• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.846-855
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• 2020

A loose part monitoring system is used to detect unexpected loose parts in a reactor coolant system in a nuclear power plant. It is still necessary to develop a new methodology for the localization and mass estimation of loose parts owing to the high estimation error of conventional methods. In addition, model-based diagnostics recently emphasized the importance of a model describing the behavior of a mechanical system or component. The purpose of this study is to propose a new localization and mass-estimation method based on finite element analysis (FEA) and optimization technique. First, an FEA model to simulate the propagation behavior of the bending wave generated by a metal sphere impact is validated by performing an impact test and a corresponding FEA and optimization for a downsized steam-generator structure. Second, a novel methodology based on FEA and optimization technique was proposed to estimate the impact location and mass of a loose part at the same time. The usefulness of the methodology was then validated through a series of FEAs and some blind tests. A new feature vector, the cross-correlation function, was also proposed to predict the impact location and mass of a loose part, and its usefulness was then validated. It is expected that the proposed methodology can be utilized in model-based diagnostics for the estimation of impact parameters such as the mass, velocity, and impact location of a loose part. In addition, the FEA-based model can be used to optimize the sensor position to improve the collected data quality in the site of nuclear power plants.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.4
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• pp.62-72
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• 2013

To operate an automatic picking system in distribution center with high precision and high dynamics, this paper presents a robust control scheme of a linear induction motor (LIM) using the mass estimation and disturbance force observer. The force disturbance which gives a direct influence on the control performance of LIM is estimated in real-time through the disturbance observer and compensated by a feedforward manner. To get a satisfactory performance even under the mass variation by reducing the disturbance force due to the mismatched mass during the speed transient such as the acceleration and deceleration periods, a mass estimation algorithm is proposed. A Simulink model for LIM is developed and the validity of the proposed scheme is verified through the comparative simulation studies using Matlab - Simulink.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.716-724
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• 2008

In the case of subsea tunnels, hydro-mechanical coupled analysis is necessary for an exact design and construction. The consideration of the overstretched ground condition is also required because they are usually located at the great depth unlike the usual tunnels. Many researches have been performed on the estimation of relaxed rock mass height. However, there have been no researches on the estimation of relaxed rock mass height under overstretched ground conditions. In this study, therefore, hydro-mechanical coupled analyses were performed under the overstressed ground conditions and the relaxed rock mass heights were estimated based on the contour of the local safety factor around a tunnel.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.301-303
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• 2008

Tuning of the speed controller in the linear servo applications needs the accurate information of a mover mass including a load mass. Therefore this paper proposes the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) applied at the vertical axis by using the recursive Least-Squares estimation algorithm. First, this paper derives the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system used at the vertical axis. Results obtained by the Matlab/Simulink simulation show that the mass of a PMLSM applied at the vertical axis can be accurately estimated both at no-load and at load.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.5
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• pp.541-550
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• 2008

In this investigative study, the unit mass discharge for the major water quality parameters such as flowrate, SS, BOD, CODmn, CODcr, TN, TP from textile spinning/weaving industry nearby Nakdong river basin was estimated. To represent the respective industries, three companies from hundreds of textile spinning/weaving industries located in Nakdong river basin was carefully selected based on its manufacturing goods, flowrate and location for the estimation of unit mass discharge based on unit operation and process. There was a drastic decrease of unit mass discharge estimation between influents and effluents of water quality parameters, which represents the removal capacity of wastewater treatment plant. With the advent of new regulation on the imposed payment proportional to the total amount of pollutants discharge into the water body, the concept of cleaner production technology should be employed in the unit operation/process in wastewater treatment plant as well as textile manufacturing procedure to minimize the levy on the pollutants discharge. Unit mass discharge estimations of unit process (estimated in this study) in major water quality parameters (SS, BOD, COD, TN and TP) based on land were similar to those of composite process (estimated by National Institute of Environmental Research). But the unit mass discharge estimations of unit process in BOD and CODmn based on total sale were much higher than those of composite one while in SS, TN and TP similar to each other. For the detailed estimation of the imposed payment, unit mass estimation based on unit process should be further emphasized.

• Journal of The Korean Association For Science Education
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• v.21 no.1
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• pp.76-88
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• 2001

This study explored people's accuracy and methods of estimating some base physical quantities, i.e. length, mass, time and temperature. A total of 40 members, ranging from freshmen to professors, of a physics education department of a local university were asked to make two different kinds of estimations, intuitive and operational, on two sets of objects. For intuitive estimation, they were asked to make estimations on four given objects (length - wood chopsticks, mass - rubber eraser, time electric fan, temperature - water in a cup) as soon as they faced with the objects, usually within a few seconds of seeing. For operational estimation, they were allowed to make estimations on a different set of objects (length - plastic rod, mass - lock, time - simple pendulum, temperature - water in a cup) with enough time and they could apply various available methods (e.g. using pencil to estimate the object's length, counting their own pulse rate to estimate time) for the estimation. The findings of this study can be summarized as follows: (1) for length, mass and temperature the intuitive estimations were better performed while for the time estimation the result was the reverse; (2) there was no positive relationship between the amount of physics experience and the accuracy of the estimation; (3) in general, people's accuracy of the length estimation was best performed while their mass estimation was worst performed; (4) people used their own various methods for estimation, esp. using nearby objects around them and applying mental units which have convenient values (e.g. 30cm, 50cm, 1kg, 1 Keun, 1 second).

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.1-6
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• 2012

The accurate information of mass properties is required for the precise control of the spacecraft. The mass properties, mass and inertia, are changeable by some reasons such as consumption of propellant, deployment of solar panel, sloshing, environmental effect, etc. The gyro-based attitude data including noise and bias reduces the control accuracy so it needs to be compensated for improvement. This paper introduces a real-time inertia estimation method for the attitude determination of STSAT-3, Korea Science Technology Satellite. In this method we first filter the gyro noise with the Extended Kalman Filter(EKF), and then estimate the moment of inertia by using the filtered data from the EKF based on the Recursive Least Square(RLS).

• Smart Structures and Systems
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• v.4 no.3
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• pp.279-290
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• 2008

The modeling and parameter estimation of a damped one-degree-of-freedom mass-spring system is examined. This paper presents a method for estimating the system parameters (damping coefficients and natural frequency) from measured free-vibration motion of a system that is modeled to include both subcritical viscous damping and kinetic Coulomb friction. The method applies a commercially available least-squares curve-fitting software function to fit the known solution of the equations of motion to the measured response. The method was tested through numerical simulation, and it was applied to experimental data collected from a laboratory mass-spring apparatus. The mass of this apparatus translates on linear bearings, which are the primary source of light inherent damping. Results indicate that the curve-fitting method is effective and accurate for both perfect and noisy measurements from a lightly damped mass-spring system.