• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.25-34
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• 1997

This study presents a new approach for expert opinion elicitation process to assess an uncertainty inherent in accident management. The need to work with rare event and limited data in accident management leads analysis to use expert opinions extensively. Unlike the conventional approach using point-valued probabilities, the study proposes the concept of fuzzy probability to represent expert opinion. The use of fuzzy probability has an advantage over the conventional approach when an expert's judgment is used under limited dat3 and imprecise knowledge. The study demonstrates a method of combining and propagating fuzzy probabilities. finally, the proposed methodology is applied to the evaluation of the probability of a bottom head failure for the flooded case in the Peach Bottom BWR nuclear power plant.

• Smart Structures and Systems
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• v.24 no.2
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• pp.209-221
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• 2019

The classical Kalman filter (KF) provides a practical and efficient way for state estimation. It is, however, not applicable when the external excitations applied to the structures are unknown. Moreover, it is known the classical KF is only suitable for linear systems and can't handle the nonlinear cases. The aim of this paper is to extend the classical KF approach to circumvent the aforementioned limitations for the joint estimation of structural states and the unknown inputs. On the basis of the scheme of the classical KF, analytical recursive solution of an improved KF approach is derived and presented. A revised form of observation equation is obtained basing on a projection matrix. The structural states and the unknown inputs are then simultaneously estimated with limited measurements in linear or nonlinear systems. The efficiency and accuracy of the proposed approach is verified via a five-story shear building, a simply supported beam, and three sorts of nonlinear hysteretic structures. The shaking table tests of a five-story building structure are also employed for the validation of the robustness of the proposed approach. Numerical and experimental results show that the proposed approach can not only satisfactorily estimate structural states, but also identify unknown loadings with acceptable accuracy for both linear and nonlinear systems.

• East Asian mathematical journal
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• v.31 no.5
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• pp.707-716
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• 2015

We consider a queueing system with N-limited nonstop forwarding. In this queueing system, when the server breaks down, up to N customers can be serviced during the repair time. It can be used to model an assembly line consisting of several automatic stations and a manual backup station. Within the framework of $Geo^X/D/1$ queue, the matrix analytic approach is used to obtain the performance of the system. Some numerical examples are provided.

• Journal of Microbiology and Biotechnology
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• v.7 no.1
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• pp.1-7
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• 1997

The efficient manufacture of fermented dairy products on an industrial scale requires a supply of reliable starter cultures with properties suited to desired product specifications. These cultures must be backed by relevant research and development activities. This article describes the issues involved in establishing a centre to provide starter culture R & D for a group of independent cheese manufacturing companies, and discusses a strategic approach to the management of starter cultures.

• Smart Structures and Systems
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• v.12 no.6
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• pp.619-640
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• 2013

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.

• Korean Journal of Child Studies
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• v.33 no.2
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• pp.13-35
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• 2012

This study investigated the contents and methods of science education classes based on the largely constructivist approach of pre-service early childhood teachers. The subjects of this study consisted of 8 junior students from the Early Childhood department and for reference data, reflective journals, interviews, activity planning sheets, recordings of trial lessons, and lesson analysis were used. The results of this study were as follows. First, changes in key points and contents for children science education were found, and reflective journals, interviews, activity planning sheets, recording of trial lessons, and lesson analysis clearly supported these results. Second, the actual changes in the constructivist approach to children's science education had a great impact upon the individual characters of the pre-service early childhood teachers. However, with the study period being limited to only one semester, it was found that the potential of this study to lead to any practical changes was simlilarly limited.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• 전기의세계
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• v.21 no.4
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• pp.39-44
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• 1972

This paper describes a new approach for minimizing working memory spaces without loosing too much amount of computing time in the analysis of power system faults. This approach requires the decomposition of alrge power system into several small groups of subsystems, forms individual bus impedance matrics, store them in the auxiliary memory, later assembles them to the original total system by algorithms. And also the approach uses techniques for diagonalizing primitive impedances and expanding the system bus impedance matrices by adding a fault bus. These scheme ensures a remarkable savings of working storage and continous computations of fault currents and voltages with the voried fault locations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1612-1620
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• 2004

This study presents methods to estimate elastic-plastic crack opening displacement (COD) fur circumferential through-wall cracked pipes for the Leak-Before-Break (LBB) analysis of pressurized piping. Proposed methods are based not only on the GE/EPRI approach but also on the reference stress approach. For each approach, two different estimation schemes are given, one for the case when full stress-strain data are available and the other fur the case when only yield and ultimate tensile strengths are available. For the GE/EPRI approach a robust way of determining the Ramberg-Osgood (R-O) parameters is proposed, not only fur the case when detailed information on full stress-strain data is available but also for the case when only yield and ultimate tensile strengths are available. The COD estimates according to the GE/EPRI approach, using the R-O parameters determined from the proposed R-O fitting procedures, generally compare well with the published pipe test data. For the reference stress approach, the COD estimates according to the method based on both full stress-strain data and limited tensile properties are in good agreement with pipe test data. In conclusion, experimental validation given in the present study provides sufficient confidence in the use of the proposed method to practical LBB analyses even though when information on material's tensile properties is limited.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.187-200
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• 1998

This paper presents an original approach for solving short-term power scheduling in extended power system with two fuels in a unit and a limited fuel using Lagrangian relaxations. The underlying model incorporates the full set of costs and constraints including setup, production, ramping, and operational status, and takes the form of a mixed integer nonlinear control problem. Moreover, the mathematical model developed includes two fuels in a unit and a limited fuel, regulation reserve requirements of prespecified group of units. Lagrangian relaxation is used to disaggregate the model by generator into separate subproblems which are then solved with a nested dynamic program including empirical knowledges. The strength of the methodology lies partially in its ability to construct good feasible solutions from information provided by the dual. Thus, the need for branch-and-bound is eliminated. In addition, the inclusion of two fuels in a unit and a limited fuel provides new insight into the limitations of current techniques. Computational experience with the proposed algorithm indicates that Problems containing up to 23 units including 8 unit used two fuels and 24 time periods can be readily solved in reasonable times. Duality gaps of less than 4％ were achieved.