An optimization procedure, based on a method for solving inverse problems for the design of whole multistage axial turbines and compressors, is presented in the paper. A simplified axisymmetric model of three-dimensional axial turbomachines is adopted where volume forces replace the stator and rotor. The tangential component of such blade forces represents the design parameters that are defined through the optimization algorithm, whereas the stream surfaces that represent the stators and rotors are obtained by solving the inverse flow problem governed by the time-dependent Euler equations. The current optimization procedure takes into account some three-dimensional effects, such as lean and sweep, in the early stages of the design of blade rows by directly controlling the blade loading. The optimization process is based on a multi-objective genetic algorithm where a search for an optimal Pareto front is performed. Some preliminary numerical examples, which refer to the design of a linear cascade and compressor stage, are discussed.
Multiple objective optimization and inverse design of axial turbomachinery blades / Larocca, Francesco. - In: JOURNAL OF PROPULSION AND POWER. - ISSN 0748-4658. - 24:5(2008), pp. 1093-1099. [10.2514/1.33894]
Multiple objective optimization and inverse design of axial turbomachinery blades
LAROCCA, FRANCESCO
2008
Abstract
An optimization procedure, based on a method for solving inverse problems for the design of whole multistage axial turbines and compressors, is presented in the paper. A simplified axisymmetric model of three-dimensional axial turbomachines is adopted where volume forces replace the stator and rotor. The tangential component of such blade forces represents the design parameters that are defined through the optimization algorithm, whereas the stream surfaces that represent the stators and rotors are obtained by solving the inverse flow problem governed by the time-dependent Euler equations. The current optimization procedure takes into account some three-dimensional effects, such as lean and sweep, in the early stages of the design of blade rows by directly controlling the blade loading. The optimization process is based on a multi-objective genetic algorithm where a search for an optimal Pareto front is performed. Some preliminary numerical examples, which refer to the design of a linear cascade and compressor stage, are discussed.Pubblicazioni consigliate
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https://hdl.handle.net/11583/1914995
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