• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1097-1103
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• 1988

This paper deals with surface crack behavior and the fatigue life prediction of notched specimens using the relation between surface crack length, a, and the cycle ratio, $N/N_{f}$. From the $a-N\;/\;N_{f}$ curves, UC(the upper limit curve), LC(the lower limit curve) and MC(the middle limit curve) were assumed and utilized to predict the fatigue life and crack growth rate. The data computed from the three assumed curves were compared with the experimental data. It has been found that in the stable crack growth region ($N/N_{f}=0.3-0.8$) fatigue life can be predicted within 20% errors. Using the characteristics of $a-N\;/\;N_{f}$ curve, it is possible to predict the $da/dN-K_{max}$ curve, the $da/dN-{\Delta}K_{{\varepsilon}_t}$ curve, and the $S-N_{f}$ curve.

• Journal of Environmental Science International
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• v.31 no.7
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• pp.617-635
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• 2022

The effect of coupled data assimilation (DA) on the meteorological prediction in the west coastal region of Korea was evaluated using a coupled atmosphere-ocean model (e.g., COAWST) in the spring (March 17-26) of 2019. We performed two sets of simulation experiments: (1) with the coupled DA (i.e., COAWST_DA) and (2) without the coupled DA (i.e., COAWST_BASE). Overall, compared with the COAWST_BASE simulation, the COAWST_DA simulation showed good agreement in the spatial and temporal variations of meteorological variables (sea surface temperature, air temperature, wind speed, and relative humidity) with those of the observations. In particular, the effect of the coupled DA on wind speed was greatly improved. This might be primarily due to the prediction improvement of the sea surface temperature resulting from the coupled DA in the study area. In addition, the improvement of meteorological prediction in COAWST_DA simulation was also confirmed by the comparative analysis between SST and other meteorological variables (sea surface wind speed and pressure variation).

• Corrosion Science and Technology
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• v.23 no.4
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• pp.324-333
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• 2024

Atmospheric corrosion poses a significant threat to durability of metallic materials and safety of structures, making precise prediction of corrosion rates crucial in industrial and engineering settings. Understanding the exact rate of corrosion is essential. However, accurate inclusion of various environmental factors that can influence atmospheric corrosion in the calculation of corrosion rate is a complex challenge. This study introduces a physics-based model that incorporates electrochemical methods and considers active surface area affected by surface contaminants to estimate atmospheric corrosion rate of carbon steel. The model can evaluate corrosion levels using key factors such as chloride deposition rate, relative humidity, and the presence of surface particles. By integrating these considerations, this model moves beyond empirical estimations, providing a more stable prediction of corrosion rate that is less susceptible to environmental variations. This model provides a robust tool for defense applications, offering precise insights into the dynamics of atmospheric corrosion that could enhance the maintenance and safety of weapon systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.676-679
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• 1995

Practically, induction surface hardening is used widely to enhance the local strength of structure. In this study, Fatigue limit and its S-T characteristic for raw and induction hardened specimen of SCM440 is studied experimentally. The life prediction was considered by Juvinall's equation and its predicted result is compared with experiment.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.129-141
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• 2003

The precise prediction of ground displacement plays an important role in planning and constructing tunnels. In this study, an equation for predicting the surface and crown settlement is suggested by examining the theories of ground movement caused by tunnel excavation. From the 3D numerical modeling, the reinforcement effect of UAM (Umbrella Arch Method) is quantitatively analyzed with respect to deformation modulus and overburden. By using a regression technique for the numerical results, an equation for predicting the settlement is suggested.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1195-1204
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• 2021

Recently, local torrential rain have become more frequent and severe due to abnormal climate conditions, causing a surge in human and properties damage including infrastructures along the river. In this study, water surface elevation prediction algorithm was developed using the LSTM (Long Short-term Memory) technique specialized for time series data among Machine Learning to estimate and prevent flooding of the facilities. The study area is Jamsu Bridge, the study period is 6 years (2015~2020) of June, July and August and the water surface elevation of the Jamsu Bridge after 3 hours was predicted. Input data set is composed of the water surface elevation of Jamsu Bridge (EL.m), the amount of discharge from Paldang Dam (m³/s), the tide level of Ganghwa Bridge (cm) and the number of tweets in Seoul. Complementary data were constructed by using not only structured data mainly used in precedent research but also unstructured data constructed through wordcloud, and the role of unstructured data was presented through comparison and analysis of whether or not unstructured data was used. When predicting the water surface elevation of the Jamsu Bridge, the accuracy of prediction was improved and realized that complementary data could be conservative alerts to reduce casualties. In this study, it was concluded that the use of complementary data was relatively effective in providing the user's safety and convenience of riverside infrastructure. In the future, more accurate water surface elevation prediction would be expected through the addition of types of unstructured data or detailed pre-processing of input data.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.8
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• pp.1503-1512
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• 1992

The strength evaluation and life prediction on the corrosion part of structure is one of the most important subjects, as a viewpoint of reducing economic loss by regular inspection, maintenance, repair and replace. For this purpose, it has been difficult to obtain the available data on growth of pit depth or growth rate of each pit which depends on time. In this paper, the life prediction and strength evaluation method was suggested for the structure with irregular stress concentration part by surface corrosion. The statistical distribution pattern of corrosion depth and the degree of fatigue strength decline were confirmed according to corrosion period by artificial corrosion of SS41 steel. The life prediction and the fatigue strength evaluation of materials with consideration of the corrosion period on the extreme value statistic analysis by the data of maximum depth of corrosion and on random variable was studied.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.131-140
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• 2021

It is becoming more important to utilize reclaimed lands in South Korea, due to the increasing competition for its usage among different sectors. However, the high groundwater level and poor permeability are exposing them to deterioration by salinization. Salinization is difficult to predict because the pattern changes according to various characteristics of soil and groundwater. In this study, the capillary rising time was studied by the water content profile in the soil. The prediction equation of soil salinity was developed based on simulation result of the CHEMFLO model. to enable prediction considering various soil water content and groundwater level. The two terms constituting the equation showed the coefficients of determination of 0.9816 and 0.9824, respectively. Using the prediction equation of the study, the surface salinity can be easily predicted from the initial surface salinity and the salinity of the groundwater. In the future, more precise predictions will be possible with the results of studies on the hydraulic characteristics of various reclaimed soils, changes in water content profile by seasonal and climate events.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1366-1371
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• 2003

Molecular dynamics (MD) simulations are conducted to investigate the thermophysical characteristics and the stability of liquid threads for various conditions. A cylindrical thread in the simulation domain is made of Lennard-Jones molecules. The surface tension of liquid threads can be determined from local densities, local normal and transverse components of the pressure force. In order to understand the effects of thread radii on surface tensions, the Tolman equation is modified on the basis of the cylindrical coordinates for prediction of surface tensions. Surface tensions calculated from the MD simulation agree with the prediction from the modified Tolman equation. In addition, surface tensions decrease linearly with increasing system temperature. For a binary system, the surface tension decreased linearly compared to that for a pure system with increasing binary ratio of solute molecules which have relatively large value of the affinity coefficient. For a fixed binary ratio, the surface tension increased slightly with the affinity coefficient and the maximum value appear around where the affinity coefficient is 1.5 and decreased rapidly for upper value of 1.5. In addition, the critical wavelengths of perturbations are proven to be directly proportional to the equimolar dividing radii of the liquid threads.