An optimum design procedure for an aerodynamic radial diffuser with incompressible flow at different Reynolds numbers

Abstract In this article a systematic procedure aimed at achieving the best compromise between flow deflection, static pressure recovery, and total pressure loss is proposed for aerodynamic diffusers with incompressible flow. Such a result was accomplished by using a neural network to generalize the...

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Vydáno v:Proceedings of the Institution of Mechanical Engineers. Part A, Journal of power and energy Ročník 224; číslo 1; s. 69 - 84
Hlavní autoři: Rossetti, A, Ardizzon, G, Pavesi, G, Cavazzini, G
Médium: Journal Article
Jazyk:angličtina
Vydáno: London, England SAGE Publications 01.01.2010
SAGE PUBLICATIONS, INC
Témata:
Aerodynamics
Algorithms
Charts
Compressors
Computational fluid dynamics
Design analysis
Design engineering
Diffusers
Employment
Flow deflection
Fluid dynamics
Fluid flow
Fuzzy sets
Incompressible flow
Mechanical engineering
Multiple objective analysis
Neural networks
Optimization
Optimization algorithms
Pressure loss
Pressure recovery
Recovery
Reynolds number
Static pressure
vaned diffuser
swarm particle algorithm
diffuser performance
diffuser
radial cascade
ISSN:0957-6509, 2041-2967
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Abstract Abstract In this article a systematic procedure aimed at achieving the best compromise between flow deflection, static pressure recovery, and total pressure loss is proposed for aerodynamic diffusers with incompressible flow. Such a result was accomplished by using a neural network to generalize the radial diffusers performance data obtained by numerical analyses, a multi-objective approach based on the employment of fuzzy sets, and a swarm particle algorithm to find a good compromise between flow deflection, static pressure recovery, and total pressure loss. Useful design tools, obtained by collecting the results in proper design charts, are finally proposed to simplify the design of radial diffusers without resorting to expensive and time-consuming procedures of optimization. The influence of the Reynolds number on the overall performance was also taken into account.
AbstractList In this article a systematic procedure aimed at achieving the best compromise between flow deflection, static pressure recovery, and total pressure loss is proposed for aerodynamic diffusers with incompressible flow. Such a result was accomplished by using a neural network to generalize the radial diffusers performance data obtained by numerical analyses, a multi-objective approach based on the employment of fuzzy sets, and a swarm particle algorithm to find a good compromise between flow deflection, static pressure recovery, and total pressure loss. Useful design tools, obtained by collecting the results in proper design charts, are finally proposed to simplify the design of radial diffusers without resorting to expensive and time-consuming procedures of optimization. The influence of the Reynolds number on the overall performance was also taken into account. [PUBLICATION ABSTRACT]
Abstract In this article a systematic procedure aimed at achieving the best compromise between flow deflection, static pressure recovery, and total pressure loss is proposed for aerodynamic diffusers with incompressible flow. Such a result was accomplished by using a neural network to generalize the radial diffusers performance data obtained by numerical analyses, a multi-objective approach based on the employment of fuzzy sets, and a swarm particle algorithm to find a good compromise between flow deflection, static pressure recovery, and total pressure loss. Useful design tools, obtained by collecting the results in proper design charts, are finally proposed to simplify the design of radial diffusers without resorting to expensive and time-consuming procedures of optimization. The influence of the Reynolds number on the overall performance was also taken into account.
In this article a systematic procedure aimed at achieving the best compromise between flow deflection, static pressure recovery, and total pressure loss is proposed for aerodynamic diffusers with incompressible flow. Such a result was accomplished by using a neural network to generalize the radial diffusers performance data obtained by numerical analyses, a multi-objective approach based on the employment of fuzzy sets, and a swarm particle algorithm to find a good compromise between flow deflection, static pressure recovery, and total pressure loss. Useful design tools, obtained by collecting the results in proper design charts, are finally proposed to simplify the design of radial diffusers without resorting to expensive and time-consuming procedures of optimization. The influence of the Reynolds number on the overall performance was also taken into account.
Abstract In this article a systematic procedure aimed at achieving the best compromise between flow deflection, static pressure recovery, and total pressure loss is proposed for aerodynamic diffusers with incompressible flow. Such a result was accomplished by using a neural network to generalize the radial diffusers performance data obtained by numerical analyses, a multi-objective approach based on the employment of fuzzy sets, and a swarm particle algorithm to find a good compromise between flow deflection, static pressure recovery, and total pressure loss. Useful design tools, obtained by collecting the results in proper design charts, are finally proposed to simplify the design of radial diffusers without resorting to expensive and time-consuming procedures of optimization. The influence of the Reynolds number on the overall performance was also taken into account.
Author Cavazzini, G
Rossetti, A
Ardizzon, G
Pavesi, G
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10.1109/NAFIPS.2007.383845
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Keywords vaned diffuser
swarm particle algorithm
diffuser performance
diffuser
radial cascade
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SubjectTerms Aerodynamics
Algorithms
Charts
Compressors
Computational fluid dynamics
Design analysis
Design engineering
Diffusers
Employment
Flow deflection
Fluid dynamics
Fluid flow
Fuzzy sets
Incompressible flow
Mechanical engineering
Multiple objective analysis
Neural networks
Optimization
Optimization algorithms
Pressure loss
Pressure recovery
Recovery
Reynolds number
Static pressure
Title An optimum design procedure for an aerodynamic radial diffuser with incompressible flow at different Reynolds numbers
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