• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.6
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• pp.72-79
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• 2015

An efficient and practical reliability evaluation method is proposed for the coastal structures in this paper. It is capable of evaluating reliability of real complicated coastal structures considering uncertainties in various sources of design parameters, such as wave and current loads, resistance-related design variables including Young's modulus and compressive strength of the reinforced concrete, soil parameters, and boundary conditions. It is developed by intelligently integrating the Latin Hypercube sampling (LHS), Monte Carlo simulation (MCS) and the finite element method (FEM). The LHS-based MCS is used to significantly reduce the computational effort by limiting the number of simulation cycles required for the reliability evaluation. The applicability and efficiency of the proposed method were verified using a caisson-type breakwater structure in the numerical example.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.263-269
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• 2017

'Goal Model' is core knowledge of 'Autonomic Control System' suggested to minimize human interference in system management. 'Autonomic Control System' performs 'Monitoring-Analysis-Plan-Execution', that is the four step of 'Autonomic Control', based on 'Goal Model'. Therefore, it is necessary to quantify achievement ratio of 'Goal Model' of target system. Thus, this paper present 'Probabilistic Evaluation of Goal Model' for methodology how to quantify achievement ratio of 'Goal Model'. It comprises 3-steps including 'Goal modeling and weighting', 'Goal model monitoring', 'Goal model evaluation and analysis'. Through these research, we provide core knowledge for 'Autonomic Control system' and it is possible to increase the reliability of system by evaluating 'Goal model' with applying weight. As case study, we apply 'Goal model' to a 'Smart IoT Kit' and we demonstrate the validity of the suggested research.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.578-579
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• 2007

The importance and necessity of conducting studies on area outage cost assessment have been increasingly important in recent years due to the competitive electricity market environment. The objective of operational issues would be to minimize the total area cost while satisfying all associated system constrains of each area[2]. This paper presents a methodology of the Area annual outage cost assessment by probabilistic reliability evaluation using TRELSS program for KEPCO system. The interrupted energy assessment rate (IEAR) is evaluated by macro approach that is using relations between GRDP and the electrical energy demand. The Expected Energy Not Supplied (EENS) of each area was evaluated using the Transmission Reliability Evaluation for Large-Scale Systems (TRELSS) Version 6_2, a program developed by EPRI are introduced in this paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.645-650
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• 2007

According to most studies, assessment of aging structure is trend to detect flaw size by sensor than using existing subjective evaluation by expert for objective evaluation. But Uncertainties existing in the sensor make difference between measured flaw size and actual flaw size, In this paper, Probability of Detection(POD) have been used to quantify the uncertainties and POD is updated by relationship measured flaw size and actual flaw size (Heasler, 1990), also we proposed probabilistic updating approach method to improve measurement accuracy(the difference of measured PDF and actual PDF) by using updated POD.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.137-146
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• 2008

Fault localization plays a significant role in enormous distributed system because it can identify root cause of observed faults automatically, supporting self-managing which remains an open topic in managing and controlling complex distributed systems to improve system reliability. Although many Artificial Intelligent techniques have been introduced in support of fault localization in recent research especially in increasing complex ubiquitous environment, the provided functions such as diagnosis and prediction are limited. In this paper, we propose fault localization for self-managing in performance evaluation in order to improve system reliability via learning and analyzing real-time streams of system performance events. We use probabilistic reasoning functions based on the basic Bayes' rule to provide effective mechanism for managing and evaluating system performance parameters automatically, and hence the system reliability is improved. Moreover, due to large number of considered factors in diverse and complex fault reasoning domains, we develop an efficient method which extracts relevant parameters having high relationships with observing problems and ranks them orderly. The selected node ordering lists will be used in network modeling, and hence improving learning efficiency. Using the approach enables us to diagnose the most probable causal factor with responsibility for the underlying performance problems and predict system situation to avoid potential abnormities via posting treatments or pretreatments respectively. The experimental application of system performance analysis by using the proposed approach and various estimations on efficiency and accuracy show that the availability of the proposed approach in performance evaluation domain is optimistic.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.25-34
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• 2015

