• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.1075-1084
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• 2005

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network(PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Improved probabilistic neural network was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment (DDA) algorithm. The conventional PNN and the PNN with DDA algorithm(IPNN) were applied to predict the compressive strength of concrete using actual test data of two concrete companies. IPNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.649-656
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• 2011

This study is a numerical representative modelling analysis for applying the process that unravels networks between cells in genetics to Network of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extend them to genetic representation data in the method of network modelling in informatics.

• Wind and Structures
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• v.30 no.4
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• pp.405-421
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• 2020

Quayside container cranes are important delivery machineries located in the most frontiers of container terminals, where strong wind attacks happen occasionally. Since the previous researches on quayside container cranes mainly focused on the mean wind load and static response characteristics, the fluctuating wind load and dynamic response characteristics require further investigations. In the present study, the aerodynamic wind loads on quayside container cranes were obtained from wind tunnel tests. The probabilistic and spectral models of the fluctuating aerodynamic loads were established. Then the joint probabilistic distributions of dynamic wind-induced responses were derived theoretically based on a series of Gaussian and independent assumption of resonant components. Finally, the results were validated by time domain analysis using wind tunnel data. It is concluded that the assumptions are acceptable. And the presented approach can estimate peak dynamic sliding force, overturning moments and leg uplifts of quayside container cranes effectively and efficiently.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.5
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• pp.185-190
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• 2006

The security analysis relates to the ability of the electric systems to survive sudden disturbances such as electric short circuits or unanticipated loss of system elements. It is composed of both steady state and dynamic security analyses, which are not two separate issues but should be considered together. In steady state security analysis including voltage security analysis, the analysis checks that the system is operated within security limits by OPF (optimal power flow) after the transition of a new operating point. On the other hand, dynamic security analysis deals that the transition will lead to an acceptable operating condition. Transient stability, which is the ability of power systems to maintain synchronism when subjected to a large disturbance, is a principal component in dynamic security analysis. Usually any loss of synchronism will cause additional outages. They make the present steady state analysis of the post-contingency condition inadequate for unstable cases. This is the reason of the need for dynamics of systems. Probabilistic criterion can be used to recognize the probabilistic nature of system components and shows the possibility of system security. A comprehensive conceptual framework for probabilistic static and dynamic assessment is presented in this paper. The simulation results of the Western System Coordinating Council (WSCC) system compare an analytical method with Monte-Carlo simulation (MCS). Also, a case study of the extended IEEE Reliability Test System (RTS) shows the efficiency of this approach.

• Journal of Welding and Joining
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• v.23 no.6
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• pp.61-66
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• 2005

A probabilistic approach for evaluating failure risk is suggested in this paper. Probabilistic fracture analyses were performed for a pressurized pipe of a Cr-Mo steel reflecting variation of material properties at high temperature. A crack was assumed to be located along the weld fusion line. Probability density functions of major variables were determined by statistical analyses of material creep and creep crack growth data measured by the previous experimental studies by authors. Distributions of these variables were implemented in Monte Carlo simulation of this study. As a fracture parameter for characterizing growth of a fusion line crack between two materials with different creep properties, $C_t$ normalized with $C^*$ was employed. And the elapsed time was also normalized with tT, Resultingly, failure probability as a function of operating time was evaluated fur various cases. Conventional deterministic life assessment result was turned out to be conservative compared with that of probabilistic result. Sensitivity analysis for each input variable was conducted to understand the most influencing variable to the analysis results. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.653-659
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• 2002

This paper describes a probabilistic fracture mechanics(PFM) analysis based on Monte Carlo(MC) simulation. In the analysis of CANDU pressure tube, the depth and aspect ratio of an initial semi-elliptical surface crack, a fracture toughness value and delayed hydride cracking(DHC) velocity are assumed to be probabilistic variables. As an example, some failure probabilities of piping and CANDU pressure tube are calculated using MC method with the stratified sampling MC technique, taking analysis conditions of normal operations. In the stratified MC simulation, a sampling space of probabilistic variables is divided into a number of small cells. For the verification of analysis results, a comparison study of the PFM analysis using other commercial code is carried out and a good agreement was observed between those results.

• Computers and Concrete
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• v.16 no.2
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• pp.191-207
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• 2015

It is generally accepted that, in the interest of safety, it is essential to provide a minimum level of flexural ductility, which will allow energy dissipation and moment redistribution as required. If one wishes to be uniformly conservative across all of the design variables, curvature ductility and moment redistribution factor should be calculated using a probabilistic method, as is the case for other design parameters in reinforced concrete mechanics. In this study, simple expressions are derived for the evaluation of curvature ductility and moment redistribution factor, based on the concept of demand and capacity rotation. Probabilistic models are then derived for both the curvature ductility and the moment redistribution factor, by means of central limit theorem and through taking advantage of the specific behaviour of moment redistribution factor as a function of curvature ductility and plastic hinge length. The Monte Carlo Simulation (MCS) method is used to check and verify the results of the proposed method. Although some minor simplifications are made in the proposed method, there is a very good agreement between the MCS and the proposed method. The proposed method could be used in any future probabilistic evaluation of curvature ductility and moment redistribution factors.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1146-1156
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• 2021

Single-unit probabilistic safety assessment (SUPSA) has complex Boolean logic equations for accident sequences. Multi-unit probabilistic safety assessment (MUPSA) model is developed by revising and combining SUPSA models in order to reflect plant state combinations (PSCs). These PSCs represent combinations of core damage and non-core damage states of nuclear power plants (NPPs). Since all these Boolean logic equations have complemented gates (not gates), it is not easy to generate exact Boolean solutions. Delete-term approximation method (DTAM) has been widely applied for generating approximate minimal cut sets (MCSs) from the complex Boolean logic equations with complemented gates. By applying DTAM, approximate conditional core damage probability (CCDP) has been calculated in SUPSA and MUPSA. It was found that CCDP calculated by DTAM was overestimated when complemented gates have non-rare events. Especially, the CCDP overestimation drastically increases if seismic SUPSA or MUPSA has complemented gates with many non-rare events. The objective of this study is to suggest a new quantification method named probability subtraction method (PSM) that replaces DTAM. The PSM calculates accurate CCDP even when SUPSA or MUPSA has complemented gates with many non-rare events. In this paper, the PSM is explained, and the accuracy of the PSM is validated by its applications to a few MUPSAs.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.849-861
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• 2021

This paper aims to introduce the basic concept of probabilistic record linkage and its statistical framework, and describe the specific process and principle of performing it using a real example from Statistics Korea. First, we briefly describe the deterministic record linkage and compare it with probabilistic record linkage. We introduce the Fellegi-Sunter model framework for record linkage and the related paprameters: m-probability, u-probability, matched weight and decision rule. Finally, we show the detailed process of record linkage under Fellegi-Sunter model framework and evaluate the record linkage results, using sample data from the registered-based census and Population and Housing Census survey in Statistics Korea.