• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.11
• /
• pp.2845-2852
• /
• 2000

When welding a car frame with one spot welding there are same limitations because many parts of it cannot be simplified by one spot welding alone. It is presented two spot welding model for the description of the spot welding which is usually used in a car frame structure. This study primarily covers fatigue behavior taking spot welded SPCC(Steel plate carbon C) with different ungget intervals as a tension shear specimen. It was prepared that intervals between two nuggets are varied as 9mm, 14mm, and 20mm respectively. The tensile tests and fatigue tests were executed to know the mechanical properties under static and fatigue load condition. In addition, the relationship between fatigue life and nugget intervals was illustrated by finite element method.

• Journal of Korean Society for Atmospheric Environment
• /
• v.27 no.2
• /
• pp.201-208
• /
• 2011

Recently, a real-time, pocket-sized aethalometer (microAeth$^{(R)}$ model AE51) has been developed by Magee Scientific Inc. for measuring the concentration of black carbon in the atmosphere. In this study, two aethalometers, models AE-16 and AE-51, which measure the optical absorption of carbon particles at infrared 880 nm, were operated at time interval of 5-min between January 9 and February 10, 2010 at an urban site of Gwangju, to compare the accuracy of black carbon (BC) concentrations reported from the AE-51 model and to investigate reasonable sampling time of filter media in the AE-51. The air samples in the AE-51 and AE-16 models are collected on T60 (Teflon coated glass fiber) filter media (filter spot area: 0.07 $cm^2$) and quartz fiber roll-tape filter (filter spot area: 1.67 $cm^2$), respectively. Real-time measurement results indicate that when the filters were clean, the AE-51 BC was greater than or similar to the AE-16 BC data. However as the filter spots become darker, the AE-16 BC concentrations were higher than the AE-51 BC data and the difference in the BC concentrations from two AE models becomes gradually increased. Relative error in the AE-51 and AE-16 BC concentrations showed significance difference depending on used time of the filter in the AE-51 model, weather pattern, levels of air pollution, etc, ranging from 11.5% (used time of the filter in AE-51: 1,595 min) to 52.5% (used time of the filter in AE-51: 2,085 min). When considering the used time of one filter ticket in the AE-51 model and difference (or relative error %) between AE-16 and AE-51 BC concentrations, it is recommended that the standard sampling time per one filter ticket within the AE-51 model be less than approximately 24 hr (1,440 min) under the normal weather conditions except for severe haze and mist events.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.42 no.1
• /
• pp.56-60
• /
• 1997

In order to investigate the relationships between the responses of four crops (rice, soybeans, potatoes, and red pepper) to acid rain, the simulated acid rain(SAR) of pH 1.8, 2.3, and 2.8 and normal rain of pH 6.0 were applied from 30 days after emergence to harvest at the two-week interval for rice, soybeans and red pepper and at a week interval for potatoes. SAR of pH 1.8 and 2.3 caused brown spots in the leaves of rice, soybeans, and red pepper and the damages were severer as the pH of SAR lowered, while no visual damages were observed in potatoes. The SARs did not affect chlorophyll content of rice and potatoes, while chlorophyll content of soybeans and red pepper decreased as the pH of SAR lowered. Photosynthetic activity was not significantly different among the pHs of SAR in rice, while decreased as pHs of SAR lowered from pH 2.8 to 1.8 in soybeans, potatoes, and red pepper. Yield of rice, soybeans, and potatoes was not affected by the pHs of SAR, but in red pepper the length, diameter, and weight of a fruit, the number of fruits per plant, and total matured fruit yield decreased as the pHs of SAR lowered. In rice and potatoes visual damages caused by SAR did not correlated with other observed traits. However, visual damages were negatively correlated with chlorophyll content and photosynthetic activity of soybeans and photosynthetic activity and yield of red pepper.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.10B
• /
• pp.936-944
• /
• 2006

In order to enhance their own customer satisfaction index that is one of the top level managerial performance indices, Internet communication service providers endeavor onto establishing a total quality management system. Specifically, it is under discussion that some critical Internet communication network quality characteristics closely related to customer satisfaction index should be controlled aiming to this managerial goal. This paper presents an application scheme of I-MR control charts for monitoring Internet communication network quality characteristics. This statistical quality control scheme generates a signal to practitioners when it detects the network quality characteristics out-of control. It is designed based on; 1) individual measurements; and 2) moving ranges between two consecutive individual measurements collected with a constant time interval. Empirical analyses are illustrated to estimate the expected quality improvement ratios that can be realized with the application scheme proposed in this paper. Assuming that the assignable causes can be revealed and eradicated, regarding two Internet communication services A, B, seven network quality characteristics for each service, eleven distinct measuring spots for each network quality characteristic, the expected quality improvement ratios are calculated with which the effect of the application scheme is evaluated. Results show the ranges of the expected quality improvement ratios; 1) Service A, (1) mean (0.31%-11.44%), (2) standard deviation (9.82%-71.10%): 2) Service B, (1) mean (0.29%-17.64%), (2) standard deviation (8.05%-60.59%). Hence, It is anticipated that the I-MR control charts based application scheme can be effective not only to improving the mean and dispersion of the network quality characteristics concerned but also to maintaining the network quality characteristics in-control consequently.