• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.565-574
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• 2022

The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (𝚫K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (𝚫K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (ρ) and Variance Account Factor (VAF).

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.201-202
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• 2021

Regulations on greenhouse gases emitted from ships in international shipping are being strengthened, and the greenhouse gas reduction target established by the International Maritime Organization is acting as a great challenge for shipping companies in terms of technical and operational aspects. The International Maritime Organization aims to reduce carbon intensity by 30% by 2030, 70% by 2050, and by 50% in terms of gross emissions compared to 2008. To realize this situation, the IMO adopted some short-term and mid-to-long-term measures and adopted technical measures such as the application of EEXI, an energy efficiency index, to existing ships from 2023, and the early application of EEDI phase 3 for some tpe of ships. In addition, reduction measures were introduced to reduce greenhouse gas in the operational aspect.

• Korea Trade Review
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• v.46 no.2
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• pp.19-38
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• 2021

This study aims to analyze the foreign asset leverage effect on Korean oil & gas companies' foreign profits and to maintain the appropriate foreign asset volume for reducing exchange risk. For a long time, large Korean companies, including oil companies, overheld foreign currency liabilities. For this reason, most large companies have been burdened to hedge exchange risk and this excess limit holding deteriorated total profit and reduced foreign currency asset management efficiency. Our paper proceeds in presenting a three-stage analysis considering diversified exchange risk factors through estimation on transformation of foreign transactions a/c including annual trends of foreign asset and industry specifics. We also supplement incomplete the estimation method through a practical hedging case investigation. Our research parts are differentiated on the analyzing four periods considering period-specifics The FER value of the oil firms ranged from -0.3 to +2.3 over the entire period. The results of the FER Value are volatile and irregular; those results do not represent the industry standard comparative index. The Korean oil firms are over the credit limit without accurate prediction and finance high interest rate funds from foreign-owned banks on the basis on a biased relationship. Since the IMF crisis, liabilities of global firms have decreased. Above all, oil firms need to finance a minimum limit without opportunity losses on the demand forecast and prepare for uncertainty in the market. To reduce exchange risk from the over-the-limit position, we must consider factors that affect the corporate exchange risk on the entire business process, including the contract phase.

• Journal of Korean Society of Rural Planning
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• v.23 no.1
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• pp.85-96
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• 2017

Existing agricultural reservoirs are considered as alternative source for the water welfare of rural area. In this study, domestic water supply potential of 476 reservoirs, which has storage capacity more than one million cubic meter, out of 3,377 agricultural reservoirs managed by Korean Rural Community Corporation (KRC) were investigated. Among them water quality of 136 reservoirs met the criteria of domestic water source which show less than COD 3 ppm. Available amount for domestic water of reservoirs, which meet the water quality, for ten year return period of drought was analyzed with reservoir water balance model. The results showed that 116 reservoirs has potential for supplementary domestic water supply while satisfying irrigation water supply. Finally, economic analysis using Net Present Value (NPV), Benefit-Cost (B/C) ratio, Internal Rate of Return (IRR), and Profitability Index (PI) methods was also conducted. The analysis showed that 19 reservoirs satisfied economic feasibility when water is provided from reservoir outlet but only 9 reservoirs meet the economic feasibility if water delivered from a reservoir to treatment plant by newly built conveyance canal. In order to supply the domestic water through the agricultural reservoirs managed by KRC, it is necessary to flexibly interpret and operate the 'Rearrangement of Agricultural and Fishing village Act'. Also, it is reasonable to participate in the water service business when there is a supply request from other Ministries. In addition, the KRC requires further effort to change the crop system for saving water and improve efficiency of irrigation systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.11-19
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• 2009

At present, an intelligent transport system (ITS) is being actively introduced as an alternative plan to solve various transport problems, and a traffic information provision service, a field of ITS, is being provided to users through diverse media. However, the evaluation of how useful the traffic information provided to the road users is limited to a simple questionnaire, and the systematic evaluation about what factors affect the usefulness of traffic information has not been realized. Therefore, it is impossible to calculate user convenience occurring due to traffic information, This paper aimed to develop an index to evaluate user satisfaction levels with traffic information and develop a user satisfaction level model. A result of establishing a user satisfaction level model by executing a questionnaire survey for the analysis object of variable message sign (VMS), a representative information provision medium, showed that 'desire satisfaction', 'trust', 'understanding', and 'efficiency' have an effect. Of them, the 'understanding' showed the highest level, so it was seen that, in case of VMS, how easily the character, figure, expression, etc. provided in the information was understood by users has the biggest effect on the satisfaction level of the information. The next levels of effects on the satisfaction was in the order of 'user trust', 'efficiency', and 'desire satisfaction'.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• Journal of Korea Technology Innovation Society
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• v.14 no.4
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• pp.833-859
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• 2011

