Author
Min-Chie Chiu
Other affiliations: Tatung University
Bio: Min-Chie Chiu is an academic researcher from Chung Chou University of Science and Technology. The author has contributed to research in topics: Muffler & Noise. The author has an hindex of 15, co-authored 135 publications receiving 792 citations. Previous affiliations of Min-Chie Chiu include Tatung University.
Topics: Muffler, Noise, Shape optimization, Noise control, Simulated annealing
Papers published on a yearly basis
Papers
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TL;DR: In this article, two categories of numerical approaches, including the genetic algorithm (GA) method and traditional gradient methods, are applied into the muffler design work and the acoustic impedance of sound absorber in evaluating the sound absorption coefficient is in conjunction with these numerical techniques.
48 citations
TL;DR: In this paper, a numerical case for eliminating broadband steam blow-off noise using multi-chamber plug-inlet mufflers in conjunction with a GA as well as a numerical decoupling technique, all within a space-constrained pressure drop, is introduced.
48 citations
TL;DR: In this article, both the generalized decoupling technique and plane wave theory are used to analyze the sound transmission loss of a multi-chamber perforated muffler and optimize the best design shape under space-constrained condition.
43 citations
TL;DR: In this article, the authors analyzed the sound transmission loss of three kinds of cross-flow perforated mufflers and analyzed the optimal design shape within a limited space using a decoupled numerical method.
40 citations
TL;DR: The shape optimization of multi-segments muffler coupled with the GA searching technique is presented and results verify that the optimal sound transmission loss at the designed frequency of 500 Hz is exactly maximized.
35 citations
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2,730 citations
TL;DR: The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot.
Abstract: Good path planning technology of mobile robot can not only save a lot of time, but also reduce the wear and capital investment of mobile robot. Several methodologies have been proposed and reported in the literature for the path planning of mobile robot. Although these methodologies do not guarantee an optimal solution, they have been successfully applied in their works. The purpose of this paper is to review the modeling, optimization criteria and solution algorithms for the path planning of mobile robot. The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot. Finally, future research is discussed which could provide reference for the path planning of mobile robot.
199 citations
01 Jan 2016
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193 citations
TL;DR: This improved GA presents an effective and accurate fitness function, improves genetic operators of conventional genetic algorithms and proposes a new genetic modification operator.
181 citations
TL;DR: In this paper, a gradient-based topology optimization formulation is proposed to solve acoustic-structure (vibro-acoustic) interaction problems without explicit boundary interface representation, which circumvent the explicit boundary representation by using a mixed finite element formulation with displacements and pressure as primary variables.
Abstract: The paper presents a gradient-based topology optimization formulation that allows to solve acoustic–structure (vibro-acoustic) interaction problems without explicit boundary interface representation. In acoustic–structure interaction problems, the pressure and displacement fields are governed by Helmholtz equation and the elasticity equation, respectively. Normally, the two separate fields are coupled by surface-coupling integrals, however, such a formulation does not allow for free material re-distribution in connection with topology optimization schemes since the boundaries are not explicitly given during the optimization process. In this paper we circumvent the explicit boundary representation by using a mixed finite element formulation with displacements and pressure as primary variables (a u/p-formulation). The Helmholtz equation is obtained as a special case of the mixed formulation for the elastic shear modulus equating to zero. Hence, by spatial variation of the mass density, shear and bulk moduli we are able to solve the coupled problem by the mixed formulation. Using this modelling approach, the topology optimization procedure is simply implemented as a standard density approach. Several two-dimensional acoustic–structure problems are optimized in order to verify the proposed method. Copyright © 2006 John Wiley & Sons, Ltd.
180 citations