Proposed equation is used many time in calculation of concrete compressive strength using the non-destructive testing at precision safety diagnosis. Most of proposed equation is suggested in abroad and have an error to estimate concrete compressive strength in the domestic. Therefor, proposed equation is low reliability to estimate concrete compressive and it has a significant effect in reliability of precision safety diagnosis. Nevertheless, It is possible to increase the reliability through a number of experiments from this problem that occurs in some localized part. This paper is proposed assessment formula of reliability related core compressive strength to increase the reliability. It is verified that reliability of proposed assessment formula is useful by probabilistic techniques. It is compared with each graphs of concrete compressive strength of proposed equation. It has been found that the present methods are very efficient.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.548-556
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• 2005

Reliability evaluation of power distribution system is very important to both power utilities and customers. It present the probabilistic number and duration of interruption such as failure rate, SATDI, SAIFI, and CAIDI. However, it has a fatal weakness at reliability index because of accuracy of failure rate. In this paper, the Time-varying Failure Rate(TFR) of power distribution system equipment is extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) in Korea. For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential(random failure) and Weibull(aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate(MfR) through the comparison between TFR and MFR

• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1297-1306
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• 2019

Probabilistic safety assessments (PSA) have been used for several decades to visualize the risk level of commercial nuclear power plants (NPPs). Since the role of a human reliability analysis (HRA) is to provide human error probabilities for safety critical tasks to support PSA, PSA quality is strongly affected by HRA quality. Therefore, it is important to understand the underlying limitations or problems of HRA techniques. For this reason, this study conducted a survey among 14 subject matter experts who represent the HRA community of domestic Korean NPPs. As a result, five significant HRA issues were identified: (1) providing a technical basis for the K-HRA (Korean HRA) method, and developing dedicated HRA methods applicable to (2) diverse external events to support Level 1 PSA, (3) digital environments, (4) mobile equipment, and (5) severe accident management guideline tasks to support Level 2 PSA. In addition, an HRA method to support multi-unit PSA was emphasized because it plays an important role in the evaluation of site risk, which is one of the hottest current issues. It is believed that creating such a catalog of prioritized issues will be a good indication of research direction to improve HRA and therefore PSA quality.

• Earthquakes and Structures
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• v.9 no.5
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• pp.937-956
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• 2015

Seismic isolation systems decouple structures from ground motions to protect them from seismic events. Seismic isolation devices have been implemented in many full-scale buildings and bridges because of their simplicity, economic effectiveness, inherent stability, and reliability. It is well known that the most uncertain aspect for obtaining the accurate responses of an isolated structure from seismic events is the seismic loading itself. It is needed to know the seismic response distributions of the isolated structure resulting from the randomness of earthquakes when probabilistic designing or probabilistic evaluating an isolated structure. Earthquake time histories are useful and often an essential element for designing or evaluating isolated structures. However, it is very challenging to gather the design and evaluation information for an isolated structure from many seismic analyses. In order to evaluate the seismic performance of an isolated structure, numerous nonlinear dynamic analyses need to be performed, but this is impractical. In this paper, the concept of the stochastic response database (SRD) is defined to obtain the seismic response distributions of an isolated structure instantaneously, thereby significantly reducing the computational efforts. An equivalent model of the isolated structure is also developed to improve the applicability and practicality of the SRD. The effectiveness of the proposed methodology is numerically verified.

• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.115-132
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• 2015

This paper presents a new method for seismic vulnerability assessment of buildings with reference to their operational limit state. The importance of this kind of evaluation arises from the civil protection necessity that some buildings, considered strategic for seismic emergency management, should retain their functionality also after a destructive earthquake. The method is based on the identification of experimental modal parameters from ambient vibrations measurements. The knowledge of the experimental modes allows to perform a linear spectral analysis computing the maximum structural drifts of the building caused by an assigned earthquake. Operational condition is then evaluated by comparing the maximum building drifts with the reference value assigned by the Italian Technical Code for the operational limit state. The uncertainty about the actual building seismic frequencies, typically significantly lower than the ambient ones, is explicitly taken into account through a probabilistic approach that allows to define for the building the Operational Index together with the Operational Probability Curve. The method is validated with experimental seismic data from a permanently monitored public building: by comparing the probabilistic prediction and the building experimental drifts, resulting from three weak earthquakes, the reliability of the method is confirmed. Finally an application of the method to a strategic building in Italy is presented: all the procedure, from ambient vibrations measurement, to seismic input definition, up to the computation of the Operational Probability Curve is illustrated.