This study aims to draw the characteristics of the regional operation system of the shared research instrument service, which contributes to the R&D investment efficiency by the avoidance of duplicated research instrument investment and the enhancement of the network collaboration. So from the perspective of technology infrastructure policy and regional innovation system, Gyeonggi region of Korean metropolitan area has been analyzed for the case study. The case study has been conducted by 2 step process of within-case analysis and cross-case analysis. Firstly, the characteristics of operation system of the shared research instrument have been examined through various research methods. Secondly, in the cross-case analysis, the examined issues and problems have been organized by the matrix of 3 organizational governance characteristics and 4 issues to facilitate the regional policy approach. The issues deducted by the cross-case analysis have been deducted as (1) 'usage fee charge system', 'relevant method for the performance index and measurement of the instrument service management' for the regional policy led case, (2) 'performance management issue', 'financial and managerial accounting system for the instrument operating division', and 'change of budget support scheme' for the joint operation case and lastly (3) 'usage facilitation after the expiration of research lab support project' for the university led case.

• Steel and Composite Structures
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• v.47 no.1
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• pp.91-102
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• 2023

To study the evaluation standard and control limit of mortar filling layer void length, in this paper, the train sub-model was developed by MATLAB and the track-bridge sub-model considering the mortar filling layer void was established by ANSYS. The two sub-models were assembled into a train-track-bridge coupling dynamic model through the wheel-rail contact relationship, and the validity was corroborated by the coupling dynamic model with the literature model. Considering the randomness of fastening stiffness, mortar elastic modulus, length of mortar filling layer void, and pier settlement, the test points were designed by the Box-Behnken method based on Design-Expert software. The coupled dynamic model was calculated, and the support vector regression (SVR) nonlinear mapping model of the wheel-rail system was established. The learning, prediction, and verification were carried out. Finally, the reliable probability of the amplification coefficient distribution of the response index of the train and structure in different ranges was obtained based on the SVR nonlinear mapping model and Latin hypercube sampling method. The limit of the length of the mortar filling layer void was, thus, obtained. The results show that the SVR nonlinear mapping model developed in this paper has a high fitting accuracy of 0.993, and the computational efficiency is significantly improved by 99.86%. It can be used to calculate the dynamic response of the wheel-rail system. The length of the mortar filling layer void significantly affects the wheel-rail vertical force, wheel weight load reduction ratio, rail vertical displacement, and track plate vertical displacement. The dynamic response of the track structure has a more significant effect on the limit value of the length of the mortar filling layer void than the dynamic response of the vehicle, and the rail vertical displacement is the most obvious. At 250 km/h - 350 km/h train running speed, the limit values of grade I, II, and III of the lengths of the mortar filling layer void are 3.932 m, 4.337 m, and 4.766 m, respectively. The results can provide some reference for the long-term service performance reliability of the ballastless track-bridge system of HRS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.50-62
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• 2015

Recently, Subway Line No. 9, described as a 'hell-like' subway for its recorded load factor of max. 240% due to the opening of the 2nd phase extension section, has been causing problems of recurrent congestion in a subway station building. A recurrent congestion in the station building becomes a factor to offend rail users and to reduce the efficiency of railway management. This study aims to establish the methodology for effect evaluation of information provided to rail users, and conducts a gate metering case study considering the congested conditions at a platform among the methodologies for effect evaluation. The metering effect evaluation by load factor was conducted through selecting the micro simulation and pedestrian simulation tool grafting a gate metering. As a result, it was confirmed that, if gate metering is performed, the service level and pedestrian density of a platform by load factor would improve. In other words, if metering is conducted at a platform, it is possible to control the load factor in the waiting space of a platform. Therefore, it was judged through this study that it is possible to set up the index for effect evaluation of information provided to manage congestion of rail users, and establish the methodology for effect evaluation of information provided to rail users through a program.