Optimal design of multichannel fiber Bragg grating filters using Pareto multi-objective optimization algorithm

Chen, Jing; Liu, Tundong; Jiang, Hao

doi:10.1016/j.optcom.2015.09.026

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…TOPSIS and VIKOR are mainly applied to the Pareto frontier obtained by NSGA-II. 34,35 In this paper, the Pareto front was obtained by MOPSO, and the fuzzy membership function is used to determine the BCS.…”

Section: Introductionmentioning

confidence: 99%

Research on lightweight and fatigue life of engine hood based on multi-objective particle swarm optimization

Liu

et al. 2022

Advances in Mechanical Engineering

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A multi-objective optimization method is presented in this paper, aiming at improving the fatigue life of the engine hood while achieving light weight. By analyzing the factors affecting the fatigue life of the engine hood, a multi-objective optimization model was established that considered five design variables including the thickness of the inner plate, the thickness of the outer plate, the stiffness of the hook, the stiffness of the sealing strip, and the height of the buffer block. Then, the multi-objective particle swarm method was used for optimization, and the optimal solution was obtained in the form of a Pareto set. The ideal compromise solution was determined from the Pareto set by using fuzzy membership functions. On this basis, the optimal solution was determined from the Pareto set by comprehensively considering the steel plate material specification, mold and cost constraints. The torsional deformation test and switch fatigue test show that for the optimized engine hood, the fatigue life is increased by 117%, the mass is reduced by 0.51 kg, and the torsional deformation of the engine hood does not increase significantly. The proposed multi-objective optimization method is proved to be feasible and effective in improving engine hood fatigue life and lightweight design.

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Section: Introductionmentioning

confidence: 99%

Research on lightweight and fatigue life of engine hood based on multi-objective particle swarm optimization

Liu

et al. 2022

Advances in Mechanical Engineering

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Multi-Objective Optimization of Manufacturing Process in Carbon Fiber Industry Using Artificial Intelligence Techniques

et al. 2019

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Seeking high profitability by improving energy efficiency and production quality is the prime goal of manufacturing industries. However, achieving this aim involves the realization of several conflicting objectives. In carbon fiber industry, the stabilization process is the most vital step with high energy consumption. The aim of this study is to use intelligent modeling methods in the stabilization process to maximize energy efficiency while considering better production quality, avoiding defects, and not scarifying the prediction accuracy. To this aim, a modified DOE method was used to reduce the number of required experiments. The mechanical and physical properties were then modeled based on input-output data derived from the experiments. In this way, the SVR method is used to develop a set of mathematical models for mechanical and physical properties of the fibers. The skin-core defect and energy consumption were considered as objective functions within the given range of physical and mechanical properties of fibers. The state-of-the-art NSGA-II algorithm used to find the optimum Pareto front, including non-dominated solutions among these conflicting objective functions. The results showed that by using the integrated NSGA-II and technique for order preference by similarity to ideal solution (TOPSIS), the energy efficiency of the system was improved. Moreover, the discussions showed how similar hybrid algorithms with high accuracy can be used by other industries to reduce the overall energy consumptions.

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Fabrication of precise aperiodic multichannel fibre Bragg grating filters for spectral line suppression in hydrogenated standard telecommunications fibre

Gbadebo¹,

Turitsyna²,

Williams³

2018

Opt. Express

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We demonstrate the design and fabrication of multichannel fibre Bragg gratings (FBGs) with aperiodic channel spacings. These will be suitable for the suppression of specific spectral lines such as OH emission lines in the near infrared (NIR) which degrade ground based astronomical imaging. We discuss the design process used to meet a given specification and the fabrication challenges that can give rise to errors in the final manufactured device. We propose and demonstrate solutions to meet these challenges.

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Optimal design of multichannel fiber Bragg grating filters using Pareto multi-objective optimization algorithm

Cited by 3 publications

References 24 publications

Research on lightweight and fatigue life of engine hood based on multi-objective particle swarm optimization

Research on lightweight and fatigue life of engine hood based on multi-objective particle swarm optimization

Multi-Objective Optimization of Manufacturing Process in Carbon Fiber Industry Using Artificial Intelligence Techniques

Fabrication of precise aperiodic multichannel fibre Bragg grating filters for spectral line suppression in hydrogenated standard telecommunications fibre

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