Main Article Content

Mrs. Radha Aloori
Mr. S Suresh
Mr. Avinash Ollam


When it comes to the construction of hydraulic structures, the hydraulic performance and acoustic
performance of centrifugal pumps are connected and conflicting. In order to find a solution to this issue, a
technique for optimising the design of a volute that is based on a radial basis function (RBF) neural
network and a genetic algorithm (GA) has been developed. The effectiveness of the centrifugal pump as
well as the total amount of sound pressure level are employed as the targets for optimisation. The factors
that are used for optimisation purposes are the installation angle of the volute tongue, the height of the
volute diffuser tube, the installation angle of the volute tongue, and the diameter of the base circle. The
Latin hyper-cube sampling (LHS) method is used to construct the sample space. The RBF neural network
method is used to develop the agent model between the optimisation variables and goals. Finally, the GA
method is utilised to do multi-objective optimisation. In order to do a comparative investigation of the
hydraulic and acoustic performance of the persons in the Pareto solution set under a variety of different
working situations, the initial individuals and two individuals from the set's extremes are chosen. The
findings indicate that under the rated working conditions, the efficiency of the optimal individual of
efficiency increases by 3.79%, while the internal noise of the optimal individual of sound pressure level
decreases by 5.5% and the external noise decreases by 2.3%. The results also show that the initial
individual had a lower level of efficiency than the optimal individual.


Download data is not yet available.


Metrics Loading ...

Article Details

How to Cite
Aloori, M. R. ., Suresh, M. S. ., & Ollam, M. A. . (2020). THE USE OF AN RBF NEURAL NETWORK AND A GENETIC ALGORITHM FOR MULTI-OBJECTIVE OPTIMISATION OF A CENTRIFUGAL PUMP VOLUTE. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 11(3), 2711–2722.
Research Articles


Zakeri B, Paulavets K, Barreto-Gomez

L, et al. Pan- demic, war, and global energy

transitions. Energies 2022; 15: 6114.

Gangipamula R, Ranjan P and Patil RS.

Flow-induced noise sources and reduction

methods in centrifugal pumps: a literature

review. Phys Fluids 2022; 34: 081302.

Guo R, Li RN, Zhang RH, et al.

Influence of blade pro- file on the hydraulic and

rotating noise characteristics of a jet centrifugal

pump. Shock Vib 2019; 38: 223–230.

Ji Y, Yang Z, Ran J, et al. Multiobjective parameter optimization of turbine

impeller based on RBF neural network and

NSGA-II genetic algorithm. Energy Rep 2021;

: 584–593.

Zhang DS, Yang G, Zhao XT, et al.

Optimization design of vane diffuser and volute

in vertical centrifugal pump based on back

propagation neural network. J Trans Chin Soc

Agric Mach 2022; 53: 130–139.

Chen Q, Xin L, Zuguang L, et al. Multiobjective optimi- zation of multistage pump

balance drum system based on bp neural

network and genetic algorithm. Int J Fluid

Machinery Syst 2021; 14: 80–94.

Wu T, Wu D, Ren Y, et al. Multiobjective optimization on diffuser of multistage

centrifugal pump base on ANN-GA. Struct

Multidiscipl Optim 2022; 65: 182.

Kim JH, Ovgor B, Cha KH, et al.

Optimization of the aerodynamic and

aeroacoustic performance of an axial- flow fan.

AIAA J 2014; 52: 2032–2044.

Si QR, Lin G, Yuan SQ, et al. Multiobjective optimiza- tion on hydraulic design of

non-overload centrifugal pumps with high

efficiency and low noise. J Trans Chin Soc

Agric Eng 2016; 32: 69–77.

Zhao WG, Xia T, Sheng YZ, et al.

Multi-objective para- meters optimization of low

specific speed centrifugal pump based on

NSGA-II genetic algorithm. J Lanzhou Univ

Technol 2020; 46: 55–61.

Zhang L, Davila G and Zangeneh M.

Multi-objective optimization of a high specific

speed centrifugal volute pump using threedimensional inverse design coupled with

computational fluid dynamics simulations. J

Fluid Eng 2021; 143: 021202.

Zhang ZX and Yu D. Comparison and

research of BP and RBF neural networks in

function approximation. Ind Control Comput

; 31: 119–120.

Lu R, Yuan J, Wei G, et al.

Optimization design of energy-saving mixed

flow pump based on MIGA-RBF algorithm.

Machines 2021; 9: 365.

Du MX, Wang YW and Zhang XZ.

Optimal design of centrifugal pump based on

RBF neural network and genetic algorithm. J

China Three Gorges Univ Nat Sci 2020; 42: 88–

Wang W, Han Z, Pei J, et al. Energy

efficiency optimiza- tion of water pump based on heuristic algorithm and CFD. J Comput Des

Eng 2022; 10: 382–397.

Wang C, Chen X, Ge J, et al. Internal

flow characteristics of high-specific-speed

centrifugal pumps with different number of

impeller blades under large flow conditions.

Machines 2023; 11: 138.

Xi B, Wang C, Xi W, et al.

Experimental investigation on the water hammer

characteristic of stalling fluid in eccentric

casing-tubing annulus. Energy 2022; 253:

Liu H, Cheng Z, Ge Z, et al.

Collaborative improvement of efficiency and

noise of bionic vane centrifugal pump based on

multi-objective optimization. Adv Mech Eng.

Epub ahead of print 14 February 2021. DOI:

1177/ 1687814021994976.

Shim HS and Kim KY. Design

optimization of the impel- ler and volute of a

centrifugal pump to improve the hydraulic

performance and flow stability. J Fluid Eng

; 142: 101211.

Zheng P, Liu J, Song W, et al.

Preliminary study on improved Latin hypercube

sampling. Nucl Electron Detect Technol 2017;

: 734–738.

Jiang BX, Yang JH, Bai XB, et al.

Optimization of cen- trifugal pump blade based

on high-dimensional hybrid model and genetic

algorithm. J Huazhong Univ Sci Tech- nol Nat

Sci Ed 2020; 48: 128–132.

Zhao J, Pei J, Yuan J, et al. Energysaving oriented opti- mization design of the

impeller and volute of a multi- stage doublesuction centrifugal pump using artificial neural

network. Eng Appl Comput Fluid Mech 2022;

: 1974–2001.