• Journal of the Korean Institute of Gas
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• v.26 no.1
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• pp.1-6
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• 2022

This paper is a purpose to study and analyze the engine starting failure examples for LPG car. The first example, the researcher verified the phenomenon that didn't supply the fuel because of filter clogging by fine alien substance in the gas valve line when he inspected the emergency cutting valve. The second example, there was no the influence of gas leakage when the solenoid operated at first. But the damage part of solenoid assemblying face wad downed a durability according to running a valve. Eventually, the researcher checked on the phenomenon of engine stopping by no gas feeding in solenoid because of leaking of gas. The third example, the researcher sought that the wiring sheaths of connector fin between EGR 10A fuse and LPG switch verified the burn-out phenomenon due to the bad contacting as tension damage produced the overheating. Therefore, the manager of a car has to do pre-inspection no producing electric failure and he must maintain his car with optimum condition.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.51-61
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• 2021

As a result of examining the germination rate between ginseng varieties, Jagyongjong varieties had the highest germination rate, and Yeonpung. had the lowest germination rate. In the ginseng seed germination rate experiment, the highest germination rate and growth condition were shown in artificial soil conditions of the ratio of Peatmoss 6.5: Pearlite 2: Masato 1.5. Good soil conditions require adequate soil moisture forces during the incubation period. The cultivation of ginseng medicinal crops requires optimal soil breathability, soil pH, and soil stabilization, which are important for root breathing. Microbial activity in the soil has a great influence on the growth of ginseng. The optimum pH of the soil for ginseng cultivation is 5.0-5.5 As a result of the experiment, the soil remained in an appropriate range after a month. In general, when the EC concentration value of the soil for ginseng cultivation is 0.2 mS/cm or more, growth deteriorates, and when the EC concentration value is 0.5 mS/cm or more, concentration obstacles such as root decay occur. As a result of the analysis, the higher the concentration value of EC, the more likely it is to interfere with ginseng growth.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.610-619
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• 2022

Hydrogen is emerging as an alternative fuel for eco-friendly ships because it reacts with oxygen to produce electrical energy and only water as a by-product. However, unlike regular fossil fuels, hydrogen has a material with a high risk of explosion due to its low ignition point and high flammability range. In order to safely use hydrogen in ships, it is an essential task to study the flow characteristics of hydrogen leakage and diffusion need to be studied. In this study, a numerical analysis was performed on the effect of leakage, ventilation, etc. on ventilation performance when hydrogen leaks in an enclosed space such as inside a ship. ANSYS CFX ver 18.1, a commercial CFD software, was used for numerical analysis. The leakage rate was changed to 1 q, 2 q, and 3 q at 1 q = 1 g/s, the ventilation rate was changed to 1 Q, 2 Q and 3 Q at 1 Q = 0.91 m/s, and the ventilation method was changed to type I, type II, type III to analyze the ventilation performance was analyzed. As the amount of leakage increased from 1 q to 3 q, the HMF in the storage room was about 2.4 to 3.0 times higher. Furthermore, the amount of ventilation to reduce the risk of explosion should be at least 2 Q, and it was established that type III was the most suitable method for the formation of negative pressure inside the hydrogen tank storage room.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.299-307
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• 2021

This study is a research study to identify the recognition, experiences, needs of convergence education in occupational therapy students. Therefore, it is intended to provide basic data when developing convergence subjects and non-regular programs within the occupational therapy (department) curriculum. From December 03, 2020, a web questionnaire consisting of 14 questions in 4 areas was distributed over a month, and the data of 130 people were finally analyzed. The results are as follows. First, the recognition and experiences of occupational therapy students in convergence education were low. Second, 57.7% of students recognized that occupational therapy majors need convergence education, and the expected effect of convergence education was 'improvement of occupational therapy job-related knowledge'. Third, it was recognized that 'natural science', 'prosthesis and assistive technology, activity of daily living(ADL)', and 'ADL training' convergence education was necessary for the students of occupational therapy department. The results of this study are expected to be used as basic data in the future development of occupational therapy curriculum and non-regular programs for convergence education. In the future, I think that the demand for convergence education and program development in preparation for the 4th industrial revolution will increase in the occupational therapy curriculum. It is expected that the data of this study will be used meaningfully by professors in charge of occupational therapy education at universities.

