• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.289-296
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• 2021

The Korean construction industry has been implementing G-SEED, a certification system that evaluates the environmental properties of buildings for the purpose of reducing environmental burdens such as energy and resource consumption and pollutant emissions. Also, creating a pleasant environment in general is one more purpose of G-SEED certification system. However, G-SEED certification in practice is difficult and time consuming due to the complexity of the certification acquisition process coupled with little economic consideration for the materials of each certification item. Therefore, in this study, we present a model for the optimal selection of materials and economic assessment using a genetic algorithm. The development of the model involves building a material database based on life-cycle costing (LCC) targeted at "Application of Indoor Air Pollutant Low Emission Material" from G-SEED. Next, the model was validated using a real non-residential building case study. The result shows an average cost reduction rate of 74.5 % compared with the existing cost. This model is expected to be used as an economically efficient tool in G-SEED.

• IE interfaces
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• v.9 no.2
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• pp.191-202
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• 1996

A variety of approaches on performance evaluation modeling have appeared in the technical literature for flexible manufacturing systems(FMS) which can be evaluated only through computer simulation. This study represents a comparative approach for FMS performance evaluation modeling based on reliability, availability and maintainability, and life cycle cost. The methodology proposed in this research includes the following three-step generative approaches. First, a static model to find the initial system configuration is considered under the assumption that the system availability is given as one (failure and maintenance are not considered), and in second step, a stochastic simulation is proposed to serve as a performance evaluation model for FMS with stochastic failure and repair time. In the last step, we developed a simulation modeling using a simulator, FACTOR/AIM to consider a variety of performance factors and dynamic behavior of FMS. Also the applicability and validity of the proposed approaches has been tested and compared through the results of a sample problem using computer programs and procedures developed in each step.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.905-908
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• 2008

The BTL project, 4 years since its operation, has benchmarked the PFI Project in Japan and has been introduced. Given the evaluation step to select a preferred bidder, in a technological factor, the basic plans are corrected and complemented, whereas in a price factor, the low price bidding system is being enforced. There is concern that how to select preferred bidders and how to operate project costs during operation and management period may be problematic. Thus, in this study, using the Analytic Hierarchy Process, the method of deciding the pribrity to select preferred bidders in an early stage of the project and the evaluation model to evaluate the validity of BTL project expenses in process of project enforcement are established. Targeting the group. composed of experts who have experiences in the BTL project. Then, the levelling of evaluation factors and grouping have been carried out as following: LCC analysis and disbursement for government including two more detailed factors.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.869-877
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• 2016

Necessity has compelled man to improve upon the art of tapping wind energy for power generation; an apt reliever of strain exerted on the non-renewable fossil fuel. The power generation in a Wind Farm (WF) depends on site and wind velocity which varies with time and season which in turn determine wind power modeling. It implies, the development of an accurate wind speed model to predict wind power fluctuations at a particular site is significant. In this paper, Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) time series model for wind speed is developed for a 99MW wind farm in the southern region of India. Because of the uncertainty in wind power developed, the economic viability and reliability of power generation is significant. Life Cycle Costing (LCC) method is used to determine the economic viability of WF generated power. Reliability models of WF are developed with the help of load curve of the utility grid and Capacity Outage Probability Table (COPT). ARIMA wind speed model is used for developing COPT. The values of annual reliability indices and variations of risk index of the WF with system peak load are calculated. Such reliability models of large WF can be used in generation system planning.

• Journal of the Korean Society of Safety
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• v.17 no.2
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• pp.63-68
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• 2002

Life Cycle Cost analysis technique is introduced to evaluate cost-effectiveness of two paint systems of steel bridges. The systems are a conventional paint system and a galvanized paint system. The all costs during safe lift such as initial cost repainting costs, disposal costs are considered for the lift cycle cost analysis. The NIST model is used and BridgeLCC 1.0 developed by the NST is utilized as the lift cycle cost analysis tool. It is concluded that, in spite of expensive initial cost, the durable paint system may be cost-effective compared with conventional paint system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.8
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• pp.313-321
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• 2006

This paper describes the overvoltage obtained by surge behavior analysis in testing underground distribution systems. Model systems consist of overhead distribution line and underground cable. Such model system considered various characteristics of actual distribution systems will be soon constructed at testing yard. Simulation is carried out under various states such as cable kinds, cable length, lightning wave and time, and branch circuits. Model is established by EMTP/ATPDraw. Line Constants are calculated by ATP_LCC. When the direct lightning surge strikes on conductor of overhead line, the overvoltage is calculated using EMTP/ATPDraw in many cases. Simulation results will be compared with real testing results at testing yard in the near future. The compared results will be used to establish protection methods in actual underground distribution systems.

• Journal of Applied Reliability
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• v.16 no.3
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• pp.238-244
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• 2016

Purpose: Domestic electric railway Regenerative Energy Storage System seriously affects the maintenance cost of the total operating expenses of nearly 60% of the total LCC (Life Cycle Cost) due to high dependence on foreign Leading company. Therefore by developing the system, it is important to lower the maintenance cost in the domestic supply. This study about the capacitor Reliability test and the purpose of this study is development electric railway Regenerative Energy Storage System. Methods: In case of, having a close relation between the temperature and the reaction rate, Accelerated Model was known that according to Arrhenius' law of chemical activity. If you apply this formula in using allowable temperature range of the capacitor can induce the Arrhenius empirical formula used in much Manufacture Fields. We evaluate the capacitors Leading company through the Arrhenius model. in order to providing a base for the localization of Ultra Capacitor. Conclusion: In this paper, we conducted a reliability test. And it was performed by the accelerated life test and Cycle Test with temperature and C-rate. and then MTBF and B10 life are estimated by analyzing the accelerated life test result. This is thought to need detailed study applying complex stress than about whether it matches the actual behavior in electric railway.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.6
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• pp.1-9
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• 2016

The paper aims at evaluating effects of preventive maintenance on life cycle cost(LCC) reduction of bridges. The preventive maintenance activities capable to delay bridge deteriorations can reduce overall maintenance costs and extend service life of a bridge by regularly providing maintenance activities and avoiding larger maintenance(repairs or rehabilitations) costs. Couple of prediction models were proposed in order to calculate LCC of a typical bridge: a health score model and repair rehabilitation cost model. In addition, the maintenance activities such as wash and painting were also suggested in order to consider effects of preventive maintenance in the analysis based on literature reviews. According to analysis results, new maintenance strategy(reactive maintenance + preventive maintenance) can save \0.5 billion per bridge for future life-cycle costs over 100 year analysis or \184 billion for entire HBMS(Highway Bridge Management System) inventory over 20 years. Small investments for preventive maintenance in improved bridge management can have a very significant return when considering the large bridge inventory.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.331-336
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• 2018

In this paper, the life cycle cost of the auxiliary power unit in the conventional 8200 series electric locomotive is evaluated and an effective life cycle cost reduction method is sought. For this, a life cycle cost evaluation model was proposed using IEC 60300-3-3 standard. As a result of analysis, material cost which accounted for a large percentage of preventive maintenance cost, accounted for 64% of total cost, and breakdown maintenance cost was as high as 27%. Except for the cost of preventive maintenance, the breakdown maintenance cost ratio was the highest. In order to reduce the LCC of the auxiliary power unit(APU) of the 8200 series in the future, it is necessary to reduce the material cost in case of development and to secure the high reliability according to the parts manufacturing so as to minimize the maintenance cost.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.