• Proceedings of the KSR Conference
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• 2011.05a
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• pp.988-992
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• 2011

The buckling characteristics of the continuous welded rail track(CWR) is uncertainly varied by many influence factors, such as rail temperature, operating conditions of a train and maintenance of the track etc. Therefore, applying the probabilistic approach method is essential to rationally consider uncertainty and randomness of the various parameters that affect the track buckling. In this study, the probabilistic approach analysis was carried out and the results were compared with the deterministic approach using the buckling probability evaluation system of CWR tracks developed by our research team. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of the CWR tracks based on failure probability and can be used as a tool for decision making in track design, maintenance and operating etc.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.444-449
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• 2009

This paper introduces a method to establish performance criteria of the in-house power supply system in nuclear power plants. The performance criteria of the system is presented in terms of the number of function failures and amount of the out-of-service time that can be allowed commensurate with the probabilistic safety assessment results of the nuclear power plants. To obtain the performance criteria such as reliability and availability, the functions of the system were analyzed and probabilistic assessment results were utilized. This method provides quantitative guidelines in selecting and monitoring system functions to determine an adequate level of maintenance quality in order to ensure the probabilistic goals for the safety of the nuclear power plants.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.804-806
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are new iy defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.48-55
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• 2016

The assessment and prediction of service life of a structure are usually under uncertainty so that rational probabilistic concepts and methods have to be applied. Based on these rational assessment and prediction, optimum maintenance strategies to minimize the life-cycle cost and/or maximize the structural safety can be established. The service life assessment and prediction considering maintenance actions generally includes effects of maintenance types and times of the structural components on the service life extensions of structural system. Existing researches on the service life management have revealed the appropriate system modeling considering the correlation among the components is required for system reliability analysis and probabilistic service life estimation. However, the study on correlation among the maintenance actions is still required. This paper deals with such a study for more effective and efficient service life management. In this paper, both the preventive and essential maintenances are considered for the extended service life estimation and management.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1507-1513
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• 2010

The $CO_2$ emission can be decreased due to freedom of generator maintenance scheduling(GMS). This paper proposes assessment of $CO_2$ emission considering generator maintenance scheduling(GMS) and evaluates effect of the GMS on $CO_2$ emission. And also, this paper assesses the $CO_2$ emission and the probabilistic production cost simulation of nuclear and thermal power generators considering operation of hydro and pumped generator. The minimum reliability criterion level satisfied production cost minimization function model is used in this paper. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system in Korea in 2010.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.8-15
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• 2010

A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.

• Computers and Concrete
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• v.17 no.4
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• pp.499-521
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• 2016

In this paper, a probabilistic- and finite element-based approach to evaluate and predict the lifetime performance of reinforced concrete (RC) bridges undergoing various maintenance actions is proposed with the time-variant system reliability being utilized as a performance indicator. Depending on their structural state during the degradation process, the classical maintenance actions for RC bridges are firstly categorized into four types: Preventive type I, Preventive type II, Strengthening and Replacement. Preventive type I is used to delay the onset of steel corrosion, Preventive type II can suppress the corrosion process of reinforcing steel, Strengthening is the application of various maintenance materials to improve the structural performance and Replacement is performed to restore the individual components or overall structure to their original conditions. The quantitative influence of these maintenance types on structural performance is investigated and the respective analysis modules are written and inputted into the computer program. Accordingly, the time-variant system reliability can be calculated by the use of Monte Carlo simulations and the updated the program. Finally, an existing RC continuous bridge located in Shanghai, China, is used as an illustrative example and the lifetime structural performance with and without each of the maintenance types are discussed. It is felt that the proposed approach can be applied to various RC bridges with different structural configurations, construction methods and environmental conditions.

• International Journal of Highway Engineering
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• v.8 no.2 s.28
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• pp.49-54
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• 2006

The purpose of this study was to determine the effect of expansion joint spacing (slab size) on the life cycle costs of owning Portland Cement Concrete (PCC) airfield pavements. Previous research has shown that slab size has a statistically significant impact on pavement performance. A probabilistic life cycle cost analysis was performed to determine if the effect of slab size on pavement performance would affect the total cost of ownership of PCC pavements. Data from 48 Pavement Condition Index (PCI) inspections of military and civilian airfields were used to develop probability-of-distress-by-condition curves, which were then used to develop probabilistic cost-of-repair-by-condition curves. A present worth life cycle cost analysis was then performed for various slab sizes, using construction costs, rehabilitation costs, and maintenance costs. Maintenance costs were determined by assuming a condition deterioration rate appropriate for each slab size and applying the cost-by-condition curves. The probabilistic cost-of-repair-by-condition curves indicated that smaller slabs are more expensive to repair on a unit cost basis. Life cycle cost analysis showed that larger slabs have a higher total cost of ownership than smaller slabs due to a faster rate of deterioration.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.4
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• pp.109-120
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• 2001

Live load data were collected with a systematic manner from a survey of a refrigeration stores. Using the collected floor live load survey data, the basic statistics, a histogram of the uniformly distributed loads, and the equivalent uniformly distributed loads are computed for various structural members. Based on the above results, the maximum values of a combined live loads during the design life have been estimated and compared with current design live loads. The ultimate goals of this study are to develop probabilistic live load models to analyze survey data of domestic refrigeration stores, and to propose design live loads for structural types.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.5
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• pp.601-610
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• 2018

The purpose of this paper is to establish a new optimum Generator Maintenance Scheduling(GMS) considering renewable energy generator. In this paper, the total renewable energy generation is estimated using hourly capacity factor of renewable energy generator. The GMS was optimized with the objective function of maximizing the minimum reserve rate, minimizing the probabilistic production cost, minimizing the loss of load expectation, and minimizing $CO_2$ emissions. In the case study of this paper, GMS considering renewable energy and GMS not considering renewable energy are shown by each objective function. And it shows scenarios of the reliability, the environmental and economical factors when two nuclear power plants inputted and ten coal thermal power plants shut downed respectively.