으로서 가정용 냉장고의 최적 설정조건을 제시하고자 한다. 그 결과, 냉동실 온도가 $-18^{\circ}C$를 실현한 조건은 Case 3, Case 6, Case 8, Case 9로 냉동실 조건보다는 냉장실의 설정온도를 저온으로 할 경우에만 냉동실의 온도가 적정온도를 나타냈다. 이 조건에서 냉장실의 온도는 최저 $-1.1^{\circ}C$, Case 6은 $-1.5^{\circ}C$, Case 8은 $-1.1^{\circ}C$, Case 9는 $-0.8^{\circ}C$로 영하의 온도를 보였다. 또한 각 케이스의 운전시작 10시간 동안 누적소비전력량은 Case 4를 제외하고는 냉동실 및 냉장실의 설정온도가 낮을수록 컸으며, Case 4는 운전시작이 13:30분에 시작되었기에 09시경에 운전을 시작한 다른 조건보다는 낮시간의 환경온도가 높은 이유로 전력소비가 크다는 것을 확인하였다.

• International Journal of Advanced Culture Technology
• /
• 제4권2호
• /
• pp.47-56
• /
• 2016

In transformer cooling systems, oil temperature is controlled through the use of a blower and oil pump. For this paper, set-point algorithms, a reset algorithm and control algorithms of the cooling system were developed by neural networks and fuzzy logics. The oil inlet temperature was set by a $2{\times}2{\times}1$ neural network, and the oil temperature difference was set by a $2{\times}3{\times}1$ neural network. Inputs used for these neural networks were the transformer operating ratio and the air inlet temperature. The inlet set temperature was reset by a fuzzy logic based on the transformer operating ratio and the oil outlet temperature. A blower was used to control the inlet oil temperature while the oil pump was used to control the oil temperature difference by fuzzy logics. In order to analysis the performance of these algorithms, the initial start-up test and the step change test were performed by using the dynamic model of a transformer cooling system. Test results showed that algorithms developed for this study were effective in controlling the oil temperature of a transformer cooling system.

• 한국소성가공학회:학술대회논문집
• /
• 한국소성가공학회 2009년도 춘계학술대회 논문집
• /
• pp.252-255
• /
• 2009

The roll gap set-up in the finishing mill is one of the most important technologies in the hot plate rolling process. As the target thickness can be obtained by the correct set-up of the roll gap, improving the roll gap set-up technology is very critical for plate thickness accuracy. The main cause of thickness variation in hot plate mills is the non-uniform temperature distribution along the length of the slab. The objective of this study is to adjust the roll gap set-up for the thickness accuracy of plate in hot rolling process considering top-end temperature drop. Therefore this study has concentrated on determining the correct amounts of roll gap to compensate thickness variation due to top-end temperature drop. The off-line simulation of compensated roil gap significantly decreases top-end thickness variation.