• Journal of the Korean Vacuum Society
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• v.19 no.4
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• pp.249-255
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• 2010

Methods of the characteristics evaluation of turbo-molecular pumps (TMP) are well-defined in the international measurement standards such as ISO, PNEUROP, DIN, JIS, and AVS. The Vacuum Center in the Korea Research Institute of Standards and Science (KRISS) has recently designed, constructed, and established the integrated characteristics evaluation system of TMPs based on the international documents by continuously pursuing and acquiring the reliable international credibility through measurement perfection. The measurement of TMP pumping speed is normally performed with the throughput and orifice methods dependent on the mass flow regions. However, in the UHV range of the molecular flow region, the high uncertainties of the gauges, mass flow rates, and conductance are too critical to precisely accumulate reliable data. In order to solve the uncertainty problems of pumping speeds in the UHV range, we introduced a SRG with 1% accuracy and a constant volume flow meter (CVFM) to measure the finite mass flow rates down to $10^{-1}$ Pa-L/s with 3% uncertainty for the throughput method. In this way we have performed the measurement of pumping speed down to $10^{-4}$ Pa with an uncertainty of less than 6% for a 1000 L/s TMP. In this article we suggest that the CVFM has an ability to measure the conductance of the orifice experimentally with flowing the known mass through the orifice chambers, so that we may overcome the discontinuity problem encountering during introducing two measurement methods in one pumping speed evaluation sequence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.527-535
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• 2017

Heat management is one of the most critical issues in Polymer Electrolyte Membrane Fuel Cells (PEMFCs) installed inside the fuel cell power pack of a fuel cell battery hybrid UPS. If the heat generated by the chemical reaction in the fuel cell is not rapidly removed, the durability and performance of the fuel cell may be affected, which may shorten its lifetime. Therefore, the objective of this study is to select and propose a proper cooling method for the fuel cells used in the fuel cell power pack of a UPS. In order to find the most appropriate cooling method, the various design factors affecting the cooling performance were studied. The numerical analysis was performed by a commercial program, i.e., COMSOL Multiphysics. Firstly, the surface temperature of the 1 kW class fuel cell stack with the cooling fans placed at the top was compared with the one with the cooling fans placed at the bottom. Various rotation speeds of the cooling fan, viz. 2,500, 3,000, 3,500, and 4,000 RPM, were tested to determine the proper cooling fan speed. In addition, the influence of the inhaled air flow rate was investigated by changing the porous area of the grille, which is the entrance of the air flowing from the outside to the inside of the power pack. As a result, it was found that for the operating conditions of the 1 kW class PEMFC to be acceptable, the cooling fan was required to have a minimum rotating speed of 3500 RPM to maintain the fuel cell surface temperature within an acceptable range. The results of this study can be effectively applied to the development of thermal management technology for the fuel cells inside the fuel cell power pack of a UPS.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.165-172
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• 2020

In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.707-717
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• 2006

As an alternative to conventional prestressed concrete (PSC) girders, various types of PSC girders are either under development or have already been applied in bridge structures. Incrementally prestressed concrete girder is one of these newly developed girders. According to the design concept, these new types of PSC girders have the advantages of requiring less self-weight while having the capability of longer spans. However, the dynamic interaction between bridge superstructures and passing trains is one of the critical issues concerning these railway bridges designed with more flexibility. Therefore, it is very important to evaluate modal parameters of newly designed bridges before doing dynamic analyses. In the present paper, a 25 meters long full scale PSC girder was fabricated as a test specimen and modal testing was carried out to evaluate modal parameters including natural frequencies and modal damping ratios at every prestressing stage. During the modal testing, a digitally controlled vibration exciter as well as an impact hammer is applied, in order to obtain precise frequency response functions and the modal parameters are evaluated varying with construction stages. Prestressed force effects on changes of modal parameters are analyzed at every incremental prestressing stage. With the application of reliable properties from modal experiments, estimation of dynamic performances of PSC girder railway bridges can be obtained from various parametric studies on dynamic behavior under the passage of moving train. Dynamic displacements, impact factor, acceleration of the slab, end rotation of the girder, and other important dynamic performance parameters are checked with various speeds of the train.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• ALGAE
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• v.32 no.2
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• pp.101-130
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• 2017

