• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.12
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• pp.10-19
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• 2008

Daylight responsive dimming systems are energy saving systems using available daylight. It is not popular to be adopted in buildings because of blocked daylight by shading systems. Therefore, both daylight responsive dimming systems and automated roller shading systems should be integrated. In this research, prediction process of yearly lighting energy savings is developed for application integrated systems in buildings, and then the process is applied to an example building. The predicted data which are yearly lighting energy savings using developed process in a building are useful as a part of feasibility study for determination of application of such integrated systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3081-3086
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• 2015

Development of a extra-large hydraulic breaker, which could be used for a 100 ton-class excavator were carried out Hot-firing tests were carried out. Before designing a hydraulic breaker, the analysis method to predict the performance such as impact energy and impact rate were studied. Based on the analysis result, the design and manufacture of a extra-large hydraulic breaker were performed, and the breaker were confirmed to operate successfully. The data of impact energy and impact rate were measured during the operation of the breaker, and were compared with the analysis result. The analysis result of impact rate anticipated well the test data, but that of impact energy showed a large difference with the test data. The extra-large hydraulic breaker were successfully developed and the analysis method of impact energy will be updated taking into account friction, hydraulic circuit, etc.

• Explosives and Blasting
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• v.37 no.3
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• pp.25-33
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• 2019

Controlling the blast-induced damage zone(BDZ) in mining excavation is a significant issue for the safety of employees and the maintenance of facilities. Numerous studies have been conducted to accurately predict the BDZ in underground mining. This study employed the dynamic fracture process analysis (DFPA) to estimate the BDZ from a single hole blasting. The estimated BDZ were compared with the results obtained by Swedish empirical equation. The DFPA was also used to investigate the control mechanism of BDZ and fracture plane formation around perimeter holes for underground mining blasting.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1143-1150
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• 2023

The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R² values.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.47-52
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• 2013

The higher energy efficiency for ship and the lower pollution for global environment are required strictly. However the performance of marine diesel engine is gradually deteriorated with time. And also the operation condition is varied with sea conditions. Hence the optimization for operating condition of marine engines is needed for energy saving and environment kindly. In this paper, it was attempted to investigate the influence of aging for marine diesel engine. The deterioration of engine performance is assessed by the calculation results of the simulation program for two-stroke marine diesel engine developed by author which was reported before. And three parameters for deterioration of engine performance were considered such as lower efficiency of turbocharger by fouling, increase of blow-by gas due to wear of cylinder liner and getting worse of combustion by poor injection. By the results, it was shown that the influence of engine performance by aging was relatively not so small - 10.4 bar low in Pmax and 3.2% decrease in Pmi.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.10
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• pp.1403-1409
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• 2010

For many years, high-strength nickel-base superalloys have been used to manufacture turbine blades because of their excellent performance at high temperatures. The prediction of fatigue life of superalloys is important for improving the efficiency of the turbine blades. In this study, low cycle fatigue tests are performed for different values of total strain and temperature. The relations between strain energy density and number of cycles before failure occurs are examined in order to predict the low cycle fatigue life of IN738LC super alloy. The results of low cycle fatigue lives predicted by strain energy methods are found to coincide with experimental data and with the results obtained by the Coffin-Manson method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.489-496
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• 2011

Energy efficiency in wireless sensor networks is a principal issue to prolong applications to track the movement of the large-scale phenomena. It is a selective wakeup approach that is an effective way to save energy in the networks. However, most previous studies with the selective wakeup scheme are concentrated on individual objects such as intruders and tanks, and thus cannot be applied for tracking continuous objects such as wild fire and poison gas. This is because the continuous object is pretty flexible and volatile due to its sensitiveness to surrounding circumferences so that movable area cannot be estimated by the just spatiotemporal mechanism. Therefore, we propose a cluster-based algorithm for applying the efficient and more accurate technique to the continuous object tracking in enough dense sensor networks. Proposed algorithm wakes up the sensors in unit cluster where target objects may be diffused or shrunken. Moreover, our scheme is asynchronous because it does not need to calculate the next area at the same time.

• Economic and Environmental Geology
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• v.50 no.5
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• pp.415-422
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• 2017

This study focuses on the sustainable development and intelligence information society, analyzing the results of science and technology forecasts from Korea and Japan for 2040-2050. Future geological environment and disaster technologies are presented, such as base geology, geophysical geological disaster, weather adjustment, $CO_2$ reduction, environmental disaster, and smart ecocity developments. For the future technologies in energy and resources technology, space resources development and nuclear fusion will be realized by 2040 and 2050. Moreover, new material and resource technologies will be applied to replace existing energy and mineral resources by 2040. Japan has introduced intelligent information viewpoints and presented new technologies.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.137-146
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• 2011

In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.172-178
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• 2017

Thermal property is one of the important characteristic in the field of energetic materials. As the energy material is released during decomposition, DSC(Differential Scanning Calorimetry) is frequently used for the thermal analysis. In case of the dynamic DSC measurements, thermal dynamic change like melting is prevented from the thermal property measurements. And due to the predicting kg scale, the conditions of the heat exchange with the environment significantly is changed. In this study, As the method to resolve the problem, we predict the thermal aging property using the AKTS thermokinetic program from DSC measurements which performed isothermal method. Predicting the thermal aging properties from ARC(Accelerating Rate Calorimetry) measurement, we compare two results.