• Nuclear Engineering and Technology
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• 제52권1호
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• pp.211-221
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• 2020

One fundamental element of probabilistic safety assessment (PSA) is the initiating event (IE) analysis. Since IE frequencies can change over time, time-trend analysis is required to obtain optimized IE frequencies. Accordingly, such time-trend analyses have been employed to estimate industry-average IE frequencies for use in the PSAs of U.S. nuclear power plants (NPPs); existing PSAs of Korean NPPs, however, neglect such analysis in the estimation of IE frequencies. This article therefore provides the method for and results of estimating Korean industry-average IE frequencies using time-trend analysis. It also examines the effects of the IE frequencies obtained from this study on risk insights by applying them to recently updated internal events Level 1 PSA models (at-power and shutdown) for an OPR-1000 plant. As a result, at-power core damage frequency decreased while shutdown core damage frequency increased, with the related contributions from each IE category changing accordingly. These results imply that the incorporation of time-trend analysis leads to different IE frequencies and resulting risk insights. The IE frequency distributions presented in this study can be used in future PSA updates for Korean NPPs, and should be further updated themselves by adding more recent data.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.625-632
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• 2004

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Structural Engineering and Mechanics
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• 제83권2호
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• pp.179-193
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• 2022

The shear behaviour of reinforced concrete members has been studied over the past decades by various researchers, and it can be simulated by analysing shear panel elements which has been regarded as a basic element of reinforced concrete members subjected to in-plane biaxial stresses. Despite various experimental studies on shear panel element which have been conducted so far, there are still a lot of uncertainties related to what influencing factors govern the shear behaviour and affect failure mechanism in reinforced concrete members. To identify the uncertainties, a finite element analysis can be used, which enables to investigate the impact of specific variables such as the reinforcement ratio, the shear retention factor, and the material characteristics including aggregate interlock, tension stiffening, compressive softening, and shear behaviour at the crack surface. In this study, a non-linear probabilistic analysis was conducted on reinforced concrete panels using a finite element method optimized for reinforced concrete members and advanced sampling techniques so that probabilistic analysis can be performed effectively. Consequently, this study figures out what analysis methodology and input parameters have the most influence on shear behaviour of reinforced concrete panels.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.511-525
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• 2021

Aluminium outfitting is widely used in offshore platforms owing to its anti-corrosion ability and its light weight. However, various standards exist (ISO, NORSOK and EN) for the design of handrails used in offshore platforms, and different suppliers have different criteria. This causes great confusion for designers. Moreover, the design load required by the standards is not clearly defined or is uncertain. Thus, many offshore projects reference previous project details or are conservatively designed without additional clarification. In this study, all of the codes and standards were reviewed and analysed through prior studies, and data on variable factors that directly and indirectly affect the handrails applied to offshore platforms were analysed. A total of 50 handrail design load scenarios were proposed through deterministic and probabilistic approaches. To verify the proposed new handrail design load selection scenario, structural analysis was performed using SACS (offshore structural analysis software). This new proposal through deterministic and probabilistic approaches is expected to improve safety by clarifying the purpose of the handrails. Furthermore, the acceptance criteria for probabilistic scenarios for handrails suggest considering the frequency of handrail use and the design life of offshore platforms to prevent excessive design. This study is expected to prevent trial and error in handrail design while maintaining overall worker safety by applying a loading scenario suitable for the project environment to enable optimal handrail design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2259-2277
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• 2023

We propose a probabilistic fish growth model for smart aquaculture systems equipped with IoT sensors that monitor the ecological environment. As IoT sensors permeate into smart aquaculture systems, environmental data such as oxygen level and temperature are collected frequently and automatically. However, there still exists data on fish weight, tank allocation, and other factors that are collected less frequently and manually by human workers due to technological limitations. Unlike sensor data, human-collected data are hard to obtain and are prone to poor quality due to missing data and reading errors. In a situation where different types of data are mixed, it becomes challenging to develop an effective fish growth model. This study explores the unique characteristics of such a combined environmental and weight dataset. To address these characteristics, we develop a preprocessing method and a probabilistic fish growth model using mixed data sampling (MIDAS) and overlapping mixtures of Gaussian processes (OMGP). We modify the OMGP to be applicable to prediction by setting a proper prior distribution that utilizes the characteristic that the ratio of fish groups does not significantly change as they grow. We conduct a numerical study using the eel dataset collected from a real smart aquaculture system, which reveals the promising performance of our model.

• 스마트미디어저널
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• 제2권2호
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• pp.20-27
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• 2013

The concept of social media is top of the agenda for many business executives and decision makers, as well as consultants try to identify ways where companies can make profitable use of applications such as Netflix, Flixster. The social media is playing an increasingly important role as the information sources for customers making product choices etc. With the flourish of Web 2.0 technology, customer reviews are becoming more and more useful and important information resources for people to save their time and energy on purchasing products that they want. This paper proposes the Bayesian Probabilistic Classification algorithm to mine the social media review, and evaluates it by different splits and cross validation mechanism from the real data set. The explored study experimental results show the robustness and effectiveness of proposed approach for mining the social media review.

• 대한전기학회논문지:전력기술부문A
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• 제51권9호
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• pp.425-432
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• 2002

This Paper illustrates a method for evaluating nodal probabilistic production cost using the CMELDC. A new method for constructing CMELDC(CoMposite Power System Equivalent Load Duration Curve) has been developed by authors. The CMELDC can be obtained by convolution integral processing between the probability distribution functions of the fictitious generators outage capacity and the load duration curves at each load point. In general, if complex operating conditions are involved and/or the number of severe events is relatively large, Monte Carlo methods are more efficient. Because of that reason, Monte Carlo Methods are applied for the construction of CMELDC in this study. And IEEE-RTS 24 buses model is used as our case study with satisfactory results.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 추계학술대회 논문집(II)
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• pp.265-270
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• 2003

Though the probability of tunnel fire accident is very low, but critical fatalities are expected when it occurred. In this study the effect of critical safety parameters on tunnel fire accident are examined using probabilistic technique. Fire detection time, smoke spread velocity, passenger escape velocity, flash-over time, and emergency service arrival time are considered. In order to estimate the uncertainties of input parameters Monte Carlo simulation are used, and fatalities for each assumed accident scenarios are obtained as results. For the efficiency of iterative calculation PRA(Probabilistic Risk Analysis) code is developed in this study. As a result fire detection have large effect.

• 산업기술연구
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• 제22권B호
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• pp.231-240
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• 2002

The rational method of estimating peak flow is used largely for the simplicity. But the accuracy of rational method is not easy to estimate, because the rational method is analyzed by the deterministic point or view and the runoff coefficients of the rational method are proposed from other countries. In this study the rational method is analyzed by the probabilistic way to be a more reliable method. The runoff coefficient is regarded to parameter that changes the probabilistic rainfall to the peak flow. The runoff coeffient for each return period is analyzed to be a reliable index which is used to estimate the peak flow of ungauged natural catchments.

• 대한기계학회논문집A
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• 제28권3호
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• pp.289-295
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• 2004

Pressure tubes are major component of nuclear reactor, but only selected samples are periodically examined due to numerous numbers of tubes. Current in-service inspection result show there is high probability of flaw existence at uninspected pressure tube. Probabilistic analysis is applied in this study for the integrity assessment of uninspected pressure tube. All the current integrity evaluations procedures are based on conventional deterministic approaches. So it is expected that the results obtained are too conservative to perform a rational evaluation of lifetime. More realistic failure criteria, based on FAD are also proposed for the probabilistic analysis. As a result of this study failure probabilities for various conditions are calculated, and examined application of FAD and LBB concept.