• 한국가스학회지
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• 제10권2호
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• pp.55-60
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• 2006

Detailed modeling of PEMFCs has been getting considerable interest for predicting the fuel cell performance and also for use in various systems engineering activities. While CFD-based equipment models provide detailed analyses of the performance, they are very time-consuming to develop and run. The computations become quite complex when such models have to be embedded into the flowsheet-level optimization of fuel cell systems. In this paper, we present results about building and using NN-based reduced order models for quickly and repetitively predicting the flow of reactants in a PEMFC manifold.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제13권2호
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• pp.141-159
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• 2009

In this article, we consider a weighted CVT-based reduced-order modelling for Burgers equation. Brief review of the CVT (centroidal Voronoi tessellation) approaches to reduced-order bases are provided. In CVT-reduced order modelling, we start with a snapshot set just as is done in a POD (Proper Orthogonal Decomposition)-based setting. So far, the CVT was researched with uniform density ($\rho$(y) = 1) to determine the basis elements for the approximatin subspaces. Here, we shall investigate the technique of CVT with nonuniform density as a procedure to determine the basis elements for the approximating subspaces. Some numerical experiments including comparison of two CVT (CVT-uniform and CVT-nonuniform)-based algorithm with numerical results obtained from FEM(finite element method) and POD-based algorithm are reported.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.688-698
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• 2012

This paper deals with ROLSO (Reduced Order Luenberger State Observer) design to prevent jackknifing phenomenon of articulated vehicles consisting of the tractor and semi-trailer by using GPS. In addition, by applying the regulator system using ROLSO feedback system, simulation's result presents that articulated vehicle's states are stabilized than the human's PR time (Preception Response time) rapidly. This simulation verifies that the automatic control of articulated vehicle's can be applied for the accident prevention for the time that the driver is unable to manage with the sudden accident. For this simulation, by using the equation of planar motion, the modeling of the articulated vehicle was performed. This modeling was expressed in the state space model. And FOLSO (Full Order Luenberger State Observer), ROLSO were designed by using the state space model of an articulated vehicle's dynamics.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2011년 춘계학술대회논문집
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• pp.458-464
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• 2011

A new method identifies coupled fluid-structure system with a reduced set of state variables is presented. Assuming that the structural model is known a priori either from an analysis or a test and using linear transformations between structural and aeroelastic states, it is possible to deduce aerodynamic information from sampled time histories of the aeroelastic system. More specifically given a finite set of structural modes the method extracts generalized aerodynamic force matrix corresponding to these mode shapes. Once the aerodynamic forces are known, an aeroelastic reduced-order model can be constructed in discrete-time, state-space format by coupling the structural model and the aerodynamic system. The resulting reduced-order model is suitable for constant Mach, varying density analysis.

• 전기학회논문지
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• 제59권6호
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• pp.1126-1130
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• 2010

Speech production can be viewed as a filtering operation in which a sound source excites a vocal tract filter. The vocal tract is modeled as a chain of cylinders of varying cross-sectional area in linear prediction acoustic tube modeling. In this modeling the most common implementation assumes equal length of tube sections. Therefore, to model complex vocal tract shapes, a large number of tube sections are needed. This paper proposes a new vocal tract model with unfixed sectionlengths, which uses the reduced lattice filter for modeling the vocal tract. This model transforms the lattice filter to reduced structure and the Burg algorithm to modified version. When the conventional and the proposed models are implemented with the same order of linear prediction analysis, the proposed model can produce more accurate results than the conventional one. To implement a system within similar accuracy level, it may be possible to reduce the stages of the lattice filter structure. The proposed model produces the more similar vocal tract shape than the conventional one.

• 한국항공우주학회지
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• 제40권10호
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• pp.833-839
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• 2012

본 논문에서는 후향계단 유동장 모델링 및 복원오차를 분석한다. 유동장의 밀도를 POD(Proper Orthogonal Decomposition) 기법을 통해 공간모드와 시간모드로 추출하여 수학적으로 모델링한다. 모델링 오차를 정립하여 유동에너지와 오차 사이의 관계를 정리한다. 모델링 오차를 시간영역 뿐만 아니라 주파수 영역에서의 분석을 통하여 제어측면에서 오차의 한계를 규정한다.

• International Journal of Aeronautical and Space Sciences
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• 제13권2호
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• pp.127-153
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• 2012

This paper presents an advanced computational method for the prediction of the responses in the frequency domain of general linear dissipative structural-acoustic and fluid-structure systems, in the low-and medium-frequency domains and this includes uncertainty quantification. The system under consideration is constituted of a deformable dissipative structure that is coupled with an internal dissipative acoustic fluid. This includes wall acoustic impedances and it is surrounded by an infinite acoustic fluid. The system is submitted to given internal and external acoustic sources and to the prescribed mechanical forces. An efficient reduced-order computational model is constructed by using a finite element discretization for the structure and an internal acoustic fluid. The external acoustic fluid is treated by using an appropriate boundary element method in the frequency domain. All the required modeling aspects for the analysis of the medium-frequency domain have been introduced namely, a viscoelastic behavior for the structure, an appropriate dissipative model for the internal acoustic fluid that includes wall acoustic impedance and a model of uncertainty in particular for the modeling errors. This advanced computational formulation, corresponding to new extensions and complements with respect to the state-of-the-art are well adapted for the development of a new generation of software, in particular for parallel computers.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.805-808
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• 1991

In this paper, dynamical model and control architecture are developed for the closed chain motion of two N-joint manipulators holding a rigid object. Controller consist of forward controller which is reduced order model and compensator that compensates for modeling error. Control laws are determined so as to decouple the force and position controlled degree of freedom(DOF) during motion of the system.

• International Journal of Control, Automation, and Systems
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• 제4권1호
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• pp.1-9
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• 2006

This paper presents the modeling and multivariable feedback control of a novel high-precision multi-dimensional positioning stage. This integrated 6-degree-of-freedom. (DOF) motion stage is levitated by three aerostatic bearings and actuated by 3 three-phase synchronous permanent-magnet planar motors (SPMPMs). It can generate all 6-DOF motions with only a single moving part. With the DQ decomposition theory, this positioning stage is modeled as a multi-input multi-output (MIMO) electromechanical system with six inputs (currents) and six outputs (displacements). To achieve high-precision positioning capability, discrete-time integrator-augmented linear-quadratic-regulator (LQR) and reduced-order linearquadratic-Gaussian (LQG) control methodologies are applied. Digital multivariable controllers are designed and implemented on the positioning system, and experimental results are also presented in this paper to demonstrate the stage's dynamic performance.

• Nuclear Engineering and Technology
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• 제49권6호
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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.