• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.6
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• pp.66-72
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• 2012

The main sources of energy consumption in warehouses are MHE(Material Handling Equipment), HVAC(Heating, Ventilating and Air Conditioning) and Lighting. Warehouses in advanced countries raise energy efficiencies with energy consumption diagnosis, technology development and systematic management and improvements for MHE, HVAC and Illuminating, etc. They have managed illuminating system, air conditioning, motor driven system, air circulation method, dock facility, layout, AS/RS, conveyor system and battery management, etc. Ansong Pyeongtaek area investigation resulted that 43.9[%] of enterprises are managing partly energy consumption source. But the data resulted with not substantial management of energy consumption but passive management for only electric bill curtailment. Therefore through survey research & visiting interviews of some companies in Ansong Pyeongtaek area, we understood the status of energy consumption source management and proposed energy efficiency methods on the basis of that results.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1256-1263
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• 2022

With the advent of the Fourth Industrial Revolution, the amount of energy used in buildings has been increasing due to changes in the energy use structure caused by the massive spread of information-oriented equipment, climate change and greenhouse gas emissions. For the efficient use of energy, it is necessary to have a plan that can predict and reduce the amount of energy use according to the type of energy source and the use of buildings. To address such issues, this study presents a model embedded in a digital twin that predicts energy use in buildings. The digital twin is a system that can support a solution of urban problems through the process of simulations and analyses based on the data collected via sensors in real-time. To develop the energy use prediction model, energy-related data such as actual room use, power use and gas use were collected. Factors that significantly affect energy use were identified through a correlation analysis and multiple regression analysis based on the collected data. The proof-of-concept prototype was developed with an exhibition facility for performance evaluation and validation. The test results confirm that the error rate of the energy consumption prediction model decreases, and the prediction performance improves as the data is accumulated by comparing the error rates of the model. The energy use prediction model thus predicts future energy use and supports formulating a systematic energy management plan in consideration of characteristics of building spaces such as the purpose and the occupancy time of each room. It is suggested to collect and analyze data from other facilities in the future to develop a general-purpose energy use prediction model.

• Journal of the Korean Solar Energy Society
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• v.23 no.2
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• pp.51-58
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• 2003

PSHC(Prismatic Solar Hybrid Collector) is a passive solar system composed of prismatic acrly glazing, glazing and ventilating fan. This PSHC system is applied to effectively reduce heating ventilation load as well as lighting load. But so far no method appraising thermal performance of this PSHC system has been developed yet. To assess thermal performance of the PSHC system, a prototype PSHC experimental facility and TRNSYS subroutine type-205 model have been developed in Korea Institute of Energy Research (KIER). The results indicated that l)TRNSYS empirical model of PSHC has been properly modeled with actual performance data, 2)a more reliable source of weather data such as NASA and KIER weather station have been also obtained, and therefore, 3)the annual energy performance of PSHC could be assessed based on this proposed TRNSYS model.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.591-594
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• 2005

Geothermal energy becomes to be one of the promising energy sources. In this study, technology using water thermal energy from riverbank filtration system(including alluvial and riverbed deposit) is reviewed and checked as an energy resources. The objects of this study are (1) long-term monitoring of alluvial and riverbed sites, (2) preliminary design of cooling and heating system at riverbank filtration facility, and (3) calculation of potential groundwater heat energy, including riverbank filtration system. Measuring data of alluvial and riverbank filtration show slight fluctuations comparing to temperature of atmospheric air which indicates that groundwater obtained from the riverbank filtration system have a sufficient potential as a source of cooling and heating energy.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.81-94
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• 2022

This study sets the research goal of reducing energy consumption which 'H' University Industry-University Cooperation Foundation and resident companies are concerned with, as well as conducting policy research and data analysis. We tried to present a solution to the problem using the technique. The algorithm showing the greatest reliability in the power of the model for the analysis algorithm of this paper was selected, and the power consumption trend curves per minute and hour were confirmed through predictive analysis while applying the algorithm, as well as confirming the singularity of excessive energy consumption. Through an additional sub-sensor analysis, the singularity of energy consumption of the unit was identified more precisely in the facility rather than in the building unit. Through this, this paper presents a system building model for real-time monitoring of campus power usage, and expands the data center and model for implementation. Furthermore, by presenting the possibility of expanding the field through research on the integration of mobile applications and IoT hardware, this study will provide school authorities and resident companies with specific solutions necessary to continuously solve data-based field problems.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.10 no.3
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• pp.143-149
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• 2012

Groundwater flow simulations were performed to obtain data of groundwater flow used in a safety assessment for a hypothetical geological disposal facility assumed to be located in the KURT (KAERI Underground Research Tunnel) site. A regional scale modeling of the groundwater flow system was carried out to make boundary conditions for a local scale modeling. And, fracture zones identified at the study site were involved in the local scale groundwater flow model. From the results of the local scale modeling, a hydraulic head distribution was indicated and it was used in a particle tracking simulation for searching pathway of groundwater from the location of the hypothetical disposal facility to the surface where the groundwater reached. The flow distance and discharge rate of the groundwater in the KURT site were calculated. It was thought that the modeling methods used in this study was available to prepare the data of groundwater flow in a safety assessment for a geological disposal facility of radioactive wastes.

