REAL-TIME PERFORMANCE PREDICTION OF A PHYSICS-BASED PUMP SYSTEM SIMULATION USING BAYESIAN OPTIMIZATION

G. Kang; S. Kim; K. Cha; J.-H. Kim; M. Lee; J. Lee

doi:10.6112/kscfe.2024.29.1.113

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2024 Vol.29, Issue 1 Preview Page

Original Article

REAL-TIME PERFORMANCE PREDICTION OF A PHYSICS-BASED PUMP SYSTEM SIMULATION USING BAYESIAN OPTIMIZATION 베이지안 최적화를 활용한 물리 기반 펌프 시스템 시뮬레이션의 실시간 성능 예측

31 March 2024. pp. 113-129

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Abstract

This study aims to develop a model designed to effectively respond to fluctuations in energy demand. It involves constructing a physics-based simulation capable of real-time performance prediction for a two-stage centrifugal pump system. The model is composed of Modelica and a Reduced-order Model(ROM). It predicts key performance indicators such as pump head and flow rate in real-time. Additionally, a multi-parameter calibration framework using Bayesian optimization was applied to reflect the actual performance of the pump. This framework calibrates the parameters of the Modelica model. As a result, the error rates for flow rate and head were reduced to 2.87% and 3.58%, respectively.

Keywords

전산유체역학(Computational Fluid Dynamics)

입형 원심 펌프(Vertical Centrifugal Pump)

디지털트윈(Digital Twin)

베이지안 최적화(Bayesian Optimization)

가우시안 프로세스(Gaussian Process)

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Information

Publisher :Korean Society for Computational Fluids Engineering
Publisher(Ko) :한국전산유체공학회
Journal Title :Journal of Computational Fluids Engineering
Journal Title(Ko) :한국전산유체공학회지
Volume : 29
No :1
Pages :113-129
Received Date : 2024-03-08
Revised Date : 2024-03-22
Accepted Date : 2024-03-25
DOI :https://doi.org/10.6112/kscfe.2024.29.1.113

Journal of Computational Fluids Engineering ISSN:1598-6071(Print) 3022-6252(Online) 한국전산유체공학회지

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