• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2835-2843
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• 2023

After an emergency shutdown of a lead-bismuth fast reactor, thermal stratification occurs in the upper Plenum, which negatively impacts the integrity of the reactor structure and the residual heat removal capacity of natural circulation flow. The research on thermal stratification of reactors has mainly been conducted using an experimental method, a system program, and computational fluid dynamics (CFD). However, the equipment required for the experimental method is expensive, accuracy of the system program is unpredictable, and resources and time required for the CFD approach are extensive. To overcome the defects of thermal stratification analysis, a high-precision full-order thermal stratification model based on CFD technology is prepared in this study. Furthermore, a reduced-order model has been developed by combining proper orthogonal decomposition (POD) with Galerkin projection. A comparative analysis of thermal stratification with the proposed full-order model reveals that the reduced-order thermal stratification model can well simulate the temperature distribution in the upper plenum and rapidly elucidate the thermal stratification interface characteristics during the lead-bismuth fast reactor accident. Overall, this study provides an analytical tool for determining the thermal stratification mechanism and reducing thermal stratification.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.9
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• pp.660-669
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• 1987

Routh approximation method is the most computationally attractive. But this method may cause time-response error because this method does not match the time-response directly. In this paper a new mixed method for obtaining stable reduced-order models for high-order continuous-time systems is proposed. It makes use of the advantages of the Routh approximation method and the Minimization of Integral Squared Error(MISE) criterion approach. In this mixed method the characteristic polynomial of the reduced-order model is first obtained from that of original system by using the Auxiliary Denominator Polynomial(ADP). The numerator polynomial is then determined so as to minimize the intergral squared-error of unit step responses. The advantages of the propsed method are that the reduced models are always stable if the original system are stable and the frequency domain and time domain characteristic of the original system will be preserved in the reduced models.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.41-54
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• 2015

In this article, we propose nonconcave penalties on a reduced-rank regression model to select variables and estimate coefficients simultaneously. We apply HARD (hard thresholding) and SCAD (smoothly clipped absolute deviation) symmetric penalty functions with singularities at the origin, and bounded by a constant to reduce bias. In our simulation study and real data analysis, the new method is compared with an existing variable selection method using $L_1$ penalty that exhibits competitive performance in prediction and variable selection. Instead of using only one type of penalty function, we use two or three penalty functions simultaneously and take advantages of various types of penalty functions together to select relevant predictors and estimation to improve the overall performance of model fitting.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.476-479
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• 2008

Understanding the dynamics of proteins is essential to gain insight into biological functions of proteins. The protein dynamics is delineated by conformational fluctuation (i.e. thermal vibration), and thus, thermal vibration of proteins has to be understood. In this paper, a simple mechanical model was considered for understanding protein's dynamics. Specifically, a mechanical vibration model was developed for understanding the large protein dynamics related to biological functions. The mechanical model for large proteins was constructed based on simple elastic model (i.e. Tirion's elastic model) and model reduction methods (dynamic model condensation). The large protein structure was described by minimal degrees of freedom on the basis of model reduction method that allows one to transform the refined structure into the coarse-grained structure. In this model, it is shown that a simple reduced model is able to reproduce the thermal fluctuation behavior of proteins qualitatively comparable to original molecular model. Moreover, the protein's dynamic behavior such as collective dynamics is well depicted by a simple reduced mechanical model. This sheds light on that the model reduction may provide the information about large protein dynamics, and consequently, the biological functions of large proteins.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1392-1397
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• 2003

This paper deals with a control technique of eliminating the transient vibration of a twin-drive geared mechanical system. This technique is based on a model-based control in order to establish the damping effect at the driven machine part. The control model is composed of reduced-order electrical and mechanical parts. This control model estimates a load speed converted to the motor shaft. The difference between the estimated load speed and the motor speed is calculated dynamically and it is added to the velocity command to suppress the transient vibration generated at the load. This control technique is applied to a twin-drive geared system with backlash. In the previous work, the performance of this control method is examined by simulations. In this paper, the effectiveness of this control technique is verified by experiments. The settling time of the residual vibration generated at the loading inertia can be shortened down to about 1/2 of the uncompensated vibration level.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.925-933
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• 2006

Using the physics-based model for the vibration isolation system, the model uncertainties are described. With the model including parameter perturbations, the robust controller to meet the robust performance and stability is designed through $\mu$-synthesis by DK-iteration. The order of controller is reduced by virtue of Hankel norm approximation technique to allow the efficient implementation in the real-time experimental environment without any performance degradation. The performance of the reduced $\mu$-controller is accessed in comparison with the original one. The experiments validate the superiority of the proposed control scheme against the model uncertainties and its applicability with varying payload.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1262-1271
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• 2006

Using the physics-based model for the vibration isolation system, the model uncertainties are described. With the model including parameter perturbations, the robust controller to meet the robust performance and stability is designed through $\mu$-synthesis by DK-iteration. The order of controller is reduced by virtue of Hankel norm approximation technique to allow the efficient implementation in the real-time experimental environment without any performance degradation. The performance of the reduced $\mu$-controller is accessed in comparison with the original one. The experiments validate the superiority of the proposed control scheme against the model uncertainties and its applicability with varying payload.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.419-425
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• 1998

This paper presents a method of enhancing the accuracy of hybrid modelling that predicts dynamic characteristics of the coupled structure by synthesizing after FE analysis and vibration experimental analysis of the relevant individual substructure. Since most FE models in engineering problems are very large, dynamic analysis with the full FE model is costly. Frequency response function(FRF) synthesis after reducing the FE model can reduce this computational cost but introduce mode truncation error similarly in the case of considering only low-frequency mode after eigensolutions of the complete structure. This paper introduces a FRF of FE model for hybrid FRF synthesis, which is reduced by using IIRS methods and compensated through eigensolutions of the reduced model, and shows the effectiveness of the presented method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.34-40
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• 2005

This paper presents a frequency transfer function synthesis for simplifying a high-order model with time delay to a low-order model. A model reduction is based on minimizing the error function weighted by the numerator polynomial of reduced systems. The proposed method provides better low frequency fit and a computer aided algorithm. And in this paper, we present a design method of PID controller for achieving the desired specifications via the reduced model. The proposed method identifies the parameter vector of PID controller from a linear system that develops from rearranging the two dimensional input matrices and output vectors obtained from the frequency bounds.