Multi-Objective Pareto Optimization of Centrifugal Pump Using Genetic Algorithms
نویسندگان
چکیده
Multi-objective genetic algorithm (GAs) is used for pump design pareto optimization, competing objectives for centrifugal pump design are total head (H), input power (Ps), hydraulic efficiency ( H η ), and input parameter are capacity (Q), and the outer radius of the impeller ( ). Multi-objective presents a set of compromised solution, and provides non-dominated optimal choices for designer. 2 r Key-Words: Centrifugal Pump, Pareto Optimization, Head, Hydraulic Efficiency, Input Power, Multi-objective Optimization, GAs.
منابع مشابه
Modeling and Multi-Objective Optimization of Centrifugal Pumps Using CFD and Neural Networks
Modeling and multi-objective optimization of centrifugal pumps is performed at three steps. At the first step, η and NPSHr in a set of centrifugal pump are numerically investigated using commercial software NUMECA. Two metamodels based on the evolved group method of data handling (GMDH) type neural networks are obtained, at the second step, for modeling of η and NPSHr with respect to geometrica...
متن کاملAERO-THERMODYNAMIC OPTIMIZATION OF TURBOPROP ENGINES USING MULTI-OBJECTIVE GENETIC ALGORITHMS
In this paper multi-objective genetic algorithms were employed for Pareto approach optimization of turboprop engines. The considered objective functions are used to maximize the specific thrust, propulsive efficiency, thermal efficiency, propeller efficiency and minimize the thrust specific fuel consumption. These objectives are usually conflicting with each other. The design variables consist ...
متن کاملMulti-Objective Optimization of Centrifugal Pumps Using Particle Swarm Optimization Method
In the present study, multi-objective optimization of centrifugal pumps is performed at three steps. At the first step, η and NPSHr in a set of centrifugal pump are numerically investigated using commercial software. Two meta-models based on the evolved group method of data handling (GMDH) type neural networks are obtained, at the second step, for modeling of η and NPSHr with respect to geometr...
متن کاملPareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...
متن کاملMulti-objective optimization of nanofluid flow in microchannel heat sinks with triangular ribs using CFD and genetic algorithms
Abstract In this paper, multi-objective optimization (MOO) of Al2O3-water nanofluid flow in microchannel heat sinks (MCHS) with triangular ribs is performed using Computational Fluid Dynamics (CFD) techniques and Non-dominated Sorting Genetic Algorithms (NSGA II). At first, nanofluid flow is solved numerically in various MCHS with triangular ribs using CFD techniques. Finally, the CFD data will...
متن کامل