• Journal of the Korea Concrete Institute
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• v.11 no.6
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• pp.89-100
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• 1999

Service life of concrete structures that are exposed to the environmental attack is largely influenced by the corrosion of reinforcing bare due to the chloride contamination. Chloride ions penetrate continuously into concrete from the environment, and chloride diffusion velocity is governed by a mechanical steady stage. In this study, a method is developed to predict corrosion initiation of reinforcing bars in the sea-shore structures, based on governing equations that take into account the diffusing of chloride ions and a mechanical steady state. As a result of this study, Corrosion Prediction System (CPS) is developed, and it can be used to determine an optimal time for repair and rehabilitation actions need to be taken. Futhermore, CPS assists the concrete mixing structures by predicting of chloride concentrations in concrete mixture, exposed to salt concentrations and service environment.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.102-111
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• 2021

Maintainability is a major design parameter that includes availability as well as reliability in a RAM (reliability, availability, maintainability) analysis, and is an index that must be considered when developing a system. There is a lack of awareness of the importance of predicting and analyzing maintainability; therefore, it is dependent on past-experience data. To improve the utilization rate, maintainability must be managed as a key indicator to meet the user's requirements for failure maintenance time and to reduce life-cycle costs. To improve the maintainability-prediction accuracy in the detailed design stage, we present a maintainability-prediction method that applies Method B of the Military Standardization Handbook (MIL-HDBK-472) Procedure V, as well as a Korean maintainability-prediction software package that reflects the system complexity.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.100-106
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• 2012

Recently, the demand to acquire and improve durability performance has steadily risen in rubber components design. In design process of a rubber component, an analytical prediction is the most effective way to improve fatigue life. Existing methods of analytical estimation have mainly used an equation for fatigue life obtained from fatigue test data. However, such formula is rarely used due to costs and time required for fatigue testing, as well as randomness of rubber materials. In this paper, we describe fatigue life estimation of rubber component using only the results from a relatively simple tearing test. We estimated fatigue life of the Janggu type fatigue specimen and the automotive motor mount, and evaluated reliability of the proposed method by comparing the estimated values with actual test results.

• Elastomers and Composites
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• v.54 no.1
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• pp.70-76
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• 2019

The function and purpose of the marine rubber fender, to prevent the damage of the ship and the mooring while the ship is being attached to the pier. However, maintenance of the fender after installation is not enough, because it is generally handled as an attachment facility. Estimation the life of a marine rubber fender is important in the maintenance of a port. When manufacturers design and produce marine rubber fenders, they do so according to various conditions such as the reaction force acting on the hull and docking vessel and deformation after absorbing the kinetic energy of the ship. In this study, a method for predicting and evaluating service life from the product design and development stage was established, in order to evaluate the durability of the marine rubber fenders. The SSp-300H and HSP-300H models were used to predict the service life. The method developed in this study, is expected to predict the service life of the marine rubber fender accurately and in a comparatively shorter time, thereby contributing to the evaluation standard and quality stability of the product.

• Corrosion Science and Technology
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• v.12 no.5
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• pp.209-214
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• 2013

In the industry, accelerated corrosion test is used for the life time prediction. When anti-corrosion test proceeds in real environments, it is difficult that we predict and evaluate the corrosion life time because of the long test time such as 10 years or more time. Accelerated corrosion test and Salt spray test are able to test corrosion life time of products in the laboratory instead of outdoor corrosion test. Experimental procedure is selected for the corrosion standard specimen, exposure of the specimens, measurements of the mass loss and evaluating the mass loss data. As a result, the acceleration factor of the accelerated corrosion test to the outdoor corrosion test is 414.8. Therefore we can predict the corrosion life time of carbon steel during a short time period.

• Journal of Applied Reliability
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• v.14 no.4
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• pp.230-235
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• 2014

The failure modes of pneumatic directional control valves include leakage, wear of the spool seal, and sticking of the spool. Among them, the main failure mode of the valve is leakage. The leakage is caused by the wear of the spool seal. However, due to the characteristics of the seal material, the leakage rate is fluctuated a lot rather than constantly increased over time. If life analysis is performed using the first time data of leakage failure, predicted life cycles can be different from the real life cycles. This paper predicts life cycles of the pilot pneumatic directional control valve based on the three point moving average which considers the average of the fluctuating leakage rate.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.419-430
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• 2014

An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.739-744
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• 2009

Rail-pad is an important and readily replaceable component of a railway track, as it is the elastic layer between the rail and the sleeper. Characteristics and useful lifetime prediction of rail-pad was very important in design procedure to assure the safety and reliability. In this paper, the degradation of rail pad properties as a function of their in-service life is studied with a view of developing a technique for predicting the optimum period of track maintenance with regard to pad replacement. In order to investigate the useful lifetime, the accelerate test were carried out. Accelerated test results changes as the threshold are used for assessment of the useful life and time to threshold value were plotted against reciprocal of absolute temperature to give the Arrhenius plot. By using the acceleration test, several useful lifetime prediction for rail-pads were proposed.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.739-742
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• 1999

A reinforcement corrosion prediction model was proposed using the results from accelerated testing and mathematical equation from the Fick's 2nd law for chloride-induced corrosion of reinforcement in concrete. The input data included the chloride concentration, mix characteristics of concrete, and environmental conditions. This model can be used to predict the chloride concentration pertaining to corrosion time and loading age for marine concrete structures. This model can also be used to predict the service life.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.