• Title/Summary/Keyword: Constraint methods

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A Study on the Improvement of Numeric Integration Algorithm for the Dynamic Behavior Analysis of Flexible Machine Systems (탄성기계 시스템의 동적 거동 해석을 위한 수치 적분 알고리즘 개선에 관한 연구)

  • Kim, Oe-Jo;Kim, Hyun-chul
    • Journal of the Korean Society of Industry Convergence
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    • v.4 no.1
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    • pp.87-94
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    • 2001
  • In multibody dynamics, differential and algebraic equations which can satisfy both equation of motion and kinematic constraint equation should be solved. To solve this equation, coordinate partitioning method and constraint stabilization method are commonly used. The coordinate partitioning method divides the coordinate into independent and dependent coordinates. The most typical coordinate partitioning method arc LU decomposition, QR decomposition, projection method and SVD(sigular value decomposition).The objective of this research is to find a efficient coordinate partitioning method in flexible multibody systems and a hybrid decomposition algorithm which employs both LU and projection methods is proposed. The accuracy of the solution algorithm is checked with a slider-crank mechanism.

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Robust Energy Efficiency Power Allocation for Uplink OFDM-Based Cognitive Radio Networks

  • Zuo, Jiakuo;Dao, Van Phuong;Bao, Yongqiang;Fang, Shiliang;Zhao, Li;Zou, Cairong
    • ETRI Journal
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    • v.36 no.3
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    • pp.506-509
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    • 2014
  • This paper studies the energy efficiency power allocation for cognitive radio networks based on uplink orthogonal frequency-division multiplexing. The power allocation problem is intended to minimize the maximum energy efficiency measured by "Joule per bit" metric, under total power constraint and robust aggregate mutual interference power constraint. However, the above problem is non-convex. To make it solvable, an equivalent convex optimization problem is derived that can be solved by general fractional programming. Then, a robust energy efficiency power allocation scheme is presented. Simulation results corroborate the effectiveness of the proposed methods.

Explicit Motion of Dynamic Systems with Position Constraints

  • Eun, Hee-Chang;Yang, Keun-Hyuk;Chung, Heon-Soo
    • Journal of Mechanical Science and Technology
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    • v.17 no.4
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    • pp.538-544
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    • 2003
  • Although many methodologies exist for determining the constrained equations of motion, most of these methods depend on numerical approaches such as the Lagrange multiplier's method expressed in differential/algebraic systems. In 1992, Udwadia and Kalaba proposed explicit equations of motion for constrained systems based on Gauss's principle and elementary linear algebra without any multipliers or complicated intermediate processes. The generalized inverse method was the first work to present explicit equations of motion for constrained systems. However, numerical integration results of the equation of motion gradually veer away from the constraint equations with time. Thus, an objective of this study is to provide a numerical integration scheme, which modifies the generalized inverse method to reduce the errors. The modified equations of motion for constrained systems include the position constraints of index 3 systems and their first derivatives with respect to time in addition to their second derivatives with respect to time. The effectiveness of the proposed method is illustrated by numerical examples.

Optimum Sensitivity of Objective Function Using Equality Constraint (등제한조건을 이용한 목적함수에 대한 최적민감도)

  • Shin Jung-Kyu;Lee Sang-Il;Park Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.12 s.243
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    • pp.1629-1637
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    • 2005
  • Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

Hologram segmentation for relaxing sampling constraint in digital hologram (디지틀 홀로그램에서 샘플링 조건 완화를 위한 홀로그램 Segmentation)

  • 양훈기;류치연;김은수
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.35D no.8
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    • pp.76-81
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    • 1998
  • This paper presents a new method to synthesize a digital hologram that meets the resolution of a currently manufactured LCD while capable of displaying a 3-D object. That is accomplished by segmenting a hologram, resulting in relaxed sampling constraint. We show that the segmentation of a hologram enables us to utilize the planewave approximation and, unlike in a holographic stereogram, it does not require projection process, but directly takes fourier transform of horizontally sliced 2-D images that constitute a 3-D object, which makes it possible to reconstruct a higher resolution image with depth information. We also show that proposed hologram contains data significantly smaller than the conventional hologram does, which is quite useful for constructing wide-viewing hologram. Finally, simulation results obtained by both methods are compared.