• Nuclear Engineering and Technology
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• v.33 no.6
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• pp.638-651
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• 2001

The present study is to assess the applicability of the best-estimate thermal-hydraulic code, MARS 1.4, for the analysis of thermal-hydraulic behavior in PWRs during natural circulation conditions. The code simulates a natural circulation test, BETHSY test 4. la, which was conducted on the integral test facility of BETHSY. The test represented the cooling states of the primary cooling system under single-phase natural circulation, two-phase natural circulation and the reflux condensation mode with conditions corresponding to the residual power, 2% of the rated core power value and 6.8 MPa at the secondary system. Based on MARS 1.4 calculations, the major thermal-hydraulic behaviors during natural circulation are evaluated and the differences between the experimental data and calculated results are identified. The calculated results show generally good behavior with regard to the experimental results; the region of single-phase natural circulation is 100-92% of the initial mass inventory, two-phase natural circulation is 84-63 %, and the reflux condensation mode occurred below 58 %. U-tubes empty and the core uncovery are obtained at 39 % and 34 % of the initial mass inventory, respectively.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.175-186
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• 2009

Power consumed by modern computer systems, particularly servers in data centers has almost reached an unacceptable level. However, their energy consumption is often not justifiable when their utilization is considered; that is, they tend to consume more energy than needed for their computing related jobs. Task scheduling in distributed computing systems (DCSs) can play a crucial role in increasing utilization; this will lead to the reduction in energy consumption. In this paper, we address the problem of scheduling precedence-constrained parallel applications in DCSs, and present two energy- conscious scheduling algorithms. Our scheduling algorithms adopt dynamic voltage and frequency scaling (DVFS) to minimize energy consumption. DVFS, as an efficient power management technology, has been increasingly integrated into many recent commodity processors. DVFS enables these processors to operate with different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. Our algorithms effectively balance these two performance goals using a novel objective function and its variant, which take into account both goals; this claim is verified by the results obtained from our extensive comparative evaluation study.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.386-391
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• 1997

It is important to understand correctly a CHF under low flow condition for the purpose of enhancing the reactor safety and performance in the LWRs. The CHF experiments have been carried out for an internally heated vertical annulus in RCS loop facility. The experimental conditions cover ranges of pressure from 1.82 to 12.08 MPa, mass flux from 300 to 550kg/$m^2$. s and inlet subcooling of 210kJ/kg. The CHF data decrease with increasing pressure at high value of mass flux. For mass flux of about 300kg/$m^2$. s, the CHF rue little influenced by pressure. The CHF data are correlated well by using the dimensionless heat flux and dimensionless mass flux for a fixed inlet subcooling except the data group of 12.08 MPa. It seems that the Doerffer correlation and Katto correlation overestimate the CHF for low pressure and lower value of mass flux within this experimental ranges. The Bowling correlation gives a better prediction than the other two correlations.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.426-432
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• 2022

HVAC systems play a critical role in reducing energy consumption in buildings. Integrating occupants' thermal comfort evaluation into HVAC control strategies is believed to reduce building energy consumption while minimizing their thermal discomfort. Advanced technologies, such as visual sensors and deep learning, enable the recognition of occupants' discomfort-related actions, thus making it possible to estimate their thermal discomfort. Unfortunately, it remains unclear how accurate a deep learning-based classifier is to recognize occupants' discomfort-related actions in a working environment. Therefore, this research evaluates the classification performance of occupants' discomfort-related actions while sitting at a computer desk. To achieve this objective, this study collected RGB video data on nine college students' cold discomfort-related actions and then trained a deep learning-based classifier using the collected data. The classification results are threefold. First, the trained classifier has an average accuracy of 93.9% for classifying six cold discomfort-related actions. Second, each discomfort-related action is recognized with more than 85% accuracy. Third, classification errors are mostly observed among similar discomfort-related actions. These results indicate that using human action data will enable facility managers to estimate occupants' thermal discomfort and, in turn, adjust the operational settings of HVAC systems to improve the energy efficiency of buildings in conjunction with their thermal comfort levels.