The ichthyotoxic Cochlodinium polykrikoides red tides have caused great economic losses in the aquaculture industry in the waters of Korea and other countries. Predicting outbreak of C. polykrikoides red tides 1-2 weeks in advance is a critical step in minimizing losses. In the South Sea of Korea, large C. polykrikoides red tide patches have often been recorded offshore and transported to nearshore waters. To explore the processes of offshore C. polykrikoides red tides, temporal variations in 3-dimensional (3-D) distributions of red tide organisms and environmental parameters were investigated by analyzing 4,432 water samples collected from 2-5 depths of 60 stations in the South Sea, Korea 16 times from May to Nov, 2014. In the study area, the vegetative cells of C. polykrikoides were found as early as May 7, but C. polykrikoides red tide patches were observed from Aug 21 until Oct 9. Cochlodinium red tides occurred in both inner and outer stations. Prior to the occurrence of large C. polykrikoides red tides, the phototrophic dinoflagellates Prorocentrum donghaiense (Jun 12 to Jul 11), Ceratium furca (Jul 11 to Aug 21), and Alexandrium fraterculus (Aug 21) formed red tides in sequence, and diatom red tides formed 2-3 times without a certain distinct pattern. The temperature for the optimal growth of these four red tide dinoflagellates is known to be similar. Thus, the sequence of the maximum growth rates of P. donghaiense > C. furca > A. fraterculus > C. polykrikoides may be partially responsible for this sequence of red tides in the inner stations following high nutrients input in the surface waters because of heavy rains. Furthermore, Cochlodinium red tides formed and persisted at the outer stations when $NO_3$ concentrations of the surface waters were < $2{\mu}M$ and thermocline depths were >20 m with the retreat of deep cold waters, and the abundance of the competing red-tide species was relatively low. The sequence of the maximum swimming speeds and thus potential reachable depths of C. polykrikoides > A. fraterculus > C. furca > P. donghaiense may be responsible for the large C. polykrikoides red tides after the small blooms of the other dinoflagellates. Thus, C. polykrikoides is likely to outgrow over the competitors at the outer stations by descending to depths >20 m and taking nutrients up from deep cold waters. Thus, to predict the process of Cochlodinium red tides in the study area, temporal variations in 3-D distributions of red tide organisms and environmental parameters showing major nutrient sources, formation and depth of thermoclines, intrusion and retreat of deep cold waters, and the abundance of competing red tide species should be well understood.

• Maritime Security
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• v.7 no.1
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• pp.31-60
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• 2023

This study proposes a new convergence weapon system that combines the covert placement and detection abilities of a self-propelled mobile mine with the rapid tracking and attack abilities of supercavitating rocket torpedoes. This innovative system has been designed to counter North Korea's new underwater weapon, 'Haeil'. The concept behind this convergence weapon system is to maximize the strengths and minimize the weaknesses of each weapon type. Self-propelled mobile mines, typically placed discreetly on the seabed or in the water, are designed to explode when a vessel or submarine passes near them. They are generally used to defend or control specific areas, like traditional sea mines, and can effectively limit enemy movement and guide them in a desired direction. The advantage that self-propelled mines have over traditional sea mines is their ability to move independently, ensuring the survivability of the platform responsible for placing the sea mines. This allows the mines to be discreetly placed even deeper into enemy lines, significantly reducing the time and cost of mine placement while ensuring the safety of the deployed platforms. However, to cause substantial damage to a target, the mine needs to detonate when the target is very close - typically within a few yards. This makes the timing of the explosion crucial. On the other hand, supercavitating rocket torpedoes are capable of traveling at groundbreaking speeds, many times faster than conventional torpedoes. This rapid movement leaves little room for the target to evade, a significant advantage. However, this comes with notable drawbacks - short range, high noise levels, and guidance issues. The high noise levels and short range is a serious disadvantage that can expose the platform that launched the torpedo. This research proposes the use of a convergence weapon system that leverages the strengths of both weapons while compensating for their weaknesses. This strategy can overcome the limitations of traditional underwater kill-chains, offering swift and precise responses. By adapting the weapon acquisition criteria from the Defense force development Service Order, the effectiveness of the proposed system was independently analyzed and proven in terms of underwater defense sustainability, survivability, and cost-efficiency. Furthermore, the utility of this system was demonstrated through simulated scenarios, revealing its potential to play a critical role in future underwater kill-chain scenarios. However, realizing this system presents significant technical challenges and requires further research.