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A Constraint-based Semi-supervised Clustering Through Initial Prediction of Unlabeled Data (비분류표시 데이터의 초기예측을 통한 제약기반 부분-지도 군집분석)

  • Kim, Eung-Gu;Jeon, Chi-Hyeok
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2007.11a
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    • pp.383-387
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    • 2007
  • Traditional clustering is regarded as an unsupervised teaming to analyze unlabeled data. Semi-supervised clustering uses a small amount of labeled data to predict labels of unlabeled data as well as to improve clustering performance. Previous methods use constraints generated from available labeled data in clustering process. We propose a new constraint-based semi-supervised clustering method by reflecting initial predicted labels of unlabeled data. We evaluate and compare the performance of the proposed method in terms of classification errors through numerical experiments with blinded labeled data.

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The Phonetics and Phonology of English Schwa

  • Ahn, Soo-Woong
    • Korean Journal of English Language and Linguistics
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    • v.1 no.2
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    • pp.311-329
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    • 2001
  • This paper wanted to test the reality of English schwa by phonetic and phonological methods. Phonetically it wanted to see acoustic evidence of the relationship between the full vowels and their reduced vowels in the unstressed positions. Phonologically it wanted to prove how systematic the schwa sound is by the constraint-based grammar. As a result, the schwa phenomenon in English was supported both phonetically and phonologically. In the phonetic analysis no relationship Was found in the distribution of the F1 and F2 of the full vowels and their reduced vowels in the unstressed syllables of the derived words. The reduced vowels tended to converge into a target of F1 516 and F2 1815. The view that the schwa sounds have a target was supported. On the phonological side the constraint-based tableau produced the successful output by using FAITH (V), (equation omitted)V, FAITH V[-BACK+HiC], V[-Low, -TNS]#, REDUCE V[-STR, -TNS] as constraints. No ranking was found. Any violation of the constraints ousted the candidates.

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Computational Method for Dynamic Analysis of Constrained Mechanical Systems Using Partial Velocity Matrix Transformation

  • Park, Jung-Hun;Yoo, Hong-Hee;Hwang, Yo-Ha
    • Journal of Mechanical Science and Technology
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    • v.14 no.2
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    • pp.159-167
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    • 2000
  • A computational method for the dynamic analysis of a constrained mechanical system is presented in this paper. The partial velocity matrix, which is the null space of the Jacobian of the constraint equations, is used as the key ingredient for the derivation of reduced equations of motion. The acceleration constraint equations are solved simultaneously with the equations of motion. Thus, the total number of equations to be integrated is equivalent to that of the pseudo generalized coordinates, which denote all the variables employed to describe the configuration of the system of concern. Two well-known conventional methods are briefly introduced and compared with the present method. Three numerical examples are solved to demonstrate the solution accuracy, the computational efficiency, and the numerical stability of the present method.

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STUDY OF RELIABILITY BASED FLEXIBLE WING SHAPE DESIGN OPTIMIZATION (신뢰성을 고려한 유연 날개 형상 최적 설계에 대한 연구)

  • Kim S.W.;Kwon J.H.
    • Journal of computational fluids engineering
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    • v.11 no.1 s.32
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    • pp.21-28
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    • 2006
  • Reliability Based Design Optimization(RBDO) is one of the optimization methods that minimize the product failure due to small changes of operating conditions or process errors. It searches the optimum that satisfies the safety margin of each constraint, and it gives stable and reliable designs. However, RBDO requires many times oj computational efforts compared with the conventional deterministic optimization(DO) to evaluate the probability of failure about each constraint, therefore it is hard to apply directly to large-scaled problems such as a flexible wing shape design optimization. For the efficient reliability analysis, the approximate reliability analysis method with the two-point approximation(TPA) is proposed In this study, the lift-to-drag ratio maximization designs are performed with 3-dimensional Navier-Stokes analysis and NASTRAN structural analysis, and the optimization results about the deterministic, FORM and SORM are compared.

A Study on Multiobjective Genetic Optimization Using Co-Evolutionary Strategy (공진화전략에 의한 다중목적 유전알고리즘 최적화기법에 관한 연구)

  • Kim, Do-Young;Lee, Jong-Soo
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.699-704
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    • 2000
  • The present paper deals with a multiobjective optimization method based on the co-evolutionary genetic strategy. The co-evolutionary strategy carries out the multiobjective optimization in such way that it optimizes individual objective function as compared with each generation's value while there are more than two genetic evolutions at the same time. In this study, the designs that are out of the given constraint map compared with other objective function value are excepted by the penalty. The proposed multiobjective genetic algorithms are distinguished from other optimization methods because it seeks for the optimized value through the simultaneous search without the help of the single-objective values which have to be obtained in advance of the multiobjective designs. The proposed strategy easily applied to well-developed genetic algorithms since it doesn't need any further formulation for the multiobjective optimization. The paper describes the co-evolutionary strategy and compares design results on the simple structural optimization problem.

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