An efficient calibration approach for cavitation model constants based on OpenFOAM platform

Zhou, Hongwei; Xiang, Min; Okolo, Patrick N.; Wu, Zeping; Bennett, Gareth J.; Zhang, Weihua

doi:10.1007/s00773-018-0604-9

Cited by 13 publications

(13 citation statements)

References 23 publications

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“…Recently, Jin et al [33] designed a model to relate the values of the condensation and evaporation coefficients to the operating conditions, trying, in this way, to overcome the limitation of using empirical constants. Other examples of optimization of these empirical parameters are the surrogate-based sequential approximate optimization (SAO) method considered by Zhou et al [34] or the machine learning method employed by Sikirica et al [35]. Both were applied within the Kunz mixture cavitation model and provided better performances in cavitation prediction and simulation than the use of constant coefficients.…”

Section: Homogeneous Modelsmentioning

confidence: 99%

Impact of Cryogenics on Cavitation through an Orifice: A Review

2021

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Cryogenic cavitation affects the operation of liquid propulsion systems during the first phase of a launch. Its effects within orifices or turbopumps can range from mild instabilities to catastrophic damages to the structures, jeopardizing the launch itself. Therefore, to ensure the proper designing of propulsion systems, cavitation phenomena cannot be neglected. Although hydrodynamic cavitation has been studied for decades, the impact of the nature of the fluid has been sparsely investigated. Therefore, this review, beginning from the basic concepts of cavitation, analyzes the literature dedicated to hydrodynamic cryogenic cavitation through an orifice. Our review provides a clear vision of the state-of-the-art from experimental and modeling viewpoints, identifies the knowledge gaps in the literature, and proposes a way to further investigate cryogenic cavitation in aerospace science.

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Section: Homogeneous Modelsmentioning

confidence: 99%

Impact of Cryogenics on Cavitation through an Orifice: A Review

2021

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“…Bensow et al [15] 20,000 1000 Morgut et al [17] 455 4100 Kunz et al [4] 100 100 Kunz et al [5] 0.2 0.2 Vaz et al [40] 10,000 500 Zhou et al [41] 4328 3323 Predicted 172 5 Figure 4 illustrates disparity in cavity extents depending on C prod and C dest . Included are experimental results, results obtained in this study and results for values presented in Table 5.…”

Section: Reference C Prod C Destmentioning

confidence: 99%

“…Included are experimental results, results obtained in this study and results for values presented in Table 5. [5], (e) Vaz et al [40], (f) Zhou et al [41], (g) predicted values C prod = 172, C dest = 5 and (h) experimental observations [30].…”

Section: Reference C Prod C Destmentioning

confidence: 99%

Cavitation Model Calibration Using Machine Learning Assisted Workflow

et al. 2020

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Conventional cavitation assessment methodology in industrial and scientific applications generally depends on cavitation models utilizing homogeneous mixture assumption. These models have been extensively assessed, modified and expanded to account for deficiencies of their predecessors. Unfortunately, none of the proposed models can be classified as the universal solution for all engineering applications, with usage mainly directed by experience or general availability of the models. In this study we propose a workflow through which the empirical constants governing the phase change of the Kunz mixture cavitation model can be calibrated for a given application or a series of problems, with machine learning as a tool for parameter estimation. The proposed approach was validated on a three-dimensional propeller test case with results in excellent agreement for the case in question. Results for thrust and torque were within 2% with cavity extents differing by up to 20%. This is a significant improvement when compared to previously proposed parameters. Despite the lack of generalization due to the limited nature of the dataset on which the model was trained, the proposed parameters entail acceptable results for similar cases as well. The overall methodology is applicable to other problems as well and should lead to more accurate cavitation predictions.

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“…An important issue related to these models is the use of empirical coefficients, which are needed since the terms describing the condensation/vaporization processes are simplified version of complex physical relationship (the most indicative is perhaps the Schnerr-Sauer model, which considers only the terms of the Rayleigh-Plesset equation related to the asymptotic growth of bubbles). The condensation/vaporization coefficients C c and C v may be calibrated for the study of the specific problem such as the flow around a hydrofoil [22] or a marine propeller [23]; usually calibration of the coefficients is performed using optimization techniques [24], where the values of the coefficients are evaluated forcing the solution to obtain optimal values of some mean quantities, such as the pressure coefficient or thrust and torque coefficients, the latter in case of marine propellers.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Performance of Cavitation Models with Analytically Calculated Coefficients

2021

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Cavitation is often simulated using a mixture model, which considers the transport of an active scalar, namely the vapor fraction αv. Source and sink terms of the transport equation of αv, namely vaporization and condensation terms, rule the dynamics of the cavity and are described through different models. These models contain empirical coefficients generally calibrated through optimization processes. The purpose of this paper is to propose an analytical approach for the calculation of the coefficients, based on the time scales of vaporization and condensation processes. Four different models are compared considering as a test-case a two-dimensional flow around a cylinder. Some relevant quantities are analyzed both for standard value of coefficients, as found in the literature, and the coefficients calculated through the analytical approach. The study shows that the analytical computation of the coefficients of the model substantially improve the results, and the models considered give similar results, both in terms of cavitation regime and mean vapor fraction produced.

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An efficient calibration approach for cavitation model constants based on OpenFOAM platform

Cited by 13 publications

References 23 publications

Impact of Cryogenics on Cavitation through an Orifice: A Review

Impact of Cryogenics on Cavitation through an Orifice: A Review

Cavitation Model Calibration Using Machine Learning Assisted Workflow

Analysis of Performance of Cavitation Models with Analytically Calculated Coefficients

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