Application of multi-phase particle swarm optimization technique to inverse radiation problem

Qi, Hong; Ruan, Li-Ming; Shi, Ming; An, Wei; Tan, He‐Ping

doi:10.1016/j.jqsrt.2007.07.013

Cited by 67 publications

(19 citation statements)

References 26 publications

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“…And the particle swarm optimization (PSO) was able to find a global optimum solution or a good approximation of the solution to the multimodal function [71]. There were a few reports concerning the application of PSO to inverse radiation analysis in recent years [66,[72][73][74][75]. In ref.…”

Section: Emission Computed Tomographymentioning

confidence: 99%

Review of soot measurement in hydrocarbon-air flames

Lou

Chen

Sun

et al. 2010

Sci. China Technol. Sci.

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Soot, which is produced in fuel-rich parts of flames as a result of incomplete combustion of hydrocarbons, is the No. 2 contributor to global warming after carbon dioxide. Developing soot measurement techniques is important to understand soot formation mechanism and control soot emission. The various soot measurement techniques, such as thermophoretic sampling particles diagnostics followed by electron microscopy analysis, thermocouple particle densitometry, light extinction, laser-induced incandescence, two-color method, and emission computed tomography, are reviewed in this paper. The measurement principle and application cases of these measurement methods are described in detail. The development trend of soot measurement is to realize the on-line measurement of multi-dimensional distributions of temperature, soot volume fraction, soot particle size and other parameters in hydrocarbon-air flames. Soot measurement techniques suitable for both small flames in laboratories and large-scale flames in industrial combustion devices should be developed. Besides, in some special situations, such as high-pressure, zero gravity and micro-gravity flames, soot measurement also should be provided. hydrocarbon-air flames, combustion measurement, soot, laser-induced incandescence, emission CT Citation:Lou C, Chen C, Sun Y P, et al. Review of soot measurement in hydrocarbon-air flames.

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Section: Emission Computed Tomographymentioning

confidence: 99%

Review of soot measurement in hydrocarbon-air flames

Lou

Chen

Sun

et al. 2010

Sci. China Technol. Sci.

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show abstract

“…It is one of the swarm intelligence techniques, which use group intelligence behavior along with individual intelligence to solve the combinatorial optimization problems. The BPSO algorithm is characterized as being simple in concept and easy to implement [23]. It is not necessary to calculate the gradient of the objective function with respect to retrieval variables, and only the functional value of the objective function and primi- tive mathematical operators are required.…”

Section: Introductionmentioning

confidence: 99%

Solving inverse problems of radiative heat transfer and phase change in semitransparent medium by using Improved Quantum Particle Swarm Optimization

Zhang

Sun

et al. 2015

International Journal of Heat and Mass Transfer

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“…To circumvent this issue, the intelligent optimization algorithms based on the population exhaustive search has been proposed to solve the ill-posed inverse heat transfer problems in recent years, such as the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), the Ant Colony Optimization (ACO), and the Neural Network Algorithm (NNA) [12][13][14][15][16][17][18][19]. A characteristic feature of these evolutionary search optimization methods is that they can solve the global optimal problem reliably and obtain high quality global solutions with enough computational time.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, they adopted the Lattice Boltzmann method (LBM) and the Finite Volume Method (FVM) to retrieve the extinction coefficient and conduction-radiation parameter of non-Fourier coupled conduction-radiation heat transfer combining with GA [15]. Our research group has demonstrated the use of several PSO-based algorithms to determine the radiative properties, particle size distributions and geometry conditions in various inverse radiation problems [18][19][20][21]. More recently, some new intelligent optimization techniques have been proposed to solve the coupled conductionradiation problems to look for improvements besides GA and PSO.…”

Section: Introductionmentioning

confidence: 99%