• Resources Recycling
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• v.31 no.5
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• pp.42-51
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• 2022

Aggregate resources in Korea are expected to run out owing to an increase in development demand and construction investment. Recycled concrete aggregates (RCA), extracted from waste concrete, have a lower quality than natural aggregates. However, RCA can produce concrete similar in quality to the normal concrete by aggregate pretreatment, use of admixtures, and quality control. RCA are most suitable for use in precast concrete products such as sidewalk blocks and revetment blocks. Herein, the feasibility of producing revetment blocks using recycled aggregate concrete (RAC), similar in quality to normal concrete, was analyzed. The amount of RCA was varied, and moderate high early strength cement and steam curing were used to produce the concrete test blocks. In the block test, the load resistance characteristics of the blocks were evaluated to determine optimal RAC and glass fiber reinforced polymer (GFRP) rebar compositions. Thus, the variable that reduced the cement content was determined at the same level as that of natural aggregate concrete by the control of steam curing. In the concrete block test, although this depends on the reinforcement ratio, the RAC block exhibited the same or better performance than a normal concrete block. Therefore, the low quality of RCA in RAC is no longer a problem when concrete mixing and curing are controlled and appropriate reinforcement is used.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1527-1539
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• 2022

As coastal erosion of the east coast is accelerating, the need for scientific and quantitative coastal erosion monitoring technology for a wide area increases. The traditional method for observing changes in the coast was precision monitoring based on field surveys, but it can only be applied to a small area. The airborne bathymetric Light Detection And Ranging (LiDAR) system is a technology that enables economical surveying of coastal and seabed topography in a wide area. In particular, it has the advantage of constructing topographical data for the intertidal zone, which is a major area of interest for coastal erosion monitoring. In this study, time series analysis of coastal seabed topography acquired in Aug, 2021 and Mar. 2022 on the littoral cell GW36 in Gangwon was performed using the Seahawk Airborne Bathymetric LiDAR (ABL) system. We quantitatively monitored the topographical changes by measuring the baseline length, shoreline and Digital Terrain Model (DTM) changes. Through this, the effectiveness of the ABL surveying technique was confirmed in coastal erosion monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.599-606
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• 2022

Strain gauges and the bridge weigh-in-motion (BWIM) method are the representative field measurement methods used for fatigue evaluationsof a steel bridge-in-service. For a fatigue reliability evaluation to assess fatigue damage accumulation, the effective stress range and the number of stress cycles applied as the fatigue details can be estimated based on the AASHTO Manual for Bridge Evaluations with the field measurement data of the target bridge. However, the procedure for estimating the effective stress range and the stress cycles from field measurement data has not been explicitly presented. Furthermore, studies that quantitatively compare differences in fatigue evaluation results according to the field measurement data type or processing method used are still insufficient. Here, a fatigue reliability evaluation is conducted using strain and BWIM data that are measured simultaneously. A frame model and a shell-solid model were generated to examine the effect of the accuracy of the structural analysis model when using BWIM data. Also, two methods of handling BWIM data when estimating the effective stress range and average daily cycles are defined. As a result, differences in evaluation results according to the type of field measurement data used, the accuracy of the structural analysis model, and the data handling method could be quantitatively confirmed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.117-126
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• 2022

Currently, the number of bridge structures in Korea is continuously increasing and enlarged, and the number of old bridges that have been in service for more than 30 years is also steadily increasing. Bridge aging is being treated as a serious social problem not only in Korea but also around the world, and the existing manpower-centered inspection method is revealing its limitations. Recently, various bridge damage detection studies using deep learning-based image processing algorithms have been conducted, but due to the limitations of the bridge damage data set, most of the bridge damage detection studies are mainly limited to one type of crack, which is also based on a close set classification model. As a detection method, when applied to an actual bridge image, a serious misrecognition problem may occur due to input images of an unknown class such as a background or other objects. In this study, five types of bridge damage including crack were defined and a data set was built, trained as a deep learning model, and an open set recognition-based bridge multiple damage recognition model applied with OpenMax algorithm was constructed. And after performing classification and recognition performance evaluation on the open set including untrained images, the results were analyzed.

• Journal of the Korean Geotechnical Society
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• v.37 no.12
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• pp.47-56
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• 2021

The cryosuction (negative pore pressure) in freezing soils causes groundwater migration from the frozen fringe to freezing front for ice lens formation. Frost heave and heaving pressure by ice lens cause damage to ground infrastructure. In order to prevent damage by the frost heave, various frost susceptibility criteria have been proposed. The SP (Segregation Potential) is the most widely used classification criterion for frost susceptibility in cold regions. The expansion of the ice lens by the migration of the groundwater is a key role in frost heave mechanism, and thus it is necessary to evaluate the hydraulic conductivity. In this paper, soil mixtures of coarse-fines (sand-silt) were prepared in various weight fractions and used for frost heave and column permeability test. For each case, the SP and the hydraulic conductivity were derived and correlations were analyzed. As a results, the transition threshold of the SP and the hydraulic conductivity were shown at 20% and 50% of the silt weight fraction, respectively. Although there are difference between these transition thresholds, these two coefficients show a specific correlation. In the future, additional study should be conducted for detailed analysis of the threshold transition values between SP and hydraulic conductivity.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.